US0094.58509B2

(12) United States Patent (10) Patent No.: US 9.458,509 B2 Benenson et al. 45) Date of Patent: Oct. 4,9 2016

(54) MULTIPLE INPUT BIOLOGIC CLASSIFIER (52) U.S. Cl. CIRCUITS FOR CELLS CPC ...... CI2O 1/6886 (2013.01): CI2N 15/63 (2013.01); C12O 1/6897 (2013.01); G06F (75) Inventors: Yates'Biseiss. Newton :"A Liliana Ron 19/20 (2013.01); G06F 19/24 (2013.01) Wroblewska,s Arlington,s MAs (US); (58)58) Field ofO ClassificationSSCO SSea h Zhen Xie, Malden, MA (US) See application file for complete search history. (73) Assignees: PRESIDENT AND FELLOWS OF HARVARD COLLEGE, Cambridge, (56) References Cited MA (US); MASSACHUSETTS INSTITUTE OF TECHNOLOGY, FOREIGN PATENT DOCUMENTS Cambridge, MA (US) WO WO 2008134593 A1 * 11/2008 (*) Notice: Subject to any disclaimer, the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 U.S.C. 154(b) by 385 days. “Encode” definition; Oxford dictionary; http://www.oxford dictionaries.com/us/definition/american english encode; accessed (21) Appl. No.: 13/811,126 Apr. 27, 2015; pp. 5-6.* (22) PCT Filed: Jul. 22, 2011 * cited by examiner (86). PCT No.: PCT/US2O11AO45038 Primary Examiner — Antonio Galisteo Gonzalez S 371 (c)(1), (74) Attorney, Agent, or Firm — Nath, Goldberg & Meyer; (2), (4) Date: Apr. 5, 2013 Tanya E. Harkins (87) PCT Pub. No.: WO2012/012739 (57) ABSTRACT PCT Pub. Date: Jan. 26, 2012 Provided herein are high-input detector modules and multi input biological classifier circuits and systems that integrate (65) Prior Publication Data Sophisticated sensing, information processing, and actuation in living cells and permit new directions in basic biology, US 2013/02O2532 A1 Aug. 8, 2013 biotechnology and medicine. The multi-input biological Related U.S. Application Data classifier circuits described herein comprise synthetic, scale able transcriptional/post-transcriptional regulatory circuits (60) Provisional application No. 61/366,787, filed on Jul. that are designed to interrogate the status of a cell by 22, 2010. simultaneously sensing expression levels of multiple endog enous inputs, such as microRNAS. The classifier circuits (51) Int. Cl thenh compute whetherheth to trigger a desired output or response CI2O I/68 (2006.01) if the expression levels match a pre-determined profile of CI2N 15/63 (2006.01) interest. GO6F 9/20 (2011.01) GO6F 9/24 (2011.01) 21 Claims, 22 Drawing Sheets U.S. Patent Oct. 4, 2016 Sheet 1 of 22 US 9.458,509 B2

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st e i eAguiyipads) US 9,458,509 B2 1. 2 MULTIPLE INPUT BIOLOGIC CLASSIFIER molecular information in mammalian cells. These classifier CIRCUITS FOR CELLS circuits use transcriptional and posttranscriptional regulation in order to classify the status of a cell, i.e., determine CROSS-REFERENCE TO RELATED whether a cell is in a specific state of interest. The biological APPLICATIONS classifier circuits described herein implement this task by interrogating the state of the cell through simultaneous This is a National Phase Application filed under 35 U.S.C. assessment of multiple inputs, such as the expression levels 371 as a national stage of PCT/US2011/045038, filed on 22 of a Subset of predefined markers, for example, endogenous, Jul. 2011, an application claiming the benefit under 35 mature microRNAs. The classifier circuits described herein U.S.C. S 119(e) from U.S. Provisional Patent Application 1 No. 61/366,787, filed on Jul 22, 2010, the entire content of O are designed to compute whether the expression profile of each of which is hereby incorporated by reference in its the markers matches a pre-determined reference profile that entirety. characterizes the specific cell state that the classifier circuits are intended to detect. If so, the classifier circuits produce a GOVERNMENT SUPPORT biological response, Such as expression of a reporter mol 15 ecule. These biological circuits are termed herein as clas This invention was made with Government support under sifiers because they classify individual cells into a number NIGMS Grant GMO68763 from the National Institutes of of categories based on processing a multitude of inputs Health and grant W81XWH-09-1-0240 BC085163 from the indicative of the cells internal states, in a manner similar to Department of Defense Congressionally Directed Medical current practices for characterizing bulk tissue (e.g., biopsy Research Program (CDMRP). The Government has certain samples) using gene array analysis and computer algorithms rights in the invention. (31). The biological classifier circuits described herein can be FIELD OF THE INVENTION used in a variety of applications, such as those requiring precise classification and identification of cell types. In some The present invention relates to multi-input engineered 25 aspects, described herein are biological classifier circuits for genetic circuits for classifying cells. use as therapeutic agents, for example, in highly precise and The Sequence Listing submitted in text format (..txt) filed selective cancer therapy. Many mainstream and experimen on Jan. 18, 2013, named “50295PCT.txt', (created on Jan. 8, tal drugs exhibit a degree of selectivity toward cancer cells 2013, 222 KB), is incorporated herein by reference. by relying on individual cancer markers (32). However, 30 cancer cells exhibit a complex set of conditions deviating BACKGROUND from the normal state of their progenitor tissue (33, 34), and using a single marker to distinguish them from healthy cells An important feature of biological pathways is their is rarely sufficient and often results in harmful side-effects two-way interaction with the cellular environment in which (35). Therefore, sensing and integration of information from they operate. Such interaction usually involves (1) sensing 35 multiple markers by a therapeutic agent is crucial for cre of relevant input conditions in the cell, (2) processing those ating next-generation treatments, and for use in a variety of inputs to determine whether and which action to take; and applications, which can include, but are not limited to, (3) producing a biologically-active output to actuate a physi identification, sorting, or targeting of stem cells from het ological effect in the cell. Some engineered analogues of erogenous populations of differentiated cells; identification, natural pathways with sensing, computational and actuation 40 sorting, or targeting of specific cell types for the treatments functionalities (1, 2) have been developed that can augment of various diseases, such as cancer, identification, Sorting, endogenous processes and enable rational manipulation and targeting, or detection of cell types at various developmental control of biological systems. While reporter constructs (3) stages; drug screening assays; and identification, Sorting, that transduce cellular inputs into a detectable output, and targeting, or detection of cell types in experimental models tissue-specific transgenes controlled transcriptionally and/or 45 to be used in tracking therapuetic treatment responses to a posttranscriptionally (4-6) lack complexity, they represent drug or other molecule. Such as during a tumor treatment. useful components for the development of synthetic circuits. For example, described herein is an exemplary biological Some synthetic circuits have demonstrated programmed classifier circuit tested in human cell culture that acts as a dynamic behavior in cells (oscillators (7-10), memory (11 programmed therapeutic agent that, via identification and 14), spatial patterns (15), cascades (16) and pulse generators 50 processing of a combination of input markers, selectively (17)), digital and analog computations (18-20), and complex identifies and triggers apoptosis in a cancer cell line, but not biosynthetic pathways (21), but the interaction of these in healthy cells. circuits with the cellular context has been limited (22, 23). Accordingly, provided herein are high-input detector Similarly, molecular network prototypes have demonstrated modules for classifying a cell status based on detecting sensing, computation and actuation (24-28) in cell-free 55 whether an input microRNA is expressed at a specific level environments, but their utility in cellular contexts has been or higher than a reference level. Such high-input detector inadequate. modules comprise a constitutive or inducible promoter Hence, engineered biological systems described thus far sequence operably linked to: (i) a repressor sequence, which have lacked the necessary complexity, Sophistication, and encodes a repressor product, and (ii) a sequence which discriminatory capacities to be functional and responsive to 60 encodes one or more microRNA target sequences, such that the multitude of inputs that are found in the normal, unma the one or more microRNA target sequences comprise target nipulated cellular millieu. sequences of the one or more input microRNAs the module is designed to detect. In some embodiments, such high-input SUMMARY OF THE INVENTION detector modules can further comprise a repressible pro 65 moter sequence operably linked to an output sequence Described herein are multi-input biological classifier cir encoding an ouput product, wherein the repressor product is cuits and methods of use thereof developed for processing specific for the repressible promoter sequence. US 9,458,509 B2 3 4 In some embodiments of the high-input detector modules expressed at a lower level than a reference expression level. described herein, the high-input detector module can further Such low-input detector modules comprise a repressible comprise one or more regulatory units. Such regulatory units promoter sequence operably linked to: (i) an output comprise a constitutive or inducible promoter sequence sequence, which encodes an output product, and (ii) a operably linked to: (i) a sequence that encodes for a tran sequence encoding at least one microRNA target sequence Scriptional activator product, and (ii) a sequence encoding specific for the at least one input microRNA having a lower one or more microRNA target sequences, such that the expression level than a reference expression level. In Such transcriptional activator product activates the inducible pro multiple-input biological classifier circuits, one of the at moter sequence operably linked to the repressor sequence least two input detector modules is designated a high-input and the sequence encoding the one or more microRNA target 10 detector module for detecting the at least one input micro sequences. In Such embodiments, the sequences encoding RNA expressed at a higher level than a reference expression one or more microRNA target sequences are the same level. Such high-input detector module comprise a consti throughout all the units and components of the high-input tutive or inducible promoter sequence operably linked to (i) detector module, i.e., each unit and component of the a repressor sequence that encodes for a repressor product, high-input detector module detects the same input microR 15 and (ii) a sequence encoding for a microRNA target NA(s). In some embodiments, the inducible promoter of a sequence specific for the at least one input microRNA second regulatory unit is activated by the transcriptional having a higher expression level than a reference expression activator encoded by a first regulatory unit, such that the level. In Such circuits, the repressor product represses the repressor product of the high-input detector module is repressible promoter of the low-input detector module. In expressed only when the transcriptional activator of the Such circuits, each microRNA target sequence encoded by second regulatory unit is expressed following activation by the low-input detector module(s) and the high-input detector the transcriptional activator encoded by the first regulatory module(s) is different from each other, and expression of the unit. In Such embodiments, the sequences encoding one or output product classifies a cell status. more microRNA target sequences are the same throughout In some aspects, multiple-input biological classifier cir all the units and components of the high-input detector 25 cuits are provided for classifying a cell status based on module, i.e., each unit and component of the high-input detecting in parallel an expression pattern of a Subset of at detector module detects the same input microRNA(s). least three different input microRNAs. In such aspects, In some aspects, described herein are multiple-input bio expression of at least three different input microRNAs are logical classifier circuits for classifying a cell status, based detected by at least two input detector modules, such that on detecting in parallel an expression pattern of a Subset of 30 expression at least one of the three different input microR at least two different input microRNAs, each of which is NAS has a lower expression level than a reference expres expressed at a specific level or higher than a reference level, sion level, at least one of the at least three different input Such that the biological classifier circuit circuit comprises at microRNAs has a higher expression level than a reference least two high-input detector modules as described herein. expression level, and wherein one or more of the at least In some aspects, described herein are multiple-input bio 35 three different input microRNAs has a different expression logical classifier circuits for classifying a cell status based on level (higher or lower) than a reference expression level. detecting in parallel an expression pattern of a Subset of at In Such multiple-input biological classifier circuits, one of least three different input microRNAs, each of which is the at least two input detector modules is designated a expressed at a lower level than a reference expression level. low-input detector module for detecting each of the different In Such aspects, the biological classifier circuit comprises 40 input microRNAs expressed at a lower level than a reference one or more low-input detector modules for detecting the at expression level. The low-input detector modules can com least three input microRNAs expressed at a lower level than prise a repressible promoter sequence operably linked to: (i) a reference expression level, where the low-input detector an output sequence that encodes an output product and (ii) module comprises a constitutive or repressible promoter a sequence encoding one or more microRNA target sequence operably linked to: (i) an output sequence that 45 sequences specific for each of the different input microR encodes an output product, and (ii) a sequence encoding at NAs having a lower expression level than a reference least one microRNA target sequence specific for the at least expression level to be detected. The high-input detector one of the at least three input microRNA having a lower modules can comprise a promoter sequence operably linked expression level than a reference expression level; and to (i) a repressor sequence that encodes for a repressor where expression of the output product classifies a cell 50 product and (ii) a sequence encoding a microRNA target Status. sequence, where the microRNA target sequence is specific In some aspects, described herein are multiple-input bio for one of the different input microRNAs having a higher logical classifier circuits for classifying a cell status based on expression level than a reference expression level, and Such detecting in parallel an expression pattern of a Subset of at that the repressor product represses the repressible promoter least two different input microRNAs, where the biological 55 of the low-input detector module. In such circuits, each classifier circuit comprises at least two input detector mod microRNA target sequence encoded by the low-input detec ules. In such aspects, expression of at least two different tor module(s) and the high-input detector module(s) is input microRNAs are detected by at least two types of input different from each other, and expression of the output detector modules, such that at least one of the at least two product classifies a cell status. In some circuits, the repressor different input microRNAs has a lower expression level than 60 protein encoded by the high-input detectors are the same, a reference expression level, and at least one of the at least while in other such circuits the repressor protein can be two different input microRNAs has a higher expression level different. than a reference expression level. In Some embodiments of the multiple-input biological In Such multiple-input biological classifier circuits com classifier circuits described herein, the promoter sequence prising at least two input detector modules, one of the at least 65 operably linked to (i) a repressor sequence and (ii) a two input detector modules is designated a low-input detec sequence encoding a microRNA target sequence, of any of tor module, for detecting the at least one input microRNA the high-input detector modules, can be an inducible pro US 9,458,509 B2 5 6 moter. In some embodiments, such inducible promoters of receptor. In some embodiments, the repressor sequence of at the high-input detector modules can be activated by a least one high-input detector module further comprises a transcriptional activator. sequence encoding for a protein or agent that is a functional In some embodiments of the multiple-input biological or physiological inhibitor of the output product of the classifier circuits described herein, the high-input detector multiple-input biological classifier circuit. module can further comprise one or more regulatory units. In other aspects, provided herein are pharmaceutical com Such regulatory units comprise a constitutive or inducible positions comprising one or more high-input detector mod promoter sequence operably linked to: (i) a sequence that ules and a pharmaceutically acceptable compound. encodes for a transcriptional activator product, and (ii) a In other aspects, described herein are pharmaceutical sequence encoding one or more microRNA target 10 compositions comprising one or more multiple-input bio sequences. Such that the transcriptional activator product logical classifier circuits and a pharmaceutically acceptable activates the inducible promoter sequence operably linked to compound. the repressor sequence and the sequence encoding the one or In other aspects, the multiple-input biological classifier more microRNA target sequences. In some embodiments, circuits described herein are provided for use in identifying the transcriptional activator encoded by the regulatory unit 15 a specific target cell, or a cell population in a population of induces transcription from the promoter sequence operably heterogenous cells. In some embodiments of Such aspects, linked to (i) the repressor sequence and (ii) the sequence the multiple-input biological classifier circuit can be intro encoding the microRNA target sequence of the at least one duced to the heterogenous population of cells using one or high-input detector module of the classifier circuit. In such more vectors comprising the sequences encoding for the embodiments, the sequences encoding one or more micro components of the circuits. In some embodiments, the one or RNA target sequences are the same throughout all the units more vectors is a lentiviral vector or lentiviral particle. In and components of the high-input detector module, i.e., each Some embodiments, the cell or population of heterogenous unit and component of the high-input detector module cells is a mammalian cell or a population of heterogenous detects the same input microRNA(s). mammalian cells. In some embodiments of the multiple-input biological 25 In other aspects, methods are provided for identifying a classifier circuits described herein, the inducible promoter of cell or population of cells based on an expression pattern of a second regulatory unit is activated by the transcriptional at least three different input microRNAs. Such methods activator encoded by a first regulatory unit, such that the comprise introducing any of the high-input detector modules repressor product of the high-input detector module is or multiple-input biological classifier circuits described expressed only when the transcriptional activator of the 30 herein into a cell or population of cells, such that expression second regulatory unit is expressed following activation by of an output product by the cell identifies the cell or the transcriptional activator encoded by the first regulatory population of cells. In some embodiments of these aspects, unit. the cell or population of cells is in vitro, ex vivo, or in vivo. In some embodiments, at least three, at least four, at least In some aspects, methods are provided for diagnosing a five, at least six, at least seven, at least eight, at least nine, 35 disease or condition in a subject in need thereof. Such at least 10, at least 11, at least 12, at least 13, at least 14, at methods comprise administering to a Subject in need thereof least 15, at least 16, at least 17, at least 18, at least 19, or at an effective amount of one or more of any of the high-input least 20 different input microRNAs are detected by the detector modules or multiple-input biological classifier cir multiple-input classifier circuit. cuits described herein, wherein expression of one or more In some embodiments, the at least two detector modules 40 output products is indicative that the Subject has the disease comprise at least two, at least three, at least four, at least five, or condition. In some embodiments of these aspects, the at least six, at least seven, at least eight, at least nine, at least disease or condition can be a cancer, a proliferative disorder, 10, at least 11, at least 12, at least 13, at least 14, at least 15, a metabolic disorder, a neurological disorder, an immuno at least 16, at least 17, at least 18, or at least 19 different logical disorder, or an infection. high-input detector modules. 45 In some aspects, described herein are methods for treating In some embodiments, the output sequence of the circuit a disease or condition in a subject in need thereof. Such encoded by a low-input module comprises at least two, at methods comprise administering to a Subject in need thereof least three, at least four, at least five, at least six, at least an effective amount of one or more of any of the high-input seven, at least eight, at least nine, at least 10, at least 11, at detector modules or multiple-input biological classifier cir least 12, at least 13, at least 14, at least 15, at least 16, at least 50 cuits described herein, such that one or more of the output 17, at least 18, at least 19, or at least 20 different microRNA products is a therapeutic agent. In some embodiments of target sequences. In some embodiments, where the output these aspects, the disease or condition can be a cancer, a sequence of the circuit encoded by a high-input module, no proliferative disorder, a metabolic disorder, a neurological target microRNA target sequences are linked to the sequence disorder, an immunological disorder, or an infection. encoding the output product. 55 In some aspects, multiple-input biological classifier cir In some embodiments, the repressor sequence of at least cuits are provided for use in diagnosing a disease or condi one high-input detector module further comprises a tion in a subject in need thereof. Such that expression of one sequence encoding a microRNA, such that the microRNA is or more output products produced by the multiple-input different from each of the different microRNA inputs biological classifier circuit is indicative that the subject has detected by the modules of the circuit, and such that the 60 the disease or condition. In some embodiments of these output sequence of the circuit, present in a low-input detec aspects, the disease or condition is a cancer, proliferative tor module or in a high-input detector module, further disorder, metabolic disorder, neurological disorder, immu comprises a microRNA target sequence for the microRNA. nological disorder, or infection. In some embodiments of the aspects described herein, the In some aspects, provided herein are multiple-input bio output product is a reporter protein, a transcriptional acti 65 logical classifier circuits for use in treating a disease or vator, a transcriptional repressor, a pro-apoptotic protein, a condition in a subject in need thereof. Such that one or more lytic protein, an enzyme, a cytokine, or a cell-surface output products produced by the multiple-input biological US 9,458,509 B2 7 8 classifier circuit is a therapeutic agent. In some embodi FIGS. 5A-5E show that a classifier circuit can be used to ments of these aspects, the therapeutic agent is a drug or distinguish and specifically kill HeLa cells. Plasmids encod small molecule that causes cell death or inhibition of cell ing the circuits and transfection protocols are listed in Tables proliferation. In some embodiments of these aspects, the 55 and 56. Fluorescent reporter assays are shown in FIGS. disease or condition is a cancer, proliferative disorder, 5A and 5B. FIG. 5A shows schematics of the circuits and metabolic disorder, neurological disorder, immunological controls. O1, CAGop-driven DsRed with target sites for disorder, or infection. HeLa-low microRNAs (miRs-HeLa-low). O2, CAGop driven DsRed without microRNA target sites. R1, CAGop BRIEF DESCRIPTION OF THE DRAWINGS driven Dsked constitutively repressed by rtTA-activated 10 LacI and engineered intronic miR-FF4 with HeLa-low tar FIGS. 1A-1D show a schematic operation of a cell type gets. R2, similar to R1 but without the HeLa-low targets. C1, classifier. FIG. 1A shows multi-input logic used to selec full classifier circuit. C2, circuit variant without HeLa-low tively identify a specific cell type. FIG. 1B depicts a sche targets. FIG. 5B shows experimental results from a classifier matic representation of a HeLa-specific classifier circuit. circuit used to distinguish and kill HeLa cells. In addition to 15 the circuits and controls (FIG. 5A) the cells were also FIG. 1C shows experimental confirmation of various transfected with marker CAG-AmCyan. The constructs used reporter construct knock-downs by corresponding micro in each case are indicated on the X-axis. Each bar represents RNA markers identified by our bioinformatics analysis in the meant-SD of Dsked/AmCyan value with three indepen HeLa, HEK293, and MCF7 cell lines. Scatter plots show dent replicates measured by FACS 48 h post-transfection. flow cytometry data measured at 48 hours post-transfection. All values are normalized to constitutive output level (O1) FIG. 1D depicts the overall knock-down efficiency by the in HeLa cells. Representative images of the cell culture microRNA biomarkers in different cell lines (top). The bars obtained in these experiments are overlays of the DsRed and show meaniSD of DsRed/AmCyan values from three inde AmCyan channels captured 48 h post-transfection. The pendent replicates. The corresponding published microRNA constructs used are indicated above the images. FIGS. 5C cloning frequencies are shown below, indicating the desired 25 and 5D show apoptosis assays in HeLa (5C) and HEK293 inverse relationship between those frequencies and Dsked (SD) cell lines. A complete apoptosis-inducing classifier reporter levels. circuit (Circuit, FIG. 2F) was co-transfected with the FIGS. 2A-2F depict the schematics of a classifier circuit. AmCyan marker to determine cell survival due to selective FIG. 2A shows an abstract network diagram for sensing hBax activation. Each bar in the charts represents the HeLa-low microRNA, whereby an output is directly tar 30 meant-SD of the percentage of AmCyan" cells with three geted for degradation by the marker. FIG. 2B depicts a independent replicates measured by FACS 4 days post detailed circuit diagram for sensing HeLa-low markers. transfection. The histograms compare gated AmCyan" Output mRNA is knocked down by a corresponding marker populations obtained in FACS measurements from pooled via a target sequence fused in this mRNA3'-UTR. DNA and replicas after examining equal number of events in the RNA species are indicated. FIG. 2C shows a coherent type 35 different pools. FIG. 5E shows a comparison of circuit 2 feed-forward motif for sensing HeLa-high microRNAs killing efficiency for two cell lines. that enables output expression by down-regulating a repres FIGS. 6A-6B show fluorescent reporter assays and killing sor (i.e., double-inversion module). FIG. 2D depicts a experiments in cell mixtures. Transfection protocols are detailed circuit diagram for a HeLa-high marker sensor. The listed in Table 57. FIG. 6A shows fluorescent reporter genes, their promoters and microRNA targets used in mod 40 assays. The scheme on the left illustrates experimental ule construction are indicated. FIG. 2E depicts a represen set-up and data analysis. The histograms on the right show tative schematic of a complete classifier circuit. For sim contribution of the two cell types, HeLa and HEK-Cerulean, plicity, four adjacent microRNA target sites are shown as a to the Dsked cell population. The inset shows the fraction wider box and DNA and RNA species are lumped together of DsRed" cells either transfected with the circuit or with as in FIG. 2D. Two double inversion modules for HeLa high 45 constitutively-repressed output, relative to the constitutively markers are shown and rtTA crosstalk is indicated with expressed output for each cell type. FIG. 6B shows apoptotic dotted lines. The logic computed by this classifier circuit is assays in a cell mixture. The scheme at the top of the panel shown. FIG. 2F depicts how, in some embodiments, the illustrates experimental set-up and data analysis. The scatter circuit of FIG. 2E can be modified to result in apoptotic plots at the bottom show the contributions of the HeLa output production. 50 EYFP and HEK293-Cerulean cells to the Dsked" cell popu FIGS. 3A-3B depict extensive validation of a classifier lation considered to be surviving cells. The bar chart shows circuit's logic operation. FIG. 3A shows that four versions of the fraction of surviving cells either transfected with the the circuit with specific microRNA regulatory links inter circuit or with the constitutively-expressed hEBax, relative to rupted (denoted by stars) can be used to emulate the various the number of DsRed" cells measured without hEBax for each combinations of microRNA input levels. FIG. 3B shows 55 cell type. output values measured for all 32 input combinations FIG. 7 depicts initial marker screening. Expression his (Tables 52-54 describe the constructs and experimental tograms for the top 12 HeLa microRNAs, ranked in conditions). The images are overlays of DsRed and AmCyan descending order according to their cloning frequency (CF). channels taken ~48 h post-transfection. The bar charts show Expression levels in HeLa cells are indicated by an arrow in meant-SD of normalized DsRed intensity obtained from 60 each histogram. Horizontal axes show cloning frequency in three independent replicates measured by fluorescence-ac percent units. tivated cell sorting (FACS) ~48 h post-transfection. FIGS. 8A-8G depict a circuit performance analysis and FIG. 4 depicts an optimized sensor configuration for profile determination. FIG. 8A shows a simplified dose HeLa-high markers. Detailed implementation showing indi response of an output to changing concentrations of a vidual DNA and RNA species and a mechanism of operation 65 repressor in a HeLa-high marker sensor. FIG. 8B depicts a are shown. The inset depicts a simplified network diagram of fit of the data shown in FIG. 9A to an exponential output a sensing process. restoration function. The lower and upper bounds of the US 9,458,509 B2 9 10 output amplitude (O and Ox) as well as the theoretical the value in the OFF state (the first three categories). The upper limit on output intensity (O) are shown. FIG. 8C images are overlays of DsRed and AmCyan channels taken shows a dose response of a repressor concentration to ~48 h post-transfection. changing microRNA input levels. Lower and upper bounds FIG. 11 shows an operation of partially-assembled cir of the repressor concentration are shown. FIG. 8D is a cuits in HeLa, HEK293 and MCF7 cell lines. Transfection contour plot of the mapping between two hypothetical protocol is described in Table 58. ON State, no repression of HeLa-high markers A and B and the output of a two-input DsRed output: OFF state, constitutive repression on DsRed circuit that uses them as inputs. Marker concentrations are output: T17-30a, only sensor for miR-17-30a is used; T21, normalized to their levels in HeLa cells denoted as A. only sensor for miR-2 1 is used; T1 41, only sensor for 10 miR-141 is used; "+” represents a combination of sensors. and B that result in 99% output repression relief. FIG. The bar charts show meaniSD of Dsked/AmCyan values 8E depicts plots showing predicted output levels in different from three independent replicates measured by FACS ~48 h. cell lines from different combinations of microRNA markers posttransfection. All Dsked/AmCyan values are normalized relative to the output in HeLa cells. Each marker sensor is to that of HeLa cells at the ON state. Images are overlays of assumed to be tuned to relieve 99% output repression in 15 DsRed and AmCyan channels taken ~48 h post-transfection. HeLa cells by its cognate input marker. The numbers on the FIG. 12 shows a separation of HEK-Cerulean cells from axes are given in cloning frequency (CF) units. Each dot HeLa cells using Cerulean fluorescent channel. The histo represents one cell type and the contour lines show input grams on the left show contributions of the two cell types, combinations that result in 20% output compared to HeLa HeLa and HEK-Cerulean to Cerulean-negative (Cerulean) cells. Dots above the contour line are cell types that generate and Cerulean-positive (Cerulean') cells. The chart on the more than 20% of HeLa output and they represent false right show the relative percentage of HeLa and HEK positive cell types for this specific circuit configuration. Cerulean in Cerulean and Cerulean cells respectively. FIG. 8F shows an analysis of additional microRNA markers FIGS. 13 A-13B show an exemplary parallel operation of not expressed in HeLa cells but highly expressed in cells that classifier circuits. FIG. 13A depicts three hypothetical can be misidentified based on the profile composed of only 25 microRNA markers A1, A2 and A3 that are used to deter miR-21 and miR-17-30a HeLa-high markers. The heat map mine a specific cell state A. Hypothetical microRNA mark shows the cloning frequency of selected HeLa-low markers, ers B1, B2 and B3 are used to determine specific cell state with blue and red colors indicating low and high CF values, B. Cells in state A or B, e.g. two different phases in cancer respectively. FIG. 8G depicts simulated output levels in development, are both intended targets for a multi-purpose different cell types using a full classifier. From left to right, 30 therapeutic agent. Two classifier circuits A and B operating in parallel with no crosstalk between them are used to output levels histogram for a complete set of markers using identify cell types A and B, respectively. RA1 and RA2 are sensor parameters defined in the text; output levels histo 'double-inversion modules in Circuit A; RB1 is the double gram with the 99% repression relief values for HeLa-high inversion module in Circuit B. FIG. 13B shows output marker sensors doubled compared to their default values: 35 proteins A and B represent two different therapeutic agents output levels histogram when the 99% repression relief for type A and B cells, respectively. Outputs A and B are values for the HeLa-high marker sensors are half of the controlled by circuits A and B that detect profiles charac default values. terizing type A and type B cells, respectively. FIGS. 9A-9C show optimization of sensors for highly FIGS. 14A-14C show exemplary operational decisions expressed markers. Transcriptional activator rtTA and 40 that can be executed by a multi-input biological classifier repressor LacI are fused to indicated targets for either circuit comprising an embodiment of a "kill and rescue exogenous siRNA-FF5 or endogenous microRNAs. FF5, output module as described herein. FIG. 14A shows a target for siRNA-FF5: T21, target for miR-21; T17-30a, schematic flow diagram of high-level operation of a multi targets for miR-17 and 30a. Left panels show the schematics input biological classifier circuit. Different outcomes are of different sensor variants. Charts on the right show quan 45 shown depending on whether the cell is a stem cell (elimi titative results measured by FACS 48 h post-transfection. nation required) or a differentiated cell (rescue required). FIG. 9A shows an effect of a coherent feed-forward motif on The cells that do not receive the classifier circuit will be sensor performance in response to exogenous siRNA-FF5. eliminated due to the presence of antibiotic in the cell culture Each bar represents the meant-SD of DsRed/AmCyan value medium. The outcomes that result depending on the cell type with three independent replicates. FIG. 9B shows an effect 50 and on whether the cell is transfected or not is summarized. of LacI dose on sensor performance for highly-expressed FIG. 14B depicts molecular implementation of the sche endogenous microRNA markers. Each bar represents the matic shown in FIG. 14A. The “kill and rescue' output meant-SD of DsRed/AmCyan value obtained from three module shown controls a fusion protein that is cleaved to independent replicates. FIG. 9C shows an effect of rtTA generate a killer protein hEBax and a repressor cI-Krab. The dosage on the performance of sensors for highly-expressed 55 repressor inhibits expression of an antibiotic resistance gene. endogenous microRNA markers. Overall, if the classifier positively identifies a cell as a stem FIG. 10 shows a representative circuit optimization with cell, the fusion protein is expressed at a high level, inducing engineered intronic microRNA miR-FF4. Transfection pro cell death, and inhibiting resistance. If the classifier makes tocol is described in Table 58. Four versions of the circuit a negative decision, neither the apoptotic protein nor the (FIG. 2E), with specific microRNA regulatory links inter 60 repressor of the antibiotic resistance is expressed. Therefore, rupted (denoted as “-”) or functional (denoted as “+”), are the antibiotic resistance gene permits those cells to Survive used to emulate four different combinations of input levels in selective medium. FIG. 14C depicts a schematic of a full for two HeLa-high microRNA markers (FIG. 3A). The bar multi-input biological classifier circuit that identified six charts show meant-SD of DsRed/AmCyan values from three input microRNAS that comprises a kill and rescue output independent replicates measured by FACS ~48 h post 65 module. transfection. The ON:OFF ratio is calculated by dividing the FIG. 15 shows experimental confirmation of microRNA DsRed/AmCyan ratio of the ON state (the last category) by markers in various cell lines. Transiently-transfected bidi US 9,458,509 B2 11 12 rectional constructs include Dsked reporter with fused A profile of interest that a biological classifier is designed microRNA targets (four tandem repeats of the same target to identify can be based on selecting a small, non-redundant fully complementary to the corresponding mature micro set of inputs that together generate a unique and robust RNA sequences), and an internal reference reporter molecular signature for a specific cell type. The classifier AmCyan. Schematics diagrams for bidirectional reporters 5 circuits described herein are designed to identify molecular are shown in the left panel. Transfection experiments were signatures or profiles that comprise both high and low/absent performed with Effectene transfection reagent for all cell inputs using Boolean logic, such as AND-like, OR-like, lines except for SH-SY5Y and T47D. FACS data for NOT-like operations, or any combination thereof. For HEK293, HeLa and MCF7 cells were measured at 48 hours example, a molecular profile to be identified can comprise 10 two different microRNAs that are highly expressed, and post-transfection with BD LSRII flow analyzers using a three different microRNAs that are low/absent. Such bio filter set for AmCyan (405 nm Laser, 460 nm Longpass filter, logical classifier circuits can be used, for example, to 480/40 emission filter and PMT 225 V) and a filter set for selectively identify and destroy cancer cells using specific Dsked (561 nm Laser, 585/20 emission filter and PMT 210 microRNA expression profiles as inputs. Such an approach V). FACS data for SKBR3, DAOY, SH-SY5Y and BE(2)-C 15 allows highly-precise cancer treatments with little collateral were measured at 48 hours post-transfection with BDLSRII damage. Numerous other applications can also benefit from flow analyzers using a filter set for AmCyan (405 nm Laser, accurate single-cell in-vivo identification and classification 510/50 emission filter and PMT 230 V) and a filter set for of highly-complex cell states using the high-input detector Dsked (561 nm laser, 610/20 emission filter and PMT 230 modules and biological classifier circuits, and methods of V). Scatter plots of raw FACS data are shown in the right their use thereof described herein, such as drug screening panel. experiments, developmental studies, pharmacokinetics, FIGS. 16A-16E demonstrate operation of circuits in vari diagnostic and therapeutic applications, and genetic manipu ant cells. CAG-AmCyan was co-transfected in all cases as lations. an internal control. FIG. 16A depicts schematics of a com Accordingly, described herein are multi-input biological plete circuit (C1), partially-assembled circuits (P17-30a, 25 classifier circuits and methods of use thereof for the detec P21, R1, C2 and O1) and controls (O2 and R2). FIG. 16B tion of and discrimination between multiple (i.e., at least shows results from transfection experiments performed with two) inputs. These multi-input biological classifier circuits Effectene transfection reagent. Scatter plots of FACS data use transcriptional and posttranscriptional regulation mecha measured at 48 hours post-transfection with BDLSRII flow nisms in modular components, such as high-input detector analyzers using a filter set for AmCyan (405 nm Laser, 30 modules, in order to classify the status of a cell, i.e., 510/50 emission filter and PMT 230 V) and a filter set for determine whether a cell is in a specific state of interest DsRed (561 nm laser, 610/20 emission filter and PMT 290 defined by a specific subset of two or more markers that V for all cell lines except HEK293 (PMT 230V)). FIG.16C serve as inputs for the circuit. The biological classifier shows results from transfection experiments performed with circuits described herein implement this task by interrogat Nucleofection protocol. Scatter plots of FACS data mea 35 ing the state of the cell through simultaneous assessment of sured at 48 hours post-transfection with BD LSRII flow a predefined Subset of multiple inputs by modular compo analyzers using the same filter sets in FIG. 16B. FIG. 16D nents using Boolean-like logic, such as AND-like, OR-like, shows results from transfection experiments performed with and NOT-like operations. In some embodiments, such cir Nucleofection protocol. Scatter plots of FACS data mea cuits can implement a multi-input AND-like logic function, sured at 48 hours post-transfection with BD LSRII flow 40 where all inputs must be present at their defined levels analyzers using a filter set for AmCyan (405 nm Laser, simultaneously, in order to identify or classify a cell. In other 525/50 emission filter and PMT 200 V) and a filter set for embodiments, such circuits can implement a multi-input Dsked (561 nm laser, 582/15 emission filter and PMT 220 logic function, comprising AND-like, OR-like, or NOT-like V). FIG. 16E is a graph summarizing the results obtained. operations, or any combination thereof, in order to identify Each bar represents the meant-SD of DsRed/AmCyan value 45 or classify a cell. Examples of Such inputs include endog with at least three independent replicates. All values are enous mature microRNAS or transcription factors. normalized to constitutive output level (O1) in HeLa cells. Described herein are multiple-input biological classifier circuits for classifying a cell. A multiple-input biological DETAILED DESCRIPTION classifier circuit classifies a cells status based on an expres 50 sion pattern of a subset of at least two different microRNAs. The high-input detector modules and multi-input biologi Such a biological classifier circuit comprises at least two cal classifier circuits and systems described herein integrate input detector modules, which detect expression of at least Sophisticated sensing, information processing, and actuation two different microRNAs. In some embodiments of the in living cells and permit new directions in basic biology, aspects described herein, a multiple-input biological classi biotechnology and medicine. The multi-input biological 55 fier circuit detects at least three, at least four, at least five, at classifier circuits described herein comprise synthetic, scale least six, at least seven, at least eight, at least nine, at least able transcriptional/post-transcriptional regulatory circuits ten, at least eleven, at least twelve, at least thirteen, at least that are designed to interrogate the status of a cell by fourteen, at least fifteen, at least sixteen, at least seventeen, simultaneously sensing expression levels of multiple endog at least eighteen, at least nineteen, at least twenty, or more, enous inputs, such as microRNAS. The classifier circuits 60 different microRNAs present in a cell or cellular system. then compute whether to trigger a desired output or response In some aspects described herein, input detector modules if the expression levels match a pre-determined profile of are provided comprising different components, such as pro interest. In other words, when operating in a heterogeneous moter sequences, transcriptional activator sequences, tran cell population, the circuits described herein can selectively Scriptional repressor sequences, microRNA target identify a specific cell population expressing a profile of 65 sequences, and output sequences, to be used as modular interest and output a desired response based on the simul components in the biological classifier circuits described taneous interrogation of a multitude of inputs. herein. Such detector or sensor modules are used to link, for US 9,458,509 B2 13 14 example, intracellular, endogenous microRNA activity to not expressing a specific reference profile, i.e., an output the expression level of an output protein, such as a phar product is not expressed, when it does express or match the maceutical agent or a molecule that inpacts cellular activi specific reference profile. ties. Specific combinations of these input detectors are used High-Input Detector Modules or Double-Inversion Sensor to implement molecular Boolean logic comprising AND 5 Modules like, OR-like, NOT-like, or any combination thereof, Bool In some aspects, provided herein are high-input detector ean operations, such that the circuit expresses a specific modules for use in classifying one or more inputs, such as output protein only when all Boolean conditions are satis microRNAs, that are expressed at a specific level or higher fied. Further, in some embodiments, such input detector in a cell or cellular system in comparison to a reference 10 level. modules can be designed such that the biological classifier A “high-input detector module.’” also referred to herein as circuits essentially convert analog input signals into reliable, a "double-inversion sensor module.’ comprises a constitu digital output(s). tive or inducible promoter sequence operably linked to: (i) Depending on the combination of components used in a a repressor sequence that encodes a repressor product, and biological classifier circuit described herein, an input detec 15 (ii) one or more microRNA target sequences, such that the tor module can be designated as a “low input detector one or more microRNA target sequences comprise target module', for detecting microRNAs inputs expressed at low sequences of the one or more input microRNAs the high levels within a cell, or a “high-input detector module, for input module is designed to detect. In some embodiments, detecting microRNAs inputs expressed at high levels within the one or more microRNA target sequences are preferably a cell. Thus, when a cell or cellular system expresses a after the 3' end of the sequence encoding the repressor particular combination of microRNAs and lacks another product. In some embodiments, the one or more microRNA combination of microRNAS, i.e., matches a specific micro target sequences can be before the 5' end of the sequence RNA reference profile for a cell type, as detected by a encoding the repressor product, in an intronic region within combination of high- and low-input detectors respectively the sequence encoding the repressor product, or within the using, for example, AND-like Boolean logic, a classifier 25 coding region of the sequence encoding the repressor prod circuit designed to detect that specific microRNA profile can uct. express an output product. The ability to modulate the type The expression of the repressor product output of a and number of input detector modules, and their constituent high-input detector module, in contrast to a low-input detec components, provide flexibility in the designs and uses of tor module, as described herein, occurs when the input the multiple-input biological classifier circuits described 30 condition(s) of the biological classifier circuit is/are not met. herein. Thus, a high-input detector module is designed to be “OFF.” The biological classifier circuits described herein can be i.e., not express the repressor output product, when one or designed to produce a specific output product, Such as a more input, endogenous, mature microRNAS that is/are reporter molecule, in response to detecting an appropriate intended to be expressed at a specific level or higher than a expression profile within a cell or cellular system. Thus, a 35 reference level is/are detected in a cell or cellular system. A biological classifier circuit produces an output and classifies high-input detector module is designed to be “ON” i.e., a cell only when all the conditions of the circuit are met, i.e., express the repressor output product, when one or more the cell or cellular system is a true positive. These circuits input, endogenous, mature microRNAs that is/are intended can be further modified to incorporate components or mod to be expressed at a specific level or higher than a reference ules that prevent or minimize misclassification of cells, i.e., 40 level is not/are not detected in a cell or cellular system. expression of an output product when a specific microRNA In Such high-input detector modules, the constitutive or profile is not detected. In preferred embodiments of the inducible promoter drives transcription of the repressor aspects described herein, the output level of a biological sequence, resulting in an RNA sequence comprising the classifier circuit is at least two, at least three, at least four, at repressor sequence RNA and the one or more microRNA least five, at least six, at least seven, at least eight, at least 45 target sequences. In the absence of the specific level of the nine, at least ten, at least eleven, at least twelve, at least input, endogenous microRNA(s) that recognizes the one or thirteen, at least fourteen, at least fifteen, at least twenty, at more microRNA target sequences encoded by the high-input least twenty five, at least fifty, at least 100x, at least 1000x detector module, translation of the repressor occurs and the greater in a cell expressing the appropriate combination of module is “ON” and produces the repressor protein. When inputs as opposed to a cell not expressing the appropriate 50 the input microRNA(s) that recognize(s) or is/are specific combination of inputs. for the microRNA target sequence(s) is/are present at a As used herein, when a biological classifier circuit clas specified level or higher, than when the repressor sequence sifies a cell or cellular system correctly and expresses an is transcribed to a repressor RNA and the one or more output product in a cell or cellular system that matches a microRNA target sequences, the input microRNA(s) bind(s) specific reference profile, then the cell or cellular system is 55 its cognate microRNA target sequence(s) and prevent(s) considered to be a “true positive.” As used herein, when a translation of the repressor product. Thus, production of a biological classifier circuit classifies a cell or cellular system repressor product by the high-input detector module in Such correctly and does not express an output product in a cell or embodiments is regulated at a post-transcriptional level. cellular system that does not match a specific reference In some aspects, the high-input detector module further profile, then the cell or cellular system is considered to be a 60 comprises an inducible promoter sequence operably linked “true negative.” As used herein, the term “false positive' to an output sequence encoding an output product, such as refers to a cell or cellular system which is classified by a a reporter output or an apoptosis inducing protein. In Such biological classifier circuit as expressing a specific reference aspects, the inducible promoter sequence is repressed by the profile, i.e., an output product is expressed, when it does not repressor product encoded by the high-input detector mod express or match the specific reference profile. As used 65 ule, such that when the module is “ON” and produces the herein, the term “false negative' refers to a cell or cellular repressor product, the output product is not transcribed, i.e., system which is classified by a biological classifier circuit as the production of the output product by the high-input US 9,458,509 B2 15 16 detector module in Such aspects is regulated at the transcrip Low-Input Detector Modules tional level. Conversely, when the module is "OFF' and Described herein are low-input detector modules for use does not produce the repressor product, the output product as modular components of biological classifier circuits. A is transcribed. Thus, in Such aspects, if the input “low-input detector module' comprises a repressible pro microRNA(s) that recognize(s) the one or more microRNA moter sequence operably linked to an output sequence that target sequences is/are not expressed at the specific level(s) encodes an output product, and at least one microRNA target or higher than the reference level(s), the repressor product is sequence. In some embodiments, the at least one microRNA expressed, and prevents expression of the ouput product. target sequence is preferably after the 3' end of the output In other aspects, the repressor product of a high-input sequence encoding the output product. In some embodi module is specific for the repressible promoter of a low 10 ments, the at least one microRNA target sequence can be input module as described herein, such that production of an before the 5' end of the sequence encoding the output output product is regulated by both a high-input module and product, in an intronic region within the sequence encoding a low-input module. the output product, or within the coding region of the In further embodiments of the aspects described herein, sequence encoding the output product. expression of the repressor product of a high-input detector 15 In Such low-input modules, transcription from the repres module is further regulated at the transcriptional level. In sible promoter results in an output mRNA sequence directly Such embodiments, the high-input detector modules fused at its 3' end with the at least one microRNA target described herein can further comprise one or more regula sequence. A low-input detector module is designed to be tory units. Such “regulatory units, as defined herein, com “OFF, i.e., not express the output product, when an input, prise a constitutive or inducible promoter sequence operably endogenous, mature microRNA that is intended to be low or linked to: (i) a sequence that encodes for a transcriptional absent in a cell in comparison to a reference level is detected. activator product, and (ii) a sequence encoding one or more Accordingly, the output sequence encodes at least one microRNA target sequences. Such that the transcriptional microRNA target sequence that the at least one microRNA activator product activates the inducible promoter sequence intended to be absent or low in a cell specifically recognizes operably linked to the repressor sequence and the sequence 25 or is cognate for. encoding the one or more microRNA target sequences of the In Such low-input detector modules, activation or dere high-inout module. In such embodiments, the promoter pression of the repressible promoter results in transcription sequence operably linked to: (i) a repressor sequence that of the output sequence, resulting in an mRNA of the output encodes a repressor product, and (ii) one or more microRNA sequence fused to at least one microRNA target sequence. If target sequences, is an inducible promoter that is induced by 30 a microRNA specific or cognate for that target sequence is one or more transcriptional activators encoded by the regu present, then that microRNA binds to the congnate target latory units of the high-input module. In some embodiments, sequence, thus preventing translation of the output sequence the inducible promoter of a second regulatory unit is acti upon transcription from the repressible promoter, i.e., no vated by the transcriptional activator encoded by a first output product is expressed, and the low-input module regulatory unit, such that the repressor product of the 35 remains “OFF. In some embodiments, a low-input detector high-input detector module is expressed only when the module comprises an output sequence encoding an output transcriptional activator of the second regulatory unit is product and two different microRNA target sequences. In expressed following activation by the transcriptional acti such embodiments, only when both microRNAs specific for vator encoded by the first regulatory unit. In such embodi the microRNA target sequences are absent or expressed at ments, the sequences encoding one or more microRNA 40 low levels, does translation of the output product occur upon target sequences are the same throughout all the units and transcription from the repressible promoter. Thus, a low components of the high-input detector module, i.e., each unit input detector module comprises at least one microRNA and component of the high-input detector module detects the target sequence to compute the absence or low level of at same input microRNA(s). least one microRNA to generate a response or output. For example, if a reverse tetracycline-controlled transac 45 In some embodiments of the aspects described herein, a tivator is used, the inducible promoter driving expression of low-input detector module comprises a sequence encoding the repressor sequence and the one or more microRNA target at least two, at least three, at least four, at least five, at least sequences comprises a tetracycline response element (TRE). six, at least seven, at least eight, at least nine, at least ten, at In such embodiments, the one or more microRNA target least eleven, at least twelve, at least thirteen, at least four sequences attached or linked to the transcriptional activator 50 teen, at least fifteen, at least sixteen, at least seventeen, at sequence, and the one or more microRNA target sequences least eighteen, at least nineteen, at least twenty, or more, attached or linked to the repressor sequence is/are the same, different microRNA target sequences. Such that the presence of a cognate input endogenous Biological Classifier Circuits microRNA(s) at a specific level or higher than a reference Described herein are multi-input biological classifier cir level(s) in a cell prevents translation of both the transcrip 55 cuits and methods of use thereof for the detection of and tional activator and the repressor product, by binding to discrimination between multiple (i.e., at least two) inputs. its/their cognate microRNA target sequences. Thus, in Such These multi-input biological classifier circuits use transcrip embodiments of the high-input detector modules described tional and posttranscriptional regulation mechanisms herein, expression of the repressor product of a high-input encoded in modular components, such as high-input or detector module is regulated at both the transcriptional level 60 low-input detector modules, and components thereof. Such (i.e., requires binding of the transcriptional activator to the as regulatory units, in order to classify the status of a cell, promoter driving the repressor product sequence for tran i.e., identify whether a cell is in a specific state of interest as scription of mRNA) and at the post-transcriptional level determined by a specific subset of two or more markers that (i.e., binding of the microRNA(s) expressed at the required serve as inputs for the circuit. The biological classifier level(s) to its microRNA target sequence(s) upon transcrip 65 circuits described herein implement this task by interrogat tion of the repressor sequence, prevents translation of the ing the state of the cell through simultaneous assessment of repressor mRNA to repressor protein). a predefined Subset of multiple inputs by modular compo US 9,458,509 B2 17 18 nents, such as high-input or low-input detector modules that transcribed, i.e., the production of the output product by the use Boolean-like logic (i.e., AND-like, OR-like, and NOT high-input detector module in Such aspects is regulated at like operations). the transcriptional level. Conversely, when the module is In some embodiments of the aspects described herein, a “OFF' and does not produce the repressor product, the biological classifier circuit comprises at least one, at least 5 output product is transcribed. Thus, in Such embodiments of two, at least three, at least four, at least five, at least six, at these aspects, if the input microRNA that recognized the at least seven, at least eight, at least nine, at least ten, at least least one microRNA target sequence is not expressed at the eleven, at least twelve, at least thirteen, at least fourteen, at specific level or higher than the reference level, the repressor least fifteen, at least sixteen, at least seventeen, at least product is expressed, and prevents expression of the ouput eighteen, at least nineteen, at least twenty, or more, different 10 product. high-input detector modules, wherein each high-input detec In some embodiments of the aspects described herein, tor module encodes a different microRNA target sequence or each high-input detector module, in a biological classifier microRNA target sequence. In preferred embodiments of the circuit comprising both high- and low-input detector mod aspects described herein, each microRNA target sequence ules, encodes for the same repressor product. In other encoded by a low-input detector module is different from 15 embodiments of the aspects described herein, different high each microRNA target sequence encoded by each high-input input detector modules in a biological classifier circuit detector module in a biological classifier circuit. For encode for different repressor products. example, a biological classifier circuit can comprise one In some embodiments of the aspects described herein, the low-input detector module comprising three different micro same or different repressor products of one or more high RNA target sequences, and four different high-input detector 20 input detector modules are all specific for the repressible modules, each comprising a different microRNA target promoter of the low-input detector module in a biological sequence from each other, and from each of the microRNA classifier circuit, or the promoter sequence of the output target sequences of the low-input module. product of the at least one high-input detector module in a In some embodiments of the aspects described herein, biological classifier circuit comprising only high-input each high-input detector module in a biological classifier 25 detector modules, and thus prevent transcription of the circuit comprising only high-input detector modules output product by the low-input detector module or the at encodes for the same repressor product. In other embodi least one high-input detector module. Thus, in Such embodi ments of the aspects described herein, different high-input ments, unless all the different microRNA inputs that are detector modules in a biological classifier circuit encode for detected by each of the high-input detectors are present and different repressor products. 30 expressed at the specific level or higher than a reference In some embodiments of the aspects described herein, the level, repressor product will be produced by at least one of same or different repressor products of one or more high the high-input detector modules, and repress transcription input detector modules are all specific for the repressible from the repressible promoter of the low-input detector promoter operably linked to the sequence encoding the module and prevent generation of the output product of the output product of a high-input detector module in a biologi- 35 biological classifier circuit. cal classifier circuit comprising only high-input modules, In Some embodiments, a a biological classifier circuit and thus prevent transcription of the output product by the comprises at least one, at least two, at least three, at least circuit. Thus, in such embodiments, unless all the different four, at least five, at least six, at least seven, at least eight, microRNA inputs that are detected by each of the high-input at least nine, at least ten, at least eleven, at least twelve, at detectors are present and expressed at the required level, 40 least thirteen, at least fourteen, at least fifteen, at least repressor product will be produced by at least one of the sixteen, at least seventeen, at least eighteen, at least nine high-input detector modules, and repress transcription from teen, at least twenty, or more, different detector modules, the repressible promoter of the high-input detector module wherein each detector module encodes a different micro encoding for the output product, and prevent generation of RNA target sequence, and at least one low-input module and the output product of the biological classifier circuit. 45 at least one high-input module are included in the circuit. In some embodiments, a a biological classifier circuit In some embodiments of the aspects described herein, comprises at least one, at least two, at least three, at least each microRNA target sequence of a low- or high-input four, at least five, at least six, at least seven, at least eight, detector module is present as two or more multiple, tandem at least nine, at least ten, at least eleven, at least twelve, at repeats in a sequence. Varying the number of copies or least thirteen, at least fourteen, at least fifteen, at least 50 repeats of a microRNA target sequence in a module or sixteen, at least seventeen, at least eighteen, at least nine classifier circuit adds further flexibility and sensitivity to the teen, at least twenty, or more, different high-input detector amount of input microRNA required to inhibit translation of modules, wherein each high-input detector module encodes a given RNA sequence. For example, in a low-input sensor, a different microRNA target sequence, and no low-input each microRNA target sequence attached to or linked to the modules are included in the circuit. In such embodiments, 55 5' end of the sequence encoding the output product can be the biological classifier circuit is designed to detect only present in two or more tandem copies, such as four tandem microRNA inputs that are at a specific level or higher than microRNA target sequence repeats. a reference level, and no microRNA inputs that are absent. Accordingly, in Some embodiments, a microRNA target In Such embodiments, where no low-input module is present sequence is present as at least two tandem repeats, at least in a circuit, at least one high-input module further comprises 60 three tandem repeats, at least four tandem repeats, at least an inducible promoter sequence operably linked to an output five tandem repeats, at least six tandem repeats, at least sequence encoding an output product, such as a reporter seven tandem repeats, at least eight tandem repeats, at least output or an apoptosis inducing protein. In such embodi nine tandem repeats, or at least ten tandem repeats. In Such ments, the inducible promoter sequence is repressed by the embodiments, where a specific microRNA target sequence repressor product encoded by the at least one high-input 65 occurs as tandem repeats in a high-input detector module, detector module, such that when the module is “ON” and the number of tandem repeats of a specific microRNA target produces the repressor product, the output product is not sequence present in a sequence encoding a transcriptional US 9,458,509 B2 19 20 activator in a high-input detector module is the same as the In other embodiments, an output product can, in addition, number of tandem repeats of the specific microRNA target be regulated by expression of a known physiological or sequence present in the sequence encoding the repressor of functional inhibitor of the output product by the circuit. In that same high-input module. Such embodiments, sequences encoding Such inhibitors can In further embodiments of the aspects described herein, be included in at least one high-input detector modules. Such additional modules, units, components and parts can be that at least one high-input module further comprises an added to the biological classifier circuits described herein in inducible promoter operably linked to a sequence encoding order to improve, for example, the sensitivity and the fidelity a repressor, an output product inhibitor, and one or more of a biological classifier circuit. Selectivity of a circuit, i.e., microRNA target sequences. Accordingly, transcription expression of an output product only in cells expressing the 10 appropriate input profile, or the degree of false-positive from the promoter results in an RNA sequence for the outputs, for example, increases as the number of input repressor, output product inhibitor, and the microRNA target factors that the circuit must detect increases. For example, sequence. In the absence of the cognate microRNA for the when the total number of high-input modules increase, i.e., microRNA target sequence, translation of the sequence the required number of microRNAs to be detected at high 15 produces the repressor that prevents transcription of the levels increase, the level of repressor protein increases, output product, and the output product inhibitor that func which prevents transcription of the output product from the tionally inhibits the output product. If such a sequence promoter of the low-input detector module, which makes it further comprises a microRNA targeting its cognate micro more difficult for a circuit to mis-classify a cell or cellular RNA target sequence within the output product sequence, system. then actuation of the circuit via expression of the output Accordingly, in some embodiments of the aspects product can designed to be regulated at the transcriptional, described herein, the sequence encoding the repressor prod post-transcriptional, and functional (post-translational) lev uct of a high-input module of a biological classifier circuit els by the high-input detector module. can further comprise a sequence encoding an intronic micro The biological classifier circuits described herein can be RNA sequence. In Such embodiments, the encoded micro 25 used in various combinations and can be designed to incor RNA is not any of the microRNA inputs being detected by porate sensors for additional input types, such as transcrip the biological classifier circuit. In Such embodiments, the tion factors, to effect other Boolean-like operations in a cells. sequence encoding the output product of the low-input For example, expressing two biological classifier circuits module of a biological classifier circuit, or the at least one that each detect a unique expression profile in a call can be high-input module of a biological classifier circuit compris 30 used to effectively achieve an OR-like Boolean operation, ing only high-input modules, further comprises a microRNA i.e., if a cell expresses either of two expression profiles target sequence specific for the intronic microRNA encoded satisfying an AND-like operation, an output product is by the high-input module. In such embodiments, synethesis generated. An exemplary logic operation for Such a parallel of the output product is being regulated at both the tran circuit design could be: (miRNA-A AND miRNA-B AND Scriptional level (by the repressor protein) and at the post 35 miRNA-C) AND (NOT miRNA-D AND NOT miRNA-E) transcriptional level (by the microRNA encoded by the OR (miRNA-F AND miRNA-G AND miRNA-H) AND circuit). Examples of biological classifier circuits according (NOT miRNA-I AND NOT miRNA-J). to the present invention comprising Such additional compo Accordingly, in other aspects described herein described nents can be found at FIG. 4 and FIG. 10, and in the herein, two or more biological classifier circuits can be Examples section. 40 operated in parallel in order to classify, discriminate or In other embodiments of the biological classifier circuits distinguish, for example, multiple cell types within a het described herein, the high-input detector modules can fur erogenous population, such as two distinct cell populations ther comprise one or more regulatory units. Scuh regulatory in a larger cell population or tissue preparation, using units comprise a constitutive or inducible promoter sequence combinations of OR-like and AND-like Boolean operations. operably linked to: (i) a sequence that encodes for a tran 45 In Such aspects, the biological classifier circuits operating in Scriptional activator product, and (ii) a sequence encoding parallel can be designed so that there is no cross talk one or more microRNA target sequences, such that the between the circuits. An exemplary depiction of Such a transcriptional activator product activates the inducible pro parallel set-up is shown in FIG. 13. In some embodiments of moter sequence operably linked to the repressor sequence Such aspects, upon detection of an appropriate expression and the sequence encoding the one or more microRNA target 50 profile, each circuit produces a different output product. In sequences of the high-input module of the classifier circuit. Some embodiments of Such aspects, upon detection of an In Such embodiments, the promoter sequence of the high appropriate expression profile, each circuit produces the input module is an inducible promoter that is induced by one same output product, such as a therapeutic agent. or more transcriptional activators encoded by the regulatory The sub-sections below further illustrate and describe units of the high-input module. 55 exemplary component parts that can be used according to In some embodiments, the inducible promoter of a second the methods described herein to design biological classifier regulatory unit is activated by the transcriptional activator circuits and low- and high-input detector modules. encoded by a first regulatory unit, Such that the repressor MicroRNAs and MicroRNA Target Sequences product of the high-input detector module is expressed only The biological classifier circuits, detector modules, and when the transcriptional activator of the second regulatory 60 uses thereof described herein, utilize, in part, endogenous unit is expressed following activation by the transcriptional expression of multiple, mature microRNAs as inputs. The activator encoded by the first regulatory unit. In Such modules and circuits are designed to incorporate cognate embodiments, the sequences encoding one or more micro microRNA target sequences that are specific for the mature, RNA target sequences are the same throughout all the units endogenous microRNAs being detected. Described herein and components of the high-input detector module, i.e., each 65 are references and resources, such as programs and data unit and component of the high-input detector module bases found on the World Wide Web, that can be used for detects the same input microRNA(s). obtaining information on microRNAS and their expression US 9,458,509 B2 21 22 patterns, as well as information in regard to cognate micro high complementarities in 3' end and insufficient pairings in RNA sequences and their properties. 5' end. The seed region of the miRNA is a consecutive Mature microRNAs (also referred to as miRNAs) are stretch of seven or eight nucleotides at 5' end. The 3' short, highly conserved, endogenous non-coding regulatory complementary sites have an extensive base pairing to 3' end RNAs (18 to 24 nucleotides in length), expressed from of the miRNA that compensate for imperfection or a shorter longer transcripts (termed “pre-microRNAs) encoded in stretch of base pairing to a seed portion of the miRNA. All animal, plant and virus genomes, as well as in single-celled of these site types are used to mediate regulation by miRNAs eukaryotes. Endogenous miRNAs found in genomes regu and show that the 3' complimentary class of target site is late the expression of target genes by binding to comple used to discriminate among individual members of miRNA mentary sites, termed herein as “microRNA target 10 families in vivo. A genome-wide statistical analysis shows sequences.” in the mRNA transcripts of target genes to cause that on an average one miRNA has approximately 100 translational repression and/or transcript degradation. miR evolutionarily conserved target sites, indicating that miR NAS have been implicated in processes and pathways Such NAS regulate a large fraction of protein-coding genes. as development, cell proliferation, apoptosis, metabolism At present, miRNA databases include miRNAs for and morphogenesis, and in diseases including cancer (S. 15 human, Caenorhabditis elegans, D. melanogaster, Danio Griffiths-Jones et al., “miRBase: tools for microRNA rerio (Zebrafish), Gallus gallus (chicken), and Arabidopsis genomics.” Nuc. Acid. Res., 2007: 36, D154-D158). thaliana. miRNAs are even present in simple multicellular “Expression of a microRNA target sequence” refers to organisms, such as poriferans (sponges) and cnidarians transcription of the DNA sequence that encodes the micro (starlet sea anemone). Many of the bilaterian animal miR RNA target sequence to RNA. In some embodiments, NAs are phylogenetically conserved; 55% of C. elegans expression of a microRNA target sequence is operably miRNAS have homologues in humans, which indicates that linked to or driven by a promoter sequence. In some miRNAs have had important roles throughout animal evo embodiments, a microRNA target sequence comprises part lution. Animal miRNAs seem to have evolved separately of another sequence that is operably linked to a promoter from those in plants because their sequences, precursor sequence. Such as a sequence encoding an output product or 25 structure and biogenesis mechanisms are distinct from those a repressor product, and is said to be linked to, attached to, in plants (Kim V N et al., “Biogenesis of small RNAs in or fused to, the sequence encoding the output product or a animals.” Nat Rev Mol Cell Biol. 2009 February; 10(2): repressor product. 126-39). The way microRNA and their targets interact in animals miRNAs useful for designing the modules and circuits and plants is different in certain aspects. Translational 30 described herein can be found at a variety of databases as repression is thought to be the primary mechanism in known by one of skill in the art, such as those described at animals, with transcript degradation the dominant mecha “miRBase: tools for microRNA genomics.” Nuc. Acid. Res., nism for plant target transcripts. The difference in mecha 2007: 36 (Database Issue), D154-D158; “miRBase: micro nisms lies in the fact that plant miRNA exhibits perfect or RNA sequences, targets and gene nomenclature. Nuc. Acid. nearly perfect base pairing with the target but in the case of 35 Res., 2006 34 (Database Issue):D140-D144; and “The animals, the pairing is rather imperfect. Also, miRNAS in microRNA Registry. Nuc. Acid. Res., 2004 32 (Database plants bind to their targets within coding regions cleaving at Issue): D109-D111), which are incorporated herein in their single sites whereas most of the miRNA binding sites in entirety by reference. animals are in the 3' un-translated regions (UTR). In ani In some embodiments of the aspects described herein, a mals, functional miRNA:miRNA target sequence duplexes 40 microRNA target sequence can be an engineered microRNA are found to be more variable in structure and they contain target sequence, Such as one having full sequence comple only short complementary sequence stretches, interrupted by mentarity to an input microRNA of interest. In addition, a gaps and mismatches. In animal miRNA: miRNA target number of computational tools are available for animal and sequence interactions, multiplicity (one miRNA targeting plant miRNA target sequence identification. Most of these more than one gene) and cooperation (one gene targeted by 45 approaches are based on evolutionary conservation and the several miRNAs) are very common but rare in the case of presence of miRNA target sites in 3' UTRs of target mRNAs plants. All these make the approaches in miRNA target and their relatively better complementarities to 5' end of prediction in plants and animals different in details (V. miRNAs. Tools like miRCheck (Johnes-Rahoades MW and Chandra et al., “MTar: a computational microRNA target Bartel D P: “Computational identification of Plant microR prediction architecture for human transcriptome.” BMC 50 NAs and their targets, inducing a stress-induced miRNA. Bioinformatics 2010, 11 (Suppl 1):S2). Mol Cell 2004, 14:787-799), findmiRNA (Adai A et al., Experimental evidence shows that the miRNA target “Computational Prediction of miRNAs in Arabidopsis thali sequence needs enough complementarities in either the 3' ana.” Genome Research 2005, 15:78-91), PatScan (Rhoades end or in the 5' end for its binding to a miRNA. Based on B et al., “Prediction of Plant microRNA Targets.” Cell 2002, these complementarities of miRNA: miRNA target sequence 55 110:513-520), and mirU (Zhang Y. “miRU: an automated target duplex, the miRNA target sequence can be divided plant miRNA target prediction server: Nucleic Acids Res into three main classes. They are the 5' dominant seed site 2005, 33:W701-W704) can be used for rapid prediction of targets (5' seed-only), the 5' dominant canonical seed site miRNA target sequences in plants where perfect comple targets (5' dominant) and the 3' complementary seed site mentarities of miRNA and miRNA target sequences are targets (3' canonical). The 5' dominant canonical targets 60 found. possess high complementarities in 5' end and a few comple Target prediction in animal transcriptomes can call for mentary pairs in 3' end. The 5' dominant seed-only targets more complex algorithms due to the imperfect complemen possess high complementarities in 5' end (of the miRNA) tarities of miRNA: mRNA pairs. Databases, computational and only a very few or no complementary pairs in 3' end. programs, and references for use in predicting and obtaining The seed-only sites have a perfect base pairing to the seed 65 miRNA target sequences for animal cells that can be used in portion of 5' end of the miRNA and limited base pairing to the biological classifier circuits and methods of their use 3' end of the miRNA. The 3' complimentary targets have described herein, include, but are not limited to: (i) PicTar US 9,458,509 B2 23 24 (Grun D et al., “microRNA target predictions across seven non-conserved targets. (ix) MTar can identify all known Drosophila species and comparison to mammalian targets.” three types of miRNA targets (5' seed-only, 5' dominant, and PLoS Comput Biol 2005, 1:e13: Kreket al., “Combinatorial 3' canonical). MTar uses all these features and also takes into microRNA target predictions.” Nat Genet. 2005, 37:495 consideration the structural and positional features of 500; Lall S, et al., “A genome-wide map of conserved miRNA: microRNA target sequences. The method predicts microRNA targets in C. elegans. Curr Biol 2006, 16:460 the three types of targets with a prominent accuracy (92.8%), 471), which predicts miRNA targets in Drosophila and other sensitivity (94.5%) and specificity (90.5%). The false posi species based on complementarities between miRNA and 3' tive rate of MTar is 9.5% for MFEs-17.0 Kcal/mol (V. UTR of mRNA sequence. PicTar uses techniques like seed Chandra et al., “MTar: a computational microRNA target match, free energy calculation and species conservation. Its 10 prediction architecture for human transcriptome.” BMC false positive rate has been estimated to be 30.0%. (ii) Bioinformatics 2010, 11 (Suppl 1):S2). TargetScan (Lewis B P et al. “Prediction of mammalian Promoters microRNA targets.” Cell 2003, 115:787-798) is a tool used Provided herein are promoter sequences for use in the to predict miRNAs which bind to 3' UTRs of vertebrate multi-input biological classifier circuits, and component transcriptomes. TargetScan has been used to predict more 15 low- and high-input detector modules. In some embodi than 451 human microRNA targets. TargetSanS, a modified ments of the aspects described herein, the promoters used in version of TargetScan, omits multiple sites in each target and the multi-input biological classifier circuits and low- and further filters the targets using thermodynamic stability high-input detector modules drive expression of an operably criterion. Using this modified method more than 5300 linked output sequence or repressor sequence, and one or human genes and their microRNA target sequences have more microRNA target sequences. been predicted as possible targets of miRNAs (Lewis Bet The term “promoter as used herein refers to any nucleic al., “Conserved Seed Pairing. Often Flanked by Adenosines, acid sequence that regulates the expression of another Indicates that Thousands of Human Genes are microRNA nucleic acid sequence by driving transcription of the nucleic Targets.” Cell 2005, 120:15-20). The false positive rate acid sequence, which can be a heterologous target gene, varies between 22% to 31%. (iii) MiRanda (John B et al. 25 encoding a protein or an RNA. Promoters can be constitu “Human MicroRNA Targets.” PLoS Biol 2004, 2:e363: tive, inducible, activateable, repressible, tissue-specific, or Enright A J et al. “MicroRNA Targets in Drosophila.” any combination thereof. A promoter is a control region of Genome Biol 2003, 5:R1; Betel D et al., “The microR a nucleic acid sequence at which initiation and rate of NA.org resource: targets and expression.” Nucleic Acids transcription of the remainder of a nucleic acid sequence are Res 2008, 36:D149-D153), a target prediction tool, relies on 30 controlled. A promoter can also contain genetic elements at the evolutionary relationships between miRNAs and their which regulatory proteins and molecules can bind, such as targets. This tool focuses on sequence matching of miRNA: RNA polymerase and other transcription factors. In some miRNA target sequences, by estimating energy of physical embodiments of the aspects, a promoter can drive the interaction. The miRanda algorithm works by Scanning for expression of a transcription factor that regulates the expres miRNA complementary pairs in the 3' UTR of an mRNA. 35 sion of the promoter itself, or that of another promoter used Using this software, a large number of miRNA target in another modular component described herein. sequences have been identified including protein-coding A promoter can be said to drive expression or drive genes in Homo sapiens. The false positive rate was esti transcription of the nucleic acid sequence that it regulates. mated to be 24%. (iv) DIANA-microT (Kiriakidou Met al., The phrases “operably linked, “operatively positioned.” “A combined computational-experimental approach predicts 40 “operatively linked,” “under control,” and “under transcrip human microRNA targets.” Genes Dev 2004, 18:1165-1178) tional control' indicate that a promoter is in a correct is a method based on the rules of single miRNA: mRNA functional location and/or orientation in relation to a nucleic pairing. It predicts targets which contain a single comple acid sequence it regulates to control transcriptional initiation mentary site based on binding energies. (v) MiTarget algo and/or expression of that sequence. An "inverted promoter” rithm (Kim Set al., “MiTarget: miRNA target gene predic 45 is a promoter in which the nucleic acid sequence is in the tion using an SVM.” BMC Bioinformatics 2006, 7:441) reverse orientation, such that what was the coding strand is combines thermodynamics based processing of RNA: RNA now the non-coding strand, and Vice versa. In addition, in duplex interactions with the sequence analysis to predict various embodiments described herein, a promoter can or miRNA target sequences. (vi) RNAhybrid is another com cannot be used in conjunction with an "enhancer, which puter program for predicting miRNA targets based on 50 refers to a cis-acting regulatory sequence involved in the complementarities between miRNA and 3' UTR of coding transcriptional activation of a nucleic acid sequence down sequence (Rehmsmeier M et al., “Fast and Effective predic stream of the promoter. The enhancer can be located at any tion of microRNA/target duplexes.” RNA 2004, 10:1507 functional location before or after the promoter, and/or the 1517. (vii) MovingTarget (Burgler C and Macdonald PM, encoded nucleic acid. A promoter for use in the biological “Prediction and verification of microRNA targets by Moving 55 classifier circuits described herein can also be “bidirec Targets, a highly adaptable prediction method.” BMC Bio tional,” wherein Such promoters can initiate transcription of informatics 2005, 6:88) is a program used to detect miRNA operably linked sequences in both directions. target sequences satisfying a set of biological constraints. A promoter can be one naturally associated with a gene or (viii) MicroTar (Thadani R and Tammi M T: “MicroTar: sequence, as can be obtained by isolating the 5' non-coding Predicting microRNA targets from RNA duplexes.” BMC 60 sequences located upstream of the coding segment and/or Bioinformatics 2006, 7 (Suppl 5):S20) is a program that has exon of a given gene or sequence. Such a promoter can be been used to detect target sites in C. elegans, Drosophila and referred to as "endogenous.” Similarly, an enhancer can be mouse by target complementarities and thermodynamic one naturally associated with a nucleic acid sequence, data. This algorithm uses predicted free energies of located either downstream or upstream of that sequence. unbounded mRNA and putative mRNA:miRNA hetero 65 Alternatively, certain advantages can be gained by posi dimers, implicitly addressing the accessibility of the mRNA tioning a coding nucleic acid segment under the control of 3' UTR. This software is able to predict both conserved and a recombinant or heterologous promoter, which refers to a US 9,458,509 B2 25 26 promoter that is not normally associated with the encoded by, in part, either of two mechanisms. In particular embodi nucleic acid sequence in its natural environment. A recom ments described herein, the biological classifier circuits and binant or heterologous enhancer refers to an enhancer not their component low- and high-input modules comprise normally associated with a nucleic acid sequence in its suitable inducible promoters that can be dependent upon natural environment. Such promoters or enhancers can transcriptional activators that, in turn, are reliant upon an include promoters or enhancers of other genes; promoters or environmental inducer. In other embodiments, the inducible enhancers isolated from any other prokaryotic, viral, or promoters can be repressed by a transcriptional repressor eukaryotic cell; and synthetic promoters or enhancers that which itself is rendered inactive by an environmental are not “naturally occurring’, i.e., contain different elements inducer. Such as the product of a sequence driven by another of different transcriptional regulatory regions, and/or muta 10 promoter. Thus, unless specified otherwise, an inducible tions that alter expression through methods of genetic engi promoter can be either one that is induced by an inducing neering that are known in the art. In addition to producing agent that positively activates a transcriptional activator, or nucleic acid sequences of promoters and enhancers syntheti one which is derepressed by an inducing agent that nega cally, sequences can be produced using recombinant cloning tively regulates a transcriptional repressor. In Such embodi and/or nucleic acid amplification technology, including 15 ments of the various aspects described herein, where it is PCR, in connection with the biological classifier circuits and required to distinguish between an activating and a repress modules described herein (see U.S. Pat. No. 4,683.202, U.S. ing inducing agent, explicit distinction will be made. Pat. No. 5,928,906, each incorporated herein by reference). Inducible promoters that are useful in the biological Furthermore, it is contemplated that control sequences that classifier circuits and methods of use described herein direct transcription and/or expression of sequences within include those controlled by the action of latent transcrip non-nuclear organelles Such as mitochondria, chloroplasts, tional activators that are subject to induction by the action of and the like, can be employed as well. environmental inducing agents. Some non-limiting Inducible Promoters examples include the copper-inducible promoters of the As described herein, an “inducible promoter' is one that yeast genes CUP1, CRS5, and SOD1 that are subject to is characterized by initiating or enhancing transcriptional 25 copper-dependent activation by the yeast ACE 1 transcrip activity when in the presence of influenced by, or contacted tional activator (see e.g. Strain and Culotta, 1996; Hottiger by an inducer or inducing agent. An "inducer or “inducing et al., 1994: Lapinskas et al., 1993; and Gralla et al., 1991). agent can be endogenous, or a normally exogenous com Alternatively, the copper inducible promoter of the yeast pound or protein that is administered in Such a way as to be gene CTT1 (encoding cytosolic catalase T), which operates active in inducing transcriptional activity from the inducible 30 independently of the ACE 1 transcriptional activator (Lap promoter. In some embodiments, the inducer or inducing inskas et al., 1993), can be utilized. The copper concentra agent, i.e., a chemical, a compound or a protein, can itself be tions required for effective induction of these genes are the result of transcription or expression of a nucleic acid suitably low so as to be tolerated by most cell systems, sequence (i.e., an inducer can be a transcriptional repressor including yeast and Drosophila cells. Alternatively, other protein, such as Lad), which itself can be under the control 35 naturally occurring inducible promoters can be used in the of an inducible promoter. In some embodiments, an induc present invention including: Steroid inducible gene promot ible promoter is induced in the absence of certain agents, ers (see e.g. Oligino et al. (1998) Gene Ther. 5: 491-6): Such as a repressor. In other words, in Such embodiments, galactose inducible promoters from yeast (see e.g. Johnston the inducible promoter drives transcription of an operably (1987) Microbiol Rev 51: 458-76; Ruzzi et al. (1987) Mol linked sequence except when the repressor is present. 40 Cell Biol 7: 991-7); and various heat shock gene promoters. Examples of inducible promoters include but are not limited Many eukaryotic transcriptional activators have been shown to, tetracycline, metallothionine, ecdysone, mammalian to function in a broad range of eukaryotic host cells, and so, viruses (e.g., the adenovirus late promoter, and the mouse for example, many of the inducible promoters identified in mammary tumor virus long terminal repeat (MMTV-LTR)) yeast can be adapted for use in a mammalian host cell as and other Steroid-responsive promoters, rapamycin respon 45 well. For example, a unique synthetic transcriptional induc sive promoters and the like. tion system for mammalian cells has been developed based Inducible promoters useful in the biological classifier upon a GAL4-estrogen receptor fusion protein that induces circuits, methods of use, and systems described herein are mammalian promoters containing GAL4 binding sites capable of functioning in both prokaryotic and eukaryotic (Braselmann et al. (1993) Proc Natl Acad Sci USA 90: host organisms. In some embodiments of the different 50 1657-61). These and other inducible promoters responsive aspects described herein, mammalian inducible promoters to transcriptional activators that are dependent upon specific are included, although inducible promoters from other inducers are suitable for use with the biological classifier organisms, as well as synthetic promoters designed to func circuits described herein. tion in a prokaryotic or eukaryotic host can be used. One Inducible promoters useful in the biological classifier important functional characteristic of the inducible promot 55 circuits and methods of use disclosed herein also include ers described herein is their ultimate inducibility by expo those that are repressed by “transcriptional repressors” that Sure to an externally applied inducer, such as an environ are subject to inactivation by the action of environmental, mental inducer. Appropriate environmental inducers include external agents, or the product of another gene. Such induc exposure to heat (i.e., thermal pulses or constant heat ible promoters can also be termed “repressible promoters' exposure), various steroidal compounds, divalent cations 60 where it is required to distinguish between other types of (including Cu" and Zn"), galactose, tetracycline or doxy promoters in a given module or component of a biological cycline, IPTG (isopropyl-B-D thiogalactoside), as well as classifier circuit described herein. Examples include pro other naturally occurring and synthetic inducing agents and karyotic repressors that can transcriptionally repress eukary gratuitous inducers. otic promoters that have been engineered to incorporate The promoters for use in the biological classifier circuits 65 appropriate repressor-binding operator sequences. In some and low- and high-input modules described herein encom embodiments, repressors for use in the circuits described pass the inducibility of a prokaryotic or eukaryotic promoter herein are sensitive to inactivation by physiologically benign US 9,458,509 B2 27 28 agent. Thus, where a lac repressor protein is used to control genes, inducible by various stresses; hormone-inducible the expression of a promoter sequence that has been engi genes, such as the estrogen gene promoter, and such. neered to contain a lacO operator sequence, treatment of the The administration or removal of an inducer or repressor host cell with IPTG will cause the dissociation of the lac as disclosed herein results in a switch between the “on” or repressor from the engineered promoter containing a lacO “off” states of the transcription of the operably linked operator sequence and allow transcription to occur. Simi heterologous target gene. Thus, as defined herein the “on” larly, where a tet repressor is used to control the expression state, as it refers to a promoter operably linked to a nucleic of a promoter sequence that has been engineered to contain acid sequence, refers to the state when the promoter is a tetO Operator sequence, treatment of the host cell with actively driving transcription of the operably linked nucleic tetracycline or doxycycline will cause the dissociation of the 10 acid sequence, i.e., the linked nucleic acid sequence is tet repressor from the engineered promoter and allow tran expressed. Several Small molecule ligands have been shown Scription of the sequence downstream of the engineered to mediate regulated gene expressions, either in tissue cul promoter to occur. ture cells and/or in transgenic animal models. These include An inducible promoter useful in the methods and systems the FK1012 and rapamycin immunosupressive drugs (Spen as disclosed herein can be induced by one or more physi 15 cer et al., 1993; Magari et al., 1997), the progesterone ological conditions, such as changes in pH, temperature, antagonist mifepristone (RU486) (Wang, 1994; Wang et al., radiation, osmotic pressure, Saline gradients, cell Surface 1997), the tetracycline antibiotic derivatives (Gossen and binding, and the concentration of one or more extrinsic or Bujard, 1992: Gossen et al., 1995; Kistner et al., 1996), and intrinsic inducing agents. The extrinsic inducer or inducing the insect steroid hormone ecdysone (No et al., 1996). All of agent can comprise amino acids and amino acid analogs, these references are herein incorporated by reference. By saccharides and polysaccharides, nucleic acids, protein tran way of further example, Yao discloses in U.S. Pat. No. Scriptional activators and repressors, cytokines, toxins, 6,444,871, which is incorporated herein by reference, pro petroleum-based compounds, metal containing compounds, karyotic elements associated with the tetracycline resistance salts, ions, enzyme Substrate analogs, hormones, and com (tet) operon, a system in which the tet repressor protein is binations thereof. In specific embodiments, the inducible 25 fused with polypeptides known to modulate transcription in promoter is activated or repressed in response to a change of mammalian cells. The fusion protein is then directed to an environmental condition, Such as the change in concen specific sites by the positioning of the tet operator sequence. tration of a chemical, metal, temperature, radiation, nutrient For example, the tet repressor has been fused to a transac or change in pH. Thus, an inducible promoter useful in the tivator (VP16) and targeted to a tet operator sequence methods and systems as disclosed herein can be a phage 30 positioned upstream from the promoter of a selected gene inducible promoter, nutrient inducible promoter, tempera (Gussen et al., 1992: Kim et al., 1995; Hennighausen et al., ture inducible promoter, radiation inducible promoter, metal 1995). The tet repressor portion of the fusion protein binds inducible promoter, hormone inducible promoter, steroid to the operator thereby targeting the VP16 activator to the inducible promoter, and/or hybrids and combinations specific site where the induction of transcription is desired. thereof. 35 An alternative approach has been to fuse the tet repressor to Promoters that are inducible by ionizing radiation can be the KRAB repressor domain and target this protein to an used in certain embodiments, where gene expression is operator placed several hundred base pairs upstream of a induced locally in a cell by exposure to ionizing radiation gene. Using this system, it has been found that the chimeric such as UV or x-rays. Radiation inducible promoters include protein, but not the tet repressor alone, is capable of pro the non-limiting examples of foS promoter, c-jun promoter 40 ducing a 10 to 15-fold suppression of CMV-regulated gene or at least one CArG domain of an Egr-1 promoter. Further expression (Deuschle et al., 1995). non-limiting examples of inducible promoters include pro One example of a repressible promoter useful in the moters from genes such as cytochrome P450 genes, induc modules and biological classifier circuits described herein is ible heat shock protein genes, metallothionein genes, hor the Lac repressor (lacR)/operator/inducer system of E. coli mone-inducible genes, such as the estrogen gene promoter, 45 that has been used to regulate gene expression by three and such. In further embodiments, an inducible promoter different approaches: (1) prevention of transcription initia useful in the methods and systems as described herein can be tion by properly placed lac operators at promoter sites (Hu Zn" metallothionein promoter, metallothionein-1 promoter, and Davidson, 1987: Brown et al., 1987: Figge et al., 1988: human metallothionein IIA promoter, lac promoter, lacO Fuerst et al., 1989: Deuschle et al., 1989; (2) blockage of promoter, mouse mammary tumor virus early promoter, 50 transcribing RNA polymerase II during elongation by a mouse mammary tumor virus LTR promoter, triose dehy LacR/operator complex (Deuschle et al. (1990); and (3) drogenase promoter, herpes simplex virus thymidine kinase activation of a promoter responsive to a fusion between promoter, simian virus 40 early promoter or retroviral LacR and the activation domain of herpes simples virus myeloproliferative sarcoma virus promoter. Examples of (HSV) virion protein 16 (VP16) (Labow et al., 1990; Baim inducible promoters also include mammalian probasin pro 55 et al., 1991). In one version of the Lac system, expression of moter, lactalbumin promoter, GRP78 promoter, or the bac lac operator-linked sequences is constitutively activated by terial tetracycline-inducible promoter. Other examples a LacR-VP16 fusion protein and is turned off in the presence include phorbol ester, adenovirus E1A element, interferon, of isopropyl-B-D-1-thiogalactopyranoside (IPTG) (Labow and serum inducible promoters. et al. (1990), cited supra). In another version of the system, Inducible promoters useful in the modules and biological 60 a lacR-VP16 variant is used that binds to lac operators in the classifier circuits as described herein for in vivo uses can presence of IPTG, which can be enhanced by increasing the include those responsive to biologically compatible agents, temperature of the cells (Baim et al. (1991), cited supra). Such as those that are usually encountered in defined animal Thus, in some embodiments described herein, components tissues or cells. An example is the human PAI-1 promoter, of the Lac System are utilized. For example, a lac operator which is inducible by tumor necrosis factor. Further suitable 65 (LacO) can be operably linked to tissue specific promoter, examples include cytochrome P450 gene promoters, induc and control the transcription and expression of the heterolo ible by various toxins and other agents; heat shock protein gous target gene and another repressor protein, Such as the US 9,458,509 B2 29 30 TetR. Accordingly, the expression of the heterologous target cin-dependent transactivator, wherein providing a macrollide gene is inversely regulated as compared to the expression or antibiotic represses transgene expression. In the E system, presence of Lac repressor in the system. the binding of the repressor to the operator results in Components of the tetracycline (Tc) resistance system of repression of transgene expression. Therein, in the presence E. coli have also been found to function in eukaryotic cells 5 of macrollides gene expression is induced. and have been used to regulate gene expression. For Fussenegger et al. (2000) describe repressible and induc example, the Tet repressor (TetR), which binds to tet opera ible systems using a Pip (pristinamycin-induced protein) tor (tetO) sequences in the absence of tetracycline or doxy repressor encoded by the streptogramin resistance operon of cycline and represses gene transcription, has been expressed Streptomyces coelicolor, wherein the systems are responsive in plant cells at Sufficiently high concentrations to repress 10 transcription from a promoter containing tet operator to streptogramin-type antibiotics (Such as, for example, sequences (Gatz, C. et al. (1992) Plant J. 2:397-404). In pristinamycin, Virginiamycin, and Synercid). The Pip DNA some embodiments described herein, the Tet repressor sys binding domain is fused to a VP16 transactivation domain or tem is similarly utilized in the biological classifier circuits to the KRAB silencing domain, for example. The presence and low- and high-input detector modules described herein. 15 or absence of for example, pristinamycin, regulates the A temperature- or heat-inducible gene regulatory system PipON and PipOFF systems in their respective manners, as can also be used in the circuits and modules described described therein. herein, Such as the exemplary TIGR system comprising a Another example of a promoter expression system useful cold-inducible transactivator in the form of a fusion protein for the modules and biological classifier circuits described having a heat shock responsive regulator, rheA, fused to the herein utilizes a quorum-sensing (referring to particular VP16 transactivator (Weber et al., 2003a). The promoter prokaryotic molecule communication systems having dif responsive to this fusion thermosensor comprises a rheC) fusible signal molecules that prevent binding of a repressor element operably linked to a minimal promoter, Such as the to an operator site, resulting in derepression of a target minimal version of the human cytomegalovirus immediate regulon) system. For example, Weber et al. (2003b) employ early promoter. At the permissive temperature of 37°C., the 25 a fusion protein comprising the Streptomyces coelicolor cold-inducible transactivator transactivates the exemplary quorum-sending receptor to a transactivating domain that rheo-CMVmin promoter, permitting expression of the target regulates a chimeric promoter having a respective operator gene. At 41° C., the cold-inducible transactivator no longer that the fusion protein binds. The expression is fine-tuned transactivates the rheC) promoter. Any such heat-inducible or with non-toxic butyrolactones, such as SCB1 and MP133. heat-regulated promoter can be used in accordance with the 30 In Some embodiments, multiregulated, multigene gene circuits and methods described herein, including but not limited to a heat-responsive element in a heat shock gene expression systems that are functionally compatible with (e.g., hsp20-30, hsp27, hsp40, hsp60, hsp70, and hsp90). one another are utilized in the modules and biological See Easton et al. (2000) Cell Stress Chaperones 5(4):276 classifier circuits described herein (see, for example, Kramer 290; Csermely et al. (1998) Pharmacol Ther79(2): 129-168: 35 et al. (2003)). For example, in Weber et al. (2002), the Ohtsuka & Hata (2000) Int J Hyperthermia 16(3):231-245; macrollide-responsive erythromycin resistance regulon sys and references cited therein. Sequence similarity to heat tem is used in conjunction with a streptogramin (PIP)- shock proteins and heat-responsive promoter elements have regulated and tetracycline-regulated expression systems. also been recognized in genes initially characterized with Other promoters responsive to non-heat stimuli can also respect to other functions, and the DNA sequences that 40 be used. For example, the mortalin promoter is induced by confer heat inducibility are suitable for use in the disclosed low doses of ionizing radiation (Sadekova (1997) Int J gene therapy vectors. For example, expression of glucose Radiat Biol 72(6):653-660), the hsp27 promoter is activated responsive genes (e.g., grp94, grp78, mortalin/grp75) (Mer by 17-B-estradiol and estrogen receptor agonists (Porter et ricket al. (1997) Cancer Lett 119(2): 185-190; Kiang et al. al. (2001) J MoI Endocrinol 26(1):31-42), the HLA-G (1998) FASEB J 12(14): 1571-16-579), calreticulin (Szew 45 promoter is induced by arsenite, hsp promoters can be czenko-Pawlikowski et al. (1997) MoI Cell Biochem 177 activated by photodynamic therapy (Luna et al. (2000) (1-2): 145-1 52); clusterin (Viard et al. (1999) J Invest Cancer Res 60(6): 1637-1 644). A suitable promoter can Dermatol 112(3):290–296; Michel et al. (1997) Biochem J incorporate factors such as tissue-specific activation. For 328(Pt 1):45-50; Clark & Griswold (1997) J Androl 18(3): example, hsp70 is transcriptionally impaired in stressed 257-263), histocompatibility class I gene (HLA-G) (Ibrahim 50 neuroblastoma cells (Drujan & De Maio (1999) 12(6):443 et al. (2000) Cell Stress Chaperones 5(3):207-218), and the Kunitz protease isoform of amyloid precursor protein (Shep 448) and the mortalin promoter is up-regulated in human herdet al. (2000) Neuroscience 99(2):317-325) are upregu brain tumors (Takano et al. (1997) Exp Cell Res 237(1):38 lated in response to heat. In the case of clusterin, a 14 base 45). A promoter employed in methods described herein can pair element that is sufficient for heat-inducibility has been 55 show selective up-regulation in tumor cells as described, for delineated (Michel et al. (1997) Biochem J328(Pt1):45-50). example, for mortalin (Takano et al. (1997) Exp Cell Res Similarly, a two sequence unit comprising a 10- and a 237(1):38-45), hsp27 and calreticulin (Szewczenko-Paw 14-base pair element in the calreticulin promoter region has likowski et al. (1997) MoI Cell Biochem 177(1-2): 145-152: been shown to confer heat-inducibility (Szewczenko-Paw Yu et al. (2000) Electrophoresis 2 1 (14):3058-3068)), grp94 likowski et al. (1997) MoI Cell Biochem 177(1-2): 145-1 60 and grp78 (Gazit et al. (1999) Breast Cancer Res Treat 52). 54(2): 135-146), and hsp27, hsp70, hsp73, and hsp90 (Car Other inducible promoters useful in the biological clas dillo et al. (2000) Anticancer Res 2006B):4579-4583: Strik sifier circuits described herein include the erythromycin et al. (2000) Anticancer Res 20(6B):4457-4552). resistance regulon from E. coli, having repressible (E) and In some embodiments, the inducible promoter comprises inducible (E) systems responsive to macrollide antibiotics, 65 an Anhydrotetracycline (aTc)-inducible promoter as pro Such as erythromycin, clarithromycin, and roXithromycin vided in PLtetO-1 (Pubmed Nucleotide# U66309) with the (Weber et al., 2002). The E system utilizes an erythromy sequence comprising: US 9,458,509 B2 31 32

(SEQ ID NO: 1) GCATGCTCCCTATCAGTGATAGAGATTGACATCCCTATCAGTGATAGAGATACTGAGCACAT

CAGCAGGACGCACTGACCAGGA.

In some embodiments, the inducible promoter is an ara binose-inducible promoter P, comprising the sequence: Anasaccartorcaratrocarcascarraccarcacrocarcrafécific,

CGCTAACCAAACCGGTAACCCCGCTTATTAAAAGCATTCTGTAACAAAGCGGGACCAAAGC

CATGACAAAAACGCGTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGATTAT

TTGCACGGCGTCACACTTTGCTATGCCATAGCATTTTTATCCATAAGATTAGCGGATCCTACC

TGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATA.

In some embodiments, the inducible promoter is an iso- 20 propyl B-D-1-thiogalactopyranoside (IPTG) inducible pro moter. In one embodiment, the IPTG-inducible promoter comprises the P. sequence found in the vector encoded by PubMed Accession ID HEU546824. In one embodiment, the IPTG-inducible promoter sequence comprises the P Sequence:

(SEQ ID NO : 3) CCATCGAATGGCTGAAATGAGCTGTTGACAATTAATCATCCGGCTCGTATAATGTGTGGAAT

TGTGAGCGGATAACAATTTCACACAGGA.

In some embodiments, the IPTG-inducible promoter com prises the P. sequence found in the vector encoded by PubMed Accession ID HEU546816. 35 In some embodiments, the IPTG-inducible promoter com prises the Pro Sequence:

(SEQ ID NO : 4) ATAAATGTGAGCGGATAACATTGACATTGTGAGCGGATAACAAGATACTGAGCACTCAGCAGG

ACGCACTGACC.

In some embodiments, the IPTG-inducible promoter com prises the Paleo-I sequence:

(SEO ID NO. 5) AAAATTTATCAAAAAGAGTGTTGACTTGTGAGCGGATAACAATGATACTTAGATTCAATTGT

GAGCGGATAACAATTTCACACA.

In some embodiments, the IPTG-inducible promoter com prises the P-- Sequence

(SEQ ID NO : 6) CATAGCATTTTTATCCATAAGATTAGCGGATCCTAAGCTTTACAATTGTGAGCGCTCACAATT

ATGATAGATTCAATTGTGAGCGGATAACAATTTCACACA.

In some embodiments, the inducible promoter sequence comprises the P. Slcoa Sequence:

(SEO ID NO: 7) GCATGCACAGATAACCATCTGCGGTGATAAATTATCTCTGGCGGTGTTGACATAAATACCAC TGGCGGTtATAaTGAGCACATCAGCAGG/AGTATGCAAAGGA US 9,458,509 B2 33 34 Other non-limiting examples of promoters that are useful biological classifier circuits described herein are provided in for use in the low- and high-input detector modules and Tables 1-36. TABLE 1. Examples of Constitutive E.coli o' Promoters Name Description Promoter Sequence BBa. I14018 SEQ ID NO: 8 P(Bla) ...gtttatacataggcgagtactctgttatgg BBa. I14033 SEQ ID NO:9 P(Cat) ...agaggttccaactittcaccataatgaaa.ca BBa. I14034 SEQ ID NO: 10 P(Kat) ...taaacaactaacggacaattctacctaa.ca BBa I732021 SEQ ID NO: 11 Template for ...acatcaagccaaattaalacaggattaa.cac Building Primer Family Member BBa I742126 SEQ ID NO: 12 Reverse lambda ...gaggtaaaatagtCaacacgcacggtgtta cI-regulated promoter BBa JO1006 SEQ ID NO: 13 Key Promoter ...CaggccggaataactCcctataatgcgcca absorbs 3 BBa J23100 SEQ ID NO: 14 constitutive ...ggctagotcagtCctaggtacagtgctago promoter Tamily member BBa J23101 SEQ ID NO: 15 constitutive ...agctagotcagtCctaggtatatgctagc promoter family member BBa J23102 SEQ ID NO: 16 constitutive ...agctagotcagtCctaggtactgtgctage promoter family member BBa J23103 SEQ ID NO: 17 constitutive ...agctagotcagtCctagggattatgctage promoter family member BBa J23104 SEQ ID NO: 18 constitutive ...agctagotcagtCctaggtattgttgctage promoter family member BBa J23105 SEQ ID NO: 19 constitutive ...ggctagotcagtCctaggtactatgctage promoter family member BBa J23106 SEQ ID NO: 20 constitutive ...ggctagotcagtCctaggtatagtgctage promoter family member BBa J23107 SEQ ID NO: 21 constitutive ...ggctagotcagccCtaggtatatgctage promoter family member BBa J23108 SEQ ID NO: 22 constitutive ...agctagotcagtCctaggtataatgctagc promoter family member BBa J23109 SEQ ID NO: 23 constitutive ...agctagotcagtCctagggactgtgctago promoter Tamily member BBa J23110 SEQ ID NO: 24 consti ive ...ggctagotcagtCctaggtacaatgctage promoter family member BBa J23111 SEQ ID NO: 25 constitutive ...ggctagotcagtCctaggtatagtgctage promoter Tamily member BBa J23112 SEQ ID NO: 26 consti ive ...agctagotcagtCctagggattatgctage promoter family member BBa J23113 SEQ ID NO: 27 consti ive ...ggctagotcagtCctagggattatgctage promoter family member BBa J23114 SEQ ID NO: 28 constitutive ...ggctagotcagtCctaggtacaatgctage promoter Tamily member BBa J23115 SEQ ID NO: 29 consti ive ...agctagotcageccttggtacaatgctage promoter family member BBa J23116 SEQ ID NO:30 constitutive ...agctagotcagtCctagggactatgctage promoter Tamily member

BBa J23117 SEOID NO:31 constitutive ...agctagotcagtCctagggattgtgctage promoter family member US 9,458,509 B2 35 36 TABLE 1-continued Examples of Constitutive E.coli o' Promoters Name Description Promoter Sequence BBa J23118 SEQ ID NO: 32 constitutive ...ggctagotcagtCctaggtattgttgctage promoter family member BBa J23119 SEQ ID NO: 33 constitutive ...agctagotcagtCctaggtataatgctagc promoter family member BBa J23150 SEQ ID NO: 341 bp mutant ...ggctagcticagtCctaggtatatgctage from J23107 BBa J23151 SEQ ID NO: 35 1 bp mutant ...ggctagotcagtCctaggtacaatgctage from J23114 BBa J44002 SEQ ID NO:36 pBAD reverse ...aaagtgtgacgcc.gtgcaaataatcaatgt BBa J48104 SEQ ID NO:37 NikR promoter, ...gacgaatacttaaaatcgtCatacttattt a protein of the ribbon helix helix family of transcription factors that repress expre BBa J54200 SEQ ID NO:38 lacq Promoter ...aalaccttitcgcggtatggcatgatagogCC BBa J56015 SEQ ID NO:39 lacIQ-promoter ...tgatagogcccggaagagagtCaattCagg Sequence

BBa J64951 SEOID NO: 40 E. coi CreABCD ...ttatttaccgtgacgaactaattgctcgtg phosphate sensing operon promoter BBa KO88007 SEQ ID NO: 41 GlnRS promoter ... catacgcc.gttatacgttgtttacgctittg BBa K119000 SEQ ID NO: 42 Constitutive ...ttatgctitccggctcgtatgttgtgtggac weak promoter of lacz BBa K119001 SEQ ID NO: 43 Mutated Lacz ...ttatgctitccggctcgtatggtgtgtggac Older BBa K137029 SEQ ID NO: 44 constitutive ...atatatatatatatataatggaagcg promoter with (TA) 10 between -10 and -35 elements BBal K137030 SEQ ID NO: 45 constitutive ...atatatatatatatataatggaagcg promoter with (TA)9 between -10 and -35 elements BBal K137031 SEQ ID NO: 46 constitutive ...ccccgaaagcttaagaatataattgtaage promoter with (C) 10 between -10 and -35 elements BBal K137032 SEQ ID NO: 47 constitutive ...ccccgaaagcttaagaatataattgtaage promoter with (C)12 between -10 and -35 elements BBa K137085 SEQ ID NO: 48 optimized (TA) ...tgacaatatatatatatatataatgctagc repeat constitutive promoter with 13 bp between -10 and -35 elements BBal K137086 SEQ ID NO: 49 optimized (TA) ...acaatatatatatatatatataatgctage repeat constitutive promoter with 15 bp between -10 and -35 elements

BBal K137087 SEQ ID NO: 50 optimized (TA) ...aatatatatatatatatatataatgctagc repeat constitutive promoter with 17 bp between -10 and -35 elements

BBal K137088 SEQ ID NO: 51 optimized (TA) ...tatatatatatatatatatataatgctagc repeat constitutive promoter with 19 bp between -10 and -35 elements BBal K137089 SEQ ID NO: 52 optimized (TA) ...tatatatatatatatatatataatgctagc repeat constitutive promoter with 21 bp between -10 and -35 elements US 9,458,509 B2 37 38 TABLE 1-continued Examples of Constitutive E.coli o' Promoters Name Description Promoter Sequence

BBa K137090 SEQ ID NO: 53 optimized (A) ...aaaaaaaaaaaaaaaaaatataatgctagc repeat constitutive promoter with 17 bp between -10 and -35 elements BBa K137091 SEQ ID NO: 54 optimized (A) ...aaaaaaaaaaaaaaaaaatataatgctagc repeat constitutive promoter with 18 bp between -10 and -35 elements BBa K256002 SEQ ID NO: 55 J23101:GFP ... cacctitcggggggcctittctg.cgtttata BBa K256018 SEQ ID NO: 56 J23119:IFP ... cacctitcggggggcctittctg.cgtttata BBa K256020 SEQ ID NO: 57 J23119:HO1 ... cacctitcggggggcctittctg.cgtttata BBa K256033 SEQ ID NO: 58 Infrared signal ... cacctitcggggggcctittctg.cgtttata reporter (J23119:IFP:J23119:HO1) BBa K292000 SEQ ID NO: 59 Double terminator + ...ggctagotcagtCctaggtacagtgctage constitutive promoter BBa K292001 SEQ ID NO: 60 Double terminator + ...tgctagotactagagattaaagaggagaaa. constitutive promoter + Strong RBS BBa M13101 SEQ ID NO: 61 M13K07 gene I ... cctgtttittatgttattotctctgaaagg Older BBa M13102 SEQ ID NO: 62 M13K07 gene II ...aaatatttgcttatacaatctitcctgttitt Older BBa M13103 SEQID NO: 63 M13K.07 gene III ...gctgataaa.ccgatacaattaaaggctCct Older BBa M13104 SEQ ID NO: 64 M13K07 gene IV ...ctCttcticagcgtcttaatctaagctatog Older BBa M13105 SEQ ID NO: 65 M13K07 gene V ...atgagecagttcttaaaatcgcataaggta Older BBa M13106 SEQ ID NO: M13K07 gene VI ...ctattgattgtgacaaaataaacttattoc Older BBa M13108 SEQ ID NO: 67 M13K07 gene VIII ...gttcgc.gcttggtataatcgctgggggtC Older BBa M13110 SEQ ID NO: 68 M13110 ...ctittgcttctgactataatagtCagggtaa BBa M31519 SEQ ID NO: 69 Modified promoter ...aaaccgatacaattaaaggctCctgctage sequence of g3.

BBa R1074 SEOID NO: 70 Constitutive ...gccggaataactCcctataatgcgccacca Promoter I

BBa R1075 SEOID NO: 71 Constitutive ...gccggaataactCcctataatgcgccacca Promoter II BBa SO3331 SEQ ID NO: 72 ttgacaagcttittCcticagctCcgtaaact

TABLE 2 Examples of Constitutive E. coli o' Promoters Identifier Sequence BBa J23119 SEQ ID NO: 73 ttgacagctagotcagtic ctaggtataatgctago n/a BBa J23100 SEQ ID NO: 74 ttgacggctagotcagtic ctagg tacagtgctago: 1 BBa J23101 SEQ ID NO: 75 tttacagctagotcagtic ctagg tatt atgctago O. 70 US 9,458,509 B2 39 40 TABLE 2 - continued Examples of Constitutive E. coli o' Promoters Identifier Sequence BBa J23102 SEQ ID NO: 76 ttgacagctagotcagtic ctagg tact.gtgctago O.86 BBa J23103 SEQ ID NO: 77 citgatagctagotcagtic ctagggattatgctago O. O1 BBa J23104 SEQ ID NO: 78 ttgacagctagotcagtic ctagg tattgttgctago O. 72 BBa J23105 SEQ ID NO: 79 tttacggctagotcagtic ctagg tact atgctago O. 24 BBa J23106 SEQ ID NO: 8 O tittacggctagotcagtic ctaggtatagtgctago O. 47 BBa J23107 SEQ ID NO: 81 tttacggctagotcagcc ctagg tatt atgctago O.3 6 BBa J23108 SEQ ID NO: 82 ctgacagctagotcagtic ctaggtataatgctago O. 51 BBa J23109 SEQ ID NO: 83 tttacagctagotcagtic ctagggactgtgctago O. O4 BBa J23110 SEQ ID NO: 84 tttacggctagotcagtic ctagg tacaatgctago O.33 BBa J23111 SEQ ID NO: 85 ttgacggctagotcagtic ctaggtatagtgctago O. 58 BBa J23112 SEQ ID NO: 86 citgatagctagotcagtic ctagggattatgctago O. OO BBa J23113 SEQ ID NO : 87 citgatggctagotcagtic ctagggattatgctago O. O1 BBa J23114 SEQ ID NO: 88 tittatggctagotcagtic ctagg tacaatgctago O. 10 BBa J23115 SEQ ID NO: 89 tittatagctagotcagcc cttggtacaatgctago O. 15 BBa J23116 SEQ ID NO: 90 ttgacagctagotcagtic ctagggactatgctago O. 16 BBa J23117 SEQ ID NO: 91 ttgacagctagotcagtic ctagggattgttgctago O. O6 BBa J23118 SEQ ID NO: 92 ttgacggctagotcagtc.ctagg tattgttgctago 0.56

TABLE 3 Examples of Constitutive E. coli o' Promoters Name Description Promoter Sequence BBa J45992 SEQ ID NO: 93 Full-length stationary . . . ggitttcaaaattgttgat ctatatttaacaa phase osmY promoter BBa J45993 SEQ ID NO: 94 Minimal stationary . . . ggitttcaaaattgttgat ctatatttaacaa phase osmY promoter

TABLE 4 Examples of Constitutive E. coli o' Promoters Name Description Promoter Sequence BBa J45504 SEQ ID NO: 95 httpG Heat Shock Promoter . . . tctattocaataaagaaatcttcctg.cgtg

TABLE 5 Examples of Constitutive B. subtilis o Promoters Name Description Promoter Sequence BBa K143 012 SEQ ID NO: 96 Promoter veg a . . . aaaaatgggct cqtgttgtacaataaatgt constitutive promoter for B. subtilis US 9,458,509 B2 41 42 TABLE 5 - continued Examples of Constitutive B. subtilis o Promoters Name Description Promoter Sequence BBa K143013 SEQ ID NO: 97 Promoter 43 a . . . aaaaaaag.cgc.gc.gattatgtaaaatataa constitutive promoter for B. subtilis

TABLE 6 Examples of Constitutive B. subtilis o Promoters Name Description Promoter Sequence BBa K143 010 SEQ ID NO: 98 Promoter citc for B. subtilis . . . atcc ttatcgittatggg tattgtttgtaat BBa K143 011 SEQ ID NO: 99 Promoter gsiB for B. subtilis . . . taaaagaattgtgagcgggaatacaacaac BBa K143013 SEQ ID NO: 100 Promoter 43 a constitutive . . . aaaaaaag.cgc.gc.gattatgtaaaatataa promoter for B. subtilis

TABLE F Examples of Constitutive Promoters from Miscellaneous Prokaryotes Name Description Promoter Sequence BBa K112706 SEQ ID NO: 101 Pspv2 . . . tacaaaataattic cc ct gcaaacattatca from Salmonella

BBa K112707 SEQ ID NO: 102 Pspv . . . tacaaaataattic cc ct gcaaacattatcq from Salmonella

TABLE 8 Examples of Constitutive Promoters from bacteriophage T7 Name Description Promoter Sequence BBa I712074 SEQ ID NO: 103 T7 promoter (strong . . . agggaatacaa.gctacttgttctttittgca promoter from T7 bacteriophage) BBa I719005 SEQ ID NO: 104 T7 Promoter taatacgact cact at agggaga BBa J34814 SEQ ID NO: 105 T7 Promoter gaatttaatacgact cactatagggaga BBa J64997 SEQ ID NO: 106 T7 consensus -10 taatacgact cactatagg and rest BBa K113010 SEQ ID NO: 107 overlapping T7 . . . gagt cqtattaatacgact cactatagggg promoter BBa K113 011 SEQ ID NO: 108 more overlapping . . . agtgagtcgtact acgact cactatagggg T7 promoter BBa K113 012 SEQ ID NO: 109 weaken overlapping . . . gagt cqtattaatacgact ct ctatagggg T7 promoter

BBa ROO85 SEQ ID NO: 110 T7 Consensus taatacgact cact at agggaga Promoter Sequence BBa R0180 SEQ ID NO: 111 T7 RNAP promoter ttatacgact cactatagggaga

BBa RO181 SEQ ID NO: 112 T7 RNAP promoter gaatacgact cact at agggaga

BBa RO182 SEQ ID NO: 113 T7 RNAP promoter taatacgt.ct cact at agggaga

BBa RO183 SEQ ID NO: 114 T7 RNAP promoter t catacgact cact at agggaga US 9,458,509 B2 43 44 TABLE 8 - continued

Examples of Constitutive Promoters from bacteriophade T7

Name Description Promoter Sequence

BBa Z0251 SEQ ID NO: 115 T7 strong promoter . . . taatacgactic actatagggagaccacaac BBa Z0252 SEQ ID NO: 116 T 7 weak binding . . . taattgaact cactaaagggagaccacagc and processivity BBa Z0253 SEQ ID NO: 117 T7 weak binding . . . Caagtaatacgact cact attagggalaga promoter

SEQ ID NO: 118 T7 14.3 m attaa.ccct cactaaagggaga

15

TABLE 9 Examples of Constitutive Promoters from bacteriophage SP6

Name Description Promoter Sequence BBa J64998 SEQ ID NO: 119 consensus -10 and rest from SP6 atttaggtgacactataga

25

TABL 1O

Examples of Constitutive Promoters from Yeast Description Promoter Sequence BBa I766 555 SEO ID NO : 20 pCyc (Medium) Promoter acaaacacaaatacacacactalaattaata BBa I766 556 SEO ID NO : 21 pAdh (Strong) Promoter c caag catacaatcaactat ct catataca BBa I766 557 SEO ID NO : 22 pSte5 (Weak) Promoter gatacaggatacagcggaaacaacttittaa BBa J63 OO5 SEQ ID NO : 23 yeast ADH1 promoter tittcaagctataccaa.gcatacaat caact

BBa K105O27 SEQ ID NO : 24 cyc100 minimal promoter c ctittgcagdataaattactatact tctat

BBa K105O28 SEQ ID NO : 25 cyc70 minimal promoter c ctittgcagdataaattactatact tctat

BBa K105O29 SEQ ID NO : 26 cyc43 minimal promoter c ctittgcagdataaattactatact tctat

BBa K10503 O SEQ ID NO : 27 cyc28 minimal promoter c ctittgcagdataaattactatact tctat

BBa K105031 SEQ ID NO : 28 cyc1.6 minimal promoter c ctittgcagdataaattactatact tctat

BBa K122 OOO SEQ ID NO : 29 pPGK1 ttatctacttitt tacaacaaatataaaa.ca

BBa K1 24 OOO SEQ ID NO : 3 O pCYC Yeast Promoter acaaacacaaatacacacactalaattaata BBa K1 24 OO2 SEQ ID NO : 31 Yeast GPD (TDH3) Promoter gtttcqaataaacacacataaacaaacaaa

BBa M312O1 SEQ D NO : 32 Yeast CLB1 promoter region, accatcaaaggaagctittaatcttct cata G2/M cell cy cle specific

TABL E 11

Examples of Constitutive Promoters from Miscellaneous Eukaryotes

Name Description Promoter Sequence

BBa I712004 SEQ ID NO : 1 33 CMV promoter agaac cc actgct tactggcttatcgaaat

BBa KO 76017 SEQ ID NO : 1 34 Ubc Promoter ggc.cgtttittggctttitttgttagacgaag US 9,458,509 B2 45 46 TABL E 12 Examples of Cell Sicinalind Promoters Name Description Promoter Sequence BBa I1051 SEQ ID NO: 135 Lux cassette right promoter tgttatagt caatacct Ctggcggtgata BBa I14015 SEQ ID NO: 136 P (Las) Teto ttittggtacact coct at cagtgatagaga BBa I14016 SEQ ID NO: 137 P (Las) CIO Ctttittgg tacactacct ctdgcggtgata BBa I14017 SEQ ID NO: 138 P(Rhl) tacgcaagaaaatggitttgttatagt cala BBa I739105 SEQ ID NO: 139 Double Promoter (LuxRAHSL, cgtgcgtgttgata acaccgtgcgtgttga positive/cI, negative) BBa I746104 SEQ ID NO: 140 P2 promoter in agr operon agattgtact aaatcgtataatgacagtga from S. aureus BBa I751501 SEQ ID NO: 141 plux-cI hybrid promoter gtgttgatgcttitt at Caccgc.cagtggta BBa I751502 SEQ ID NO: 142 plux-lac hybrid promoter agtgtgtggaattgtgagcggataacaatt BBa J761011 SEQ ID NO: 143 CinR, CinL and glucose acat cittaaaagttittagtat catatt cqt controlled promoter BBa J06403 SEQ ID NO : 44 RhIR promoter repressible by tacgcaagaaaatggitttgttatagt cala CI

BBa J64000 SEQ ID NO : 45 rhill promoter atcct cotttagt ctitcc cc ct catgtgtg BBa J64010 SEQ ID NO : 46 lasI promoter taaaattatgaaatttgcataaattcttca BBa J64067 SEQ ID NO : 47 LuxR + 3OC6HSL independent gtgttgactattttacct Ctggcggtgata ROO65

BBa J647 SEQ ID NO : 48 LasR/LaSI Inducible & gaaatctggcagtttittggtacacgaaagc RHLR/RHLI repressible Promoter BBa. KOS1 SEQ ID NO: 149 pLux/cI Hybrid Promoter acaccgtgcgtgttgatatagt caataaa

BBa. KOS1 17 SEQ ID NO: 150 pLas promoter aaaattatgaaatttgtataaattctt cag

BBa. KOS1 43 SEQ ID NO: 151 pLas/cI Hybrid Promoter ggttctttittgg tacctctggcggtgataa

BBa. KOS1 46 SEQ ID NO: 152 pLas/Lux Hybrid Promoter tgtaggat.cgtacaggtataaattctt cag

BBa. KOS1 56 SEQ ID NO: 153 pLux caagaaaatggtttgttatagt cqaataaa

BBa. KOS1 SEQ ID NO: 154 pLux/Las Hybrid Promoter citat ct catttgctagtatagt cqaataaa

BBa. K145 SO SEQ ID NO: 155 Hybrid promoter: HSL-LuxR tag tittataatttalagtgttctittaatttic activated, P22 C2 repressed

BBa. K266 O OO SEQ ID NO: 156 PAI + LasR -> LuxI (AI) Cacct tcgggtgggcCtttctg.cgtttata

BBa. K266 O SEQ ID NO : 57 PAI - LaSR -> Las I & AI - LuxR. aataact citgatagtgctagtgtagat ct c -- Las I

BBa. K266 O SEQ ID NO: 158 PAI + LasR -> LaSI + GFP & Cacct tcgggtgggcCtttctg.cgtttata AI + LuxR -- Las I + GFP

BBa. K266 O SEQ ID NO : 59 Complex QS -> LuxI & Las I Cacct tcgggtgggcCtttctg.cgtttata circuit

BBa. ROO61 SEQ ID NO 60 Promoter (HSL-mediated luxR ttgacacctgtaggat.cgtacaggtataat repressor)

BBa. ROO62 SEQ ID NO 61 Promoter (luxR & HSL caagaaaatggtttgttatagt cqaataaa regulated -- lux pR)

BBa. ROO63 SEQ ID NO 62 Promoter (luxR & HSL cacgcaaaacttgcgacaaacaatagg taa regulated -- lux pl)

BBa. ROO71 SEQ ID NO 63 Promoter (RhlR & C4-HSL gttagctitt.cgaattggctaaaaagtgttc regulated)

BBa. ROO78 SEQ ID NO 64 Promoter (cinR and HSL c cattctgctitt coacgaacttgaaaacgc regu US 9,458,509 B2 47 48 TABLE 1.2 - continued Examples of Cell Sicinalind Promoters Name Description Promoter Sequence

BBa R0079 SEQ ID NO: 165 Promoter (LasR & PAI . . . g.gc.cgcgggttctttittggtacacgaaagc regulated) BBa R1062 SEQ ID NO : 166 Promoter, Standard (luxR and . . . aagaaaatggitttgttgatact.cgaataaa HSL regulated -- lux pR)

TABLE 13 Examples of Metal Inducible Promoters Name Description Promoter Sequence BBa I 721001 SEQ ID NO: 167 Lead Promoter . . . gaaaac Cttgtcaatgaagagcgatctatg BBa I731004 SEQ ID NO: 168 FecA promoter . . . ttct cott cqact catagotgaacacaa.ca BBa I760.005 SEQ ID NO: 169 Cu-sensitive promoter atgacaaaattgtcat BBa I765000 SEQ ID NO: 170 Fe promoter . . . accalatgctgggaacggcc agggcacctaa BBa I765.007 SEQ ID NO: 171 Fe and UV promoters . . . citgaaag.cgcat accgctatggagggggitt BBa J3902 SEQ ID NO : 172 PrPe (PI + PII rus operon) . . . tagatatgcc tigaaag.cgcataccgctatg

TABLE 1.4 Examples of T7 Promoters Name Description Promoter Sequence BBa I712074 SEQ ID NO: 173 T7 promoter (strong promoter . . . agggaatacaagct acttgttctttittgca from T7 bacteriophage) BBa I719005 SEQ ID NO: 174 T7 Promoter taatacgact cact at agggaga

TABL E 15 Examples of Stress Kit Promoters Name Description Promoter Sequence BBa KO 86017 SEQ ID NO: 193 unmodified Lutz-Bujard Laco . . . ttgtgagcggataacaagat actgagcaca promoter BBa KO 86018 SEQ ID NO: 194 modified Lutz-Bujard Laco . . . ttgtgagcggataacaattctgaagaacaa promoter, with alternative sigma factor O24 BBa KO 86019 SEQ ID NO: 195 modified Lutz-Bujard Laco . . . ttgtgagcggataacaattctgataaaa.ca promoter, with alternative sigma factor O24 BBa KO 8602 O SEQ ID NO: 196 modified Lutz-Bujard Laco . . . ttgtgagcggataa Catctalacc ctittaga promoter, with alternative sigma factor O24 BBa KO 86021 SEQ ID NO: 197 modified Lutz-Bujard Laco . . . ttgtgagcggataa Catagcagataagaaa promoter, with alternative sigma factor O24 BBa KO 86022 SEQ ID NO: 198 modified Lutz-Bujard Laco . . . gtttgagcgagtaacgc.cgaaaatcttgca promoter, with alternative sigma factor O28 BBa KO86O23 SEQ ID NO: 199 modified Lutz-Bujard Laco . . . gtgtgagcgagtaacgacgaaaatcttgca promoter, with alternative sigma factor O28 BBa KO 86024 SEQ ID NO: 200 modified Lutz-Bujard Laco . . . tttgagcgagta acagc.cgaaaatcttgca promoter, with alternative sigma factor O28 US 9,458,509 B2 49 50 TABLE 15- continued Examples of Stress Kit Promoters Name Description Promoter Sequence

BBa KO 86025 SEQ ID NO: 201 modified Lutz-Bujard Laco . . . tctgagcgagta acagc.cgaaaatcttgca promoter, with alternative sigma factor O28 BBa KO 86026 SEQ ID NO: 202 modified Lutz-Bujard Laco . . . ttgtgagcgagtggcaccattaagtacgta promoter, with alternative sigma factor O32 BBa KO 86027 SEQ ID NO: 203 modified Lutz-Bujard Laco . . . ttgtgagcgagtgacaccattaagtacgta promoter, with alternative sigma factor O32 BBa KO 86028 SEQ ID NO: 2O4 modified Lutz-Bujard Laco . . . ttgtgagcgagtaacaccattaagtacgta promoter, with alternative sigma factor O32 BBa KO 86029 SEQ ID NO: 205 modified Lutz-Bujard Laco . . . ttgtgagcgagtaacaccattaagtacgta promoter, with alternative sigma factor O32 BBa KO 8603 O SEQ ID NO: 206 modified Lutz-Bujard Laco . . . Cagtgagcgagtaacaactacgctgttitta promoter, with alternative sigma factor O38 BBa KO 86031 SEQ ID NO: 207 modified Lutz-Bujard Laco . . . Cagtgagcgagtaacaactacgctgttitta promoter, with alternative sigma factor O38 BBa KO 86032 SEQ ID NO: 2O8 modified Lutz-Bujard Laco . . . atgtgagcggataa Cactataattaataga promoter, with alternative sigma factor O38 BBa KO 86033 SEQ ID NO: 209 modified Lutz-Bujard Laco . . . atgtgagcggataa Cactataattaataga promoter, with alternative sigma factor O38

TABL E 16 Examples of Logic Promoters Name Description Promoter Sequence BBa I732200 SEQ ID NO: 210 NOT Gate Promoter Family . . . gaattgtgagcggataacaattggat.ccgg ember (DOO1O1wt1) BBa I7322O1 SEQ ID NO: 211 NOT Gate Promoter Family . . . ggaattgtgagcgcticacaattggat.ccgg

BBa I732202 SEQ ID NO: 212 NOT Gate Promoter Family . . . ggaattgtaa.gc.gcttacaattggat.ccgg

BBa I732203 SEQ ID NO: 213 NOT Gate Promoter Family . . . ggaattgtaaacgtttacaattggat.ccgg

BBa I732204 SEQ ID NO: 214 NOT Gate Promoter Family . . . ggaattgttgaacgttcacaattggat.ccgg

BBa I732205 SEQ ID NO: 215 NOT Gate Promoter Family . . . ggaattittgagcgctcaaaattggat.ccgg

BBa I732206 SEQ ID NO: 216 NOT Gate Promoter Family . . . ggaattatgagcgct cataattggat.ccgg

BBa I732207 SEQ ID NO: 217 NOT Gate Promoter Family . . . gggacgactgtata cagt catcggat.ccgg ember (DOO1O77) BBa I73227 O SEQ ID NO: 218 Promoter Family Member with . . . ggaattgtgagcgcttacaattggat.ccgg Hybrid Operator (DOO1O12) BBa I7322 71 SEQ ID NO: 219 Promoter Family Member with . . . ggaattgtgagcgct cataattggat.ccgg Hybrid Operator (DOO1O16) BBa I732272 SEQ ID NO: 220 Promoter Family Member with . . . ggaattgtgagctacagt catcggat.ccgg Hybrid Operator (DOO1O17) BBa I732273 SEQ ID NO: 221 Promoter Family Member with . . . ggaattgtaa.gc.gcticacaattggat.ccgg Hybrid Operator (DOO1O21) BBa I732274 SEQ ID NO: 222 Promoter Family Member with . . . ggaattgtaagcgttcacaattggat.ccgg Hybrid Operator (DOO1O24)

US 9,458,509 B2 55 56 TABLE 16- continued Examples of Lodic Promoters Name Description Promoter Sequence BBa I732437 SEQ ID NO: 273 Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg (UO49O + DOO2O22) BBa I732438 SEQ ID NO: 274 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg (UO49O + DO14O22) BBa I732439 SEQ ID NO: 275 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO49O + DO26O22) BBa I73244 O SEQ ID NO: 276 Promoter Family Member . . . tca attgtaa.gc.gcttacaattggat.ccgg (UO49O + DO38O22) BBa I732441 SEQ ID NO: 277 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg (UO49O + DO5OO22) BBa I732442 SEQ ID NO: 278 Promoter Family Member . . . Calaattgtaa.gc.gcttacaattggat.ccgg (UO49O + DO 62O22) BBa I732443 SEQ ID NO: 279 Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DOO2O22) BBa I732444 SEQ ID NO: 280 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DO14O22) BBa I732445 SEQ ID NO: 281 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DO26O22) BBa I732446 SEQ ID NO: 282 Promoter Family Member . . . tca attgtaa.gc.gcttacaattggat.ccgg (UO37o + DO38O22) BBa I732447 SEQ ID NO: 283 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DO5OO22) BBa I732448 SEQ ID NO: 284 Promoter Family Member . . . Calaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DO 62O22) BBa I732450 SEQ ID NO: 285 Promoter Family Member . . . gocaaattaaac aggattaa.caggat.ccgg (UO73O26 + DO62NUL) BBa I732451 SEQ ID NO: 286 Promoter Family Member . . . gocaaattaaac aggattaa.caggat.ccgg (UO73O27 + DO62NUL) BBa I732452 SEQ ID NO: 287 Promoter Family Member . . . Calaattatgagcgcticacaattggat.ccgg (UO73O26 + DO62O61)

TABL E 17 Examples of Positively Regulated E. coli O70 Promoters Name Description Promoter Sequence BBa IO500 SEQ ID NO: 288 Inducible pBad/araC . . . gtttct coat accc.gtttittittgggctago promoter BBa I1051 SEQ ID NO: 289 Lux cassette right promoter . . . titt at agtc.gaatacctctggcggtgata BBa. 2006 SEQ ID NO: 290 Modified lamdba Prm . . . attacaaactittcttgtatagatttalacgt. promoter (repressed by 434 cI) BBa. 2007 SEQ ID NO: 291 Modified lambda Prm . . . atttataaatagtggtgatagatttalacgt. promoter (OR-3 obliterated) BBa. 2O36 SEQ ID NO: 292 Modified lamdba Prm . . . tttcttgtatagatttacaatgitat cittgt promoter (cooperative repression by 434 cI BBa. 2O4. O SEQ ID NO: 293 Modified lambda P (RM) . . . tttcttgtagatact tacaatgitat cittgt promoter: -10 region from P(L) and cooperatively repressed by 434 cI BBa. 221 O SEQ ID NO: 294 plac Or2 - 62 (positive) . . . ctittatgct tccggctcgitatgttgttgttgg BBa. 34 O6 SEQ ID NO: 295 Pbad/AraC with extra REN . . . ttittittgggctagdaagctttaccatggat sites US 9,458,509 B2 57 58 TABLE 1.7-continued Examples of Positively Reculated E. coli O70 Promoters Name Description Promoter Sequence

BBa I13453 SEQ ID NO: 296 Pbad promoter tgtttct c cataccgtttittittgggctago BBa I14015 SEQ ID NO: 297 P (Las) Teto ttittgg tacactic cctato agtgatagaga BBa I14O16 SEQ ID NO: 298 P (Las) CIO citttittgg tacactacctctgg.cggtgata BBa I14017 SEO ID NO : 299 P (Rhl) tacgcaagaaaatggitttgttatagt cqaa BBa I 721001 SEQ ID NO: 3 OO Lead Promoter gaaaac Cttgtcaatgaagagcgatctatg BBa I723020 SEQ ID NO: 301 Pu Ctcaaag.cgggc.ca.gc.cgtagcc.gttacgc BBa I731004 SEQ ID NO: 3 O2 FecA promoter ttct cqtt cqact catagotgaacacaa.ca BBa I739 104 SEQ ID NO: 3O3 Double Promoter gttctittaattatttaagtgttctittaatt (LuxR/HSL, positive/P22 cII, negative) BBa I739105 SEQ ID NO: 304 Double Promoter cgtgcgtgttgatalacaccgtgcgtgttga (LuxR/HSL, positive/cI, negative) BBa I741.018 SEQ ID NO: 305 Right facing promoter (for gttacgtttatcgcggtgattgttactitat xylF) controlled by xylR and CRP-cAMP BBa I741019 SEQ ID NO: 306 Right facing promoter (for gcaaaataaaatggaatgatgaaactgggit xylA) controlled by xylR and CRP-cAMP BBa I741020 SEQ ID NO: 307 promoter to xylF without gttacgtttatcgcggtgattgttactitat CRP and several binding sites for xylR BBa I741021 SEQ ID NO: 308 promoter to xylA without attt cacactgctattgagataatticacaa CRP and several binding sites for xylR BBa I746104 SEQ ID NO: 309 P2 promoter in agr operon agattgtact aaatcgtataatgacagtga from S. aureus BBa I 746360 SEQ ID NO: 310 PF promoter from P2 phage gacatcto cqgcgcaactgaaaataccact BBa I 746361 SEQ ID NO: 311 PO promoter from P2 phage gaggatgcgcatcgt.cgggaaactgatgcc BBa I 746362 SEQ ID NO: 312 PP promoter from P2 phage catc.cgggactgatggcggaggatgcgcat BBa I 746363 SEQ ID NO: 313 PV promoter from P2 phage aacttittatatattgttgcaat ct cacatgc BBa I 746364 SEQ ID NO: 314 Psid promoter from P4 tgttgtc.cggtgtacgt cacaattitt citta phage BBa I 746365 SEQ ID NO: 315 PLL promoter from P4 aatggctgttgttgtttitttgttcatct coac phage BBa I751501 SEQ ID NO: 316 plux-cI hybrid promoter gtgttgatgcttittat caccgc.cagtggta BBa I751502 SEQ ID NO: 317 plux-lac hybrid promoter agtgttgttggaattgtgagcggataacaatt BBa I76.0005 SEQ ID NO: 318 Cu-sensitive promoter atgacaaaattgtcat BBa I761011 SEQ ID NO: 319 CinR, CinL and glucose acat cittaaaagttt tagtat catattogit controlled promoter BBa I765 001 SEQ ID NO: 32O UV promoter ctgaaag.cgcataccgctatggagggggitt BBa I765.007 SEQ ID NO: 321 Fe and UV promoters ctgaaag.cgcataccgctatggagggggitt BBa J01005 SEQ ID NO: 322 pspoIIE promoter aacgaatata acaggtgggagatgagagga (spo OAJO 1004, positive) BBa JO3007 SEQ ID NO: 323 Maltose specific promoter aatattitcct catttitccacagtgaagtga BBa J06403 SEQ ID NO: 324 RhIR promoter repressible tacgcaagaaaatggitttgttatagt cqaa by C BBa JO 7007 SEQ ID NO: 325 ctX promoter atttaattgttittgat caattatttittctg BBa J13210 SEQ ID NO: 326 pompR dependent POPS attatt Ctgcatttittggggagaatggact producer US 9,458,509 B2 59 60 TABLE 1.7-continued Examples of Positively Reculated E. coli O70 Promoters Name Description Promoter Sequence BBa J15502 SEQ ID NO: 327 copA promoter cc ttgctggalaggttta acct titat cacag BBa J16101 SEQ ID NO: 328 BanAp-Banana-induced atgatgtgtc. catggatta Promoter BBa J16105 SEQ ID NO: 329 HelPp- Help". Dependant atgatagacgatgtgcgga caacgtg promoter BBa J45503 SEQ ID NO: 330 hybB Cold Shock Promoter Cattagcc.gc.cac catggggittaagtagca BBa J58100 SEQ ID NO: 331 AND-type promoter atttataaatagtggtgatagatttalacgt. synergistically activated by cI and CRP BBa J61051 SEQ ID NO: 332 Psal1 at aaa.gc.cat cacgagtaccatagaggatc BBa J61054 SEQ ID NO: 333 HIP-1 Promoter tttgtc.ttitt cittgcttaataatgttgtca BBa J61055 SEQ ID NO: 334 HIP-1fnir Promoter tttgtc.ttitt cittgcttaataatgttgtca BBa J64000 SEQ ID NO: 335 rhill promoter atcc to ctittagt ct tcc.ccct catgtgtg BBa J64010 SEQ ID NO: 336 lasI promoter taaaattatgaaatttgcatalaattic titca BBa J64712 SEQ ID NO: 337 LasR/Las I Inducible & gaaatctggcagtttittgg tacacgaaagc RHLR/RHLI repressible Promoter BBa J64800 SEQ ID NO: 338 RHLR/RHILI Inducible & tgc.cagttctggCaggit ctaaaaagttgttc LasR/Las I repressible Promoter BBa J64804 SEQ ID NO: 339 The promoter region cacagaacttgcatttatataaagggaaag (inclusive of regulator binding sites) of the B. subtilis RocDEF operon BBa KO91107 SEQ ID NO: 340 pLux/cI Hybrid Promoter acaccgtgcgtgttgat at agtic gaataaa BBa K091117 SEQ ID NO: 341 pI as promoter aaaattatgaaatttgtataa attct tcag BBa KO91143 SEQ ID NO: 342 pLas/cI Hybrid Promoter ggttctttittggtacct Ctggcggtgataa BBa KO91146 SEQ ID NO. 343 pLas/Lux Hybrid Promoter tgtaggat.cgtacaggtataa attct tcag BBa KO91156 SEQ ID NO: 344 pLux caagaaaatggtttgttatagt cqaataaa BBa KO91157 SEQ ID NO. 345 pLux/Las Hybrid Promoter citat ct catttgctagtatagt cqaataaa BBa K100000 SEQ ID NO: 346 Natural Xylose Regulated gttacgtttatcgcggtgattgttactitat Bi-Directional Operator BBa K100001 SEQ ID NO: 347 Edited Xylose Regulated Bi- gttacgtttatcgcggtgattgttactitat Directional Operator 1 BBa K100002 SEQ ID NO: 348 Edited Xylose Regulated Bi- gttacgtttatcgcggtgattgttactitat Directional Operator 2 BBa K112118 SEQ ID NO: 349 rrnB P1 promoter at aaatgcttgactctgtagcgggaaggcg BBa K112320 SEO ID NO: 350 {< ft SAZ promoter >} in aaaactgg tagtaggactggagattggtac BBlo format BBa K112322 SEQ ID NO: 351 Paps in BBb format gggacacaaacat Caagaggatatgagatt BBa K112402 SEQ ID NO: 352 promoter for FabA gene- gtcaaaatgaccgaaacgggtggtaact tc Membrane Damage and Ultrasound Sensitive BBa K112405 SEQ ID NO: 353 Promoter for CadA and agtaatcttatcgc.cagtttggtctggit ca CadB genes BBa K112406 SEQ ID NO: 354 cadC promoter agtaatcttatcgc.cagtttggtctggit ca BBa K112701 SEQ ID NO: 355 has promoter aattctgaacaa.catcc.gtactic titcgtgc BBa K112900 SEQ ID NO: 356 Pbad togataagattac.cgat cittacctgaagct BBa K116 OO1 SEQ ID NO: 357 nhaA promoter, which can cgatct attcacctgaaagagaaataaaaa be regulated by pH and inhaR protein. US 9,458,509 B2 61 62 TABLE 1.7-continued Examples of Positively Reculated E. coli O70 Promoters Name Description Promoter Sequence BBa K116401 SEQ ID NO: 358 external phosphate sensing atcqcaacct atttattacaa.cactagtgc promoter BBa K116500 SEQ ID NO: 359 OmpF promoter that is aaacgttagtttgaatggaaagatgcctgc activated or repressed by OmpR according to osmolarity. BBa K116603 SEQ ID NO: 360 pRE promoter from , phage tttgcacgaaccatatgtaagtattt cott BBa K117002 SEQ ID NO: 361 LisrA promoter (indirectly taac acttatttaattaaaaagaggagaaa activated by AI-2) BBa K118011 SEQ ID NO: 362 PostA (glucose repressible tagaaacaaaatgta acat ct citatggaca promoter) BBa K121011 SEQ ID NO: 363 promoter (lacI regulated) acaggaaa.ca.gctatgaccatgattacgc.c BBa K135 000 SEQ ID NO: 364 pCpxR (CpxR responsive agcgacgtctgatgacgtaatttctgcct c promoter) BBa K136010 SEQ ID NO: 365 fliA promoter gttcactictataccgctgaaggtgtaatgg BBa K145150 SEQ ID NO: 366 Hybrid promoter: HSL- tagtttataatttaagtgttctittaattitc LuxR activated, P22 C2 repressed BBa K180000 SEQ ID NO: 367 Hybrid promoter (trp & lac cgagcactitcaccaacaaggaccatago at regulated.-- tac pR) BBa K180002 SEQ ID NO: 368 tac pR testing plasmid Cacctt.cgggtgggc ctittctg.cgtttata (GFP) BBa K180003 SEQ ID NO: 369 PTAC testing plasmid catggcatggatgaactatacaaataataa (GFP) - basic BBa K180004 SEQ ID NO: 370 Game of Life-Primary Cacctt.cgggtgggc ctittctg.cgtttata plasmid BBa K180005 SEQ ID NO: 371 GoL-Primary plasmid (part Cacctt.cgggtgggc ctittctg.cgtttata 1) /RPS-Paper primary plasmid (part 1) LuxR generator BBa K180006 SEQ ID NO: 372 Game of Life-Primary Cacctt.cgggtgggc ctittctg.cgtttata plasmid (part 2) lux pR, GFP and LacI generator BBa K180007 SEQ ID NO: 373 Game of Life-Secondary Cacctt.cgggtgggc ctittctg.cgtttata plasmidtac pR, LuxI generator BBa K180010 SEQ ID NO: 374 Rock-paper-scissors-Rock Cacctt.cgggtgggc ctittctg.cgtttata primary plasmid BBa K180011 SEQ ID NO: 375 Rock-Primary plasmid Cacctt.cgggtgggc ctittctg.cgtttata (part 1) RhlR generator BBa K180012 SEQ ID NO: 376 Rock-Primary plasmid Cacctt.cgggtgggc ctittctg.cgtttata (part 2) tac pR, mCherry and Las I generator BBa K180013 SEQ ID NO: 377 Rock-paper-scissors-Rock Cacctt.cgggtgggc ctittctg.cgtttata secondary plasmidrhl pR, Lad generator BBa K180014 SEQ ID NO: 378 Rock-paper-scissors-Paper Cacctt.cgggtgggc ctittctg.cgtttata primary plasmid BBa K180015 SEQ ID NO: 379 Paper-Primary plasmid Cacctt.cgggtgggc ctittctg.cgtttata (part 2) tac pR, GFP and Rhill generator BBa K180016 SEQ ID NO: 380 Rock-paper-scissors-Paper Cacctt.cgggtgggc ctittctg.cgtttata secondary plasmidlux pR, Lad generator BBa K180017 SEQ ID NO: 381 Rock-paper-scissors - Cacctt.cgggtgggc ctittctg.cgtttata Scissors primary plasmid BBa K180018 SEQ ID NO: 382 Scissors-Primary plasmid Cacctt.cgggtgggc ctittctg.cgtttata (part 1) LasR generator BBa. 8OO19 SEQ ID NO: 383 Scissors-Primary plasmid Cacctt.cgggtgggc ctittctg.cgtttata (part 2) tac pR, mBanana and LuxI generator US 9,458,509 B2 63 64 TABLE 1.7-continued Examples of Positively Reculated E. coli O70 Promoters Name Description Promoter Sequence

BBa K180020 SEQ ID NO: 384 Rock-paper-scissors- . . . caccitt.cgggtgggc ctittctgcgtttata Scissors secondary plasmidlas pR, Lad generator BBa K206000 SEQ ID NO: 385 pBAD strong . . . tdtttct c cataccgtttittittgggctago BBa K206001 SEQ ID NO: 386 pBAD weak . . . tdtttct c cataccgtttittittgggctago BBa K259.005 SEQ ID NO: 387 AraC Rheostat Promoter . . . ttittatcgcaact ct ct actgtttct coat BBa K259.007 SEQ ID NO: 388 AraC Promoter fused with . . . gtttct coattact agagaaagaggggaca RBS

BBa K266 000 SEQ ID NO: 389 PAI + LasR -> LuxI (AI) . . . caccitt.cgggtgggc ctittctgcgtttata BBa K26.6005 SEQ ID NO: 390 PAI + LasR -> LaSI & . . . aataactctgatagtgctagtgtagatcto AI + LuxR -- Las I BBa K266 006 SEQ ID NO: 391 PAI + LasR -> LaSI + GFP & . . . caccitt.cgggtgggc ctittctgcgtttata AI + LuxR -- Las I + GFP BBa K26.6007 SEQ ID NO: 392 Complex QS -> LuxI & LaSI circuit . . . caccitt.cgggtgggc ctittctgcgtttata

TABLE 1.8 Examples of Positively reculated E. coli OS promoters Name Description Promoter Sequence BBa K112322 SEQ ID NO: 393 (Pdps in BBb format . . . gggacacaaac at caagaggatatgagatt

35

TABLE 1.9 Examples of Positively regulated E. coli O32 promoters Name Description Promoter Sequence BBa K112400 SEQ ID NO: 394 Promoter for grpE gene-Heat . . . ataataag.cgaagttagcigagatgaatgcg Shock and Ultrasound Sensitive

TABL E Examples of Positively regulated E. coli O54 promoters Name Description Promoter Sequence BBa Jé4979 SEQ ID NO: 395 gln.Ap2 . . . agttgg cacagattt cqctittatcttttitt

TABLE 21

Examples of Positively regulated B. subtilis OA promoters

Name Description Promoter Sequence BBa R0062 SEQ ID NO: 396 Promoter (luxR & HSL regulated.-- . . . caagaaaatggtttgttatagt caataaa lux pR) US 9,458,509 B2 65 66 TABLE 21 - continued Examples of Positively reculated B. subtilis OA promoters Name Description Promoter Sequence BBa R0065 SEQ ID NO: 397 Promoter (lambda cI and luxR gtgttgact attt tacct Ctggcggtgata regulated.--hybrid) BBa R0071 SEQ ID NO: 398 Promoter (RhlR & C4-HSL regulated) gttagctitt cqaattggctaaaaagtgttc BBa R0078 SEQ ID NO: 399 Promoter (cinR and HSL regulated) ccattctgctitt.ccacgaacttgaaaacgc BBa R0079 SEQ ID NO: 400 Promoter (LasR & PAI regulated) ggcc.gcgggttctttittggtacacgaaagc BBa R0080 SEQ ID NO: 401 Promoter (AraC regulated) ttittatcgcaact citc tactgtttct coat BBa R0082 SEQ ID NO: 402 Promoter (OmpR, positive) attatt ctgcatttittggggagaatggact BBa R0083 SEQ ID NO: 403 Promoter (OmpR, positive) attatt ctgcatttittggggagaatggact BBa R0084 SEQ ID NO: 404 Promoter (OmpR, positive) aacgttagtttgaatggaaagatgcctgca BBa R1062 SEQ ID NO: 405 Promoter, Standard (luxR and HSL aagaaaatggtttgttgatact cqaataaa regulated.--lux pR)

TABLE 2.2 Examples of Miscellaneous Prokaryotic Induced Promoters Name Description Promoter Sequence BBa J64001 SEQ ID NO: 406 psicA from Salmonella aacgcagt cqttaagttctacaaagttctggit BBa J64750 SEQ ID NO. 407 SPI-1 TTSS secretion-linked gtcggtgacagata acaggagtaagtaatg promoter from Salmonella BBa K112149 SEQ ID NO: 408 PmgtCB Magnesium promoter tattggctgactataataag.cgcaaattica from Salmonella BBa K116201 SEQ ID NO: 409 ureD promoter from P mirabilis BBa K125100 SEQ ID NO: 410 nir promoter cgaaacgggaac cctatattgat ct ctact from Synechocystis sp. PCC6803 BBa K131017 SEQ ID NO: 411 p qrr-4 from Vibrio harveyi aagttggcacgcatcgtgctittatacagat

TABL E 23

Examples of Yeast Positive (Activatible Promoters Name Description Promoter Sequence BBa J63006 SEQ ID NO: 412 yeast GAL1 promoter gaggaalactaga.ccc.gc.cgc.cac catggag BBa K284.002 SEQ ID NO: 413 JEN1 Promoter from gagtaaccaaaaccaaaacagatttcaacc Kluyveromyces lactis BBa K106699 SEQ ID NO: 414 Gall Promoter aaagtaagaatttittgaaaattcaatataa BBa K165041 SEQ ID NO: 415 Zif268-HIV binding sites + atacggtcaacgaactataattalactaaac TEF constitutive yeast promoter BBa K165034 SEQ ID NO: 416 Zif268-HIV bs + LexA bs + cacaaatacacacactaaattaataac tag mCYC promoter

BBa K165031 SEQ ID NO: 417 mCYC promoter plus LexA cacaaatacacacactaaattaataac tag binding sites

BBa K16503 O SEQ ID NO: 418 moYC promoter plus Zif 268 cacaaatacacacactaaattaataac tag HW binding sites US 9,458,509 B2 67 68 TABLE 23 - continued

Examples of Yeast Positive Activatible Promoters Name Description Promoter Sequence BBa K165001 SEQ ID NO: 419 pCAL1 + w/XhoI sites at actittaacgt caaggagaaaaaactata BBa K110016 SEQ ID NO: 420 A-Cell Promoter STE2 accottaagaac catat coaagaatcaaaa (backwards) BBa K110015 SEQ ID NO: 421 A-Cell Promoter MFA1 (RtL) citt catatataaac cqccagaaatgaatta BBa K110014 SEQ ID NO: 422 A-Cell Promoter MFA2 at Cttcatacaacaatalactaccalaccitta (backwards) BBa K110006 SEQ ID NO: 423 Alpha-Cell Promoter titt catacacaatataaacgattaaaagaa MF (ALPHA) 1 BBa K110005 SEQ ID NO: 424 Alpha-Cell Promoter aaattic cagtaaatticacatattggagaaa MF (ALPHA) 2 BBa K110004 SEQ ID NO: 425 Alpha-Cell Promoter Ste2 gggagc.ca.gaacgcttctggtggtgtaaat BBa J24813 SEQ ID NO: 426 URA3 Promoter from S. gcacagacittagattggtatatatacgcat cerevisiae BBa K284003 SEQ ID NO: 427 Partial DLD Promoter from aagtgcaagaaagaccagaaacgcaactica Kluyveromyces lactis

TABL E 24

Examples of Eukaryotic Positive Activatible Promoters

Name Description Promoter Sequence BBa I10498 SEQ ID NO : 428 Oct-4 promoter taaaaaaaaaaaaaaaaaaaaaaaaaaaaa. BBa JO5215 SEQ ID NO : 429 Regulator for R1-CREBH gggg.cgagggc.ccc.gc.ctic.cggaggcgggg BBa JO5216 SEQ ID NO : 43 O. Regulator for R3-ATF6 gaggggacggctCC9gcc.ccgggg.ccggag BBa J05217 SEQ ID NO : 431 Regulator for R2-YAP7 gggg.cgagggctCC9gcc.ccgggg.ccggag BBa JO5218 SEQ ID NO : 432 Regulator for R4-cMaf gaggggacggCCCC9CCtc.cggaggcgggg

TABL 25

Examples of Nedatively redulated repressible E. coli of O Oromoters Name Description Promoter Sequence BBa I1051 SEQ ID NO : 433 Lux cassette right promoter tgttatagt caatacctctggcggtgata BBa I12001 SEQ ID NO: 434 Promoter (PRM--) gatttalacgitat cagdacaaaaaagaaacc BBa I12006 SEQ ID NO: 435 Modified lamdba Prm promoter attacaaactitt cittgtatagatttaacgt. (repressed by 434 cI BBa I12036 SEQ ID NO: 436 Modified lamdba Prm promoter tittcttgtatagatttacaatgitat cittgt (cooperative repression by 434 cI BBa I12040 SEQ ID NO: 437 Modified lambda P (RM) tittcttgtagat acttacaatgitat cittgt promoter: -10 region from P (L) and cooperatively repressed by 434 cI BBa I12212 SEQ ID NO: 438 TetR - TetR-4C heterodimer actctgtcaatgatagagtggattcaaaaa promoter (negative) BBa I14015 SEQ ID NO: 439 P (LaS) TetC) ttittgg tacact coct atcagtgatagaga BBa I14016 SEQ ID NO: 440 P (LaS) CIO Ctttittgg tacactacctctgg.cggtgata BBa. 4032 SEQ ID NO: 441 promoter P (Lac) IQ aaac Cttt cqcgg tatggcatgatagogcc US 9,458,509 B2 69 70 TABLE 25- continued

Examples of Nedativel redulated (repressible E. coli of O rooters Name Description Promoter Sequence BBa I714889 SEQ ID NO: 442 OR21 of PR and PRM tattttacct ctggcggtgataatggttgc BBa I714924 SEQ ID NO: 443 RecA DlexO DLacO1 actict cq9 catggacgagctgtacaagtaa BBa I715003 SEQ ID NO: 444 hybrid pLac with UV5 mutation ttgtgagcggataacaatatgttgagcaca BBa I718018 SEQ ID NO: 445 dapAp promoter cattgaga cacttgtttgcacagaggatgg BBa I731004 SEQ ID NO: 446 FecA promoter ttct cqtt cqact catagotgaacacaa.ca BBa I732200 SEQ ID NO: 447 NOT Gate Promoter Family gaattgtgagcggataacaattggat.ccgg ember (DOO1O1wt1) BBa I732201 SEQ ID NO: 448 NOT Gate Promoter Family ggaattgtgagcgct caca attggat.ccgg ember (DOO1O11) BBa I732202 SEQ ID NO: 449 NOT Gate Promoter Family ggaattgtaa.gc.gcttacaattggat.ccgg ember (DOO1O22) BBa I732203 SEQ ID NO: 450 NOT Gate Promoter Family ggaattgtaaacgtttacaattggat.ccgg ember (DOO1O33) BBa I732204 SEQ ID NO: 451 NOT Gate Promoter Family ggaattgttgaacgttcaca attggat.ccgg ember (DOO1O44) BBa I732205 SEQ ID NO: 452 NOT Gate Promoter Family ggaattittgagcgctcaaaattggat.ccgg ember (DOO1O55) BBa I732206 SEQ ID NO: 453 NOT Gate Promoter Family ggaattatgagcgct cataattggat.ccgg ember (DOO1O66) BBa I732207 SEQ ID NO: 454 NOT Gate Promoter Family gggacgactgtata cagtcgt.cggat.ccgg ember (DOO1O77) BBa I73227 O SEQ ID NO: 455 Promoter Family Member with ggaattgtgagcgcttacaattggat.ccgg Hybrid Operator (DOO1O12) BBa I732271 SEQ ID NO: 456 Promoter Family Member with ggaattgtgagcgct cataattggat.ccgg Hybrid Operator (DOO1O16) BBa I732272 SEQ ID NO: 457 Promoter Family Member with ggaattgtgagctacagtcgt.cggat.ccgg Hybrid Operator (DOO1O17) BBa I732273 SEQ ID NO: 458 Promoter Family Member with ggaattgtaa.gc.gct caca attggat.ccgg Hybrid Operator (DOO1O21) BBa I732274 SEQ ID NO: 459 Promoter Family Member with ggaattgtaagcgttcaca attggat.ccgg Hybrid Operator (DOO1O24) BBa I732275 SEQ ID NO: 460 Promoter Family Member with ggaattgtaa.gc.gct cataattggat.ccgg Hybrid Operator (DOO1O26) BBa I7322 76 SEQ ID NO: 461 Promoter Family Member with ggaattgtaagctacagtcgt.cggat.ccgg Hybrid Operator (DOO1O27) BBa I7322 77 SEQ ID NO: 462 Promoter Family Member with ggaattgttgaacgct cataattggat.ccgg Hybrid Operator (DOO1O46) BBa I7322 78 SEQ ID NO: 463 Promoter Family Member with ggaattgttgaactacagtcgt.cggat.ccgg Hybrid Operator (DOO1O47) BBa I732279 SEQ ID NO: 464 Promoter Family Member with ggaattatgagcgct caca attggat.ccgg Hybrid Operator (DOO1O61) BBa I732301 SEQ ID NO: 465 NAND Candidate ggaattgtgagcgct cataattggat.ccgg (UO73O26DOO1O16) BBa I732302 SEQ ID NO: 466 NAND Candidate ggaattgtgagctacagtcgt.cggat.ccgg (UO73O27DOO1O17) BBa I732303 SEQ ID NO: 467 NAND Candidate ggaattgttgaacgct cataattggat.ccgg (UO73O22DOO1O46) BBa I7323O4 SEQ ID NO: 468 NAND Candidate ggaattgttgaactacagtcgt.cggat.ccgg

US 9,458,509 B2 73 74 TABLE 25- continued

Examples of Nedatively redulated (repressible) E. coli of O promoters

Name Description Promoter Sequence BBa I732421 SEQ ID NO: 494 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO85O + DO26O22) BBa I732422 SEQ ID NO: 495 Promoter Family Member . . . tcaattgtaa.gc.gcttacaattggat.ccgg (UO85O + DO38O22) BBa I732423 SEQ ID NO: 496 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg (UO85O + DO5OO22) BBa I732424 SEQ ID NO: 497 Promoter Family Member . . . caaattgtaa.gc.gcttacaattggat.ccgg (UO85O + DO 62O22) BBa I732425 SEQ ID NO: 498 Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DOO2O22) BBa I732426 SEQ ID NO: 499 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DO14O22) BBa I732427 SEO ID NO : 5 OO Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DO26O22) BBa I732428 SEQ ID NO : 501 Promoter Family Member . . . tcaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DO38O22) BBa I732429 SEQ ID NO : 502 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DO5OO22) BBa I73243 O SEQ ID NO : 503 Promoter Family Member . . . caaattgtaa.gc.gcttacaattggat.ccgg (UO73d + DO 62O22) BBa I732431 SEQ ID NO : 504 Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DOO2O22) BBa I732432 SEQ ID NO : 505 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DO14O22) BBa I732433 SEQ ID NO : 506 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DO26O22) BBa I732434 SEQ ID NO : 507 Promoter Family Member . . . tcaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DO38O22) BBa I732435 SEQ ID NO : 508 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DO5OO22) BBa I732436 SEQ ID NO : 509 Promoter Family Member . . . caaattgtaa.gc.gcttacaattggat.ccgg (UO61O + DO 62O22) BBa I732437 SEO ID NO : 51O Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg

BBa I732438 SEQ ID NO : 511 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg

BBa I732439 SEQ ID NO : 512 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg

BBa I73244 O SEQ ID NO : 513 Promoter Family Member . . . tcaattgtaa.gc.gcttacaattggat.ccgg

BBa I732441 SEQ ID NO : 514 Promoter Family Member . . . aaaattgtaa.gc.gcttacaattggat.ccgg

BBa I732442 SEQ ID NO : 515 Promoter Family Member . . . caaattgtaa.gc.gcttacaattggat.ccgg

BBa I732443 SEQ ID NO : 516 Promoter Family Member . . . galaattgtaa.gc.gcttacaattggat.ccgg

BBa I732444 SEQ ID NO : 517 Promoter Family Member . . . taaattgtaa.gc.gcttacaattggat.ccgg

BBa I732445 SEQ ID NO : 518 Promoter Family Member . . . gtaattgtaa.gc.gcttacaattggat.ccgg (UO37o + DO26O22) US 9,458,509 B2 75 76 TABLE 25 - continued

Examples of Nedativel redulated repressible E. coli of O rooters Name Description Promoter Sequence BBa I732446 SEQ ID NO: 519 Promoter Family Member t caattgtaa.gc.gcttaca attggat.ccgg (UO37O11 + DO38O22) BBa I732447 SEQ ID NO: 520 Promoter Family Member aaaattgtaa.gc.gcttaca attggat.ccgg (UO37O11 + DO50022) BBa I732448 SEQ ID NO: 521 Promoter Family Member caaattgtaa.gc.gcttaca attggat.ccgg (UO37O11 + DO62O22) BBa I732450 SEQ ID NO: 522 Promoter Family Member gccalaattaaac aggattaac aggat.ccgg (UO73O26 + DO62NUL) BBa I732451 SEQ ID NO: 523 Promoter Family Member gccalaattaaac aggattaac aggat.ccgg (UO73O27 + DO62NUL) BBa I732452 SEQ ID NO: 524 Promoter Family Member caaattatgagcgcticaca attggat.ccgg (UO73O26 + DO62O61) BBa I739101 SEQ ID NO: 525 Double Promoter (constitutive ? tgatagagattic cctat cagtgatagagat TetR, negative) BBa I73.9102 SEQ ID NO: 526 Double Promoter (cI, negative/ tgatagagattic cctat cagtgatagagat TetR, negative) BBa I739 103 SEQ ID NO: 527 Double Promoter (lacI, negative/ gttattaattatttaagtgtt attaatt P22 cII, negative) BBa I739 104 SEQ ID NO: 528 Double Promoter (LuxRAHSL, gttctittaattatttaagtgttctittaatt positive/P22 cII, negative) BBa I739105 SEQ ID NO: 529 Double Promoter (LuxRAHSL, cgtgcgtgttgata acaccgtgcgtgttga positive / cI, negative) BBa I739106 SEQ ID NO: 530 Double Promoter (TetR, negative/ gtgttctittaat atttalagtgttctittaat P22 cII, negative) BBa I739107 SEQ ID NO: 531 Double Promoter (cI, negative/ ggaattgtgagcggataacaattt cacaca LacI, negative) BBa I746665 SEQ ID NO: 532 Pspac-hy promoter tgtgttgtaattgtgagcggataacaattaa BBa I751500 SEQ ID NO: 533 pcI (for positive control of pcI- ttttacct ctggcggtgataatggttgcag lux hybrid promoter) BBa I751501 SEQ ID NO: 534 plux-cI hybrid promoter gtgttgatgcttitt at Caccgc.cagtggta BBa I751502 SEQ ID NO: 535 plux-lac hybrid promoter agtgttgttggaattgtgagcggataacaatt BBa I756014 SEQ ID NO: 536 LexAoperator- agggggtggggg.cgc.gttggcgc.gc.cacac MajorLatePromoter BBa I761011 SEQ ID NO: 537 CinR, CinL and glucose acat cittaaaagttittagtat catatt cqt controlled promoter BBa J05209 SEQ ID NO: 538 Modified Pir Promoter tattttacct ctggcggtgataatggttgc BBa JO5210 SEQ ID NO: 539 Modified Prm + Promoter atttataaatagtggtgatagatttaacgt. BBa J07019 SEQ ID NO: 540 FecA Promoter (with Fur box) accc.ttct cott cqact catagotgaacac BBa J15301 SEQ ID NO: 541 Pars promoter from Escherichia tgactitat cogctt.cgaagagagacactac coli chromosomal airs operon. BBa J22052 SEQ ID NO: 542 Pcya aggtgttaaattgat cacgttittagac cat BBa J22106 SEQ ID NO: 543 rec A (SOS) Promoter caatttggtaaaggctic catcatgtaataa BBa J22126 SEQ ID NO: 544 Rec A (SOS) promoter gagaaacaatttggtaaaggctic catcatg BBa J31013 SEQ ID NO: 545 pLac Backwards cf. aacgc.gcggggagaggcggitttgcg tattg BBa R0010) BBa J34800 SEQ ID NO: 546 Promoter tetracycline inducible Cagtgatagagatactgagcacat cagcac BBa J34.806 SEQ ID NO: 547 promoter lac induced titatgct tcc.ggct cqtataatgtttcaaa US 9,458,509 B2 77 78 TABLE 25- continued

Examples of Nedatively redulated (repressible E. coli of O Oromoters

Name Description Promoter Sequence BBa J34.809 SEQ D NO : 548 promoter lac induced ggct cqtatgttgttgtcgaccgagctg.cgc BBa J54016 SEQ D NO : 549 promoter lacq aaac Cttt cqcgg tatggcatgatagogcc BBa J54120 SEQ D NO : 550 EmrR regulated promoter atttgtcactgtcgttactatat cqgctgc BBa J54130 SEQ D NO : 551 BetI regulated promoter gtccaatcaataac cqctittaatagataaa BBa J56012 SEQ D NO : 552 Invertible sequence of dna actittatt at caataagttaaatcgg tacc inclu des Ptric promoter BBa J64065 SEQ D NO : 553 cI repressed promoter gtgttgactattttacctctggcggtgata BBa J64067 SEQ D NO : 554 LuxR + 3OC6HSL independent gtgttgactattttacctctggcggtgata ROO65

BBa J64068 SEQ D NO : 555 increased strength ROO51 atacct ctggcggtgatatataatggttgc BBa J64069 SEQ D NO : 5.56 ROO65 with lux box deleted gtgttgactattttacctctggcggtgata BBa J64712 D NO : 5.57 LasR/LaSI Inducible & gaaatctggcagtttittgg tacacgaaagc RHLI repressible Promoter BBa J64800 SEQ D NO : 55.8 RHLRARHILI Inducible & tgc.cagttctggcaggit ctaaaaagtgttc LasR/ Las I repressible Promoter BBa J64981 SEQ D NO : 559 OmpR-P strong binding, agcgct cacaatttaatacgact cactata regu atory region for Team Challengeo3-2007 BBa J64987 SEQ D NO : 560 LacI Consensus Binding Site in taataattgtgagcgct cacaattittgaca sigma 70 binding region BBa J72005 SEQ D NO : 561 {Ptet} promoter in BBb atcc ct at cagtgatagagat actgag cac BBa. KO 86017 SEQ D NO : 562 unmodified Lutz-Bujard Laco ttgtgagcggataacaagatactgagcaca promo te

BBa. KOS11OO SEQ D NO : 563 pLac lux hybrid promoter ggaattgtgagcggataacaattt cacaca

BBa. KOS1101 SEQ D NO : 564 pTet Lac hybrid promoter ggaattgtgagcggataacaattt cacaca

BBa. KOS1104 SEQ D NO : 565 pLac/Mnt Hybrid Promoter ggaattgtgagcggataacaattt cacaca

BBa. KOS1105 SEQ D NO : 566 pTet/Mnt Hybrid Promoter agaactgtaatc.ccitat cagtgatagagat

BBa. KOS1106 SEQ D NO : 567 LSrA/CI hybrid promoter tgttgattitatic talacaccgtgcgtgttga

BBa. KOS11 Of SEQ D NO : 568 pLux/cI Hybrid Promoter acaccgtgcgtgttgat at agtic gaataaa

BBa. KOS1110 SEQ D NO : 569 LacI Promoter CCtttcgcgg tatggcatgatagcgc.ccgg

BBa. KOS1111 SEQ D NO : 570 LacIQ promoter CCtttcgcgg tatggcatgatagcgc.ccgg

BBa. KOS1112 SEQ D NO : 571 pLacIQ1 promoter CCtttcgcgg tatggcatgatagcgc.ccgg

BBa. KOS1143 SEQ D NO : 572 pLas/cI Hybrid Promoter ggttctttittgg tacct Ctggcggtgataa

BBa. KOS1146 SEQ D NO : 573 pLas/Lux Hybrid Promoter tgtaggat.cgtacaggtataa attctt cag

BBa. KOS1157 SEQ D NO : 574 pLux/Las Hybrid Promoter citat ct catttgctagtatagt cqaataaa

BBa. KOS3 OOO SEQ D NO : 575 pRecA with LexA binding site gtatatatatacagtataattgcttcaa.ca

BBa. KOS3 OO8 SEQ D NO : 576 reverse BBa R0011 cacaatgtcaattgttatcc.gct cacaatt

BBa. KOS 412 O SEQ D NO ; sif pLacI/ara-1 aattgtgagcggataacaattt cacacaga

BBa. KOS 414 O SEQ D NO : 578 pLacIq ccggaagagagt caatt Cagggtggtgaat

BBa. K1 O1 OOO SEQ D NO : 579 Dual-Repressed Promoter for acggtgacct agat Ctc.cgat actgagcac p22 m nt and TetR

BBa. K1 O1 OO1 SEQ D NO : 58O Dual-Repressed Promoter for tggaattgtgagcggataaaattt cacaca LacI and LambdacI US 9,458,509 B2 79 80 TABLE 25- continued

Examples of Nedatively redulated (repressible E. coli of O Oromoters Name Description Promoter Sequence BBa K101002 SEQ ID NO: 581 Dual Repressed Promoter for tagtagataatttalagtgttctittaattitc p22 cII and TetR BBa K101017 SEQ ID NO: 582 MioC Promoter (DNAa- c caacg.cgttcacagogtacaattact agt (Repressed Promoter) BBa K109200 SEQ ID NO: 583 AraC and TetR promoter aacaaaaaaacggat.cctic tagttgcggcc (hybrid) BBa K112118 SEQ ID NO: 584 rrnB P1 promoter ataaatgcttgact ctitagcgggaaggcg BBa K112318 SEQ ID NO: 585 {} in BBb attt catgatgatacgtgagcggatagaag format BBa K112401 SEQ ID NO: 586 Promoter for recA gene - SOS caaacagaaag.cgttggcggcagcactggg and Ultrasound Sensitive BBa K112402 SEQ ID NO: 587 promoter for FabA gene - gtcaaaatgaccgaaacgggtggta acttic Membrane Damage and Ultrasound Sensitive BBa K112405 SEQ ID NO: 588 Promoter for CadA and Cad agtaatcttatcgc.cagtttggtctggtca genes BBa K112406 SEQ ID NO: 589 cadC promoter agtaatcttatcgc.cagtttggtctggtca BBa K112701 SEQ ID NO. 590 has promoter aattctgaacaa catcc.gtactic titcgtgc BBa K112 708 SEQ ID NO. 591 PfhuA tttacgittat catt cactitta catcagagt BBa K113.009 SEQ ID NO. 592 pBad/araC gtttct coat accogtttittittgggctago BBa K116 001 SEQ ID NO. 593 nhaA promoter that can be cgatct attcacctgaaagagaaataaaaa regulated by pH and nhaR protein. BBa K116500 SEQ ID NO. 594 OmpF promoter that is activated aaacgttagtttgaatggaaagatgcctgc or repressed by OmpR according to osmolarity. BBa K119002 SEQ ID NO. 595 RcnR operator (represses RonA) attgcc gaattaatact aagaattattatc BBa K121011 SEQ ID NO. 596 promoter (lacI regulated) acaggaaa.ca.gctatgaccatgattacgc.c BBa K121014 SEQ ID NO. 597 promoter (lambda cI regulated) actggcggittataatgagcacat cago agg BBa K137046 SEQ ID NO. 598 150 bp inverted tetR promoter Caccgacaaacaacagataaaacgaaaggc BBa K137047 SEQ ID NO: 599 250 bp inverted tetR promoter agtgtt attaagctact aaag.cg tagttitt BBa K137048 SEQ ID NO: 600 350 bp inverted tetR promoter gaataagaaggctggct Ctgcaccttggtg BBa K137049 SEQ ID NO: 601 450 bp inverted tetR promoter ttagcg acttgatgct cittgat citt coaat BBa K137050 SEQ ID NO: 602 650 bp inverted tetR promoter a catctaaaacttittagcgittattacgitaa BBa K137051 SEQ ID NO: 603 850 bp inverted tetR promoter titc.cgacct cattaa.gcagctictaatgcgc BBa K137124 SEQ ID NO: 604 LacI-repressed promoter A81 caatttittaa acct gtaggat.cgtacaggt BBa K137125 SEQ ID NO: 605 LacI-repressed promoter B4 caatttittaaaattaaaggcgttacccaac BBa K145150 SEQ ID NO: 606 Hybrid promoter: HSL-LuxR tagtttataatttalagtgttctittaattitc activated, P22 C2 repressed BBa K145152 SEQ ID NO: 607 Hybrid promoter: P22 c2, LacI gaaaatgtgagcgagtaacaacct cacaca NOR gate BBa K256028 SEQ ID NO: 608 placI: CHE Cacctt.cgggtgggcct ttctg.cgtttata BBa K259005 SEQ ID NO: 609 AraC Rheostat Promoter ttittatcgcaact citct actgtttct coat BBa K259.007 SEQ ID NO: 610 AraC Promoter fused with RBS gtttct coattact agagaaagaggggaca BBa K266 001 SEQ ID NO: 611 Inverter TetR - 2 LuxR Cacctt.cgggtgggcct ttctg.cgtttata

BBa K266003 SEQ ID NO: 612 POPS - is Lac Inverter - LasR Cacctt.cgggtgggcct ttctg.cgtttata

BBa K266 OO4 SEQ ID NO : 613 Const Lac Inverter -> LaSR Cacctt.cgggtgggcct ttctg.cgtttata US 9,458,509 B2 81 82 TABLE 25- continued

Examples of Nedatively redulated (repressible) E. coli of O promoters

Name Description Promoter Sequence

BBa K26.6005 SEQ ID NO: 614 PAI - LaSR - > LaSI & AI - LuxR - - aataactctgatagtgctagtgtagat citc LaSI

BBa K266006 SEQ ID NO: 615 PAI - LaSR - > LaSI - GFP & Cacctt.cgggtgggcct ttctg.cgtttata AI - LuxR - - LaSI - GFP BBa K266.007 SEQ ID NO: 616 Complex QS -> LuxI & Las I Cacctt.cgggtgggcct ttctg.cgtttata circuit BBa K266008 SEQ ID NO: 617 J23100 + Lac inverter ttgtgagcggataacaagatactgagcaca BBa K266 009 SEQ ID NO: 618 J23100 + Lac inverter + RBS actgagcacatact agagaaagaggagaaa BBa K266 011 SEQ ID NO: 619 Lac Inverter and strong RBS actgagcacatact agagaaagaggagaaa BBa K292002 SEQ ID NO: 620 pLac (LacI regulated) + Strong t cacacatact agagattaaagaggagaaa RBS BBa M31370 SEQ ID NO: 621 tacI Promoter ggaattgtgagcggataacaattt cacaca BBa R0010 SEQ ID NO: 622 promoter (lacI regulated) ggaattgtgagcggataacaattt cacaca BBa R0011 SEQ ID NO: 623 Promoter (lacI regulated, lambda ttgtgagcggataacaagatactgagcaca pL hybrid) BBa R0040 SEQ ID NO: 624 TetR repressible promoter atcc citat cagtgatagagatactgagcac BBa R0050 SEQ ID NO: 625 Promoter (HKO22 cI regulated) cc.gt cataatatgalaccataagttcaccac BBa R0051 SEQ ID NO: 626 promoter (lambda cI regulated) tattttacct ctggcggtgataatggttgc BBa R0052 SEO ID NO : 627 Promoter (434 cI regulated) attgtatgaaaatacaagaaagtttgttga BBa R0053 SEQ ID NO: 628 Promoter (p.22 cII regulated) tagtagataatttalagtgttctittaattitc BBa R0061 SEQ ID NO: 629 Promoter (HSL-mediated luxR ttgacacctgtaggat.cgtacaggtataat repressor) BBa R0063 SEQ ID NO: 63 O Promoter (luxR & HSL regulated - - cacgcaaaacttgcgacaaacaatagg taa lux pI) BBa R0065 SEQ ID NO: 631 Promoter (lambda cI and luxR gtgttgactattttacctctggcggtgata regulated -- hybrid) BBa R0073 SEQ ID NO: 632 Promoter (Mnt regulated) tagat citcctatagtgagt cqtattaattit BBa R0074 SEQ ID NO: 633 Promoter (PenI regulated) tactittcaaagact acatttgtaagatttg BBa R0075 SEQ ID NO: 634 Promoter (TP901 cI regulated) cataaagttcatgaaacgtgaactgaaatt BBa R1050 SEO ID NO : 635 Promoter, Standard (HKO22 cI cc.gtgatact atgalaccataagttcaccac regulated)

BBa R1051 SEQ ID NO: 636 Promoter, Standard (lambda cI aattittacct ctggcggtgat actggttgc regulated)

BBa R1052 SEO ID NO : 637 Promoter, Standard (434 cI attg tatgatact acaagaaagtttgttga regulated)

BBa R1053 SEQ ID NO: 638 Promoter, Standard (p.22 cII tagtagatactittaagtgttctittaattitc regulated)

BBa R2000 SEQ ID NO: 639 Promoter, Zif23 regulated, test: tggit Cocacgc.gcgtgggatact acgt cag between

BBa R2001 SEQ ID NO: 64 O Promoter, Zif23 regulated, test: attacggtgagatact.cccacgc.gc.gtggg after

BBa R2002 SEQ ID NO: 641 Promoter, Zif23 regulated, test: acgc.gc.gtgggatact.cccacgc.gc.gtggg between and after

BBa R2108 SEQ ID NO: 642 Promoter with operator site for gattagatt cataa atttgagagaggagtt US 9,458,509 B2 83 84 TABLE 25- continued

Examples of Nedativel redulated (repressible E. coli of O rooters Name Description Promoter Sequence BBa R2109 SEQ ID NO: 643 Promoter with operator site for acttagatt cataa atttgagagaggagtt C2OO3 BBa R2110 SEQ ID NO: 644 Promoter with operator site for ggittagatt cataa atttgagagaggagtt C2OO3 BBa R2111 SEQ ID NO: 645 Promoter with operator site for acttagatt cataa atttgagagaggagtt C2OO3 BBa R2112 SEQ ID NO: 646 Promoter with operator site for aattagatt cataa atttgagagaggagtt C2OO3

BBa R2113 SEO ID NO : 647 Promoter with operator site for acttagatt cataa atttgagagaggagtt C2OO3 BBa R2114 SEQ ID NO: 648 Promoter with operator site for atttagatt cataa atttgagagaggagtt C2OO3 BBa R2201. SEQ ID NO: 649 C2OO6-repressible promoter cacgc.gcgtgggaatgttataatacgt cag BBa SO4209 SEQ ID NO: 650 ROO51: Q04121 : BOO34: COO79: BOO15 actgagcacatact agagaaagaggagaaa

TABL E 26 Examples of Negatively regulated (repressible) E. coli OS promoters

Name Description Promoter Sequence BBa KO 86030 SEQ ID NO : 651 modified Lutz-Bujard LacO cagtgagcgagtaacaactacgctgttitta promoter, with alternative sigma factor O38 BBa KO 86031 SEQ ID NO: 652 modified Lutz-Bujard LacO Cagtgagcgagtaacaactacgctgttitta promoter, with alternative sigma factor O38 BBa KO 86032 SEQ ID NO: 653 modified Lutz-Bujard LacO atgtgagcggataacactata attaataga promoter, with alternative sigma factor O38 BBa KO 86033 SEQ ID NO: 654 modified Lutz-Bujard LacO atgtgagcggataacactata attaataga promoter, with alternative sigma factor O38 BBa K112318 SEQ ID NO: 655 {

TABL E 27

Examples of Negatively regulated (repressible) E. coli O32 promoters

Name Description Promoter Sequence

BBa KO 86026 SEQ ID NO: 656 modified Lutz-Bujard LacO ttgtgagcgagtggcaccattaagtacgta promoter, with alternative sigma factor O32

BBa KO 86027 SEQ ID NO: 657 modified Lutz-Bujard LacO ttgtgagcgagtgacaccattaagtacgta promoter, with alternative sigma factor O32

BBa KO 86028 SEQ ID NO: 658 modified Lutz-Bujard LacO ttgtgagcgagtaacaccattaagtacgta promoter, with alternative sigma factor O32

BBa KO 86029 SEQ ID NO: 659 modified Lutz-Bujard LacO ttgtgagcgagtaacaccattaagtacgta promoter, with alternative sigma factor O32 US 9,458,509 B2 85 86 TABL E 28

Examples of Nedativel redulated repressible E. coli o54 rooters

Name Description Promoter Sequence BBa J64979 SEQ ID NO : 660 gln.Ap2 agttggcacagattt cqctittat cittttitt

TABL E 29 Examples of Repressible B. subtilis of promoters

Name Description Promoter Sequence BBa KO90501 SEQ ID NO: 661 Gram-Positive IPTG-Inducible tggaattgtgagcggataacaattaa.gctt Promoter

BBa K143 014 SEQ ID NO: 662 Promoter Xyl for B. subtilis agtttgtttaaacaacaaactaataggtga BBa K143015 SEQ ID NO : 663 Promoter hyper-spank for B. aatgtgtgtaattgtgagcggataacaatt subtilis

TABL E 3 O Examples of T7 Repressible Promoters Name Description Promoter Sequence BBa RO184 SEQ ID NO: 664 T7 promoter (lacI repressible) at aggggaattgtgagcggataacaatt CC BBa R0185 SEQ ID NO: 665 T7 promoter (lacI repressible) at aggggaattgtgagcggataacaatt CC BBa R0186 SEQ ID NO: 666 T7 promoter (lacI repressible) at aggggaattgtgagcggataacaatt CC BBa R0187 SEQ ID NO: 667 T7 promoter (lacI repressible) at aggggaattgtgagcggataacaatt CC

TABLE 31 Examples of Yeast Repressible Promoters

Name Description Promoter Sequence BBa I766558 SEQ ID NO: 668 pFig1 (Inducible) Promoter . aaacaaacaaacaaaaaaaaaaaaaaaaaa. BBa I766214 SEQ ID NO: 669 pGal1 at actittaacgt caaggagaaaaaactata BBa K165000 SEO ID NO : 67 O MET 25 Promoter tagatacaattic tatt acceccatc catac

50

TABLE 32 Examples of Eukaryotic Repressible Promoters

Name Description Promoter Sequence BBa I756015 SEO ID NO : 671 CMW Promoter with lac ttagtgaaccgt.ca.gatcactagt ctgcag operator sites

BBa I756016 SEO ID NO : 672 CMV-tet promoter ttagtgaaccgt.ca.gatcactagt ctgcag BBa I756017 SEO ID NO : 673 U6 promoter with tet ggaaaggacgaaac accgactagtctgcag operators

BBa I756 018 SEO ID NO : 674 Lambda Operator in SV-40 attgtttgttg tattittagacitagtctgcag intron US 9,458,509 B2 87 88 TABLE 32-continued Examples of Eukaryotic Repressible Promoters

Name Description Promoter Sequence BBa I756 019 SEQ ID NO: 675 Lac Operator in SV-40 intron attgtttgttg tattittagacitagtctgcag BBa I756,020 SEQ ID NO: 676 Tet Operator in SV-40 intron attgtttgttg tattittagacitagtctgcag BBa I756,021 SEQ ID NO: 677 CMV promoter with Lambda ttagtgaaccgt.ca.gatcactagt ctgcag Operator

TABL E 33 Examples of Combination Inducible & Repressible E. coli Promoters Name Description Promoter Sequence BBa I1051 SEO ID NO: 678 Lux cassette right promoter tgttatagt caatacctctggcggtgata BBa I12006 SEO ID NO: 679 Modified lamdba Prm promoter attacaaactittcttgtatagatttalacgt. (repressed by 434 cI BBa I12036 SEQ ID NO: 68O Modified lamdba Prm promoter tttcttgtatagatttacaatgitat cittgt (cooperative repression by 434 cI BBa I12040 SEQ ID NO: 681 Modified lambda P (RM) promoter: tttcttgtagatact tacaatgitat cittgt -10 region from P (L) and cooperatively repressed by 434 cI

BBa I14015 SEQ ID NO: 682 P (LaS) TetC) ttittgg tacactic cctato agtgatagaga BBa I14O16 SEQ ID NO: 683 P (LaS) CIO citttittgg tacactacctctgg.cggtgata BBa I714924 SEQ ID NO: 684 RecA DlexO DLacO1 actict cq9 catggacgagctgtacaagtaa BBa I731004 SEQ ID NO: 685 FecA promoter ttct cqtt cqact catagotgaacacaa.ca BBa I732301 SEQ ID NO: 686 NAND Candidate ggaattgtgagcgct cataattggat.ccgg (UO73O26DOO1O16) BBa I732302 SEQ ID NO: 687 NAND Candidate ggaattgtgagct acagtcgt.cggat.ccgg (UO73O27DOO1O17) BBa I732303 SEQ ID NO: 688 NAND Candidate ggaattgttgaacgct cataattggat.ccgg (UO73O22DOO1O46) BBa I732304 SEQ ID NO: 689 NAND Candidate ggaattgttgaact acagtcgt.cggat.ccgg (UO73O22DOO1O47) BBa I732305 SEQ ID NO: 690 NAND Candidate taaattgttgaacgct cataattggat.ccgg (UO73O22DO59046) BBa I732306 SEQ ID NO: 691 NAND Candidate galaattgtaa.gc.gct tacaattggat.ccgg (UO73O11DOO2O22) BBa I732351 SEQ ID NO: 692 NOR Candidate galaattgtaa.gc.gct tacaattggat.ccgg (UO37O11DOO2O22) BBa I732352 SEQ ID NO: 693 NOR Candidate ggaattgtaa.gc.gct tacaattggat.ccgg (UO35O44DOO1O22) BBa I732400 SEQ ID NO: 694 Promoter Family Member gccalaattaalacaggattaac aggat.ccgg (UO97NUL + DO62NUL) BBa I732401 SEQ ID NO: 695 Promoter Family Member gccalaattaalacaggattaac aggat.ccgg (UO97O11 + DO62NUL) BBa I732402 SEQ ID NO: 696 Promoter Family Member gccalaattaalacaggattaac aggat.ccgg (UO85O11 + DO62NUL) BBa I732403 SEQ ID NO: 697 Promoter Family Member gccalaattaalacaggattaac aggat.ccgg (UO73O11 + DO62NUL) BBa I732404 SEQ ID NO: 698 Promoter Family Member gccalaattaalacaggattaac aggat.ccgg (UO61O11 + DO62NUL)

US 9,458,509 B2 91 92 TABLE 33 - continued Examples of Combination Inducible & Repressible E. coli Promoters Name Description Promoter Sequence BBa I732430 SEQ ID NO: 724 Promoter Family Member . . . calaattgtaa.gc.gct tacaattggat.ccgg (UO73d + DO 62O22)

BBa I732431 SEQ D N O : 725 Promoter Family Member . . . galaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DOO2O22) BBa I732432 SEQ ID NO: 726 Promoter Family Member . . . talaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DO14O22) BBa I732433 SEO ID NO: 727 Promoter Family Member . . . gtaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DO26O22) BBa I732434 SEQ ID NO: 728 Promoter Family Member . . . tcaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DO38O22) BBa I732435 SEO ID NO: 729 Promoter Family Member . . . aaaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DO5OO22) BBa I732436 SEQ ID NO: 73 O Promoter Family Member . . . calaattgtaa.gc.gct tacaattggat.ccgg (UO61O + DO 62O22) BBa I732437 SEO ID NO: 731 Promoter Family Member . . . galaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DOO2O22) BBa I732438 SEQ ID NO: 732 Promoter Family Member . . . talaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DO14O22) BBa I732439 SEO ID NO: 733 Promoter Family Member . . . gtaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DO26O22) BBa I73244 O SEQ ID NO: 734 Promoter Family Member . . . tcaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DO38O22) BBa I732441 SEQ ID NO: 735 Promoter Family Member . . . aaaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DO5OO22) BBa I732442 SEQ ID NO: 736 Promoter Family Member . . . calaattgtaa.gc.gct tacaattggat.ccgg (UO49O + DO 62O22) BBa I732443 SEO ID NO: 737 Promoter Family Member . . . galaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DOO2O22) BBa I732444 SEQ ID NO: 738 Promoter Family Member . . . talaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DO14O22) BBa I732445 SEO ID NO: 739 Promoter Family Member . . . gtaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DO26O22) BBa I73244 6 SEQ ID NO: 74. O Promoter Family Member . . . tcaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DO38O22) BBa I732447 SEQ ID NO: 741 Promoter Family Member . . . aaaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DO5OO22) BBa I732448 SEQ ID NO: 742 Promoter Family Member . . . calaattgtaa.gc.gct tacaattggat.ccgg (UO37o + DO 62O22) BBa I732450 SEQ ID NO: 743 Promoter Family Member . . . go calaattaalacaggattaac aggat.ccgg (UO73O26 + DO62NUL)

BBa I732451 SEQ ID NO: 744 Promoter Family Member . . . go calaattaalacaggattaac aggat.ccgg (UO73O27 + DO62NUL)

BBa I732452 SEO ID NO: 745 Promoter Family Member . . . calaattatgagcgct caca attggat.ccgg (UO73O26 + DO62O61) BBa I73.9102 SEQ ID NO: 746 Double Promoter (cI, negative/ . . . tigatagagatt.ccct at cagtgatagagat TetR, negative)

BBa I7391O3 SEO ID NO: 747 Double Promoter (lacI, nega- . . . gttctittaattatttaagtgttctittaatt tive/P22 cII, negative) BBa I739 104 SEQ ID NO: 748 Double Promoter (LuxRAHSL, . . . gttctittaattatttaagtgttctittaatt positive/P22 cII, negative) US 9,458,509 B2 93 94 TABLE 33 - continued Examples of Combination Inducible & Repressible E. coli Promoters Name Description Promoter Sequence BBa I739105 SEQ ID NO: 749 Double Promoter (LuxRAHSL, cgtgcgtgttgatalacaccgtgcgtgttga positive/cI, negative) BBa I739106 SEQ ID NO: 750 Double Promoter (TetR, nega- gtgttctittaatatttalagtgttctittaat tive/P22 cII, negative) BBa I739107 SEQ ID NO: 751 Double Promoter (cI, negative/ ggaattgtgagcggataacaattt cacaca LacI, negative) BBa I741018 SEQ ID NO: 752 Right facing promoter (for gttacgtttatcgcggtgattgttactitat xylF) controlled by xylR and CRP-cAMP BBa I741019 SEQ ID NO: 753 Right facing promoter (for gcaaaataaaatggaatgatgaaactgggit xylA) controlled by xylR and CRP-cAMP BBa I 742124 SEQ ID NO: 754 Reverse complement Lac promoter aacgc.gcggggagaggcggitttgcgt attg BBa I751501 SEQ ID NO: 755 plux-cI hybrid promoter gtgttgatgcttittat caccgc.cagtggta BBa I751502 SEQ ID NO: 756 plux-lac hybrid promoter agtgttgttggaattgtgagcggataacaatt BBa I761011 SEQ ID NO: 757 CinR, CinL and glucose acat cittaaaagttt tagtat catattogit controlled promoter BBa I765.007 SEQ ID NO: 758 Fe and UV promoters ctgaaag.cgcataccgctatggagggggitt BBa J05209 SEO ID NO: 759 Modified Pir Promoter tattttacct ctggcggtgataatggttgc

BBa JO5210 SEO ID NO: 76 O Modified Prm + Promoter atttataaatagtggtgatagatttalacgt. BBa J58100 SEO ID NO: 761 AND-type promoter synergis- atttataaatagtggtgatagatttalacgt. tically activated by cI and CRP BBa J64712 SEO ID NO: 762 LasR/LaSI Inducible & gaaatctggcagtttittgg tacacgaaagc RHLR/RHLI repressible Promoter BBa J64800 SEO ID NO: 763 RHLRARHILI Inducible & tgc.cagttctggCaggit ctaaaaagttgttc LasR/Las I repressible Promoter BBa J64804 SEO ID NO: 764 The promoter region (inclusive cacagaacttgcatttatataaagggaaag of regulator binding sites) of the B. subtilis RocDEF operon BBa J64979 SEO ID NO: 765 glnAp2 agttggcacagattt cqctittat cittttitt BBa J64981 SEO ID NO: 766 OmpR-P strong binding, regula- agcgct cacaatttaatacgact cactata tory region for Team Challenge 03-2007 BBa KO91100 SEQ ID NO: 767 pLac lux hybrid promoter ggaattgtgagcggataacaattt cacaca BBa KO91101 SEQ ID NO: 768 pTet Lac hybrid promoter ggaattgtgagcggataacaattt cacaca BBa KO91104 SEQ ID NO: 769 pLac/Mnt Hybrid Promoter ggaattgtgagcggataacaattt cacaca BBa KO91105 SEQ ID NO: 770 pTet/Mnt Hybrid Promoter agaactgtaatcc citat cagtgatagagat BBa KO91106 SEQ ID NO: 771 LSrA/CI hybrid promoter tgttgatttatctaacaccgtgcgtgttga BBa KO91107 SEQ ID NO: 772 pLux/cI Hybrid Promoter acaccgtgcgtgttgat at agtic gaataaa BBa KO91143 SEQ ID NO: 773 pLas/cI Hybrid Promoter ggttctttittggtacct Ctggcggtgataa BBa KO91146 SEQ ID NO: 774 pLas/Lux Hybrid Promoter tgtaggat.cgtacaggtataa attct tcag BBa KO91157 SEQ ID NO: 775 pLux/Las Hybrid Promoter citat ct catttgctagtatagt cqaataaa BBa KO94120 SEQ ID NO: 776 pLacI/ara-1 aattgtgagcggataacaattt cacacaga BBa K100000 SEQ ID NO: 777 Natural Xylose Regulated Bi- gttacgtttatcgcggtgattgttactitat Directional Operator BBa K101000 SEQ ID NO: 778 Dual-Repressed Promoter for p22 acggtgacct agatcto catactgagcac mint and TetR BBa K101001 SEQ ID NO: 779 Dual-Repressed Promoter for LacI tggaattgtgagcggataaaattt cacaca and LambdacI US 9,458,509 B2 95 96 TABLE 33 - continued Examples of Combination Inducible & Repressible E. coli Promoters

Name Description Promoter Sequence

BBa. SEO ID NO: 78O Dual-Repressed Promoter for p22 tagtagataatttaagtgttctittaattitc cII and TetR

BBa. K1092 OO SEO ID NO: 781 AraC and TetR promoter (hybrid) aacaaaaaaacggat.cctic tagttgcggcc

BBa. K112118 SEO ID NO: 782 rrnB P1 promoter at aaatgcttgactctgtagcgggaaggcg

BBa. K112318 SEO ID NO: 783 {} in BBb format attt catgatgatacgtgagcggatagaag

BBa. K112322 SEO ID NO: 784 {Pdps in BBb format gggacacaaacat Caagaggatatgagatt

BBa. K1124 O2 SEO ID NO: 785 promoter for FabA gene gtcaaaatgaccgaaacgggtggtaact tc Membrane Damage and Ultrasound Sensitive

BBa. K1124 O5 SEO ID NO: 786 Promoter for CadA and Cad agtaatcttatcgc.cagtttggtctggit ca genes

BBa. K1124O6 SEO ID NO: 787 cadC promoter agtaatcttatcgc.cagtttggtctggit ca

BBa. K112701 SEO ID NO: 788 hns promoter aattctgaacaa.catcc.gtactic titcgtgc

BBa. K116 OO1 SEO ID NO: 789 nhaA promoter, that can be cgatct attcacctgaaagagaaataaaaa regulated by pH and nhaR protein.

BBa. K1165OO SEO ID NO: 79 O OmpF promoter that is activated aaacgttagtttgaatggaaagatgcctgc or repressed by OmpR according to osmolarity.

BBa. K121 O11 SEO ID NO: 791 promoter (lacI regulated) acaggaaa.ca.gctatgaccatgattacgc.c

BBa. SEO ID NO: 792 fliA promoter gttcactictataccgctgaaggtgtaatgg

BBa. K14515 O SEO ID NO: 793 Hybrid promoter: HSL-LuxR tagtttataatttaagtgttctittaattitc activated P22 C2 repressed

BBa. K1451-52 SEO ID NO: 794 Hybrid promoter: P22 c2, LacI gaaaatgtgagcgagtaacaacct cacaca NOR gate

BBa. K259 OOS SEO ID NO: 795 AraC Rheostat Promoter ttittatcgcaact ct ct actgtttct coat

BBa. K259 OOf SEO ID NO: 796 AraC Promoter fused with RBS gtttct coattact agagaaagaggggaca

BBa. K266 OOS SEO ID NO: 797 PAI - LaSR - > LaSI & AI - aataactctgatagtgctagtgtagatcto LuxR -- Las I

BBa. SEO ID NO: 798 PAI - LaSR - > LaSI - GFP & Cacctt.cgggtgggc ctittctg.cgtttata AI + LuxR -- Las I +

BBa. K266 OOf SEO ID NO: 799 Complex QS -> LuxI & Las I Cacctt.cgggtgggc ctittctg.cgtttata circuit

BBa. ROO65 SEQ ID NO: 800 Promoter (lambda cI and luxR gtgttgactattt tacctctggcggtgata regulated -- hybrid)

TABL E 34

Examples of Combination Inducible & Repressible Miscellaneous Prokaryotic Promoters

Name Description Promoter Sequence

BBa K125100 SEQ ID NO: 801 nir promoter cgaaacgggaac cctatattgatct citact from Synechocystis sp. PCC6803 US 9,458,509 B2 97 98 TABL E 35 Examples of Combination Inducible & Repressible Miscellaneous Yeast Promoters Name Description Promoter Sequence BBa I766200 SEQ ID NO: 802 pSte2 accottaagaaccatat coaagaatcaaaa BBa K110016 SEQ ID NO: 803 A-Cell Promoter STE2 accottaagaaccatat coaagaatcaaaa (backwards) BBa K165034 SEQ ID NO: 804 Zif268-HIV bs + LexA bs + cacaaatacacacactaaattaataac tag mCYC promoter BBa K165041 SEQ ID NO : 805 Zif268-HIV binding sites + TEF atacggit caacgaactataattaactaaac constitutive yeast promoter BBa K165043 SEQ ID NO: 806 Zif268-HIV binding sites + tagatacaattictatt acccc.catccatac MET25 constitutive yeast promoter

TABLE 36 Examples of Combination Inducible & Repressible Miscellaneous Eukaryotic Promoters Name Description Promoter Sequence BBa JO5215 SEQ ID NO: 807 Regulator for R1-CREBH gggg.cgagggc.ccc.gc.ctic.cggaggcgggg BBa JO5216 SEQ ID NO: 808 Regulator for R3-ATF6 gaggggacggctCC9gcc.ccgggg.ccggag BBa J05217 SEQ ID NO: 809 Regulator for R2-YAP7 gggg.cgagggctCC9gcc.ccgggg.ccggag BBa JO5218 SEQ ID NO: 810 Regulator for R4-cMaf gaggggacggCCCC9CCtc.cggaggcgggg

Output Product Sequences and Output Products B-galactosidase convert a Substrate to a colored product. In A variety of biological output gene and output product Some embodiments, reporters are used as output products to nucleic acid sequences are provided for use in the various identify those cells in a population of cells expressing a low- and high-input detector modules and biological clas specific microRNA expression profile that a biological clas sifier circuits described herein. The biological outputs, or sifier circuit is designed to detect. In some embodiments, output products, as described herein, refer to products of reporters are used to quantify the strength or activity of the nucleic acid sequences that can be used as markers of 40 signal received by the modules or biological classifier cir specific states of the low- and high-input detector modules cuits described herein. In some embodiments, reporters can and biological classifier circuits described herein. be fused in-frame to other protein coding sequences to An output nucleic acid sequence can encode for a protein identify where a protein is located in a cell or organism. or RNA that is used to track or identify the state of the cell There are several different ways to measure or quantify a upon receiving a specific combination of inputs, as detected 45 reporter depending on the particular reporter and what kind by the biological classifier circuits described herein. Such of characterization data is desired. In some embodiments, output products can be used to distinguish between various microscopy can be a useful technique for obtaining both states of a cell or a population of cells, such as a heterog spatial and temporal information on reporter activity, par enous population. Representative output products for use ticularly at the single cell level. In other embodiments, flow with the biological classifier circuits and low- and high-input 50 cytometers can be used for measuring the distribution in detector modules described herein include, but are not reporter activity across a large population of cells. In some limited to, reporter proteins, transcriptional repressors, tran embodiments, plate readers can be used for taking popula Scriptional activators, selection markers, enzymes, receptor tion average measurements of many different samples over proteins, ligand proteins, RNAS, riboswitches, or short time. In other embodiments, instruments that combine Such hairpin RNAs. 55 various functions, can be used. Such as multiplex plate Reporter Outputs readers designed for flow cytometers, and combination In some embodiments of the aspects described herein, an microscopy and flow cytometric instruments. output gene product of a biological classifier circuit or a Fluorescent proteins are convenient ways to visualize or component high- or low-input module thereof is a “reporter quantify the output of a module or biological classifier output.” As defined herein, reporters refer to proteins or 60 circuit. Fluorescence can be readily quantified using a molecules that can be used to produce a measurable signal microscope, plate reader or flow cytometer equipped to Such as fluorescence, color, or luminescence. Reporter pro excite the fluorescent protein with the appropriate wave tein coding sequences encode proteins whose presence in the length of light. Since several different fluorescent proteins cell or organism is readily observed. For example, fluores are available, multiple gene expression measurements can cent proteins cause a cell to fluoresce when excited with 65 be made in parallel. Non-limiting examples of fluorescent light of a particular wavelength, luciferases cause a cell to proteins useful for the e biological classifier circuits catalyze a reaction that produces light, and enzymes such as described herein are provided in Table 37. US 9,458,509 B2 99 100 TABLE 37 Examples of Fluorescent Protein Reporters Name Protein Description Tag Emission Excitation Length BBa EOO30 EYFP enhanced yellow fluorescent protein None 527 S1.4 723 derived from A. victoria GFP BBa E0O20 ECFP engineered cyan fluorescent protein None 476 439 723 derived from A. victoria GFP BBa E1010 RFP1 **highly engineered mutant of red None 607 S84 681 fluorescent protein from Discosoma striata (coral) BBa E2050 mCorange derivative of mRFP1, yeast-optimized None S62 S48 744 BBa E0040 GFPmut3b green fluorescent protein derived from None 511 5O1 720 jellyfish Aequeora victoria wild-type GFP (SwissProt: P42212 BBa J52021 dnTrafö-linker-GFP 1446 BBa J52026 dnMyD88-linker-GFP 1155 BBa I715022 Amino Portion of RFP 462 BBa I715023 Carboxyl portion of RFP 220 BBa. I712028 CherryNLS - synthetic construct 733 monomeric red fluorescent protein with nuclear localization sequence BBa K125500 GFP fusion brick 718 BBa K106OOO GFP, AarI BD part 714 BBa K106004 mCherry, Aarl AB part 708 BBa K106005 mCherry, Aarl BD part 708 BBa K106028 GFP, Aari AB part 714 BBa K16SOOS Venus YFP, yeast optimized for fusion 744 BBa K157005 Split-Cerulean-cCFP 261 BBa K157006 Split-Cerulean-nCFP 483 BBa K157007 Split-Venus-cYFP 261 BBa K157008 Split-Venus-nyFP 486 BBa K125810 slr2016 signal sequence + GFP fusion for 779 Secretion of GFP BBa KO82003 GFP GFP(+LVA) 756 BBa K156009 OFP (orange fluorescent protein) 864 BBa K156010 SBFP2 (strongly enhanced blue 720 fluorescent protein) BBa K106671 GFP, Aarl AD part 714 BBa K294055 GFPmut3b GFP RFP Hybrid None 511 5O1 720 BBa K192001 CFP + tigt + lva 858 BBa K180001 GFPmut3b Green fluorescent protein (+LVA) LVA 754 BBa K283005 lipp omp A eGFP streptavidin 1533 BBa K180008 mCherry mCherry (rights owned by Clontech) 708 BBa K18.0009 mBanana mBanana (rights owned by Clontech) 708

40 Luminescence can be readily quantified using a plate TABLE 39 reader or luminescence counter. Luciferases can be used as output gene products for various embodiments described Examples of Enzymes that Produce Colored Substrates herein, for example, in Samples where background fluores Name Protein Description Length cence might result in an ability to distinguish between cells 45 BBa I732006 lacZ alpha fragment 234 expressing an output and those that do not, because cells BBa I732005 lacZ (encoding beta-galactosidase, 3075 tend to have little to no background luminescence in the full-length) absence of a luciferase. Non-limiting examples of BBa K147002 xylE 924 luciferases are provided in Table 38. 50 Another reporter output product for use in the different TABLE 38 aspects described herein includes:

Examples of Luciferases TABLE 40 55 Name Description Length Examples of Other Reporter Genes BBa JS2011 dnMyD88-linker-Rluc 1371 Name Protein Description Length BBa JS2013 dnMyD88-linker-Rluc-linker-PEST191 1872 BBa I712019 Firefly luciferase-luciferase 1653 BBa K157004 Fluoresceine-A-binding 522 from Photinus pyralis 60 Transcriptional Outputs: In some embodiments of the different aspects described In other embodiments, enzymes that produce colored herein, the output product of a given low- or high-input Substrates can be quantified using spectrophotometers or module or biological classifier circuit is itself a transcrip other instruments that can take absorbance measurements 65 tional activator or repressor, the production of which by a including plate readers. Like luciferases, enzymes like B-ga module or circuit can provide additional input signals to lactosidase tend to amplify low signals. Subsequent or additional modules or biological classifier US 9,458,509 B2 101 102 circuits. For example, the output product encoded by a Transcriptional repressors bind to transcriptional promoters high-input detector module can be a transcriptional repressor and sterically hinder transcriptional initiation by RNA poly that prevents transcription from a low-input detector module merase. Some transcriptional regulators serve as either an of a biological classifier circuit. activator or a repressor depending on where it binds and Transcriptional regulators either activate or repress tran cellular conditions. Examples of transcriptional regulators Scription from cognate promoters. Transcriptional activators for use as output products in the classifier circuits and high typically bind nearby to transcriptional promoters and and low-input modules described herein are provided in recruit RNA polymerase to directly initiate transcription. Table 41. TABLE 41 Examples of Transcriptional Regulators Name Protein Description Tag Direction Uniprot Length BBa COO79 lasR- asR activator from P. aeruginosa LVA Forward P25084 756 LVA PAO1(+LVA) BBa COO77 cinR cinRactivator from Rhizobium LVA Forward -Q84HT2 762 legitiminosartin (+LVA) BBa CO179 lasR asR activator from P. aeruginosa PAO1 (no None Forward P25084 723 LVA) BBa JO7009 ToxR oxicity-gene activator from Vibrio cholerae None Forward P15795 630 BBa K118001 appy coding sequence encoding a DNA- 753 binding transcriptional activator BBa K1371.13 rcSA 624 BBal K131022 LuxO D47E, Vibrio harveyi 1362 BBa K131023 LuxO D47A, Vibrio harveyi 1362 BBa KO82006 LuxR-G2F 753 BBa K294205 This is a coding sequence of heat shock 402 protein from E. coi BBa S04301 lasR- COO79:BOO15 LVA Forwar P25084 918 LVA BBa K266002 lasR- LasR + Term LVA Forwar P25084 918 LVA BBa COO12 LacI acI repressor from E. coli (+LVA) LVA Forwar PO3O23 1128 BBa C0040 TetR etracycline repressor from transposon Tn 10 LVA Forwar P04483 660 (+LVA) BBa COOSO CI cI repressor from phage HKO22 (+LVA2) LVA Forwar P1868O 744 HKO22 BBa C0051 CI cI repressor from E. coli phage lambda LVA Forwar PO3O34 750 lambda (+LVA) BBa C0052 CI 434- cI repressor from phage 434 (+LVA) LVA Forwar P16117 669 LVA BBa COO53 C2 P22 c2 repressor from Salmonella phage P22 LVA Forwar P692O2 687 (+LVA) BBa COO73 nint- mint repressor (weak) from Salmonella LVA Forwar PO3O49 288 weak phage P22 (+LVA) BBa COO75 cITP901 TP901 cI repressor from phage TP901-1 LVA Forwar Ole 579 (+LVA) BBa C0074 penI penI repressor from Bacilius licheniformis LVA Forwar PO6555 423 (+LVA) BBa COO72 mint mint repressor (strong) from Salmonelia LVA Forwar PO3O49 288 phage P22 (+LVA) BBa C2001 Zif23- Zif23-GCN4 engineered repressor (+LVA, LVA Forwar PO3069 300 GCN4 C2000 codon-optimized for E. coli) BBa COO56 CI 434 cI repressor from phage 434 (no LVA) None Forwar P16117 636 BBa J06501 LacI- LacI repressor (temperature-sensitive mut LVA Forwar -PO3O23 153 mut2 265) (+LVA) BBa J06500 LacI- LacI repressor (temperature-sensitive mut LVA Forwar -PO3O23 153 mut1 241) (+LVA) BBa C2006 MalE.Factorxa.Zif268-GCN4 428 BBa I715032 acIq reverse 128 BBa I732100 LaC O86 BBa. I732101 LRLa O86 BBa I732105 ARL2AO1O1 O86 BBa I732106 ARL2AO1O2 O86 BBa I732107 ARL2AO103 O86 BBa. I732110 ARL2AO2O3 O86 BBa I732112 ARL2AO3O1 O86 BBa I732115 ARL4AO604 O86 BBa KO91001 LSrR gene Forward 954 BBa KO91121 LacI wild-type gene O83 BBa KO91122 LacI I12 protein O83 BBa K143033 LacI (Liva, N-terminal deletion) regulatory O86 protein BBa K142000 lacI IS mutant (IPTG unresponsive) R197A 128 BBa K142001 lacI IS mutant (IPTG unresponsive) R197F 128 BBa K142002 lacI IS mutant (IPTG unresponsive) T276A 128 BBa K142003 lacI IS mutant (IPTG unresponsive) T276F 128 BBa K106666 Lac Repressor, AarIAB part 104 US 9,458,509 B2 103 104 TABLE 41-continued Examples of Transcriptional Regulators Name Protein Description Tag Direction Uniprot Length BBa K1066.67 Lac Repressor, AarI BD part 1107 BBa K142004 acI IS mutant (IPTG unresponsive) R197A 1128 T276A BBa K106668 Tet Repressor, AarIAB part 618 BBa K106669 Tet Repressor, AarI BD part 621 BBa K142005 acI IS mutant (IPTG unresponsive) R197A 1128 T276F BBa K142006 acI IS mutant (IPTG unresponsive) R197F 1128 T276A BBa K142007 acI IS mutant (IPTG unresponsive) R197F 1128 T276F BBa KO82004 LacI LacI-wild type 1083 BBa KO82005 LacI LacI-Mutant 1083 BBa COO62 LuxR uXR repressor activator, (no LVA2) None Forward P12746 756 BBa COO71 rhR- rhIR repressor activator from P. aeruginosa LVA Forward P54292 762 LVA PA3477 (+LVA) BBa CO080 araC araCarabinose operon regulatory protein LVA Forward P0A9EO 915 (repressor activator) from E. coli (+LVA) BBa CO171 rhIR rhIR repressor activator from P. aeruginosa None Forward P54292 729 PA3477 (no LVA) BBa K108021 Fis 297

Selection Markers 25 selection marker, often termed a positive selection marker, In various embodiments of the aspects described herein, includes those selection markers that are toxic to the cell. nucleic acid sequences encoding selection markers are used Positive selection markers are frequently used during clon as output product sequences. "Selection markers,” as defined ing to select against cells transformed with the cloning herein, refer to output products that confer a selective so vector and ensure that only cells transformed with a plasmid advantage or disadvantage to a biological unit, Such as a cell containing the insert. Examples of selection markers for use or cellular system. For example, a common type of prokary as output products are provided in Table 42. TABLE 42 Examples of Selection Markers Name Protein Description Tag Direction UniProt KEGG Length BBa T91SO PyrF orotidine 5 None Forward PO8244 eco:b1281: 741 BBa J31002 AadA- kanamycin resistance POAGOS none 816 bkw backwards (KanB) cf. BBa J23012 & BBa J31003) BBa J31003 AadA2 kanamycin resistance forward POAGOS none 816 (KanF) cf. BBa J23012 & BBa J31002 BBa J31004 CAT-bkw chloramphenicol P62577 Ole 660 acetyltransferase (backwards, CmB) (cf. BBa J31005 BBa J31006 TetA(C)- tetracycline resistance protein PO2981 1.191 bkw TetA(C) (backwards) cf. BBa J31007 BBa J31005 CAT chloramphenicol P62577 Ole 660 acetyltransferase (forwards, CmF) (cf. BBa J31004) BBa J31007 TetA(C) etracycline resistance protein PO2981 1.191 TetA(C) (forward), cf. BBa J31006) BBa K145151 cccdB coding region 306 BBa K143031 Aad9 Spectinomycin 771 Resistance Gene BBa K156011 aadA (streptomycin 3'- 789 adenyltransferase) otic selection marker is one that confers resistance to a 60 Enzyme Outputs particular antibiotic. Thus, cells that carry the selection An output sequence can encode an enzyme for use in marker can grow in media despite the presence of antibiotic. different embodiments of the low- and high-input modules For example, most plasmids contain antibiotic selection and biological classifier circuits described herein. In some markers so that it is ensured that the plasmid is maintained embodiments, an enzyme output is used as a response to a during cell replication and division, as cells that lose a copy particular set of inputs. For example, in response to a of the plasmid will soon either die or fail to grow in media particular number of inputs received by one or more bio Supplemented with antibiotic. A second common type of logical classifier circuits described herein, a biological clas US 9,458 509 B2 105 106 sifier circuit can encode as an output product an enzyme that only in functional groups but also in their basic carbon can degrade or otherwise destroy specific products produced skeletons. Isoprenoids are synthesized from common prenyl diphosphate precursors through the action of terpene Syn by the cell. thases and terpene-modifying enzymes such as cytochrome 5 P450 monooxygenases. Plant terpenoids are used exten In some embodiments, output product sequences encode sively for their aromatic qualities. They play a role in “biosynthetic enzymes' that catalyze the conversion of traditional herbal remedies and are under investigation for Substrates to products. For example, Such biosynthetic antibacterial, antineoplastic, and other pharmaceutical func tions. Much effort has been directed toward their production enzymes can be combined together along with or within the 10 in microbial hosts. modules and biological classifier circuits described herein to There are two primary pathways for making isoprenoids: construct pathways that produce or degrade useful chemicals the mevalonate pathway and the non-mevalonate pathway. and materials, in response to specific signals. These combi nations of enzymes can reconstitute either natural or syn TABLE 44 thetic biosynthetic pathways. These enzymes have applica- 15 Examples of Isoprenoids tions in specialty chemicals, biofuels, and bioremediation. Descriptions of enzymes useful for the modules and bio Name Description Length BBa K11.8000 dxS coding sequence encoding 1- 1866 logical classifier circuits described herein are described deoxyxylulose-5-phosphate synthase herein. 2O BBa K115050 A-coA-> AA-coA 1188 BBa K115056 IPP -> OPP or DMAPP-> OPP 552 N-Acyl Homoserine lactones (AHLs or N-AHLs) are a BBa K115057 OPP-> FPP 903 class of signaling molecules involved in bacterial quorum BBa K118002 crtB coding sequence encoding phytoene 933 sensing. Several similar quorum sensing systems exists synthase BBa K118003 crtI coding sequence encoding phytoene 1482 across different bacterial species; thus, there are several 25 dehydrogenase BBa K118008 crtY coding sequence encoding lycopene 1152 known enzymes that synthesize or degrade different AHL B-cyclase molecules that can be used for the modules and biological classifier circuits described herein. TABLE 43 Examples of AHLS Name Protein Description Direction Uniprot KEGG E.C. Length

BBa COO61 uxI- autoinducer synthetase for Forwar P12747 Ole Ole 618 LVA AHL BBa COO60 aiiA- autoinducer inactivation Forwar Q1WNZ5 Ole 3.1.1.— 789 LVA enzyme from Bacilius; hydrolyzes acety homoserine lactone BBa COO70 rhI- autoinducer synthetase for Forwar Q02QW5 Ole Ole 642 LVA N-butyryl-HSL (BHL) and HHL BBa COO76 cin autoinducer synthetase Forwar Q1MDW1 Ole Ole 702 BBa COO78 as autoinducer synthetase for Forwar P33883 pae:PA1432 none 642 PAI from Pseudomonas aeruginosa BBa CO161 uxI autoinducer synthetase for Forwar P12747 Ole Ole 585 AHL (no LVA) BBa CO170 rhII autoinducer synthetase for Forwar Q02QW5 Ole Ole 609 N-butyryl-HSL (BHL) and HHL (no LVA) BBa CO178 las autoinducer synthetase for Forwar P33883 pae:PA1432 none 609 PAI from Pseudomonas aeruginosa (no LVA) Ba KO91109 LuxS S16 BBa COO60 aiiA- autoinducer inactivation Forwar Q1WNZ5 Ole 3.1.1.— 789 LVA enzyme from Bacilius; hydrolyzes acety homoserine lactone BBa CO160 aiiA autoinducer inactivation Forwar Q1WNZ5 Ole 3.1.1.— 756 enzyme aiiA (no LVA)

Isoprenoids, also known as terpenoids, are a large and Odorants are volatile compounds that have an aroma highly diverse class of natural organic chemicals with many 65 detectable by the olfactory system. Odorant enzymes con functions in plant primary and secondary metabolism. Most vert a substrate to an odorant product. Exemplary odorant are multicyclic structures that differ from one another not enzymes are described in Table 45. US 9,458,509 B2 107 108 TABLE 45 Examples of Odorant Enzymes Name Protein Description Uniprot KEGG E.C. Length

BBa J45001 SAMT SAM:salicylic acid carboxyl Ole Ole 155 methyltransferase; converts salicylic acid to methyl salicylate (winter J45002 BAMT SAM:benzoic acid carboxyl Q9FYZ9 Ole 2.1.1.— O98 methyltransferase; converts benzoic acid to methyl benzoate (floral odor) J45004 BSMT1 SAM:benzoic acid salicylic acid Q84UB5 Ole Ole O74 carboxyl methyltransferase I; converts Salicylic acid to methyl sali J45008 BAT2 branched-chain amino acid P47176 2.6.1.42 134 transaminase (BAT2); converts leucine to alpha-ketoisocaproate alcohol acetyltransferase I; converts 2.3.1.84 581 isoamyl alcohol to isoamyl acetate (banana odor) isochorismate pyruvate-lyase and 736 isochorismate synthase (pchBA); converts chorismate to salicylate I742107 COMT 101

25 The following are exemplary enzymes involved in the TABLE 47-continued biosynthesis of plastic, specifically polyhydroxybutyrate. Examples of Butanol Biosynthesis Enzymes TABLE 46 Name Description Length 30 Examples of Plastic BioSynthesis Enzymes BBa I725013 Butyryl CoA dehyrogenase 1155 BBa. I725O14 Butyraldehyde dehydrogenase 2598 Name Description Length BBa. I725O15 Butanol dehydrogenase 1188 BBa K125504 phaE BioPlastic polyhydroxybutyrate synthesis 996 pathway (origin PCC6803 slr1829) BBa K125501 phaA BioPlastic polyhydroxybutyrate synthesis 1233 35 Bisphenol A is a toxin that has been shown to leech from pathway (origin PCC6803 slr1994) certain types of plastic. Studies have shown this chemical to BBa K125502 phaB BioPlastic polyhydroxybutyrate synthesis 726 pathway (origin PCC6803 slr1993) have detrimental effects in animal studies and is very likely BBa K1255.03 phaC BioPlastic polyhydroxybutyrate synthesis 1140 to be harmful to humans as well. The following exemplary pathway (origin PCC6803 slr1830) bisphenol A degradation protein coding sequences are from BBa K156012 phaA (acetyl-CoA acetyltransferase) 1182 40 BBa K156013 phaB1 (acetyacetyl-CoA reductase) 741 Sphingomonas bisphenolicum and can aid in the remediation BBa K156014 phaC1 (Poly(3-hydroxybutyrate) polymerase) of bisphenol A contamination.

The following are exemplary enzymes involved in the TABLE 48 biosynthesis of butanol and butanol metabolism. 45 Examples of Bisphenol A Biosynthesis Enzymes TABLE 47 Name Description Length Examples of Butanol Biosynthesis Enzymes BBa K123001 BisdB 1284 50 BBa K123000 Bisda 330 Name Description Length BBa I725O11 B-hydroxy butyryl coA dehydrogenase 870 BBa. I72512 Enoyl-coa hydratase 8O1 Other miscellaneous enzymes for use in the invention are provided in Table 49. TABLE 49 Examples of Miscellaneous Biosynthetic Enzymes Name Description Direction Uniprot KEGG E.C. Length BBa K118022 ceX coding sequence encoding 1461 Cellulomonas fini exoglucanase BBa K118023 cenA coding sequence encoding 1353 Cellulomonas fini endoglucanase A BBa K118028 beta-glucosidase gene bg.IX (chu 2268) 228O from Cytophaga hutchinsonii BBa C0083 aspartate ammonia-lyase Forward POAC38 eco:b4139 4.3.1.1 1518 US 9,458,509 B2 109 110 TABLE 49-continued Examples of Miscellaneous BioSynthetic Enzymes Name Description Direction Uniprot KEGG E.C. Length BBa I15008 heme oxygenase (hol) from Forward P72849 Syn:sl1184 1.14.99.3 726 Synechocystis BBa I15009 phycocyanobilin:ferredoxin Forward Q55891 syn:slro116 1.3.7.5 750 oxidoreductase (PcyA) from Synechocystis BBa T9150 orotidine 5 Forward P08244 eco:b1281; 4.1.1.23 741 BBa I716153 hemB 975 BBa. I716154 hemC 942 BBa I716155 hemD 741 BBa I716152 hemA (from CFT703) 257 BBa. I742141 Sams (coumarate hydroxylase) coding S42 Sequence BBa. I742142 Sam8 (tyrosine-ammonia lyase) coding 536 Sequence BBa I723024 PhizM O19 BBa. I723O25 PhzS 210 BBa K137005 pab A (from pABA synthesis) 585 BBa K137006 pabB (from pABA synthesis) 890 BBa K137009 folB (dihydroneopterin aldolase) 3S4 BBa K137011 folKE (GTP Cyclohydrolase I + O53 pyrophosphokinase) BBa K137017 Galactose Oxidase 926 BBa K118015 glgC coding sequence encoding ADP- 299 glucose pyrophosphorylase BBa K118016 glgC16 (glgC with G336D Substitution) 299 BBa K123001 BisdB 284 BBa K108018 PhbAB 997 BBa K108026 XylA O53 BBa K108027 XylM 110 BBa K108028 XylB 101 BBa K108029 XylS 966 BBa K147003 ohibA 531 BBa K123000 BisdA 330 BBa K284.999 Deletar este 431 BBa. I716253 HPI, katC 2181 BBa K137000 katE 2265 BBa K137014 katE + LAA 2298 BBa K137067 katG 21.84 BBa KO78102 dxnB 886 BBa K078003 one part of the initial dioxygenase of 1897 the dioxin degradation pathway

40 Other enzymes of use in the modules and biological classifier circuits described herein include enzymes that phosphorylate or dephosphorylate either Small molecules or other proteins, and enzymes that methylate or demethylate other proteins or DNA. TABLE 50 Examples of Phosphorylation and Methylation-Related Enzymes

Name Protein Description Direction Uniprot KEGG E.C. Length BBa COO82 tar- Receptor, tar-env7. Forward 1491 envz. BBa J58104 Fusion protein Trg-EnvZ for 1485 signal transduction BBa J58105 Synthetic periplasmic binding 891 protein that docks a vanillin molecule BBa I752001 CheZ coding sequence 639 (Chemotaxis protein) BBa KO910O2 LSrK gene Forward 1593 BBa K147000 chez 835 BBa K118015 glgC coding sequence encoding 1299 ADP-glucose pyrophosphorylase BBa K118016 glgC16 (glgC with G336D 1299 substitution) BBa KO94100 cheZ gene 695 Ba K136046 envZ* 1353 BBa K283008 chez chez. Histag 713 US 9,458,509 B2 111 112 TABLE 50-continued Examples of Phosphorylation and Methylation-Related Enzymes Name Protein Description Direction Uniprot KEGG E.C. Length BBa COO24 CheB CheB chemotaxis coding Forward PO7330 JW1872 3.1.1.61 1053 sequence (protein glutamate methylesterase) BBa K108020 Dam 837

Also useful as output products for the purposes described Substances across the cell membrane. Channels are made up herein are receptors, ligands, and lytic proteins. Receptors of proteins that form transmembrane pores through which tend to have three domains: an extracellular domain for selected ions can diffuse. Pumps are membrane proteins that binding ligands such as proteins, peptides or Small mol 15 can move Substances against their gradients in an energy ecules, a transmembrane domain, and an intracellular or dependent process known as active transport. In some cytoplasmic domain which frequently can participate in embodiments, nucleic acid sequences encoding proteins and Some sort of signal transduction event Such as phosphory protein domains whose primary purpose is to bind other lation. In some embodiments, transporter, channel, or pump proteins, ions, Small molecules, and other ligands are used. gene sequences are used as output product genes. Transport Exemplary receptors, ligands, and lytic proteins are listed in ers are membrane proteins responsible for transport of Table 51. TABLE 51 Examples of Receptors. Ligands, and Lytic Proteins Name Protein Description Tag Direction UniProt Length BBa J07009 ToxR toxicity-gene activator from Vibrio cholerae None Forward P15795 630 BBa K133063 (TIR)TLR3 453 BBa K133064 (TIR)TLR9 585 BBal K133065 (TMTIR)TLR3 600 BBa K133069 (TMTIR)TLR3stop 603 BBa K133067 (TMTIR)TLR4 621 BBa K133060 (TMTIR)TLR9 645 BBa K209400 AarI B-C part, hM4D 1434 BBa K2094.01 AarI B-C part, Rs 1.3 1407 BBa I712002 CCR5 1059 BBa. I712003 CCRS-NUb 1194 BBa I712010 CD4 sequence without signal peptide 1299 BBa I712017 Chemokine (CXC motif) receptor 4, fused 1.191 to N-terminal half of ubiquitin. BBa I15010 Cph8 cph8 (Cph1/EnvZ fusion) None Forward 2238 BBa I728500 CPX Terminal Surface Display Protein with 654 Polystyrene-Binding Peptide BBa JS2O35 dnMyD88 420 BBa K259000 fhuA - Outer membrane transporter for 2247 ferrichrome-iron BBa K259001 fiu B Outer Membrane Ferric Iron 2247 Transporter BBa J58104 Fusion protein Trg-EnvZ for signal 1485 transduction BBa K137112 lamB 1339 BBa C0082 tar- Receptor, tar-envZ LVA Forward 1491 envz. BBa J58105 Synthetic periplasmic binding protein that 891 docks a vanillin molecule BBa I712012 TIR domain of TLR3 456 BBa K143037 Ytv A Blue Light Receptor for B. subtilis 789 BBa JO7006 malE 1.191 BBa JO7017 Feca protein 2325 BBa K141000 UCP1 Ucp1 924 BBa K141002 Ucp 175 deleted 921 BBa K141003 Ucp 76 deleted 921 BBa K190028 GlpF 846 BBa. I746.200 FepA L8T Mutant - Large Diffusion pore 2208 or E. coi outer membrane. BBa I7650O2 ExbB membrane spanning protein in TonB- 735 ExbB-ExbD complex Escherichia coli K12 BBa I765.003 TonB ferric siderophore transport system, 735 periplasmic binding protein TonB Pseudomonas entomophila BBa KO90000 Glutamate gated K+ channel 1194 BBa K284.000 Lactate Permease from Kluyveromyces 1873 iactis BBa K284997 Deletar este 1069 US 9,458,509 B2 113 114 TABLE 51-continued Examples of Receptors. Ligands, and Lytic Proteins Name Protein Description Tag Direction UniProt Length BBa J22101 Lac Y gene 1288 BBa KO79015 Lacy transporter protein from E. coli 1254 BBa K119003 Rcn A (YohM) 833 BBal K137001 Lacy 1254 BBa I712024 CD4 1374 BBa K133061 CD4 ecto 1113 BBa K136046 envZ* 1353 BBa K157002 Transmembrane region of the EGF-Receptor 87 (ErbB-1) BBa K227006 puc BA coding region of R. Sphaeroides forward 336 BBa M12067 E 264 BBa. I721002 Lead Binding Protein 399 BBa K126000 TE33 Fab L chain 648 BBa K133070 gyrEC 660 BBa K133062 gyrHP 660 BBa K157003 Anti-NIP singlechain Fv-Fragment 753 BBa K211001 RIT 987 BBa K211002 RI7-Odr10 chimeric GPCR 1062 BBa K103004 protein ZSP 4-1 190 BBai K128OO3 p1025 101 BBa K133059 RGD 9 BBa K283010 Streptavidin 387 BBa K103004 protein ZSP 4-1 190 BBai K128OO3 p1025 101 BBa K133059 RGD 9 BBa K283010 Streptavidin 387 BBa K112000 Holin T4 holin, complete CDS, berkeley standard 657 BBa K112002 Holin T4 holin, without stop codon, berkeley 654 standard BBa K112004 a-T4 holin in BBb 661 BBa K112006 T4 antiholin in BBb 294 BBa K112009 in BBb 288 BBa K112010 a-T4 antiholin in BBb 298 BBa K112012 T4 lysozyme in BBb 495 BBa K112015 in BBb 489 BBa K112016 a-T4 lysozyme in BBb 499 BBa K117,000 Lysis gene (promotes lysis in colicin- 144 producing bacteria strain) BBai K124O14 Bacteriophage Holin Gene pS105 317 BBa K108001 SRRz 1242 BBa K112300 {lambda lysozyme in BBb format 477 BBa K112304 {a-lambda lysozyme in BBb format 481 BBa K112306 {lambda holin in BBb format 3.18 BBa K112310 {a-lambda holin; adheres to Berkeley 322 standard BBa K112312 {lambda antiholin; adheres to Berkeley 324 standard BBa K112316 {a-lambda antiholin; adheres to Berkeley 328 standard BBa K124017 Bacteriophage Lysis Cassette S105, R, and 1257 Rz BBa K112806 T4 endolysin S14 BBa K284001 Lysozyme from Gallus gaits 539

50 Uses of Biological Classifier Circuits and ones in which the cells are used within an organism (in The high-input detector modules and biological classifier vivo), e.g., in a patient. Exemplary applications in which circuits described herein are useful for identifying and compositions comprising the biological classifier circuits classifying and discriminating between complex phenotypes and high- and low-input modules, as well as cells compris in cellular systems, such as prokaryotic, eukaryotic (animal 55 ing Such circuits and modules, can be used are detailed or plant), or synthetic cells, as well as in non-cellular herein and in the following Examples. systems, including test tubes, viruses and phages. The novel In some aspects described herein, a high-input detector biological classifier circuits described herein can be used to module or a biological classifier circuit is provided for use elicit targeted responses in cellular and non-cellular systems, in a cellular system, such as a heterogenous population of Such as the ability to discriminate, identify, mark, target, 60 mammalian cells, to identify a specific cell type endog and/or destroy cells expressing specific complex pheno enously expressing a distinct microRNA expression profile types, by identifying and responding to specific input pro or pattern, where the microRNA expression profile or pat files. The biological classifier circuits described herein and tern is based on the expression or lack of expression of a cells (e.g., transiently modified cells, transfected cells, or combination of at least two microRNAs. permanently modified cells) containing such circuits have a 65 In one aspect, a method is provided for identifying a wide variety of applications, including ones in which the specific cell type based on the expression pattern of at least cells are used outside of an organism (ex vivo or in vitro), two unique, endogenous microRNAS. In one embodiment, US 9,458,509 B2 115 116 the method is based on the expression pattern of at least detect are killed or undergo apoptosis. Such embodiments three unique, endogenous microRNAS. In one embodiment, where a high-input detector module or a biological classifier the method is based on the expression pattern of at least four circuit is coupled to the cell cycle can be useful in diagnostic unique, endogenous microRNAS. In one embodiment, the or therapeutic applications, such as in therapies for cancer or method is based on the expression pattern of at least five other proliferative disorders. unique, endogenous microRNAS. In one embodiment, the Diagnostic and Therapeutic Applications method is based on the expression pattern of at least six In some aspects, the high-input detector modules and unique, endogenous microRNAS. In one embodiment, the biological classifier circuits described herein can be used in method is based on the expression pattern of at least seven a number of diagnostic and therapeutic applications and unique, endogenous microRNAS. In one embodiment, the 10 methods. For example, in Some aspects, the biological method is based on the expression pattern of at least eight classifier circuits can be used in a method for detecting unique, endogenous microRNAS. In one embodiment, the specific microRNA profiles associated with disorders such method is based on the expression pattern of at least nine as, but not limited to, cancer, immunological disorders (e.g., unique, endogenous microRNAS. In one embodiment, the autoimmune diseases), neuronal disorders, cardiovascular method is based on the expression pattern of at least ten 15 disorders, metabolic disorders, or infections. One advantage unique, endogenous microRNAS. In one embodiment, the of the biological classifier circuits described herein in such method is based on the expression pattern of at least eleven applications is the ability to identify and target individual unique, endogenous microRNAS. In one embodiment, the cells with precision based on internal molecular cues. In method is based on the expression pattern of at least twelve other aspects, the biological classifier circuits can be used in unique, endogenous microRNAS. In one embodiment, the a method for detectingor identifying cells within a heterog method is based on the expression pattern of at least thirteen enous population, such as identifying cells having cancerous unique, endogenous microRNAS. In one embodiment, the potential. Such as teratoma cells, in a population of stem method is based on the expression pattern of at least fourteen cells, such as induced pluripotent stem cells. unique, endogenous microRNAS. In one embodiment, the In some embodiments of the aspects described herein, method is based on the expression pattern of at least fifteen 25 high-input detector modules or biological classifier circuits unique, endogenous microRNAS. In one embodiment, the are introduced into individual cells as a diagnostic molecular method is based on the expression pattern of at least sixteen probe to identify a specific cell population, in applications unique, endogenous microRNAS. In one embodiment, the Such as disease detection or Surgical guidance. Upon detect method is based on the expression pattern of at least sev ing a particular microRNA expression profile, the high-input enteen unique, endogenous microRNAS. In one embodi 30 detector modules or biological classifier circuits produce a ment, the method is based on the expression pattern of at detectable output, such as a reporter, that can be used to least eighteen unique, endogenous microRNAs. In one discriminate, and select or isolate those cells having the embodiment, the method is based on the expression pattern particular microRNA expression profile. In such embodi of at least nineteen unique, endogenous microRNAS. In one ments, a high-input detector module or biological classifier embodiment, the method is based on the expression pattern 35 circuit is being used as a means of labeling or identifying of at least twenty unique, endogenous microRNAS. In some cells. For example, a biological classifier circuit that is embodiments, the method is based on the expression pattern specific (i.e., expresses an output product) for a microRNA of at least 20-25, at least 25-30, at least 30-35, at least 35-40, profile characteristic of a particular cancer type can be at least 4-45, at least 45-50, at least 50-55, at least 55-60, at introduced into one or more cells from a biopsy from a least 60-65, at least 65-70, at least 70-75 unique, endogenous 40 Subject. In such embodiments, the output product can be a microRNAs. Accordingly, in some embodiments of the fluorescent protein or a enzyme capable of performing a aspects described herein, a method is provided for identify detectable reaction (e.g., B-galactosidase, alkaline phos ing a specific cell type based on the expression pattern of at phatase, or horseradish peroxidase). Thus, all cells express least 2, 3, 4, 5, 6, 7, 8, 9, 10 . . . 13 . . . 17 . . . 23 . . . ing the cancer-specific microRNA profile will be differen 32 . . . 41 . . . 55 . . . 69 . . . 75 or more endogenous 45 tiated from the non-cancer cells, and aid in early diagnosis microRNAs in a cellular or non-cellular system. Such meth modalities. Such detectable outputs can also be useful in ods comprise introducing a biological classifier circuit com treatment of the cancer, by, for example, aiding in precise prising at least one low-input and at least one high-input Surgical removal of the cancer or targeted chemotherapy. detector modules, or only low-input modules, or only high In other embodiments of the aspects described herein, the input modules, that can detect a specific microRNA profile, 50 high-input detector modules and biological classifier circuits into a cellular or non-cellular system for use in identifying can be used to identify specific cell populations for isolation, an endogenous microRNA expression pattern. In Such such as different immune cell types, or cells at different embodiments, the endogenous microRNA is a mature micro stages of differentiation. For example, upon introduction of RNA, as is understood by one of skill in the art, and as biological classifier circuits into a cell population, those described herein. 55 cells within the population that express a particular micro The high-input detector modules and biological classifier RNA profile can be isolated away from non-labeled cells circuits described herein can be used for a variety of based on expression of a particular output product by the applications and in many different types of methods, includ circuit. In some embodiments, such an output product can be ing, but not limited to, diagnostics and therapeutic applica a fluorescent molecule, to allow isolation of the cell using tions, drug screening, genetic manipulations, developmental 60 fluorescent cell sorting. In other embodiments, the output studies, and pharamcokinetics. For example, in some product is a cell-surface receptor normally not expressed by embodiments, a biological classifier circuit comprises an any cells in that population which can be used for isolating output product involved in the cell cycle for use in a cellular the cells, using, for example, a antibody specific to that system. In Such embodiments, the output product can be a marker. In further embodiments, a therapy can then be protein, toxin, or other agent that causes cell death, such that 65 applied in a separate step that will target only the labeled or those cells within the cellular system that express the isolated cells. Alternatively, if such labeling is done in vivo specific microRNA profile the classifier circuit is designed to or ex vivo, a sample comprising the labeled cells or tissues US 9,458,509 B2 117 118 can be imaged in order to determine the localization of the discrimination between different cells type is important, for "labeled cells; e.g., to guide Surgery or radiation therapy. e.g., cancer or other proliferative disorders, metabolic dis In some embodiments, the high-input detector modules orders, neurological disorders, immunological disorders, or and biological classifier circuits described herein can be infections, such as viral, bacterial, or parasitic infections. used to identify and select for cells at various stages of 5 Such methods includes the step of delivering to at least one differentiation, such as within a stem cell population. For cell in a subject in need thereof any of the biological example, a biological classifier circuit can be introduced into classifier circuits described herein, wherein one or more a stem cell and produce one or more outputs indicative of outputs is a therapeutic useful in treating, or ameliorating different stages of differentiation, in response to a specific one or more symptoms of the Subject in need thereof. microRNA profile indicative of a specific differentiation 10 State. In another aspect, methods of treatment using the high Tumorigenicity is a safety concern associated with the input detector modules and biological classifier circuits ultimate in vivo use of stem cell therapies involving human described herein are provides, the methods comprising embryonic stem cells or induced pluripotent stem cells, as administering to a mammal in need thereof one or more undifferentiated stem cells have the potential to form tera 15 vectors comprising one or more nucleic acid sequences tomas and have tumorigenic potential. It is important to encoding one or more low-input detector modules or high ensure that when stem cells are differentiated into a desired input detector modules of any of the biological classifier cell type, no undifferentiated or improperly differentiated circuits described herein. In some embodiments of these cells remain either in vivo, if the differentiation is induced aspects, a biological classifier circuit, upon detecting the in vivo, or in the cell population prior to stem cell therapy appropriate microRNA profile, triggers the release of a and transplantation. Hence, in some embodiments of the therapeutic agent as the output, such as a protein, an siRNA, aspects described herein, a biological classifier circuit that is an shRNA, a miRNA, a small molecule, or any of the specific for a microRNA profile characteristic of a stem cell outputs described herein. For example, a protein output can is introduced into a population of cells, such as a population be a reporter Such as luciferase, luciferin, green fluorescence of cells differentiated from a stem cell population, such as an 25 protein (GFP), red fluorescence protein (RFP). Dsked, induced pluripotent stem cell population, to identify the cells Zsyellow, or an enzyme (e.g., beta-galactosidase, horserad having the microRNA profile characteristic or indicative or ish peroxidase, alkaline phosphatase, or chloramphenicol a stem cell within the heterogenous population of cells acetyl transferase (CAT). The output protein can be a (Suhet et al. “Human embryonic stem cells express a unique selectable marker (e.g., a chemical resistance gene) Such as set of microRNAs. Dev. Biol. 2004, 270: 488-498, and 30 aminoglycoside phosphotransferase (APT) or multidrug Landgrafet et al. “A mammalian microRNA expression resistance protein (MDR). The output protein can also be a Atlas based on small RNA Library Sequencing.” Cell. 2007, pharmaceutical agent (that is an agent with therapeutic 129: 1401-1414). ability) or a moiety that triggers the availability of a phar In some further embodiments of these aspects and maceutical agent. The pharmaceutical agent can be, e.g., a embodiments, the high-input detector modules or biological 35 small molecule, a protein, or an siRNA (or shRNA). classifier circuits described herein can further comprise a In Such embodiments, the high-input detector modules constitutive promoter operably linked to a sequence that and biological classifier circuits can be used for local or encodes a protein providing resistance to a selection marker, systemic delivery of one or more therapeutic agents. For for example, an antibiotic resistance gene. Accordingly, an example, a biological classifier circuit can be introduced output product encoded by Such a high-input detector mod 40 (transfected) into cells. Systemic delivery of one or more ule or biological classifier circuit can comprise a protein or therapeutic agents by a classifier circuit can involve, e.g., molecule that inihibts or targets the protein providing resis introducing the circuit into cells, e.g., healthy and/or dis tance to the selection marker. In such embodiments, any cell eased cells, wherein production and systemic release of one not transfected with the high-input detector module or or more therapeutic agents by the classifier circuit is trig classifier circuit will be killed or die due to lack of the 45 gered by detection of the appropriate microRNA profile. appropriate resistance product. Further, those transfected For example, a biological classifier circuit can be deliv cells expressing the microRNA expression profile the bio ered to a cancer cell, or a heterogenous population of cells logical classifier circuit is specific for will be killed or die comprising cancer cells, wherein the circuit comprises one due to expression of the output product and inhibition of the or more low- and high-input detector modules that can transfected resistance molecule. 50 detect and respond to a specific microRNA expression In some aspects, an in vivo cell or tissue system com signature or profile characteristic of the cancer cells. Such prising the high-input detector modules or biological clas biological classifier circuits can be designed so that one or sifier circuits described herein can be administered to a more output products of the classifier circuits can modulate Subject. In some embodiments of these aspects, such a a cellular pathway or activity of the cell. For example, the method can comprise the following steps: 1) identifying a 55 alteration in cellular activity can cause or alter apoptotic cell tissue or cell type of interest and providing a molecular death, replication (e.g., DNA or cellular replication), cell microRNA signature as an indicator for the cell or tissue differentiation, or cell migration. For example, apoptosis can type; 2) constructing a biological classifier circuit that be the result of the expression of a classifier circuit output detects this specific signature; and 3) administering the such as a death receptor (e.g., FasR or TNFR), death components of the biological classifier circuit into a subject. 60 receptor ligand (e.g., FasL or TNF), a caspase (e.g., caspase In some embodiments, the administration involves transient 3 or caspase 9), cytochrome-c, a BH3-containing proapop delivery, or stable incorporation into the Subject's genome. totic protein (e.g., BAX, BAD, BID, or BIM), or apoptosis In further embodiments of such aspects, the cell or tissue inducing factor (AIF)). Growth arrest can be the result of a system comprising the high-input detector modules and circuit output such as p21, p19ARF, p53, or RB protein. biological classifier circuits described herein can be used as 65 Additional non-limiting example of outputs for use with the a direct therapeutic modality, or as a combination diagnos circuits have been described herein and in the Examples ticic-therapeutic modality for a variety of disorders in which section. US 9,458,509 B2 119 120 For example, as shown in FIGS. 4, 5, and 6 using HeLa infects cell can have as an output product an RNA molecule, cells as a target cancer cell type, in some embodiments, a such as an siRNA (or shRNA), that interferes with viral biological classifier circuit can be constructed comprising viability or propagation within the host cell. low-input and high-input modules that detects the expres In other embodiments, the high-input detector modules sion of a total of six distinct microRNAs, wherein 3 micro and biological classifier circuits described herein can be RNAs (expressed at high levels) are detected using two used therapeutically to promote, e.g., tissue regeneration, high-input modules, and 3 microRNAs (expressed at low localized production of a secreted protein, and certain types levels) are detected using one low-input module. of immune-like responses. In Such an embodiment, the biological classifier circuit For the clinical use of the methods described herein, can further comprise a constitutive promoter driving a 10 administration of the biological classifier circuits or com reporter protein, Such as AmCyan, so that all transfected ponent input detector modules thereof, or vectors compris cells can be identified. In such an embodiment, each high ing nucleic acid sequences encoding the biological classifier input module can further comprise a constitutive promoter circuits or component input detector modules thereof, can operably linked to a sequence encoding a transcriptional include formulation into pharmaceutical compositions or activator, Such as rtTA, and a microRNA target sequence for 15 pharmaceutical formulations for parenteral administration, one of the high microRNAs, wherein the transcriptional e.g., intravenous; mucosal, e.g., intranasal; ocular, or other activator and another agent, such as doxycycline, induces mode of administration. In some embodiments, the biologi transcription from the inducible promoter, driving expres cal classifier circuits or component input detector modules sion of the repressor protein, Such as LacI. In Such an thereof, or vectors comprising nucleic acid sequences embodiment, the sequence encoding the repressor high encoding the biological classifier circuits or component input module can further comprise an intronic microRNA input detector modules thereof described herein can be sequence. Such as miR-FF4, that targets a microRNA target administered along with any pharmaceutically acceptable sequence in the sequence encoding the output product in the carrier compound, material, or composition which results in low-input detector module. The additional microRNA target an effective treatment in the Subject. Thus, a pharmaceutical sequence in the output product sequence acts as an addi 25 formulation for use in the methods described herein can tional means to prevent output product leakiness of the comprise a biological classifier circuit or component input biological classifier circuit, by adding a post-transcriptional detector module thereof, or one or more vectors comprising repression mechanism, in addition to the transcriptional nucleic acid sequences encoding the biological classifier repression mediated by LacI. circuit or component input detector module thereof as In Such an embodiment, if a biological classifier circuit 30 described herein in combination with one or more pharma does not detect the presence of the three low-input micro ceutically acceptable ingredients. RNAs, and detects sufficient levels of the three high-input The phrase “pharmaceutically acceptable” refers to those microRNAs, then expression of both the transcriptional compounds, materials, compositions, and/or dosage forms activator and the repressor is inhibited, and the repression on which are, within the scope of Sound medical judgment, the output product is removed. Such that an output product 35 Suitable for use in contact with the tissues of human beings is expressed. In Such an embodiment, the output product of and animals without excessive toxicity, irritation, allergic the biological classifier circuit can comprise a pro-apoptotic response, or other problem or complication, commensurate gene, such as hBax, Such that any cell. Such as HeLa cell, with a reasonable benefit/risk ratio. The phrase “pharma expressing the biological classifier circuit undergoes apop ceutically acceptable carrier as used herein means a phar tosis. 40 maceutically acceptable material, composition or vehicle, In Such an embodiment, an additional layer of regulation Such as a liquid or Solid filler, diluent, excipient, Solvent, can be added to prevent leakiness of the output product (e.g., media, encapsulating material, manufacturing aid (e.g., hBax), by further engineering the circuit to add a sequence lubricant, talc magnesium, calcium or Zinc Stearate, or Steric encoding a functional inhibitor of the output product to the acid), or solvent encapsulating material, involved in main sequence encoding the repressor protein and microRNA 45 taining the stability, solubility, or activity of a biological target sequences in each high-input module. In the example classifier circuit or component input detector module described herein, Bcl2 was used to further minimize leaki thereof, or vectors comprising nucleic acid sequences ness of hBax expression. encoding the biological classifier circuits or component In another example, a biological classifier circuit that input detector modules thereof. Each carrier must be detects a specific microRNA profile characteristic of a 50 “acceptable in the sense of being compatible with the other pro-inflammatory response can be introduced into a ana ingredients of the formulation and not injurious to the tomical site having, Suspected of having, or at risk of patient. The terms “excipient”, “carrier”, “pharmaceutically developing, a pro-inflammatory response (e.g., a joint acceptable carrier' or the like are used interchangeably affected by rheumatoid arthritis). Such circuits could pro herein. duce anti-inflammatory cytokine outputs (e.g., IL-4, IL-6, 55 The biological classifier circuits or component input IL-10, IL-11, or IL-13). detector modules thereof, or vectors comprising nucleic acid In some embodiments of the aspects described herein, the sequences encoding the biological classifier circuits or com high-input detector modules and the biological classifier ponent input detector modules thereof, described herein can circuits can trigger the production of one or more siRNA (or be specially formulated for administration of the compound shRNA) therapeutic agents. For example, where a cell 60 to a subject in Solid, liquid or gel form, including those having a specific microRNA expression profile expresses an adapted for the following: (1) parenteral administration, for aberrant form of a protein, the biological classifier circuit example, by Subcutaneous, intramuscular, intravenous or can trigger the production of one or more siRNAS specific epidural injection as, for example, a sterile Solution or for the mRNA encoding the aberrant protein, thereby ablat Suspension, or Sustained-release formulation; (2) topical ing its translation. In another example, where a cell is 65 application, for example, as a cream, ointment, or a con infected with a virus, a biological classifier circuit that trolled-release patch or spray applied to the skin; (3) intra detects a unique microRNA profile characteristic of a virally vaginally or intrarectally, for example, as a pessary, cream or US 9,458,509 B2 121 122 foam; (4) ocularly; (5) transdermally; (6) transmucosally; or the circuit is designed to detect is altered or modified. In (79) nasally. Additionally, biological classifier circuits or Some such embodiments, multiple biological classifier cir component input detector modules thereof, can be implanted cuits can be introduced in parallel, in order to interrogate into a patient or injected using a drug delivery system. See, multiple pathways simultaneously. for example, Urquhart, et al., Ann. Rev. Pharmacol. Toxicol. 5 In other embodiments, the biological classifier circuits 24: 199-236 (1984); Lewis, ed. “Controlled Release of described herein can be used to monitor the pharmacokinet Pesticides and Pharmaceuticals” (Plenum Press, New York, ics of a compound. Such as a small molecule compound or 1981): U.S. Pat. No. 3,773.919; and U.S. Pat. No. 3,270,960. a therapeutic protein (e.g., an antibody, a growth factor, Therapeutic formulations of the biological classifier cir chemokine, or cytokine). Such biological classifier circuits cuits or component input detector modules thereof, or vec 10 could be useful for determining (i) the permeability of a tors comprising nucleic acid sequences encoding the bio compound (e.g., permeability of a compound through a cell logical classifier circuits or component input detector membrane) or (ii) the stability (half-life or clearance) of a modules thereof described herein can be prepared for stor compound in a cell. The cell can also be introduced into an age by mixing a biological classifier circuit or component animal model (e.g., a rodent model, a canine model, or a input detector modules thereof, or vectors comprising 15 non-human primate model), e.g., to test for the half-life of nucleic acid sequences encoding the biological classifier clearance of a compound from the blood of the animal. circuit or component input detector modules thereof, having Kits the desired degree of purity with optional pharmaceutically One or more biological classifier circuits or component acceptable carriers, excipients or stabilizers (Remington's modules described herein can be provided as a kit, e.g., a Pharmaceutical Sciences 16th edition, Osol, A. Ed. (1980)), package that includes one or more containers. In one in the form of lyophilized formulations or aqueous Solutions. example, each component, or genetic material encoding it, Acceptable carriers, excipients, or stabilizers are nontoxic to can be provided in a different container. In another example, recipients at the dosages and concentrations employed, and two or more components are combined in a container. Such include buffers such as phosphate, citrate, and other organic kits are useful for any of the diagnostic, therapeutic, or acids; antioxidants including ascorbic acid and methionine; 25 protein production modalities described herein. preservatives (such as octadecyldimethylbenzyl ammonium For example, biological classifier circuits or detector chloride; hexamethonium chloride; benzalkonium chloride, modular components thereof can be provided as a functional benzethonium chloride: phenol, butyl or benzyl alcohol: part of a kit to identify individual cells with certain complex alkyl parabens such as methyl or propyl paraben; catechol; molecular signatures/phenotypes. resorcinol, cyclohexanol: 3-pentanol; and m-cresol); low 30 molecular weight (less than about 10 residues) polypeptides; DEFINITIONS proteins, such as serum albumin, gelatin, or immunoglobu lins; hydrophilic polymers such as polyvinylpyrrolidone; The methods and uses of the biological classifier circuits amino acids such as glycine, glutamine, asparagine, histi described herein can involve in vivo, ex vivo, or in vitro dine, arginine, or lysine; monosaccharides, disaccharides, 35 systems. The term “in vivo” refers to assays or processes that and other carbohydrates including glucose, mannose, or occur in or within an organism, such as a multicellular dextrins; chelating agents such as EDTA; Sugars such as animal. In some of the aspects described herein, a method or Sucrose, mannitol, trehalose or Sorbitol; salt-forming coun use can be said to occur “in vivo” when a unicellular ter-ions such as sodium; metal complexes (e.g. Zn-protein organism, such as a bacteria, is used. The term "ex vivo complexes); and/or non-ionic Surfactants such as 40 refers to methods and uses that are performed using a living TWEENTM, PLURONICSTM or polyethylene glycol (PEG). cell with an intact membrane that is outside of the body of Exemplary lyophilized anti-VEGF antibody formulations a multicellular animal or plant, e.g., explants, cultured cells, are described in WO 97/04801, expressly incorporated including primary cells and cell lines, transformed cell lines, herein be reference. and extracted tissue or cells, including blood cells, among Optionally, but preferably, the formulations comprising 45 others. The term “in vitro” refers to assays and methods that the compositions described herein contain a pharmaceuti do not require the presence of a cell with an intact mem cally acceptable salt, typically, e.g., sodium chloride, and brane. Such as cellular extracts, and can refer to the intro preferably at about physiological concentrations. Optionally, ducing a biological classifier circuit in a non-cellular system, the formulations described herein can contain a pharmaceu Such as a media not comprising cells or cellular systems, tically acceptable preservative. In some embodiments the 50 Such as cellular extracts. preservative concentration ranges from 0.1 to 2.0%, typi A cell for use with the biological classifier circuits cally V/v. Suitable preservatives include those known in the described herein can be any cell or host cell. As defined pharmaceutical arts. Benzyl alcohol, phenol, m-cresol, herein, a “cell' or “cellular system” is the basic structural methylparaben, and propylparaben are examples of preser and functional unit of all known independently living organ vatives. Optionally, the formulations described herein can 55 isms. It is the smallest unit of life that is classified as a living include a pharmaceutically acceptable Surfactant at a con thing, and is often called the building block of life. Some centration of 0.005 to 0.02%. organisms, such as most bacteria, are unicellular (consist of Drug Screening and Pharmacokinetics a single cell). Other organisms, such as humans, are multi In some aspects, the high-input detector modules and cellular. A “natural cell,” as defined herein, refers to any biological classifier circuits described herein can be used to 60 prokaryotic or eukaryotic cell found naturally. A "prokary report on or classify the physiological state of a cell in drug otic cell' can comprise a cell envelope and a cytoplasmic screening experiments. For example, one or more biological region that contains the cell genome (DNA) and ribosomes classifier circuits specific for different molecular signatures and various sorts of inclusions. indicative of specific cell states, such as a microRNA In some embodiments, the cell is a eukaryotic cell, expression profile, can be stably introduced into cells. Such 65 preferably a mammalian cell. A eukaryotic cell comprises cells can then be tested with various drug and drug combi membrane-bound compartments in which specific metabolic nations to identify those cells in which the specific profile activities take place, such as a nucleus. In other embodi US 9,458,509 B2 123 124 ments, the cell or cellular system is an artificial or synthetic artificially upon treatment with various factors. In many cell. As defined herein, an “artificial cell' or a “synthetic biological instances, stem cells are also “multipotent cell' is a minimal cell formed from artificial parts that can because they can produce progeny of more than one distinct do many things a natural cell can do. Such as transcribe and cell type, but this is not required for “stem-ness.” Self translate proteins and generate ATP renewal is the other classical part of the stem cell definition, Cells of use in the various aspects described herein upon and it is essential as used in this document. In theory, transformation or transfection with the biological classifier self-renewal can occur by either of two major mechanisms. circuits described herein include any cell that is capable of Stem cells can divide asymmetrically, with one daughter Supporting the activation and expression of the biological retaining the stem state and the other daughter expressing classifier circuits. In some embodiments of the aspects 10 Some distinct other specific function and phenotype. Alter described herein, a cell can be from any organism or natively, Some of the stem cells in a population can divide multi-cell organism. Examples of eukaryotic cells that can symmetrically into two stems, thus maintaining some stem be useful in aspects described herein include eukaryotic cells cells in the population as a whole, while other cells in the selected from, e.g., mammalian, insect, yeast, or plant cells. population give rise to differentiated progeny only. For The molecular circuits described herein can be introduced 15 mally, it is possible that cells that begin as stem cells might into a variety of cells including, e.g., fungal, plant, or animal proceed toward a differentiated phenotype, but then (nematode, insect, plant, bird, reptile, or mammal (e.g., a “reverse' and re-express the stem cell phenotype, a term mouse, rat, rabbit, hamster, gerbil, dog, cat, goat, pig, cow, often referred to as “dedifferentiation'. horse, whale, monkey, or human)). The cells can be primary Exemplary stem cells include, but are not limited to, cells, immortalized cells, stem cells, or transformed cells. In embryonic stem cells, adult stem cells, pluripotent stem Some preferred embodiments, the cells comprise stem cells. cells, induced pluripotent stem cells (iPS cells), neural stem Expression vectors for the components of the biological cells, liver stem cells, muscle stem cells, muscle precursor classifier circuit will generally have a promoter and/or an stem cells, endothelial progenitor cells, bone marrow stem enhancer Suitable for expression in a particular host cell of cells, chondrogenic stem cells, lymphoid stem cells, mes interest. The present invention contemplates the use of any 25 enchymal stem cells, hematopoietic stem cells, central ner such vertebrate cells for the biological classifier circuits, Vous system stem cells, peripheral nervous system stem including, but not limited to, reproductive cells including cells, and the like. Descriptions of stem cells, including sperm, ova and embryonic cells, and non-reproductive cells, method for isolating and culturing them, can be found in, Such as kidney, lung, spleen, lymphoid, cardiac, gastric, among other places, Embryonic Stem Cells, Methods and intestinal, pancreatic, muscle, bone, neural, brain, and epi 30 Protocols, Turksen, ed., Humana Press, 2002; Weisman et thelial cells. al., Annu. Rev. Cell. Dev. Biol. 17:387 403; Pittinger et al., As used herein, the term "stem cells' is used in a broad Science, 284:143 47, 1999; Animal Cell Culture, Masters, sense and includes traditional stem cells, progenitor cells, ed., Oxford University Press, 2000; Jackson et al., PNAS preprogenitor cells, reserve cells, and the like. The term 96(25): 14482 86, 1999; Zuk et al., Tissue Engineering, “stem cell' or “progenitor cell are used interchangeably 35 7:211 228, 2001 (“Zuk et al.”); Atala et al., particularly herein, and refer to an undifferentiated cell which is capable Chapters 33 41; and U.S. Pat. Nos. 5,559,022, 5,672,346 and of proliferation and giving rise to more progenitor cells 5,827.735. Descriptions of stromal cells, including methods having the ability to generate a large number of mother cells for isolating them, can be found in, among other places, that can in turn give rise to differentiated, or differentiable Prockop, Science, 276:7174, 1997: Theise et al., Hepatol daughter cells. Stem cells for use with the biological clas 40 ogy, 31:235 40, 2000; Current Protocols in Cell Biology, sifier circuits and the methods described herein can be Bonifacino et al., eds. John Wiley & Sons, 2000 (including obtained from endogenous sources such as cord blood, or updates through March, 2002); and U.S. Pat. No. 4,963,489: can be generated using in vitro or ex vivo techniques as Phillips BW and Crook J M. Pluripotent human stem cells: known to one of skill in the art. For example, a stem cell can A novel tool in drug discovery. BioDrugs. 2010 Apr. 1; be an induced pluripotent stem cell (iPS cell). The daughter 45 24(2):99-108; Mari Ohnuki et al., Generation and Charac cells themselves can be induced to proliferate and produce terization of Human Induced Pluripotent Stem Cells, Cur progeny that Subsequently differentiate into one or more rent Protocols in Stem Cell Biology Unit Number: UNIT mature cell types, while also retaining one or more cells with 4A., September, 2009. parental developmental potential. The term “stem cell As indicated above, there are different levels or classes of refers then, to a cell with the capacity or potential, under 50 cells falling under the general definition of a “stem cell.” particular circumstances, to differentiate to a more special These are “totipotent,” “pluripotent” and “multipotent” stem ized or differentiated phenotype, and which retains the cells. The term “totipotency” or “totipotent” refers to a cell capacity, under certain circumstances, to proliferate without with the degree of differentiation describing a capacity to substantially differentiating. In one embodiment, the term make all of the cells in the adult body as well as the progenitor or stem cell refers to a generalized mother cell 55 extra-embryonic tissues including the placenta. The fertil whose descendants (progeny) specialize, often in different ized egg (Zygote) is totipotent as are the early cleaved cells directions, by differentiation, e.g., by acquiring completely (blastomeres) individual characters, as occurs in progressive diversifica The term “pluripotent” or a “pluripotent state' as used tion of embryonic cells and tissues. Cellular differentiation herein refers to a cell with the capacity, under different is a complex process typically occurring through many cell 60 conditions, to differentiate to cell types characteristic of all divisions. A differentiated cell can derive from a multipotent three germ cell layers: endoderm (gut tissue), mesoderm cell which itself is derived from a multipotent cell, and so (including blood, muscle, and vessels), and ectoderm (such on. While each of these multipotent cells can be considered as skin and nerve). Pluripotent cells are characterized pri stem cells, the range of cell types each can give rise to can marily by their ability to differentiate to all three germ vary considerably. Some differentiated cells also have the 65 layers, using, for example, a nude mouse teratoma formation capacity to give rise to cells of greater developmental assay. Pluripotency is also evidenced by the expression of potential. Such capacity can be natural or can be induced embryonic stem (ES) cell markers, although the preferred US 9,458,509 B2 125 126 test for pluripotency is the demonstration of the capacity to a subject. Most often, the sample has been removed from a differentiate into cells of each of the three germ layers. In subject, but the term “biological sample' can also refer to Some embodiments, a pluripotent cell is an undifferentiated cells or tissue analyzed in vivo, i.e. without removal from cell. the subject. Often, a “biological sample' will contain cells The term “multipotent” when used in reference to a 5 from the animal, but the term can also refer to non-cellular “multipotent cell' refers to a cell that is able to differentiate biological material. into some but not all of the cells derived from all three germ The term “disease' or “disorder is used interchangeably layers. Thus, a multipotent cell is a partially differentiated herein, refers to any alternation in state of the body or of cell. Multipotent cells are well known in the art, and Some of the organs, interrupting or disturbing the perfor examples of muiltipotent cells include adult stem cells, such 10 mance of the functions and/or causing symptoms such as as for example, hematopoietic stem cells and neural stem discomfort, dysfunction, distress, or even death to the person cells. Multipotent means a stem cell can form many types of afflicted or those in contact with a person. A disease or cells in a given lineage, but not cells of other lineages. For disorder can also related to a distemper, ailing, ailment, example, a multipotent blood stem cell Such as a malady, disorder, sickness, illness, complaint, interdisposi “hematopoietic stem cells' refers to all stem cells or pro 15 tion, affection. A disease and disorder, includes but is not genitor cells found interalia in bone marrow and peripheral limited to any condition manifested as one or more physical blood that are capable of differentiating into any of the and/or psychological symptoms for which treatment is desir specific types of hematopoietic or blood cells, such as able, and includes previously and newly identified diseases erythrocytes, lymphocytes, macrophages and megakaryo and other disorders. cytes. The term “multipotency” refers to a cell with the In some embodiments of the aspects described herein, the degree of developmental versatility that is less than totipo cells for use with the biological classifier circuits described tent and pluripotent. herein are bacterial cells. The term “bacteria' as used herein In the context of cell ontogeny, the adjectives “differen is intended to encompass all variants of bacteria, for tiated, or “differentiating” are relative terms. The term example, prokaryotic organisms and cyanobacteria. In some “differentiation' in the present context means the formation 25 embodiments, the bacterial cells are gram-negative cells and of cells expressing markers known to be associated with in alternative embodiments, the bacterial cells are gram cells that are more specialized and closer to becoming positive cells. Non-limiting examples of species of bacterial terminally differentiated cells incapable of further differen cells useful for engineering with the biological classifier tiation. The pathway along which cells progress from a less circuits described herein include, without limitation, cells committed cell, to a cell that is increasingly committed to a 30 from Escherichia coli, Bacillus subtilis, Salmonella typh particular cell type, and eventually to a terminally differen imurium and various species of Pseudomonas, Streptomy tiated cell is referred to as progressive differentiation or ces, and Staphylococcus. Other examples of bacterial cells progressive commitment. Cell which are more specialized that can be genetically engineered for use with the biological (e.g., have begun to progress along a path of progressive classifier circuits described herein include, but are not lim differentiation) but not yet terminally differentiated are 35 ited to, cells from Yersinia spp., Escherichia spp., Klebsiella referred to as partially differentiated. Differentiation is a spp., Bordetella spp., Neisseria spp., Aeromonas spp., Fran developmental process whereby cells assume a specialized ciesella spp., Corynebacterium spp., Citrobacter spp., Chla phenotype, e.g., acquire one or more characteristics or mydia spp., Hemophilus spp., Brucella spp., Mycobacterium functions distinct from other cell types. In some cases, the spp., Legionella spp., Rhodococcus spp., Pseudomonas spp., differentiated phenotype refers to a cell phenotype that is at 40 Helicobacter spp., Salmonella spp., Vibrio spp., Bacillus the mature endpoint in Some developmental pathway (a so spp., and Erysipelothrix spp. In some embodiments, the called terminally differentiated cell). In many, but not all bacterial cells are E. coli cells. tissues, the process of differentiation is coupled with exit Other examples of organisms from which cells can be from the cell cycle. In these cases, the terminally differen transformed or transfected with the biological classifier tiated cells lose or greatly restrict their capacity to prolifer 45 circuits described herein include, but are not limited to the ate. However, we note that in the context of this specifica following: Staphylococcus aureus, Bacillus subtilis, tion, the terms “differentiation' or “differentiated” refer to Clostridium butyricum, Brevibacterium lactofermentum, cells that are more specialized in their fate or function than Streptococcus agalactiae, Lactococcus lactis, Leuconostoc at a previous point in their development, and includes both lactis, Streptomyces, Actinobacillus actinobycetemcomitans, cells that are terminally differentiated and cells that, 50 Bacteroides, cyanobacteria, Escherichia coli, Helobacter although not terminally differentiated, are more specialized pylori, Selnomonas ruminatium, Shigella sonnei, Zymomo than at a previous point in their development. The develop nas mobilis, Mycoplasma mycoides, or Treponema denti ment of a cell from an uncommitted cell (for example, a stem cola, Bacillus thuringiensis, Staphlococcus lugdunensis, cell), to a cell with an increasing degree of commitment to Leuconostoc oenos, Corynebacterium xerosis, Lactobacillus a particular differentiated cell type, and finally to a termi 55 planta rum, Streptococcus faecalis, Bacillus coagulans, nally differentiated cell is known as progressive differentia Bacillus ceretus, Bacillus popillae, Synechocystis Strain tion or progressive commitment. A cell that is “differenti PCC6803, Bacillus liquefaciens, Pyrococcus abyssi, Sele ated relative to a progenitor cell has one or more nomonas nominantium, Lactobacillus hilgardii, Streptococ phenotypic differences relative to that progenitor cell. Phe cus ferus, Lactobacillus pentosus, Bacteroides fragilis, notypic differences include, but are not limited to morpho 60 Staphylococcus epidermidis, Staphylococcus epidermidis, logic differences and differences in gene expression and Zymomonas mobilis, Streptomyces phaechromogenes, biological activity, including not only the presence or Streptomyces ghanaenis, Halobacterium strain GRB, and absence of an expressed marker, but also differences in the Halobaferax sp. strain Aa2.2. amount of a marker and differences in the co-expression In other embodiments of the aspects described herein, patterns of a set of markers. 65 biological classifier circuits can be introduced into a non The term “biological sample' as used herein refers to a cellular system such as a virus or phage, by direct integration cell or population of cells or a quantity of tissue or fluid from of the biological classifier circuit nucleic acid, for example, US 9,458,509 B2 127 128 into the viral genome. A virus for use with the biological ing the DNA. A vector can be either a self replicating classifier circuits described herein can be a dsDNA virus extrachromosomal vector or a vector which integrates into a (e.g. Adenoviruses, Herpesviruses, Poxviruses), a ssDNA host genome. One type of vector is a genomic integrated viruses ((+)sense DNA) (e.g. Parvoviruses); a dsRNA virus vector, or “integrated vector, which can become integrated (e.g. Reoviruses); a (+)SSRNA viruses ((+)sense RNA) (e.g. into the chromosomal DNA or RNA of a host cell, cellular Picornaviruses, Togaviruses): (-)ssRNA virus ((-)sense system, or non-cellular system. In some embodiments, the RNA) (e.g. Orthomyxoviruses, Rhabdoviruses); a ssRNA nucleic acid sequence or sequences encoding the biological Reverse Transcriptase viruses ((+)sense RNA with DNA classifier circuits and component input detector modules intermediate in life-cycle) (e.g. Retroviruses); or a dsDNA described herein integrates into the chromosomal DNA or Reverse Transcriptase virus (e.g. Hepadnaviruses). 10 RNA of a host cell, cellular system, or non-cellular system Viruses can also include plant viruses and bacteriophages along with components of the vector sequence. or phages. Examples of phage families that can be used with In other embodiments, the nucleic acid sequence encod the biological classifier circuits described herein include, but ing a biological classifier circuit and component input detec are not limited to, Myoviridae (T4-like viruses; P1-like tor modules directly integrates into chromosomal DNA or viruses; P2-like viruses; Mu-like viruses; SPO1-like viruses; 15 RNA of a host cell, cellular system, or non-cellular system, (pH-like viruses); Siphoviridaew-like viruses (T1-like in the absence of any components of the vector by which it viruses; T5-like viruses: c2-like viruses; L5-like viruses; was introduced. In such embodiments, the nucleic acid up M1-like viruses; (pC31-like viruses; N15-like viruses): sequence encoding the biological classifier circuits and Podoviridae (T7-like viruses; (p.29-like viruses; P22-like component input detector modules can be integrated using viruses: N4-like viruses); Tectiviridae (Tectivirus); Cortico targeted insertions, such as knock-in technologies or viridae (Corticovirus); Lipothrixviridae (Alphalipothrixvi homologous recombination techniques, or by non-targeted rus, Betalipothrixvirus, Gammalipothrixvirus, Deltalipo insertions, such as gene trapping techniques or non-homolo thrixvirus); Plasmaviridae (Plasmavirus); Rudiviridae gous recombination. The number of copies of a biological (Rudivirus); Fuselloviridae (Fusellovirus); Inoviridae (Ino classifier circuits and component input detector modules that virus, Plectrovirus); Microviridae (Microvirus, Spiromicro 25 integrate into the chromosomal DNA or RNA of a cellular or virus, Bdellomicrovirus, Chlamydiamicrovirus); Leviviri non-cellular system can impact the fidelity of expression and dae (Levivirus, Allolevivirus) and Cystoviridae detection, and thus it is preferred that only one copy is (CyStovirus). Such phages can be naturally occurring or integrated per cellular system. Accordingly, in some engineered phages. embodiments of the aspects described herein, only one copy In some embodiments of the aspects described herein, the 30 of a biological classifier circuits and its component input biological classifier circuits are introduced into a cellular or detector modules is integrated in the chromosomal DNA or non-cellular system using a vector or plasmid. As used RNA of a cellular or non-cellular system. In some embodi herein, the term “vector” is used interchangeably with ments, the number of copies is less than 10, less than 9, less “plasmid' to refer to a nucleic acid molecule capable of than 8, less than 7, less than 6, less than 5, less than 4, less transporting another nucleic acid to which it has been linked. 35 than 3, or less than 2. Vectors capable of directing the expression of genes and/or Another type of vector for use in the methods and nucleic acid sequence to which they are operatively linked biological classifier circuits described herein is an episomal are referred to herein as “expression vectors.” In general, vector, i.e., a nucleic acid capable of extra-chromosomal expression vectors of utility in the methods and biological replication. Such plasmids or vectors can include plasmid classifier circuits described herein are often in the form of 40 sequences from bacteria, viruses or phages. Such vectors “plasmids, which refer to circular double stranded DNA include chromosomal, episomal and virus-derived vectors loops which, in their vector form are not bound to the e.g., vectors derived from bacterial plasmids, bacterio chromosome. In some embodiments, all components of a phages, yeast episomes, yeast chromosomal elements, and given biological classifier circuit can be encoded in a single viruses, vectors derived from combinations thereof. Such as vector. For example, a lentiviral vector can be constructed, 45 those derived from plasmid and bacteriophage genetic ele which contains all components necessary for a functional ments, cosmids and phagemids. A vector can be a plasmid, biological classifier circuit as described herein. In some bacteriophage, bacterial artificial chromosome (BAC) or embodiments, individual components (e.g., a low-input yeast artificial chromosome (YAC). A vector can be a single detector modules and one or more high-input detector mod or double-stranded DNA, RNA, or phage vector. In some ules) can be separately encoded in different vectors and 50 embodiments, the biological classifier circuits and compo introduced into one or more cells separately. nent input detector modules are introduced into a cellular Other expression vectors can be used in different embodi system using a BAC vector. ments described herein, for example, but not limited to, The vectors comprising the biological classifier circuits plasmids, episomes, bacteriophages or viral vectors, and and component input detector modules described herein can Such vectors can integrate into the host’s genome or repli 55 be “introduced into cells as polynucleotides, preferably cate autonomously in the particular cellular system used. DNA, by techniques well-known in the art for introducing Viral vector include, but are not limited to, retroviral vectors, DNA and RNA into cells. The term “transduction” refers to Such as lentiviral vectors or gammaretroviral vectors, adeno any method whereby a nucleic acid sequence is introduced viral vectors, and baculoviral vectors. In some embodi into a cell, e.g., by transfection, lipofection, electroporation, ments, lentiviral vectors comprising the nucleic acid 60 biolistics, passive uptake, lipid:nucleic acid complexes, viral sequences encoding the high- and low-input modules and vector transduction, injection, contacting with naked DNA, biological classifier circuits described herein are used. For gene gun, and the like. The vectors, in the case of phage and example, a lentiviral vector can be used in the form of viral vectors can also be introduced into cells as packaged or lentiviral particles. Other forms of expression vectors known encapsidated virus by well-known techniques for infection by those skilled in the art which serve the equivalent 65 and transduction. Viral vectors can be replication competent functions can also be used. Expression vectors comprise or replication defective. In the latter case, viral propagation expression vectors for stable or transient expression encod generally occurs only in complementing host cells. In some US 9,458,509 B2 129 130 embodiments, the biological classifier circuits and compo stantially identical nucleic acids and complements thereof. nent input detector modules are introduced into a cell using Nucleotide analogues include nucleotides having modifica other mechanisms known to one of skill in the art, Such as tions in the chemical structure of the base, Sugar and/or a liposome, microspheres, gene gun, fusion proteins, such as phosphate, including, but not limited to, 5-position pyrimi a fusion of an antibody moiety with a nucleic acid binding 5 dine modifications, 8-position purine modifications, modi moiety, or other such delivery vehicle. fications at cytosine exocyclic amines, Substitution of The biological classifier circuits and component input 5-bromo-uracil, and the like; and 2'-position Sugar modifi detector modules or the vectors comprising the biological cations, including but not limited to, Sugar-modified ribo classifier circuits described herein can be introduced into a nucleotides in which the 2'-OH is replaced by a group cell using any method known to one of skill in the art. The 10 selected from H, OR, R, halo, SH, SR, NH2, NHR, NR2, or term “transformation' as used herein refers to the introduc CN. shRNAs also can comprise non-natural elements such tion of genetic material (e.g., a vector comprising a biologi as non-natural bases, e.g., ionosin and Xanthine, normatural cal classifier circuit) comprising one or more modules or Sugars, e.g., 2'-methoxy ribose, or non-natural phosphodi biological classifier circuits described herein into a cell, ester linkages, e.g., methylphosphonates, phosphorothioates tissue or organism. Transformation of a cell can be stable or 15 and peptides. transient. The term “transient transformation” or “transiently The term “nucleic acid sequence' or "oligonucleotide' or transformed’ refers to the introduction of one or more "polynucleotide' are used interchangeably herein and refers transgenes into a cell in the absence of integration of the to at least two nucleotides covalently linked together. The transgene into the host cells genome. Transient transforma term “nucleic acid sequence' is also used inter-changeably tion can be detected by, for example, enzyme linked immu herein with “gene”, “cDNA, and “mRNA'. As will be nosorbent assay (ELISA), which detects the presence of a appreciated by those in the art, the depiction of a single polypeptide encoded by one or more of the transgenes. For nucleic acid sequence also defines the sequence of the example, a biological classifier circuit can further comprise complementary nucleic acid sequence. Thus, a nucleic acid a constitutive promoter operably linked to a second output sequence also encompasses the complementary strand of a product, such as a reporter protein. Expression of that 25 depicted single strand. Unless otherwise indicated, a par reporter protein indicates that a cell has been transformed or ticular nucleic acid sequence also implicitly encompasses transfected with the biological classifier circuit, and is hence conservatively modified variants thereof (e.g., degenerate being interrogated by the circuit for the presence of the codon Substitutions) and complementary sequences, as well appropriate microRNA profile. Alternatively, transient trans as the sequence explicitly indicated. As will also be appre formation can be detected by detecting the activity of the 30 ciated by those in the art, a single nucleic acid sequence protein encoded by the transgene. The term “transient trans provides a probe that can hybridize to the target sequence formant” refers to a cell which has transiently incorporated under stringent hybridization conditions. Thus, a nucleic one or more transgenes. acid sequence also encompasses a probe that hybridizes In contrast, the term “stable transformation' or “stably under stringent hybridization conditions. The term “nucleic transformed refers to the introduction and integration of 35 acid sequence” refers to a single or double-stranded polymer one or more transgenes into the genome of a cell or cellular of deoxyribonucleotide or ribonucleotide bases read from system, preferably resulting in chromosomal integration and the 5'- to the 3'-end. It includes chromosomal DNA, self stable heritability through meiosis. Stable transformation of replicating plasmids, infectious polymers of DNA or RNA a cell can be detected by Southern blot hybridization of and DNA or RNA that performs a primarily structural role. genomic DNA of the cell with nucleic acid sequences, which 40 “Nucleic acid sequence” also refers to a consecutive list of are capable of binding to one or more of the transgenes. abbreviations, letters, characters or words, which represent Alternatively, stable transformation of a cell can also be nucleotides. Nucleic acid sequences can be single stranded detected by the polymerase chain reaction of genomic DNA or double stranded, or can contain portions of both double of the cell to amplify transgene sequences. The term “stable Stranded and single stranded sequence. The nucleic acid transformant” refers to a cell or cellular, which has stably 45 sequence can be DNA, both genomic and cDNA, RNA, or integrated one or more transgenes into the genomic DNA. a hybrid, where the nucleic acid sequence can contain Thus, a stable transformant is distinguished from a transient combinations of deoxyribo- and ribo-nucleotides, and com transformant in that, whereas genomic DNA from the stable binations of bases including uracil, adenine, thymine, cyto transformant contains one or more transgenes, genomic sine, guanine, inosine, Xanthine hypoxanthine, isocytosine DNA from the transient transformant does not contain a 50 and isoguanine. Nucleic acid sequences can be obtained by transgene. Transformation also includes introduction of chemical synthesis methods or by recombinant methods. A genetic material into plant cells in the form of plant viral nucleic acid sequence will generally contain phosphodiester vectors involving epichromosomal replication and gene bonds, although nucleic acid analogs can be included that expression, which can exhibit variable properties with can have at least one different linkage, e.g., phosphorami respect to meiotic stability. Transformed cells, tissues, or 55 date, phosphorothioate, phosphorodithioate, or O-methyl plants are understood to encompass not only the end product phosphoroamidite linkages and peptide nucleic acid back of a transformation process, but also transgenic progeny bones and linkages in the nucleic acid sequence. Other thereof. analog nucleic acids include those with positive backbones; The terms “nucleic acids' and “nucleotides’ refer to non-ionic backbones, and non-ribose backbones, including naturally occurring or synthetic or artificial nucleic acid or 60 those described in U.S. Pat. Nos. 5,235,033 and 5,034,506, nucleotides. The terms “nucleic acids' and “nucleotides’ which are incorporated by reference. Nucleic acid sequences comprise deoxyribonucleotides or ribonucleotides or any containing one or more non-naturally occurring or modified nucleotide analogue and polymers or hybrids thereof in nucleotides are also included within one definition of nucleic either single- or doublestranded, sense or antisense form. As acid sequences. The modified nucleotide analog can be will also be appreciated by those in the art, many variants of 65 located for example at the 5'-end and/or the 3'-end of the a nucleic acid can be used for the same purpose as a given nucleic acid sequence. Representative examples of nucleo nucleic acid. Thus, a nucleic acid also encompasses Sub tide analogs can be selected from Sugar- or backbone US 9,458,509 B2 131 132 modified ribonucleotides. It should be noted, however, that and the reference or target nucleotide sequence is at least also nucleobase-modified ribonucleotides, i.e. ribonucle 60%, at least 70%, at least 80% or 85%, at least 90%, at least otides, containing a non naturally occurring nucleobase 93%, at least 95% or 96%, at least 97% or 98%, at least 99% instead of a naturally occurring nucleobase Such as uridines or 100% (the later being equivalent to the term “identical or cytidines modified at the 5-position, e.g. 5-(2-amino) in this context). For example, identity is assessed over a propyluridine, 5-bromo uridine; adenosines and guanosines length of 10-22 nucleotides, such as at least 10, 11, 12, 13, modified at the 8-position, e.g. 8-bromo guanosine; deaza 14, 15, 16, 17, 18, 19, 20, 21, 22 or up to 50 nucleotides of nucleotides, e.g. 7 deaza-adenosine; O- and N-alkylated a nucleic acid sequence to said reference sequence (if not nucleotides, e.g. N6-methyl adenosine are suitable. The 2 specified otherwise below). Sequence comparisons are car OH-group can be replaced by a group selected from H. OR, 10 ried out using default GAP analysis with the University of R. halo, SH, SR, NH2, NHR, NR2 or CN, wherein R is C-C6 Wisconsin GCG, SEQWEB application of GAP, based on alkyl, alkenyl or alkynyl and halo is F, Cl, Br or I. Modi the algorithm of Needleman and Wunsch (Needleman and fications of the ribose-phosphate backbone can be done for Wunsch (1970) J MoI. Biol. 48: 443-453; as defined above). a variety of reasons, e.g., to increase the stability and A nucleotide sequence that is “substantially identical to a half-life of such molecules in physiological environments or 15 reference nucleotide sequence hybridizes to the exact as probes on a biochip. Mixtures of naturally occurring complementary sequence of the reference nucleotide nucleic acids and analogs can be used; alternatively, mix sequence (i.e. its corresponding strand in a double-stranded tures of different nucleic acid analogs, and mixtures of molecule) under low Stringency conditions, preferably naturally occurring nucleic acids and analogs can be used. medium stringency conditions, most preferably high Strin Nucleic acid sequences include but are not limited to, gency conditions (as defined above). Homologues of a nucleic acid sequence encoding proteins, for example that specific nucleotide sequence include nucleotide sequences act as reporters, transcriptional repressors, antisense mol that encode an amino acid sequence that is at least 24% ecules, ribozymes, Small inhibitory nucleic acid sequences, identical, at least 35% identical, at least 50% identical, at for example but not limited to RNAi, shRNAi, siRNA, least 65% identical to the reference amino acid sequence, as micro RNAi (mRNAi), antisense oligonucleotides etc. 25 measured using the parameters described above, wherein the The term "oligonucleotide' as used herein refers to an amino acid sequence encoded by the homolog has the same oligomer or polymer of ribonucleic acid (RNA) or deoxy biological activity as the protein encoded by the specific ribonucleic acid (DNA) or mimetics thereof, as well as nucleotide. The term “substantially non-identical refers to oligonucleotides having non-naturally-occurring portions a nucleotide sequence that does not hybridize to the nucleic which function similarly. Such modified or substituted oli 30 acid sequence under stringent conditions. gonucleotides are often preferred over native forms because As used herein, the term “gene' refers to a nucleic acid of desirable properties such as, for example, enhanced sequence comprising an open reading frame encoding a cellular uptake, enhanced affinity for nucleic acid target and polypeptide, including both exon and (optionally) intron increased Stability in the presence of nucleases. An oligo sequences. A "gene' refers to coding sequence of a gene nucleotide preferably includes two or more nucleomono 35 product, as well as non-coding regions of the gene product, mers covalently coupled to each other by linkages (e.g., including 5'UTR and 3'UTR regions, introns and the pro phosphodiesters) or Substitute linkages. moter of the gene product. These definitions generally refer In its broadest sense, the term "substantially complemen to a single-stranded molecule, but in specific embodiments tary', when used herein with respect to a nucleotide will also encompass an additional Strand that is partially, sequence in relation to a reference or target nucleotide 40 Substantially or fully complementary to the single-stranded sequence, means a nucleotide sequence having a percentage molecule. Thus, a nucleic acid sequence can encompass a of identity between the substantially complementary nucleo double-stranded molecule or a double-stranded molecule tide sequence and the exact complementary sequence of said that comprises one or more complementary Strand(s) or reference or target nucleotide sequence of at least 60%, at “complement(s) of a particular sequence comprising a least 70%, at least 80% or 85%, at least 90%, at least 93%, 45 molecule. As used herein, a single Stranded nucleic acid can at least 95% or 96%, at least 97% or 98%, at least 99% or be denoted by the prefix “ss', a double stranded nucleic acid 100% (the later being equivalent to the term “identical” in by the prefix 'ds', and a triple stranded nucleic acid by the this context). For example, identity is assessed over a length prefix “ts.” of at least 10 nucleotides, or at least 11, 12, 13, 14, 15, 16, The term “operable linkage' or “operably linked' are 17, 18, 19, 20, 21, 22 or up to 50 nucleotides of the entire 50 used interchangeably herein, are to be understood as mean length of the nucleic acid sequence to said reference ing, for example, the sequential arrangement of a regulatory sequence (if not specified otherwise below). Sequence com element (e.g. a promoter) with a nucleic acid sequence to be parisons are carried out using default GAP analysis with the expressed and, if appropriate, further regulatory elements University of Wisconsin GCG, SEQWEB application of (such as, e.g., a terminator) in Such a way that each of the GAP, based on the algorithm of Needleman and Wunsch 55 regulatory elements can fulfill its intended function to allow, (Needleman and Wunsch (1970) J MoI. Biol. 48: 443-453; modify, facilitate or otherwise influence expression of the as defined above). A nucleotide sequence “substantially linked nucleic acid sequence. The expression can result complementary' to a reference nucleotide sequence hybrid depending on the arrangement of the nucleic acid sequences izes to the reference nucleotide sequence under low strin in relation to sense or antisense RNA. To this end, direct gency conditions, preferably medium stringency conditions, 60 linkage in the chemical sense is not necessarily required. most preferably high stringency conditions (as defined Genetic control sequences such as, for example, enhancer above). sequences, can also exert their function on the target In its broadest sense, the term “substantially identical, sequence from positions which are further away, or indeed when used herein with respect to a nucleotide sequence, from other DNA molecules. In some embodiments, arrange means a nucleotide sequence corresponding to a reference or 65 ments are those in which the nucleic acid sequence to be target nucleotide sequence, wherein the percentage of iden expressed recombinantly is positioned behind the sequence tity between the substantially identical nucleotide sequence acting as promoter, so that the two sequences are linked US 9,458,509 B2 133 134 covalently to each other. The distance between the promoter light, agent etc.) which is different from the level of tran sequence and the nucleic acid sequence to be expressed Scription of the operably linked nucleic acid sequence in the recombinantly can be any distance, and in some embodi absence of the stimulus. ments is less than 200 base pairs, especially less than 100 A promoter can be regulated in a tissue-specific or tissue base pairs, less than 50 base pairs. In some embodiments, the preferred manner Such that it is only active in transcribing nucleic acid sequence to be transcribed is located behind the the associated coding region in a specific tissue type(s). The promoter in Such away that the transcription start is identical term “tissue specific' as it applies to a promoter refers to a with the desired beginning of the chimeric RNA described promoter that is capable of directing selective expression of herein. Operable linkage, and an expression construct, can a nucleotide sequence of interest to a specific type of tissue 10 (e.g., liver) in the relative absence of expression of the same be generated by means of customary recombination and nucleotide sequence of interest in a different type of tissue cloning techniques as described (e.g., in Maniatis T. Fritsch (e.g., kidney). Tissue specificity of a promoter can be E F and Sambrook J (1989) Molecular Cloning: A Labora evaluated by, for example, operably linking a reporter gene tory Manual, 2nd Ed., Cold Spring Harbor Laboratory, Cold to the promoter sequence to generate a reporter construct, Spring Harbor (NY); Silhavy et al. (1984) Experiments with 15 introducing the reporter construct into the genome of an Gene Fusions, Cold Spring Harbor Laboratory, Cold Spring organism, e.g. an animal model Such that the reporter Harbor (NY); Ausubel et al. (1987) Current Protocols in construct is integrated into every tissue of the resulting Molecular Biology, Greene Publishing Assoc and Wiley transgenic animal, and detecting the expression of the Interscience; Gelvin et al. (Eds) (1990) Plant Molecular reporter gene (e.g., detecting mRNA, protein, or the activity Biology Manual: Kluwer Academic Publisher, Dordrecht, of a protein encoded by the reporter gene) in different tissues The Netherlands). However, further sequences can also be of the transgenic animal. The detection of a greater level of positioned between the two sequences. The insertion of expression of the reporter gene in one or more tissues sequences can also lead to the expression of fusion proteins, relative to the level of expression of the reporter gene in or serves as ribosome binding sites. In some embodiments, other tissues shows that the promoter is specific for the the expression construct, consisting of a linkage of promoter 25 tissues in which greater levels of expression are detected. and nucleic acid sequence to be expressed, can exist in a The term “cell type specific' as applied to a promoter refers vector integrated form and be inserted into a plant genome, to a promoter, which is capable of directing selective expres for example by transformation. sion of a nucleotide sequence of interest in a specific type of The terms “promoter,” “promoter element,” or “promoter cell in the relative absence of expression of the same sequence' are equivalents and as used herein, refers to a 30 nucleotide sequence of interest in a different type of cell DNA sequence which when operatively linked to a nucleo within the same tissue. The term “cell type specific’ when tide sequence of interest is capable of controlling the tran applied to a promoter also means a promoter capable of scription of the nucleotide sequence of interest into mRNA. promoting selective expression of a nucleotide sequence of A promoter is typically, though not necessarily, located 5' interest in a region within a single tissue. Cell type speci (i.e., upstream) of a nucleotide sequence of interest (e.g., 35 ficity of a promoter can be assessed using methods well proximal to the transcriptional start site of a structural gene) known in the art, e.g., GUS activity staining or immunohis whose transcription into mRNA it controls, and provides a tochemical staining. The term “minimal promoter as used site for specific binding by RNA polymerase and other herein refers to the minimal nucleic acid sequence compris transcription factors for initiation of transcription. A poly ing a promoter element while also maintaining a functional nucleotide sequence is "heterologous to an organism or a 40 promoter. A minimal promoter can comprise an inducible, second polynucleotide sequence if it originates from a constitutive or tissue-specific promoter. foreign species, or, if from the same species, is modified The term “expression” as used herein refers to the bio from its original form. For example, a promoter operably synthesis of a gene product, preferably to the transcription linked to a heterologous coding sequence refers to a coding and/or translation of a nucleotide sequence, for example an sequence from a species different from that from which the 45 endogenous gene or a heterologous gene, in a cell. For promoter was derived, or, if from the same species, a coding example, in the case of a heterologous nucleic acid sequence which is not naturally associated with the promoter sequence, expression involves transcription of the heterolo (e.g. a genetically engineered coding sequence or an allele gous nucleic acid sequence into mRNA and, optionally, the from a different ecotype or variety). Suitable promoters can Subsequent translation of mRNA into one or more polypep be derived from genes of the host cells where expression 50 tides. Expression also refers to biosynthesis of a microRNA should occur or from pathogens for the host cells (e.g., tissue or RNAi molecule, which refers to expression and transcrip promoters or pathogens like viruses). tion of an RNAi agent such as siRNA, shRNA, and antisense If a promoter is an “inducible promoter', as defined DNA but does not require translation to polypeptide herein, then the rate of transcription is modified in response sequences. The term "expression construct” and “nucleic to an inducing agent or inducer. In contrast, the rate of 55 acid construct’ as used herein are synonyms and refer to a transcription is not regulated by an inducer if the promoter nucleic acid sequence capable of directing the expression of is a constitutive promoter. The term “constitutive' when a particular nucleotide sequence, Such as the heterologous made in reference to a promoter means that the promoter is target gene sequence in an appropriate host cell (e.g., a capable of directing transcription of an operably linked prokaryotic cell, eukaryotic cell, or mammalian cell). If nucleic acid sequence in the absence of a stimulus (e.g., heat 60 translation of the desired heterologous target gene is shock, chemicals, agents, light, etc.). Typically, constitutive required, it also typically comprises sequences required for promoters are capable of directing expression of a nucleic proper translation of the nucleotide sequence. The coding acid sequence in Substantially any cell and any tissue. In region can code for a protein of interest but can also code for contrast, the term “regulateable' or “inducible' promoter a functional RNA of interest, for example, microRNA, referred to herein is one which is capable of directing a level 65 microRNA target sequence, antisense RNA, dsRNA, or a of transcription of an operably linked nucleic acid sequence nontranslated RNA, in the sense or antisense direction. The in the presence of a stimulus (e.g., heat shock, chemicals, nucleic acid construct as disclosed herein can be chimeric, US 9,458,509 B2 135 136 meaning that at least one of its components is heterologous “protein’ are used interchangeably herein to refer to a with respect to at least one of its other components. polymer or oligomer of consecutive amino acid residues. The term “leakiness” or “leaky” as used in reference to The term “subject” refers to any living organism from “promoter leakiness” refers to some level of expression of which a biological sample, Such as a cell sample, can be the nucleic acid sequence which is operatively linked to the 5 obtained. The term includes, but is not limited to, humans; promoter, even when the promoter is not intended to result non-human primates, such as chimpanzees and other apes in expression of the nucleic acid sequence (i.e., when the and monkey species; farm animals such as cattle, sheep, promoter is in the “off state, a background level of expres pigs, goats and horses, domestic Subjects Such as dogs and sion of the nucleic acid sequence which is operatively linked cats, laboratory animals including rodents such as mice, rats to Such promoter exists). In one illustrative example using 10 and guinea pigs, and the like. The term does not denote a inducible promoters, for example a Tet-on promoter, a leaky particular age or sex. Thus, adult and newborn Subjects, as promoter is where some level of the nucleic acid sequence well as fetuses, whether male or female, are intended to be expression (which is operatively linked to the Tet-on pro covered. The term “subject' is also intended to include moter) still occurs in the absence of the inducer agent, living organisms susceptible to conditions or diseases tetracycline. Typically, most inducible promoters and tissue 15 caused or contributed bacteria, pathogens, disease states or specific promoters have approximately 10%-30% or 10-20% conditions as generally disclosed, but not limited to, unintended or background nucleic acid sequence expression throughout this specification. Examples of Subjects include when the promoter is not active, for example, the back humans, dogs, cats, cows, goats, and mice. ground of leakiness of nucleic acid sequence expression is The terms “higher or “increased or “increase as used about 10%-20% or about 10-30%. As an illustrative example herein in the context of expression or biological activity of using a tissue-specific promoter, a “leaky promoter' is one a microRNA or protein generally means an increase in the in which expression of the nucleic acid sequence occurs in expression level or activity of the microRNA or protein by tissue where a tissue-specific promoter is not active, i.e. a statically significant amount relative to a reference level. expression occurs in a non-specific tissue. Stated in another state or condition. For the avoidance of doubt, a “higher or way using a kidney-specific promoter as an example; if at 25 “increased, expression of a microRNA means a statistically least some level of the nucleic acid sequence expression significant increase of at least about 50% as compared to a occurs in at least one tissue other than the kidney, where the reference level or state, including an increase of at least nucleic acid sequence is operably linked to a kidney specific about 60%, at least about 70%, at least about 80%, at least promoter, the kidney specific promoter would be considered about 90%, at least about 100% or more, including, for a leaky promoter 30 example at least 2-fold, at least 3-fold, at least 4-fold, at least The term "enhancer” refers to a cis-acting regulatory 5-fold, at least 6-fold, at least 7-fold, at least 8-fold, at least sequence involved in the transcriptional activation of a 9-fold, at least 10-fold, at least 20-fold, at least 30-fold, at nucleic acid sequence. An enhancer can function in either least 40-fold, at least 50-fold, at least 60-fold, at least orientation and can be upstream or downstream of the 70-fold, at least 80-fold, at least 90-fold, at least 100-fold, at promoter. As used herein, the term “gene product(s) is used 35 least 500-fold, at least 1000-fold increase or greater of the to refer to include RNA transcribed from a gene, or a level of expression of the microRNA relative to the refer polypeptide encoded by a gene or translated from RNA. A ence level. protein and/or peptide or fragment thereof can be any Similarly, the terms “lower”, “reduced', or “decreased” protein of interest, for example, but not limited to; mutated are all used herein generally to mean a decrease by a proteins; therapeutic proteins; truncated proteins, wherein 40 statistically significant amount. However, for avoidance of the protein is normally absent or expressed at lower levels in doubt, “lower”, “reduced, “reduction' or “decreased the cell. Proteins can also be selected from a group com means a decrease by at least 50% as compared to a reference prising; mutated proteins, genetically engineered proteins, level, for example a decrease by at least about 60%, or at peptides, synthetic peptides, recombinant proteins, chimeric least about 70%, or at least about 80%, or at least about 90%, proteins, antibodies, midibodies, tribodies, humanized pro 45 or at least about 95%, or up to and including a 100% teins, humanized antibodies, chimeric antibodies, modified decrease (i.e. absent level as compared to a reference proteins and fragments thereof. sample), or any decrease between 50-100% as compared to The term “nucleic acid construct” as used herein refers to a reference level. a nucleic acid at least partly created by recombinant meth As used herein, the term "comprising means that other ods. The term “DNA construct” refers to a polynucleotide 50 elements can also be present in addition to the defined construct consisting of deoxyribonucleotides. The construct elements presented. The use of "comprising indicates can be single or double stranded. The construct can be inclusion rather than limitation. Accordingly, the terms circular or linear. A person of ordinary skill in the art is “comprising means “including principally, but not neces familiar with a variety of ways to obtain and generate a DNA sary solely'. Furthermore, variation of the word “compris construct. Constructs can be prepared by means of custom 55 ing'. Such as "comprise' and "comprises', have correspond ary recombination and cloning techniques as are described, ingly the same meanings. The term “consisting essentially for example, in Maniatis T. Fritsch E F and Sambrook J of means “including principally, but not necessary solely at (1989) Molecular Cloning: A Laboratory Manual, 2nd Ed., least one', and as such, is intended to mean a “selection of Cold Spring Harbor Laboratory, Cold Spring Harbor (NY); one or more, and in any combination’. Stated another way, Silhavy et al. (1984) Experiments with Gene Fusions, Cold 60 the term "consisting essentially of means that an element Spring Harbor Laboratory, Cold Spring Harbor (NY); can be added, subtracted or substituted without materially Ausubel et al. (1987) Current Protocols in Molecular Biol affecting the novel characteristics described herein. This ogy, Greene Publishing Assoc and Wiley Interscience: applies equally to steps within a described method as well as Gelvin et al. (Eds) (1990) Plant Molecular Biology Manual: compositions and components therein. In other embodi Kluwer Academic Publisher, Dordrecht, The Netherlands. 65 ments, the inventions, compositions, methods, and respec The terms “polypeptide', 'peptide'. “oligopeptide', tive components thereof, described herein are intended to be "polypeptide'. “gene product”, “expression product” and exclusive of any element not deemed an essential element to US 9,458,509 B2 137 138 the component, composition or method ("consisting of'). Diego, USA (1987)); Current Protocols in Molecular Biol For example, a biological classifier circuit that comprises a ogy (CPMB) (Fred M. Ausubel, et al. ed., John Wiley and repressor sequence and a microRNA target sequence encom Sons, Inc.); Current Protocols in Protein Science (CPPS) passes both the repressor sequence and a microRNA target (John E. Coligan, et. al., ed., John Wiley and Sons, Inc.); sequence of a larger sequence. By way of further example, Current Protocols in Immunology (CPI) (John E. Coligan, a composition that comprises elements A and B also encom et. al., ed. John Wiley and Sons, Inc.); Current Protocols in passes a composition consisting of A, B and C. Cell Biology (CPCB) (Juan S. Bonifacino et. al. ed., John As used in this specification and the appended claims, the Wiley and Sons, Inc.); Culture of Animal Cells: A Manual of singular forms “a,” “an, and “the' include plural references Basic Technique by R. Ian Freshney, Publisher: Wiley-Liss; unless the context clearly dictates otherwise. Thus for 10 5th edition (2005); Animal Cell Culture Methods (Methods example, references to “the method’ includes one or more in Cell Biology, Vol. 57, Jennie P. Mather and David Barnes methods, and/or steps of the type described herein and/or editors, Academic Press, 1st edition, 1998) which are all which will become apparent to those persons skilled in the incorporated by reference herein in their entireties. art upon reading this disclosure and so forth. It should be understood that this invention is not limited It is understood that the foregoing detailed description and 15 to the particular methodology, protocols, and reagents, etc., the following examples are illustrative only and are not to be described herein and as Such can vary. The terminology used taken as limitations upon the scope described herein. Various herein is for the purpose of describing particular embodi changes and modifications to the disclosed embodiments, ments only, and is not intended to limit the scope described which will be apparent to those of skill in the art, can be herein, which is defined solely by the claims. made without departing from the spirit and scope described Other than in the operating examples, or where otherwise herein. Further, all patents, patent applications, publications, indicated, all numbers expressing quantities of ingredients and websites identified are expressly incorporated herein by or reaction conditions used herein should be understood as reference for the purpose of describing and disclosing, for modified in all instances by the term “about.” The term example, the methodologies described in Such publications "about when used in connection with percentages can that might be used in connection with the present invention. 25 meant 1%. These publications are provided solely for their disclosure The singular terms “a,” “an,” and “the include plural prior to the filing date of the present application. Nothing in referents unless context clearly indicates otherwise. Simi this regard should be construed as an admission that the larly, the word 'or' is intended to include “and” unless the inventors are not entitled to antedate such disclosure by context clearly indicates otherwise. Although methods and virtue of prior invention or for any other reason. All state 30 materials similar or equivalent to those described herein can ments as to the date or representation as to the contents of be used in the practice or testing of this disclosure, Suitable these documents are based on the information available to methods and materials are described below. The abbrevia the applicants and do not constitute any admission as to the tion, "e.g. is derived from the Latin exempligratia, and is correctness of the dates or contents of these documents. used herein to indicate a non-limiting example. Thus, the Unless otherwise explained, all technical and scientific 35 abbreviation “e.g. is synonymous with the term “for terms used herein have the same meaning as commonly example.” understood by one of ordinary skill in the art to which this All patents and other publications identified are expressly disclosure belongs. Definitions of common terms in molecu incorporated herein by reference for the purpose of describ lar biology can be found in The Merck Manual of Diagnosis ing and disclosing, for example, the methodologies and Therapy, 18th Edition, published by Merck Research 40 described in Such publications that might be used in con Laboratories, 2006 (ISBN 0-91 1910-18-2); Robert S. Porter nection with the present invention. These publications are et al. (eds.), The Encyclopedia of Molecular Biology, pub provided solely for their disclosure prior to the filing date of lished by Blackwell Science Ltd., 1994 (ISBN 0-632-02182 the present application. Nothing in this regard should be 9); Robert A. Meyers (ed.), Molecular Biology and Biotech construed as an admission that the inventors are not entitled nology: a Comprehensive Desk Reference, published by 45 to antedate such disclosure by virtue of prior invention or for VCH Publishers, Inc., 1995 (ISBN 1-56081-569-8); The any other reason. All Statements as to the date or represen ELISA guidebook (Methods in molecular biology 149) by tation as to the contents of these documents is based on the Crowther J. R. (2000); Fundamentals of RIA and Other information available to the applicants and does not consti Ligand Assays by Jeffrey Travis, 1979, Scientific Newslet tute any admission as to the correctness of the dates or ters: Immunology by Werner Luttmann, published by 50 contents of these documents. Elsevier, 2006. Definitions of common terms in molecular This invention is further illustrated by the following biology can be found in Benjamin Lewin, Genes IX, pub examples which should not be construed as limiting. The lished by Jones & Bartlett Publishing, 2007 (ISBN-13: contents of all references cited throughout this application, 978.0763740634); and Kendrew et al. (eds.), The Encyclo as well as the figures and tables are incorporated herein by pedia of Molecular Biology, published by Blackwell Science 55 reference. Ltd., 1994 (ISBN 0-632-02182-9). Unless otherwise Stated, the present invention was per Examples formed using standard procedures, as described, for example in Maniatis et al., Molecular Cloning: A Laboratory Manual, The engineered biological systems described herein, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, 60 which integrate Sophisticated sensing, information process N.Y., USA (1982); Sambrook et al., Molecular Cloning: A ing, and actuation in living cells, are useful for new direc Laboratory Manual (2 ed.), Cold Spring Harbor Laboratory tions in basic biology, biotechnology and medicine. The Press, Cold Spring Harbor, N.Y., USA (1989); Davis et al., complexity of the cellular environment requires elaborate Basic Methods in Molecular Biology, Elsevier Science Pub sensory and information processing capabilities in indi lishing, Inc., New York, USA (1986); Methods in Enzymol 65 vidual cells. Herein we demonstrate a multiple-input bio ogy: Guide to Molecular Cloning Techniques Vol. 152, S. L. logical classifier circuit that, in Some embodiments, can act Berger and A. R. Kimmerl Eds. Academic Press Inc., San as a programmable therapeutic agent that operates in indi US 9,458,509 B2 139 140 vidual cells, diagnose a complex cellular condition, and practices for characterizing bulk tissue (e.g., biopsy selectively trigger a therapeutic response using molecular samples) using gene array analysis and computer algorithms tools analogous to disease profiling arrays and computer (31). algorithms. This programmable therapeutic agent comprises The approaches described herein can be used in a variety a synthetic, Scalable transcriptional/posttranscriptional regu of applications. In some examples, we chose to develop a latory circuit—a classifier circuit—designed to sense multi-input classifier circuit that is applicable for highly expression levels of a customizable set of endogenous precise and selective cancer therapy. Many mainstream and microRNAS and to compute whether to trigger a response if experimental drugs exhibit some degree of selectivity the expression levels match a pre-determined profile of toward cancer cells by relying on individual cancer markers interest. Specifically, as demonstrated herein, when operat 10 (32). However, cancer cells exhibit a complex set of con ing in a heterogeneous cell population, the classifier circuits ditions deviating from the normal state of their progenitor described herein can identify and selectively destroys cancer tissue (33, 34), and using a single marker, or even two, to cells, such as HeLa cancer cells when using a HeLa-specific distinguish them from healthy cells is rarely sufficient and microRNA expression profile as a point of reference. The often results in harmful side-effects (35). Therefore, sensing approaches described herein will enable highly-precise can 15 and integration of information from multiple markers by a cer treatments with little collateral damage, as well as be therapeutic agent is crucial for creating next-generation useful for numerous other applications that benefit from treatments (26). We constructed and tested in human cell accurate single-cell in-vivo identification of highly-complex culture a programmed therapeutic agent comprising an cell states. exemplary multi-input classifier circuit that selectively iden A salient feature of biological pathways is their two-way tifies and triggers apoptosis in HeLa cell line (derived from interaction with the cellular environment in which they cervical cancer tissue), but not in healthy cells. operate. Such interaction usually involves (1) sensing of High-Level Operation of a microRNA Classifier Circuit relevant input conditions in the cell, (2) computing or RNA and protein components of the circuits described processing those inputs to determine whether and which herein are expressed from exogenously introduced genes to action to take; and (3) producing a biologically-active output 25 form a functional network in cells. The functional network to actuate a physiological effect in the cell. Engineered is designed to perform a biochemical computation with a analogues of natural pathways with elaborate sensing, com pre-defined set of inputs, such as endogenous mature micro putational and actuation functionalities (1, 2) can augment RNAs. The elementary task of this computation is to deter endogenous processes and enable rational manipulation and mine whether, for example, the microRNA expression pro control of biological systems for the benefit of basic bio 30 file, i.e. a combination of microRNA expression levels, of a logical exploration, biotechnology and medical intervention. given cell matches a profile of interest, resulting in either Reporter constructs (3) that transduce cellular inputs into a match (True) or 'no match (False) outcome. In our experi detectable output, and tissue-specific transgenes controlled ments described herein, a positive match classified a cell as transcriptionally and/or posttranscriptionally (4-6) represent a HeLa cancer cell and the circuit generated an output. Such important first steps toward this goal. The discipline of 35 as a fluorescent reporter for circuit characterization or an synthetic biology builds on these efforts to create innovative apoptotic protein to trigger biological actuation. and generally-applicable approaches to molecular sensing, As a first step in designing a classifier circuit that uses signal integration and actuation, and promises a quantum microRNA levels as inputs, a microRNA profile for the cell leap in the complexity and Sophistication of engineered type of interest, the reference profile, can be identified by biological systems by placing their construction on a rigor 40 bioinformatics analysis and experimental confirmation. In ous engineering foundation. general, a reference profile for use with the classifier circuits Synthetic circuits have already demonstrated basic pro described herein comprises a small number of microRNA grammable dynamic behavior in cells (oscillators (7-10), markers that are highly expressed in the cell type of interest, memory (11-14), spatial patterns (15), cascades (16) and but typically not in other cells, together with a few micro pulse generators (17)), digital and analog computations 45 RNA markers that are not expressed in the cell type of (18-20), and complex biosynthetic pathways (21), but the interest but are often highly expressed in others (FIG. 1A). interaction of these circuits with the cellular context has The goal is to identify a small, non-redundant set of markers been limited (22, 23). In parallel, molecular network proto that generates a unique and robust molecular signature for a types have demonstrated Sophisticated sensing, computation specific cell type. We note that multiple sets can exist to and actuation (24-28) in cell-free environments, anticipating 50 uniquely identify any cell type, and the optimal choice is the benefits of embedding similar networks in cells. likely to be dictated by practical considerations. For the Herein we describe multi-input, genetic classifier circuits classifier circuit for classifying HeLa cells described herein, that use both transcriptional and posttranscriptional regula these markers are designated as HeLa-high and HeLa tion in order to determine, for example, whether a cell of low, respectively. unknown origin is in a specific state of interest. The circuits 55 Once a profile was established, we used a modular design implement this task by interrogating the state of the host cell approach to construct a circuit that detects this profile in through simultaneous assessment of the expression levels of cells. We have created a number of sensor mechanisms that multiple different endogenous mature microRNAS impor link intracellular microRNA activity to the expression level tant regulators and indicators of specific cellular states (30). of an output protein, and a specific way to combine these In some examples, six different microRNAs were used. The 60 sensors in order to implement molecular AND-like logic circuit computes whether the expression profile of the, for with the inputs expression levels. The AND logic abstrac example, six microRNAs matches a pre-determined refer tion is inspired by a similar abstraction in computer engi ence profile that characterizes a cell state that the classifier neering and describes in a simplified fashion the general circuit is intended to detect and if so, produces a biological properties of the circuit. We discuss the underlying analog response. We call this circuit a classifier because it clas 65 properties of the circuit components and overall capacity of sifies individual cells into a number of categories based on the circuit to convert analog input signals to reliable, near the cells internal state, in a manner similar to current digital output. Some components of the sensors designed to US 9,458,509 B2 141 142 detect high marker expression, e.g., HeLa-high markers, line (HEK293) and breast cancer cell line MCF7 that comprise specially-designed double-inversion modules. represent other tissues in our experiments. We chose MCF7 These modules efficiently repress an output in the absence of cells as a model of non-cancer MCF 10 cells that are difficult their cognate microRNA inputs, while the repression is to transfect, because expression levels of the HeLa profile largely relieved and the output reaches high levels in cells microRNA markers in MCF10 cells are similar to those in that express this marker at or above its level in HeLa cells. MCF7 cells. Our fluorescent reporters were fused to appro Sensors for HeLa-low markers comprise short micoRNA priate microRNA targets to measure knock-down efficien target sequences directly fused to mRNA of the output gene cies. We observed knock-down of the miR-21 reporter in (4, 29). The sensors for detecting low-marker expression HeLa and MCF7 but not in HEK293 cells, while knock efficiently knock down output protein expression when 10 down by a combination of miR-17 and 30a was detected in microRNA level is high, but the knock-down is weak and the all three cell lines (FIGS. 1C and 1D). In addition, reporter output level is high when the microRNA is present at low knock-down by miR-141 was observed in MCF7 cells. Note levels typical of HeLa cells. that fewer than six inputs are required if our goal were to The AND-type logic behavior of the classifier circuits distinguish only between HeLa, HEK293 and MCF7. How described herein is achieved by fine tuning sensor responses 15 ever, we use all six inputs here to demonstrate that the to their cognate microRNA inputs and by properly integrat system can scale to this size and that the classifier circuit ing the sensors in the classifier circuit. Output expression is operates correctly when we artificially vary all marker programmed to trigger actuation only in cells with HeLa levels, implying that HeLa cells can be distinguished from high markers present at or above their levels in HeLa cells all healthy tissues profiled in the MicroRNA Atlas report. and HeLa-low markers present at or below their levels in Building the Classifier Circuit HeLa cells. The exemplary HeLa cell classifier described herein uses Selection of microRNA Markers for Use with HeLa Cell two sensors for HeLa-high inputs miR-21 and a combination Classifier Circuit of miR-17 and 30a, and three sensors for HeLa-low inputs Construction of a circuit involves, in part: (a) determina miR-141, 142(3p) and 146a. The sensors for HeLa-low tion of a reference profile; (b) construction, testing and 25 markers are implemented by fusing four tandem repeats (5) optimization of sensors for individual markers of the profile; of the corresponding target sites directly into the 3'-UTR of (c) assembly and fine-tuning of an integrated logic network; the output driven by a constitutive promoter (FIGS. 2A and and (d) fine-tuning an output response and actuation. 2B). Accordingly, as described herein, we first set out to deter The construction of 'double-inversion sensor modules mine whether there exists a small set of markers expessed at 30 for HeLa-high markers was much more elaborate. A mini high and low levels that can be used to distinguish HeLa mal module comprises a microRNA-targeted transcriptional cancer cell line from healthy cells and tissues (but not repressor and an output-driving promoter efficiently con necessarily other cancer cell lines) (37.38) using the micro trolled by this repressor. We explored this arrangement using RNA Atlas database (39). siRNA-targeted transcriptional repressor LacI in combina We first focused on HeLa-high markers first and found 35 tion with LacI-controlled promoter CAGop (29) (chimeric two promising candidates: miR21 and a compound marker promoter CAG (40) harboring two Lac operator binding that adds the expression levels of miR-17 and miR-30a sites) and measured ON:OFF ratios of -2-4 fold. These (miR17-30a). Our analysis Suggested that a properly-tuned proved insufficient for our purposes. We incorporated circuit that uses these two markers should provide a sub reverse tetracycline-controlled transactivator (rtTA) to regu stantial, five-fold difference between the output level in 40 late LacI expression in the presence of doxycycline to form HeLa cells and the output levels in all but a few other healthy a coherent type 2 feed-forward motif (41, 42) (FIG. 2C). cell types. We then analyzed markers highly expressed in Both rtTA and LacI mRNAs are fused with microRNA potentially misclassified cell types and unexpressed in HeLa targets for the HeLa-high markers. In the absence of the and converged on the set comprising miR-141, miR-142(3p) HeLA-high microRNA markers, constitutively expressed and miR-146a. These markers are also expressed at high 45 rtTA induces LacI via the PTA-controlled tetracycline levels in many other healthy cell types, contributing to the responsive element promoter (pTRE), LacI in turn represses overall circuit robustness (36). This collection of markers the output. Highly-expressed microRNA reduces the level of results in a unique HeLa reference profile of “HelLa-high PTA, greatly weakening LacI expression, and also targets markers: miR-21, miR-17-30a; and HeLa-low markers: LacI directly reducing its level even further and relieving miR-141, miR-142(3p), miR-146a'. This profile corre 50 repression of the CAGop-driven output (FIG. 2D). This sponds to a high level circuit wiring diagram shown in FIG. sensor optimization resulted in an ON:OFF ratio of -8-10 1B and the following abstract logic: miR-21 AND miR-17 fold in both double-inversion modules (FIG. 9). 30a AND NOT(miR-141) AND NOT(miR-142(3p)) AND Next, we proceeded to construct, test and optimize the NOT(miR-146a) complete HeLa cell classifier circuit (FIG. 2E). The con According to our computational analysis, a classifier 55 struction amounts to incorporating all HeLa-low sensors in circuit based on this profile generates at least a 7-fold output tandem in the output 3'-UTR, placing the output gene under increase in HeLa cells relative to the closest other cell type LacI-controlled promoter CAGop, and adding the genes USSC-7d (unrestricted somatic stem cells cultured for 7 encoding HeLa-high marker sensors. After circuit construc days), and on average about 350-fold increase relative to the tion, we first assayed for correct logic operation of the rest of the cells. This analysis takes into account the analog 60 classifier in response to all possible combinations of ON intermediate input values observed in all cell types consid (i.e., Saturating) and OFF (i.e., near-Zero) input values. ered. The separation of the classifier output in HeLa com We used the DsRed-Express red fluorescent protein pared to all other cells can be optimized further with (DsRed for short) as output and analyzed whether it is additional sensor fine-tuning (FIG. 8G). generated only when levels of miR-21 and the added levels Following the bioinformatics analysis, we assayed how 65 of miR-17 and 30a are at or above their levels in HeLa cells, well the chosen markers knock down reporter expression in AND levels of miRs 141, 142(3p) and 146a are below HeLa cells as well as in human embryonic kidney 293 cell detection threshold. With five inputs, this assay requires US 9,458,509 B2 143 144 2–32 different input combinations. Ideally one would need regulated by the classifier to cell death under constitutive 32 different cell lines each expressing a unique combination hBax, we observe roughly 92% HeLa cells killing efficiency of the input microRNAs with each input being either low or and 14% undesired HEK293 cell death (FIG. 5E). above saturation. Since such collection of cell lines is hardly An important measure of circuit performance is specific feasible, we used a different but equivalent approach. Spe ity and selectivity when operating in heterogeneous cell cifically, we performed all experiments in HeLa cells with populations. To enable quantification of different cell lines in their high expression of miR-21 and miR-17-30a and neg a mixture, we stably integrated a Cerulean fluorescent ligible expression of miR-141, 142(3p) and 146a. The 32 marker in HEK293 cells (HEK293-Cerulean), that is input combinations were generated in HeLa cells by mutat adequate for separating between HeLa and HEK293 cells ing target sites for HeLa-high markers to emulate artificial 10 using the Cerulean fluorescence channel (FIG. 12). Next, we low levels, and transfecting microRNA mimics of HeLa-low transfected co-cultured HEK293-Cerulean and HeLa cells markers to emulate high levels (FIG. 3A). with various circuits expressing DsRed output (FIG. 6A). In The results demonstrating correct operation of the circuit a control experiment where we transfected constitutively under all 32 conditions are shown in FIG. 3B. We detected expressed Dsked, HEK923 and HeLa cells contribute to the undesirably high output levels in the three cases where one 15 DsRed" population in roughly equal proportions. When we of the HeLa-high markers was set to OFF and microRNA transfect the mixture with the classifier circuit, the Dsked" mimics for the HeLa-low markers were absent. In order to population consists predominantly of HeLa cells as further reduce the insufficiently-low OFF levels in cases expected. Repression of the output by mutant double when only one of the two sensors for HeLa-high markers is inversion modules that are insensitive to HeLa-high micro triggered (43. 44) and combined transcriptional repression RNA markers results in substantial but not full reduction in by LacI with posttranscriptional repression by engineered the numbers of DSRed cells from both HeLa and HEK293 intronic microRNA (FIG. 4). Using this approach, we origin, representing a baseline for mis-identifying cells due observed a modest reduction in the ON state that was more to leaky expression under maximal output repression. The than compensated for by a significantly-improved OFF state, classifier circuits selectivity can be approximated by its increasing the ON: OFF ratio of the classifier circuit from 25 ability to induce Dsked above this leaky expression. -5-8 fold to -11-30 fold (FIG. 10). The output reduction in To test selective induction of HeLa cell death in a cell the ON state could occur because of additional output mixture, CAG-driven Dsked was co-transfected with the repression by residual intronic microRNA. apoptosis-inducing classifier circuit to co-cultured HEK293 We then constructed a new multi-input classifier circuit Cerulean and HeLa-EYFP cells (FIG. 6B). In one control that uses the above optimized sensors for HeLa-high mark 30 experiment without hBax, the DsRed" population comprises ers and analyzed how well it distinguishes between HeLa of roughly the same number of HeLa-EYFP and HEK293 cells and the cell lines HEK293 and MCF7. The results show Cerulean cells. In a second control experiment, constitutive that the optimized circuit indeed generates a strong fluores expression of hBax results in significant reduction in both cent signal in HeLa cells but not in HEK293 and MCF7 numbers. In comparison, the classifier circuit with hEBax cells, and that the differences are due to classifier circuit 35 results in significant apoptosis of HeLa-EYFP cells but not operation rather than differential promoter activity (FIGS. of HEK293-Cerulean cells. While the results confirm that 5A and 5B). As additional evidence that the circuit operates programmed apoptosis operates correctly in the cell mixture, consistently with our design, we constructed partial net the observed degree of false-positive cell death as well as works that only respond to a subset of microRNA markers false-negative cell Survival warrants continuing circuit and and observed that they behave as expected. These results 40 DNA delivery optimization, e.g., using lentiviruses. also show that two markers (miR-21 and miR-141) are The examples described herein demonstrate engineered sufficient for distinguishing between our three cell lines, yet synthetic biological networks that diagnose complex intra the full set of markers has much better properties when cellular conditions and execute programmed biological expanding the assays to larger cell collections. actuation by sensing and computing with multiple endog Next, we tested whether a multi-input classifier circuit can 45 enous signals. In other embodiments, the classifier circuits selectively trigger useful biological actuation, such as induc can incorporate components and features to eliminate false tion of apoptosis by human Bcl-2-associated X protein hEBax positives and false-negatives, increase the efficiency of (45). Programmed apoptotic actuation was tested in HeLa programmed apoptosis, and ensure uniform operation of the and HEK293 but not in MCF7 cells that proved resistant to circuit in noisy environments across different cell lines and hBax using our cell killing protocol. To quantify circuit 50 tissue types. The circuit design framework itself can be induced cell death, constitutively-expressed AmCyan fluo expanded, in some embodiments, by developing sensors for rescent protein driven by CAG promoter and the apoptosis non-microRNA markers, such as transcription factors, Scal inducing classifier circuit (FIG. 2F) were co-transfected into ing-up the computation to implement a "cocktail” approach cells. We reasoned that after an amount of time sufficient for to address heterogeneous cancer populations (FIG. 13), and circuit operation elapsed, the fraction of cells expressing the 55 by including additional controls for actuation timing and AmCyan in this experiment would range between the frac intensity. tion of AmCyan" cells measured in a separate experiment Apart from the technological advances, our experience using a circuit without hBax (indicating no apoptosis), and with the synthetic constructs developed here sheds light on Zero in the case of fully-efficient apoptosis. As shown in a number of important basic questions pertaining to biologi FIGS. 5C and 5D, in a control experiment constitutively 60 cal regulation in general and RNAi in particular. Recent expressed hBax reduces the number of AmCyan" cells to research has uncovered microRNA regulation complexities ~25% (HeLa) and -23% (HEK293) of the number measured that include fan-out control of multiple genes by the same in the absence of hBax 4 days post-transfection. The apop microRNA, fan-in control of a gene by multiple microRNAs tosis-inducing classifier circuit inflicts almost the same (46), and complex feedback and feed-forward interactions degree of cell death in HeLa cells but causes little cell death 65 between microRNA and transcription factors (47). MicroR in HEK293 cells, indicating highly-selective actuation NAS were also identified as key players in complex regu (FIGS. 5C and 5D). Based on comparison of cell death when latory networks (48, 49) and as stabilizing regulators of cell US 9,458,509 B2 145 146 fate (50). Our circuits implement such regulatory modalities cloning frequencies are shown below, indicating the desired in a synthetic context, confirming by construction that inverse relationship between those frequencies and DsRed microRNA can be integrated with transcriptional regulation reporter levels. in a complex fashion. Furthermore, because of the synthetic FIG. 2 depicts the schematics of a classifier circuit. FIG. construction and orthogonality of Some of the circuit mod 2A shows an abstract network diagram for sensing HeLa ules, we were able to quantify the individual contribution of low microRNA, whereby an output is directly targeted for various components and the interplay of transcriptional and degradation by the marker. FIG. 2B depicts a detailed circuit posttranscriptional regulation in complex regulatory diagram for sensing HeLa-low markers. Output mRNA is schemes. In some aspects, our systems and circuits can also knocked down by a corresponding marker via a target be used to guide further basic biological inquiry. For 10 sequence fused in this mRNA 3’-UTR. DNA and RNA example, while it is possible to engineer highly-efficient species are indicated. FIG. 2C shows a coherent type 2 repression by microRNA, such efficiency is not normally feed-forward motif for sensing HeLa-high microRNAs that observed in mammalian cells (51). Our data that show enables output expression by down-regulating a repressor residual repression activity of microRNA-targeted LacI 15 (i.e., double-inversion module). The microRNA effect was (FIG. 3 and FIG. 9) suggest that even highly-efficient amplified by targeting a repressor R and an auxiliary acti microRNA triggered knock-down can be insufficient and vator Act that regulates repressor expression. FIG. 2D inferior to transcriptional regulation, explaining the above depicts a detailed circuit diagram for a HeLa-high marker observation. Thus, in Some aspects and embodiments near sensor. DNA and RNA species are lumped together, with perfect knock-down can be achieved by hybrid regulatory transcriptional regulation occurring at the DNA level and networks that amplify the microRNA effect, as with our posttranscriptional regulation by microRNAS occurring at sensors for HeLa-high markers. The figures are described in the mRNA level, respectively. The genes, their promoters more detail below. and microRNA targets used in module construction are FIG. 1 shows a schematic operation of a cell type clas indicated. FIG. 2E depicts a representative schematic of a sifier. FIG. 1A shows multi-input logic used to selectively 25 complete classifier circuit. For simplicity, four adjacent identify a specific cell type. Three hypothetical microRNA microRNA target sites are shown as a wider box and DNA markers A, B and C are expressed at different levels in and RNA species are lumped together as in FIG. 2D. Two different cell types. Only cells with high expression of double inversion modules for HeLa high markers are shown markers A and B and low expression of C represent a and rtTA crosstalk is indicated with dotted lines. Sensors for specific type of cancer, i.e., when the logic formula A AND 30 HeLa-low markers are fused in tandem into the 3'-UTR of B AND NOT(C) is satisfied. FIG. 1B depicts a schematic the output gene. The logic computed by this classifier circuit representation of a HeLa-specific classifier circuit. Synthetic is shown. FIG. 2F depicts how, in some embodiments, the transcriptional/posttranscriptional regulatory circuits (rect circuit of FIG. 2E can be modified to result in apoptotic angles) were created that implement logic integration of output production. For example, DSRed output is replaced multiple microRNA markers and programmed actuation. 35 with a gene for hBax protein, and LacI protein in the These circuits are delivered into heterogeneous populations double-inversion modules is co-translated with an hEBax of cells comprising both healthy and HeLa cells. The circuit inhibitor bcl2 using a 2A linker (only one LacI construct is operates separately in each cell and determines whether the shown). hEax and bc12 are in some embodiments counter cell is HeLa based on a HeLa-specific microRNA expression regulated by the circuit such that residual hBax in the OFF profile. If the profiles match, the cell is targeted for apop 40 state is inhibited by highly-expressed bc12, implementing an tosis. Otherwise, the cell is classified as healthy and is not additional safety mechanism. affected. The circuit senses the levels of six endogenous FIG.3 depicts extensive validation of a classifier circuits input microRNAS and combines transcriptional and post logic operation. FIG. 3A shows that four versions of the transcriptional regulation to control output protein expres circuit with specific microRNA regulatory links interrupted sion (e.g., hBax) based on those levels. Both miR-21 and the 45 (denoted by stars) can be used to emulate the various sum of miR-17 and 30a concentrations (miR-17-30a) must combinations of microRNA input levels. Specifically, in be present at high levels and markers miR-141, 142(3p) and order to emulate low miR-21 and miR-17-30a levels, the 146a must not be present for high hBax protein expression. target sites for both those markers were eliminated from the Lines with bars indicate down-regulation. R1 and R2 rep circuit, resulting in a modified configuration denoted as resent intermediate circuit elements needed to invert micro 50 T17-30a (-) T21 (-). Target elimination disrupts RNAi even RNA activity. The entire network implements a multi-input with highly-expressed markers, and therefore is equivalent AND logic function (where all inputs must be present at to including the correct targets in the circuit but with their prescribed levels simultaneously) for identification and markers not expressed. The other three base cases for selective killing of HeLa cells. FIG. 1C shows experimental HeLa-high markers are also shown, indicating which links confirmation of various reporter construct knock-downs by 55 were interrupted in the circuit variants. To measure the corresponding microRNA markers identified by our bioin operation of each of the above variants under high levels of formatics analysis in HeLa, HEK293, and MCF7 cell lines. miRs 141, 142(3p) and/or 146a, commercial microRNA Transiently-transfected bidirectional constructs include mimics were transfected into HeLa cells as appropriate. FIG. DsRed reporter with fused microRNA targets (four tandem 3B shows output values measured for all 32 input combi repeats of the same target fully complementary to the 60 nations (Tables 53 and 54 describe the constructs and corresponding mature microRNA sequences), and an inter experimental conditions). Dsked fluorescent protein is the nal reference reporter AmCyan. Scatter plots show flow output and AmCyan protein serves as a transfection marker. cytometry data measured at 48 hours post-transfection. FIG. The images are overlays of DsRed and AmCyan channels 1D depicts the overall knock-down efficiency by the micro taken ~48 h posttransfection. The bar charts show meaniSD RNA biomarkers in different cell lines (top). The bars show 65 of normalized Dsked intensity obtained from three indepen meant-SD of Dsked/AmCyan values from three indepen dent replicates measured by fluorescence-activated cell sort dent replicates. The corresponding published microRNA ing (FACS) ~48 h post-transfection. US 9,458,509 B2 147 148 FIG. 4 depicts an optimized sensor configuration for of DsRed" cells either transfected with the circuit or with HeLa-high markers. rtTA activates expression of a LacI constitutively-repressed output, relative to the constitutively miR-FF4 pre-mRNA that is spliced to produce LacI mRNA expressed output for each cell type. The classifier circuit further translated into LacI repressor, and miR-FF4 micro used here is able to identify most transfected HeLa cells in RNA that target the output transcriptionally and posttran- 5 the mixture, while most transfected HEK293 cells are not Scriptionally, respectively. HeLa-high marker miR-X targets classified as HeLa (especially after normalizing to fully rtTA and LacI mRNA but not the intron-encoded miR-FF4. repressed Dsked transfection). FIG. 6B shows apoptotic Detailed implementation showing individual DNA and RNA assays in a cell mixture. The scheme at the top of the panel species and a proposed mechanism of operation are shown. illustrates experimental set-up and data analysis. The scatter The inset depicts a simplified network diagram of a sensing 10 plots at the bottom show the contributions of the HeLa process. EYFP and HEK293-Cerulean cells to the Dsked" cell popu FIG. 5 shows that a classifier circuit can be used to lation considered to be surviving cells. The bar chart shows distinguish and specifically kill HeLa cells. Plasmids encod the fraction of surviving cells either transfected with the ing the circuits and transfection protocols are provided in the circuit or with the constitutively-expressed hEBax, relative to tables. Fluorescent reporter assays are shown in FIGS. 5A 15 the number of DsRed" cells measured without hEBax for each and 5B. FIG. 5A shows schematics of the circuits and cell type. In the cell mixture experiment using a classifier controls. O1, CAGop-driven DsRed with target sites for circuit, the classifier circuit is almost as efficient in killing HeLa-low microRNAs (miRs-HeLa-low). O2, CAGop HeLa cells as constitutive hBax expression, while at the driven DsRed without microRNA target sites. R1, CAGop same time the HEK293 cell population survives transfection driven Dsked constitutively repressed by rtTA-activated 20 by apoptosis-inducing classifier much better than the HeLa LacI and engineered intronic miR-FF4 with HeLa-low tar cell population. gets. R2, similar to R1 but without the HeLa-low targets. C1, Analysis of a Classifier Circuit Operation in an Analog full classifier circuit. C2, circuit variant without HeLa-low Regime and Determination of HeLa-Specific microRNA targets. Experiments with O2 and R2 constructs in HeLa and Profile HEK293 cells do not provide any additional information due 25 In order to determine a HeLa reference profile, expression to the lack of specific RNAi by HeLa-low microRNAs in data from the microRNA Atlas was analyzed (51). We first those cells (FIG. 1D and FIG. 11). FIG. 5B shows experi searched for HeLa-high microRNAs expressed at high mental results from a classifier circuit used to distinguish levels in HeLa cells (so that they can be efficiently detected and kill HeLa cells. In addition to the circuits and controls by the sensors), but not expressed in the majority of other (FIG. 5A) the cells were also transfected with marker 30 tissues (FIG. 7). Of the markers considered, miR-21, miR CAG-AmCyan. The constructs used in each case are indi 30a, let-7fl and miR-17 represented good candidates for cated on the X-axis. Each bar represents the meant-SD of inclusion in the profile due to a combination of both prop DsRed/AmCyan value with three independent replicates erties. We decided to include miR-21 in the profile due to its measured by FACS 48 h post-transfection. All values are exceptionally high expression level based on the cloning normalized to constitutive output level (O1) in HeLa cells. 35 frequency estimates (51). Representative images of the cell culture obtained in these To determine which candidate markers besides miR-21 experiments are overlays of the DsRed and AmCyan chan should be included in the profile, the relationship between nels captured 48 h post-transfection. The constructs used are increasing HeLa-high microRNA input concentrations and indicated above the images. FIGS. 5C and 5D show apop increasing circuit output needed to be described. This tosis assays in HeLa (5C) and HEK293 (5D) cell lines. The 40 increase is brought about by the corresponding double CAG-AmCyan transfection marker indicates cell survival. inversion sensor module's decreasing capacity to repress AmCyan" fraction, the percentage of AmCyan-positive cells the output. We measured the dose-response curve of this gated using untransfected cells as a reference, was measured module (FIG. 2D, a version without miR-FF4 intron) by 4 days post-transfection by FACS. The percentage of constructing a sensor for an engineered siRNA (siRNA AmCyan" cells in the absence of cell death (No cell death) 45 FF5), transfecting different concentrations of siRNA-FF5 as was measured by co-ransfecting the cells with constitutive a proxy for endogenous microRNA input, and observing the DsRed-expressing control (O1). The number of AmCyan" levels of CAGop-driven DsRed reporter output (FIG. 9A). cells Surviving after maximal induction of hBax was mea In order to incorporate this dose response into our analysis, Sured by co-transfecting an hBax-expressing version of Ol we make two simplifying assumptions about the double (hBax-Tgts). A complete apoptosis-inducing classifier cir- 50 inversion module. First, we approximate output response to cuit (Circuit, FIG. 2F) was co-transfected with the the intracellular concentration of the module's repressor R AmCyan marker to determine cell survival due to selective as a linear decrease up to a point where repression is hBax activation. Each bar in the charts represents the meant-SD of the percentage of AmCyan" cells with three maximal, and by a constant output level at repressor con independent replicates measured by FACS 4 days post 55 centrations above this saturation point (leakage, or OFF transfection. The histograms compare gated AmCyan" level): populations obtained in FACS measurements from pooled replicas after examining equal number of events in the different pools. FIG. 5E shows a comparison of circuit { Ooff, if R is RSAT (1) killing efficiency for two cell lines. 60 Ooff -- (O; - Oort ( 1 (R) if Rs. RSAT FIG. 6 shows fluorescent reporter assays and killing SAT experiments in cell mixtures. Transfection protocols are listed in Table 57. FIG. 6A shows fluorescent reporter where Oi is the unrepressed output level, O is the assays. The scheme on the left illustrates experimental leakage, O(R) is the observed output in the presence of a set-up and data analysis. The histograms on the right show 65 repressor at a concentration R, and Rs is the repressor contribution of the two cell types, HeLa and HEK-Cerulean, saturation concentration (FIG. 8A). Second, we assume that to the Dsked cell population. The inset shows the fraction for a given module the initial repressor concentration used in US 9,458,509 B2 149 150 the circuit is fine-tuned to be close to its saturation point RSAT. Under these two assumptions, we can use the siRNA (1 - Y) + Yek A1. HeLal = 1 - oy (6) input dose response to derive the dose response of the double-inversion module's repressor R to siRNA input A: Yek A1. HeLal = (1 -o)Y ek A1 HeLal = (1-0) ln(1 - a) ln(1 - a) where O is the same as above, i.e., promoter leakage in A --- A ---- A. the absence of siRNA input, Ox is the maximal output measured in the presence of Saturating siRNA input Such 10 where AC. is a general notation for the marker level resulting that OsOi, A is the siRNA input concentration and k is in repression relief of C. (in percent units). This derivation a constant (FIG. 8B). shows that the value of k does not depend on sensor yield. From eq. (1) we deduce how repressor levels depend on Having constructed the dose response function of indi the output levels by deriving an inverse function, under the vidual sensors, we proceeded to construct the response assumption that the repressor in a single module is never 15 function of a composite circuit with two sensors. In one above the saturation point Rs: classifier circuit, two sensor modules converge at the expres sion of transcriptional protein repressor LacI and posttran scriptional microRNA repressor miR-FF4 (whose combina R(O) O; - O (3) tion is denoted as repressor from here on, FIG. 2E and FIG. RSAT TO; - Ooff 4), and generate a combined repressor level in the absence of both HeLa-high markers that is double the amount needed where O is the observed output level and R(O) is the inferred for full repression. A single input marker present at inter repressor level corresponding to this output. mediate levels in non-HeLa cells can reduce the contribution We now substitute eq. (2) into eq. (3) and derive a 25 of its corresponding module to the combined repressor level. dependency of the normalized repressor activity on siRNA but an increase in circuit output will only be observed when levels, which is assumed to apply for microRNA as well: repressor level decreases below the amount needed for full repression, or Rs. There are many combinations of inter mediate marker levels that do not lead to measurable output, R(AI) -O; - Oow -- OON - Ooff ek(A) = a + be kill (4) 30 and there are input combinations that lead to partial increase RSAT O - Oof F O - Ooff in output. In order to estimate composite circuit response to with a = O; - O0 and b = OaPN - OPFF varying input levels, we make a simplifying assumption that O; - Ooff O; - Ooff the double-inversion modules act additively on the output. In practice, our modules are not fully insulated because the A is the siRNA concentration and the rest of the terms have 35 activator component rtTA of each module can also regulate been defined previously. We calculate this curve using the the repressor component of the other module. This causes data measured with siRNA-FF5 and find that a 0.32, b=0.68 each module in a composite circuit to generate more repres and k=-2.84. This siRNA-FF5 sensor exhibits somewhat Sor than would be anticipated were this module operating high output leakage O in the absence of input and fails alone, resulting in more input combinations that do not to fully relieve repression for saturating input. We describe 40 trigger output formation. Hence, the following conservative the ratio between the output observed at sensor saturation analysis underestimates the total repressor levels and over and the maximally-possible output by a parameter we call estimates output levels for any input combination. yield or Y, with Y=O/O. While it is desirable to have In a two-sensor configuration where the sensors for mark both parameters optimized such that O-0 and Y=1. 45 ers A and B have identical yields Y and response parameters reducing the leakage is a top priority because high leakage kA and kB, input combinations that do not trigger output levels will cause mis-classification and mis-actuation by the expression satisfy inequality (7): circuit. We performed extensive tuning of the double-inver sion module and among other things introduced posttran Scriptional repression by engineered intronic microRNA 50 Riot RA+ RB FF4 in order to dramatically reduce this parameter, resulting RSAT RSAT in Os0 (FIGS. 4, 5A and 10). When O-0, the RARa (IAI)(A) +-- ReRR (IB)(B = (1 - Y) + Yek A1 + (1 - Y) + Yek B (P - 1 repressor dependency on the input becomes RSAT

55 ck AIAlekBB - 2 - yl R(AI) O; - Oow + O Yek (A) = (1-Y) + Yek (A (5) RSAT i O; Since Ys 1 and e is a monotonously decreasing func Setting the value of Yaside for a moment, we focus on the tion, more input combinations will not trigger output expres response parameter k which shows how quickly the sensor 60 sion with decreasing Y. In reality Y is strictly less than 1, and responds to changing input levels. We set the value of the by assuming Y=1 we perform a conservative estimation of response parameter by requiring that the repression be those combinations and false positive circuit classification. relieved to a pre-determined extent C. (C.<1), when marker A We estimate the values of the parameter k by requiring that is present at concentrations observed in HeLa cells,A. 99% of the repression be relieved by a marker level in the The resulting repression level would then be 1-CY instead 65 cell type we are interested in classifying, that is, A. Ago of the theoretical limit 1-Y. We solve this equation and and B-Boo in our case. Substituting these values into eq. obtain: (6) gives US 9,458,509 B2 151 152 combination of miR-21 and miR-17-30a are MCF 10 cells, In(1 - 0.99). In(0.01) (8) pancreatic islets and differentiated and undifferentiated A AHeLa A Hela Moins podocytes. ln(1 - 0.99) - ln(0.01) Next we searched for markers highly-expressed in these B F BHeLa Bhela four false-positive cell lines and unexpressed in HeLa cells (FIG. 8F). We found that adding miR-141 as a marker to the profile excludes MCF10 and pancreatic islets from mis We can now estimate the output generated by a classifier classification, and miR-146a excludes differentiated podo for any two input combinations in terms of their 99% cytes. The latter is also modestly expressed in undifferenti concentrations, Substituting eq. (7) into eq. (1): 10 ated podocytes. We reasoned that this marker alone can not be enough to exclude undifferentiated podocytes from mis classification and added another modestly-expressed marker O if k AIAlekBB - 1 (9) miR-142(3p). Marker miR142(3p) is an especially good - : 1-in(0.01)|All A HeLa candidate because it is also highly expressed in more than if ek AIAlekBB - 1 -inco.01)|BI Bhela 15 half of all healthy cell types, increasing the robustness of the molecular profile. This collection of markers results in reference profile that uniquely identifies HeLa cells using A contour plot of this function is shown in FIG. 8D. It shows “HeLa-high markers: miR-21, miR-17-30a; and HeLa-low input combinations where the output levels are low and do markers: miR-141, miR-142(3p), miR-146a, which can be not depend on the inputs, and a general AND-like behavior described by a logic function with high output levels obtained only when both inputs are miR-21 AND miR-17-30a AND NOT(miR-141) AND NOT high. (miR-142(3p)) AND NOT(miR-146a) Using the above function, we evaluated the performance We then analyzed how well this profile classifies HeLa of various HeLa-high marker pairs with respect to their cells. First, we estimated dose response behavior for HeLa selectivity toward HeLa cells. For this we carefully exam 25 low markers. The response function of a sensor directly ined the number of non-HelLa cells that have undesirably incorporated into the output mRNA is described by expo high classifier output levels of at least 20% compared to the nential decay (2): classifier output in HeLa cells. Note that this performance reflects and intermediate circuit architecture with only two sensors for HeLa-high markers. We describe in detail below 30 where O(X) is the output obtained with input concentration how a fully-assembled circuit with more inputs improves X, O, is the original output level and O is the residual this performance significantly. To compute expected output output level at maximal knock-down. With our sensors we levels in different cell lines for different marker pairs, we observed very efficient knock-down and hence assume that first calculate the sensors’ response parameter k for different O. O. Similarly to our treatment of HeLahigh marker candidate markers. We use equation (8) and the markers’ 35 sensors, we require that a HeLa-low marker result in 99% of expression levels in HeLa cells and calculate the following theoretically possible knock-down at levels observed in cell k values: types whose mis-classification should be avoided. If the same marker is used to exclude a number of cell types, its kiR 21-0.399, kiR-30–0.767, kei–0.795 and kir lowest expression among these cells should set the value of 17=1588 40 the response parameter. For example, miR-141 is used to We then solve the equation exclude pancreatic islets and MCF 10, but its cloning fre quency (CF) is 5.7 in the former and 13.3 in the latter. Accordingly, 99% repression should be observed with 5.7% O = 0.2 = (1- e-ka (Al-e-kB (Bl) (10)10 CF; for simplicity we set this value to 5, which results in 45 sensor parameter ek AIAlekBB = 0.8 kiR-141-0.921 Similarly, for miR-146a the threshold is about 3% CF. to estimate combinations of input values that result in 20% Since miR-142(3p) is used mostly as a robustness marker, output activation. These contour lines are overlaid with the 50 we set its 99% knockdown value arbitrarily to 3% CF. observed microRNA levels in different cell types as shown Therefore in FIG. 8E. Cells above this line are likely to generate more than 20% output and cause false-positive classification with kniR-146a kniR-142(3p)l 535 a two-input classifier. The first three diagrams examine With these parameter values for different sensors, we marker pairs miR21/miR-30a, miR-21/let-7fl and miR-21/ 55 proceed to estimate the functional form of the full multi miR-17. Using miR-17 results in a small number of false sensor integration. To assess the improvement of the circuit positive cell classifications, but we reasoned that its low performance due to the HeLa-low marker sensors for miR absolute expression level can require overly challenging 141, miR-142(3p) and miR-146a (denoted C, D and E below sensor optimization. MiR-30a also results in a few false to shorten the notation), we first approximate that the positives, while the use of let-7fl results in too many 60 sensors individual knock-down contributions combine to false-positives. Note, however, that simple arithmetic addi act as a product: tion of markers miR-30a and miR-17 into a single com pound marker (miR-17-30a, kmiR-17-30a=0.516) reduces the number of false-positives compared to using miR-21 with miR-30a alone. This pairing also has the advantage of 65 We combine this dependency with the effect of HeLa-high higher absolute expression in comparison to miR-21/miR17. sensors to obtain the following mapping of the five inputs to The four cell types with high classifier output using a the circuit output: US 9,458,509 B2 153 154 We first tested the response of the sensor to different O if k AIAlekBB 1 (13) amounts of exogenous siRNA (siRNA-FF5) in HEK293 cells. A target for endogenous microRNA miR-21 (T21) is O = (1 -ek All used as a mock target in this experiment because miR-21 is -kB (Bl -cate if k AIAlekBB - 1 undetectable by functional assays in HEK293 cells (FIG. 1). As shown in FIG. 9A, when correct targets are present in where A and B represent miR-2 1 and miR-1 7-30a, respec both rtTA and Lad, the sensor (blue line) shows a robust tively. For our specific classifier circuit we obtain equation response to a wide range of siRNA-FF5 concentrations. The 14: ON:OFF ratio reaches ~5.5 fold by comparing the value in 10 each ON state with varying amounts of siRNA-FF5 to that in the OFF state without siRNA-FF5. However, when siRNA-FF5 target is replaced with T21 to disrupt the repres O if -0.39Ale-0.52B 1 sion of rtTA by siRNA-FF5, the performance of the mutant sensor (orange line) is dramatically reduced. house if -0.39|Al-0.52(B1 - 1 15 Next we calibrated the miR-21 and miR-17-30a sensors in HeLa cells that express both these markers at high levels by varying the amount of LacI with fixed amount of 50 ng rtTA. With this function, we calculate the anticipated output in Adding FF5 sequences does not affect output expression in each cell type based on corresponding marker levels. As HeLa cells (FIGS. 1C and 1D, T-mock) and it is used as a shown in FIG. 8G, the full classifier provides clear separa mock target. The results show that the motif with both rtTA tion between the output in HeLa cells and the rest of the and LacI targeted by a microRNA almost doubles the cells. The HeLa classifier output level is 7-fold higher than ON:OFF ratio of the miR-21 sensor, but only moderately in the closest cell type USSC-7d (unrestricted somatic stem increases the ON: OFF ratio of the miR-17-30a sensor (FIG. cells cultured for 7 days), and on average is about 350-fold 9B) compared to the motif where rtTA knock-down is higher than the rest of the cells. 25 eliminated. This difference might be explained by different We emphasize that the response function is sensitive to knockdown efficiency of rtTA and LacI by miR-21 and parameter values. For example, if we choose the input miR-17-30a, respectively. Based on these results, we deter values resulting in 99% repression relief for the highly mine that the minimum amount of LacI needed for high expressed markers to be twice their level in HeLa cells (as ON:OFF ratio for both sensors is ~50 ng. Next we measured opposed to being exactly those levels), the resulting sepa 30 sensor performance with varying amounts of rtTA (12.5 ration between HeLa and the rest of the cell types improves ng-50 ng) and observed the best ON:OFF ratio with 50 ng dramatically. However, if 99% relief occurs at half the ofrtTA (FIG.9C). We decided to use a combination of 40-50 original values, the significant separation between the cell ng rtTA and 40-50 ng LacI for each sensor in all other types disappears (FIG. 8G, Half thresholds histogram). experiments in this study. This effect is intuitive, because if the sensors respond too 35 Materials and Methods quickly to low input values, in many cell types inputs are Reagents, Enzymes and Small RNAs transduced into full (false-positive) activation of the sensor. Restriction endonucleases, polynucleotide kinase (PNK), Another factor that will affect the response is the total T4 DNA ligase and Klenow DNA polymerase (Klenow in number of double inversion modules, because the excess what follows) were purchased from New England Biolabs. repressor level will grow with their increasing number 40 Shrimp alkaline phosphatase was ordered from Promega. making it increasingly more difficult for the circuit to trigger Pfu Ultra II Fusion HSDNA polymerase (Agilent Technolo mis-classification with intermediate inputs. gies) and dNTPs (Invitrogen) were used in PCR amplifica The operation of the circuit as a reliable system that takes tion. in analog input marker values and produces digital ON: OFF Oligonucleotides were made by Integrated DNA Tech output values for a given set of cell types requires that the 45 nologies. Doxycycline was purchased from Clontech. sensors’ response curves separate effectively between the siRNA-FF5 was designed to target a firefly luciferase gene values observed in the cell type of interest and the values (53), and RNA mimics of the human microRNAs miR-141, observed in most other cell types. In a sense it suggests that miR-142-3p and miR-146a were purchased from Dharma in designing the sensors it is preferable to err on the higher con RNAi Technologies. Silencer Negative Control siRNA side of the parameter values, i.e., make them saturate slower 50 (Ambion) was used as a control that does not target any rather than faster. In our experiments we observed that it is transcript used in this study. generally not trivial to make sensors respond quickly to low Plasmid DNA Constructs for Single-Cell microRNA Profil microRNA levels, and we chose highly-expressed markers 1ng in the first place. Therefore, while we did not explicitly tune When required, equal molar amounts of oligonucleotides the parameter k for the sensors and instead focused on 55 were annealed in 1xRNK buffer by heating to 95° C. and optimizing the end points of the curves to achieve robust gradually cooling down (-1° C. per min) to 37°C., and then ON: OFF ratios, we speculate that out particular sensors are 1 M of annealed product was phosphorylated by 0.5 not overly sensitive, complying with the above conclusion. unit/L PNK in presence of 0.5 mM ATP (Invitrogen). Optimization of Sensors for HeLa-High microRNA Markers All bi-directional constructs were derived from pTRE We implement a coherent type 2 feed-forward motif in the 60 tight-BI (Clontech). p-AmCyan-TRE-DsRed was cloned by sensors for HeLa-high microRNA markers by fusing micro sequentially inserting the AmCyan-containing fragment RNA targets to both PTA activator and PTA-inducible LacI from pAmCyan-C1 (Clontech) using AgeI and BglII, and repressor that in turn represses Dsked output (FIGS. 2C and the DsRed-Express containing fragment from RNAi-Ready 2D). Therefore, in principle, DsRed level remains low in the pSIREN-DNR-DsRed Express template (Clontech) using absence of microRNA marker, while high microRNA level 65 Nhel and NotI into pTRE-tight-B pamCyan-TRE-DsRed2 is expected to relieve the repression and lead to a high level was cloned by sequentially inserting the DSRed-containing of Dsked output. fragment amplified with 5'-TTTGAATTCACCGGTCGC