Shiva Razavi1, Steven Su, Takanari Inoue. 1. Department of Biomedical Engineering, §Department of Cell Biology, and ⊥Center for Cell Dynamics, Johns Hopkins University School of Medicine , Baltimore, Maryland 21205, United States.
Abstract
A negating functionality is fundamental to information processing of logic circuits within cells and computers. Aiming to adapt unutilized electronic concepts to the interrogation of signaling circuits in cells, we first took a bottom-up strategy whereby we created protein-based devices that perform negating Boolean logic operations such as NOT, NOR, NAND, and N-IMPLY. These devices function in living cells within a minute by precisely commanding the localization of an activator molecule among three subcellular spaces. We networked these synthetic gates to an endogenous signaling circuit and devised a physiological output. In search of logic functions in signal transduction, we next took a top-down approach and computationally screened 108 signaling pathways to identify commonalities and differences between these biological pathways and electronic circuits. This combination of synthetic and systems approaches will guide us in developing foundations for deconstruction of intricate cell signaling, as well as construction of biomolecular computers.
A negating functionality is fundamental to information processing of logic circuits within cells and computers. Aiming to adapt unutilized electronic concepts to the interrogation of signaling circuits in cells, we first took a bottom-up strategy whereby we created protein-based devices that perform negating Boolean logic operations such as NOT, NOR, NAND, and N-IMPLY. These devices function in living cells within a minute by precisely commanding the localization of an activator molecule among three subcellular spaces. We networked these synthetic gates to an endogenous signaling circuit and devised a physiological output. In search of logic functions in signal transduction, we next took a top-down approach and computationally screened 108 signaling pathways to identify commonalities and differences between these biological pathways and electronic circuits. This combination of synthetic and systems approaches will guide us in developing foundations for deconstruction of intricate cell signaling, as well as construction of biomolecular computers.
Boolean logic
devices that digitize
and process multiple input signals are central to digital electronics.
These devices function in a binary domain, are activated with higher
specificity than single-input devices, and thus better tolerate environmental
noise.[1−3] Hence, devising biomolecular-based Boolean logic
gates can prove promising in performing robust detection or therapeutic
functions in the inherently noisy cellular environment. This class
of devices also allows for interrogation of biology both on a molecular-
and systems-level. While assembling biomolecular parts in a biological
circuit enables reexamination of our knowledge of an individual component’s
function, deploying these devices in living cells facilitates real-time
manipulation and assessment of cellular events.Transcription-based
Boolean logic gates have been developed and
studied extensively.[4] These devices are
versatile and can be wired to each other to generate complex functions.[5−9] However, they often take hours to days to become active as the transcription
machinery dictates the speed of transcriptional-based logic operators.[3] Furthermore, one class of Boolean devices (e.g., NOT, NAND, NOR, etc.) executes negation
using an inhibitory module, such as a repressor that requires an added
layer of regulation, leading to design complexity and increased chance
of crosstalk with the endogenous molecules. Moreover, the readouts
of such devices are primarily fluorescence intensity, an output that
is not physiologically relevant. To achieve faster computation that
is not rate-limited by transcription, logic devices utilizing the
post-translational repertoire of biomolecules have been engineered.[3,10] For example, the primary Boolean logic functions have been developed
using enzymes.[11−13] Although these enzyme-based devices process the output
on an hour-time scale,[3] they are operational
only . We previously established
a system to introduce the AND and OR logic operators in living cells
to generate protein-based logic devices that are functional within
1 min.[14] However, implementation of more
complex Boolean logic operations incorporating the NOT inverting functionality
(such as NAND and NOR) remained an open challenge.
Results and Discussions
Aiming toward the eventual construction of two-input negating logic
functions in living cells, we first developed a NOT inverter (Figure 1a), an elementary component of the NOR, NAND, and
N-IMPLY logic devices. For fast operation, we coded functionality
in localization of a protein of interest. T-cell lymphoma invasion
and metastasis-inducing protein 1 (Tiam1) is a well characterized
exchange factor for Rac small GTPase[15] and
thus chosen as a proof of principle in this study because it could
later be used as the input to downstream signaling pathways. To rapidly
control localization of Tiam1, we designated three intracellular compartments
as its transient hosts: the plasma membrane (PM), cytoplasm, and mitochondria.
Tiam1 presence at the PM registered a high output,
whereas Tiam1 localization at the cytoplasm or mitochondria drove
the output to a low. To alter the localization state
of the system in a spatiotemporally controlled manner, we relocated
Tiam1 between these compartments using a chemically inducible dimerization
(CID) technique, whereby two protein modules dimerize upon addition
of a chemical dimerizer.[16,17] The CID system we chose
consisted of FKBP (FK506 binding protein) and FRB (FKBP12 rapamycin
binding protein) proteins which readily pair in the presence of rapamycin.[18]
Figure 1
|NOT gate. (a) NOT truth table. (b) Schematic of the protein
constructs
used for NOT logic implementation. For clarity, fluorescent protein
components are omitted from this and subsequent diagrams. YFP-Tiam1-FKBP-C2(LACT)
is at the PM and Tom20-CFP-FRB is mitochondria-bound. (0) and (R)
represent the DMSO and rapamycin (100 nM) inputs, respectively. DMSO
does not change the localization conditions (left panel) Rapamycin
recruits YFP-Tiam1-FKBP-C2(LACT) to the mitochondria and PM ruffles
disappear (right panel). (c) Representative cells showing YFP-Tiam1-FKBP-C2(LACT)
localization at the initial and end time points for the (0) and (R)
input conditions. The scale bars are 10 μm. The image contrasts
have been adjusted to better show relocalization. (d) Translocation
dynamics of YFP-Tiam1-FKBP-C2(LACT) construct in PM upon rapamycin
or DMSO addition. Fluorescence intensity is measured at the PM. Time
zero intercept marks the input addition time point. The gray region
highlights the time interval during which the inputs are present.
Error bars depict standard error of the mean (SEM) for n = 12.
|NOT gate. (a) NOT truth table. (b) Schematic of the protein
constructs
used for NOT logic implementation. For clarity, fluorescent protein
components are omitted from this and subsequent diagrams. YFP-Tiam1-FKBP-C2(LACT)
is at the PM and Tom20-CFP-FRB is mitochondria-bound. (0) and (R)
represent the DMSO and rapamycin (100 nM) inputs, respectively. DMSO
does not change the localization conditions (left panel) Rapamycin
recruits YFP-Tiam1-FKBP-C2(LACT) to the mitochondria and PM ruffles
disappear (right panel). (c) Representative cells showing YFP-Tiam1-FKBP-C2(LACT)
localization at the initial and end time points for the (0) and (R)
input conditions. The scale bars are 10 μm. The image contrasts
have been adjusted to better show relocalization. (d) Translocation
dynamics of YFP-Tiam1-FKBP-C2(LACT) construct in PM upon rapamycin
or DMSO addition. Fluorescence intensity is measured at the PM. Time
zero intercept marks the input addition time point. The gray region
highlights the time interval during which the inputs are present.
Error bars depict standard error of the mean (SEM) for n = 12.For the NOT logic device, we designed
two distinct fusion proteins:
one with yellow fluorescent protein (YFP), actuator (Tiam1), dimerization
(FKBP), and localization (C2 domain from lactadherin or C2(LACT))
protein constituents (termed YFP-Tiam1-FKBP-C2(LACT)) and the other
with cyan fluorescent protein (CFP), dimerization (FRB), and localization
(Tom20) elements (termed Tom20-CFP-FRB). From a design standpoint,
choosing protein localization tags with appropriate affinities for
their respective intracellular compartment was key in implementing
negation. While the C2(LACT) transiently associates with the PM by
binding to phosphatidylserine,[19] Tom20
permanently anchors at the outer leaflet of the mitochondrial membrane[20] (Figure 1b). To monitor
the PM boundary, we expressed the two fusion proteins together with
the mCherry-CAAX protein, a PM marker,[21] in COS-7 fibroblast-like cells (Supporting Information Figure 1a). The localization of YFP-Tiam1-FKBP-C2(LACT) was biased
toward the PM, leading to an initial high output
state. This protein construct remained PM-bound upon addition of the
null input of dimethyl sulfoxide (DMSO). However, adding 100 nM rapamycin
triggered its translocation away from the PM toward the mitochondria
where Tom20-CFP-FRB was expressed (Figure 1c). As a result the high fluorescence output remained
unperturbed for the null input, yet for the rapamycin input, translocation
occurred indicating successful implementation of the NOT device (Figure 1d). The average normalized Tiam1 fluorescence intensity
at the PM was at 100% immediately before rapamycin addition and dropped
to 72% 5 min post-rapamycin addition (Supporting
Information Figure 1b). This change in fluorescence intensity
was statistically significant (p = 1.7 × 10–3) at the first minute post-input addition, and thus,
the NOT device was considered active at this time point (Supporting Information Figure 1c).Using
the NOT inverting device as a basis, we next set out to develop
cascade-free, binary-input negating logic devices, starting with the
NOR function. To retain the fast activation time, we continued to
use the CID platform. As the NOR truth table suggests (Figure 2a), this gate requires a second input that functions
similar to rapamycin but does not interfere with the FKBP-FRB dimerization
process. To this end, we used a second CID system that is functionally
orthogonal to its rapamycin-based counterpart: GID (gibberellin insensitive
dwarf 1) and GAIs (gibberellin insensitive shortened) dimerization
as mediated by a synthetic gibberellin analog, GA3-AM.[14] To grant both CID systems equivalent functionality
in attenuation of the Tiam1 fluorescence signal at the PM, we fused
a single protein module of each CID system to the PM-localized Tiam1
protein (Supporting Information Figure
2a). This amounted to the design of the GAIs-YFP-Tiam1-FKBP-C2(LACT)
construct which we coexpressed with the corresponding CID binding
protein pairs placed in the Tom20-mCherry-GID and Tom20-CFP-FRB mitochondrial
proteins in COS-7 cells (Figure 2b). We first
confirmed the expected localization of each construct (Supporting Information Figure 2b). Addition of
100 nM rapamycin, 10 μM GA3-AM, or a combination
of both inputs successfully initiated the movement of the Tiam1-containing
construct away from the PM toward the mitochondria, a function not
rendered with the null DMSO input (Figure 2c and Supporting Information Figure 2b).
Thus, the Tiam1 PM fluorescence reported by the GAIs-YFP-Tiam1-FKBP-C2(LACT)
remained high only for the null DMSO input as expected
for the NOR logic (Supporting Information Figure 2c). The attenuation of the PM localized fluorescence signal
determined for the rapamycin input case was statistically significant
(p = 1.9 × 10–3) 1 min post-input
addition, indicating minute time scale execution of NOR logic (Supporting Information Figure 2d).
Figure 2
|(a) NOR logic
truth table. (b) Schematic of the localization of
the NOR device protein constituents: GAIs-YFP-Tiam1-FKBP-C2(LACT)
is PM-bound, Tom20-CFP-FRB, and Tom20-mCherry-GID are at mitochondria.
PM fluorescence only exists for the DMSO condition (top left panel).
Addition of rapamycin (100 nM), GA3-AM (10 μM), or both, relocalizes
GAIs-YFP-Tiam1-FKBP-C2(LACT) toward the mitochondria. (c) Translocation
dynamics of GAIs-YFP-Tiam1-FKBP-C2(LACT) at PM upon addition of various
combination of inputs. (d) NAND logic truth table. (e) Schematic of
the localization of the NAND device protein constituents: YFP-Tiam1-FKBP-C2(LACT)
is at the PM, Tom20-mCherry-GID is anchored at the mitochondria, FRB-mCherry-GAIs
is cytosolic. DMSO, Rapamycin (100 nM) and GA3-AM (10 μM) alone
fail to sequester YFP-Tiam1-FKBP-C2(LACT) from the PM, and the PM
fluorescence remains high. Rapamycin and GA3-AM together, result in
the recruitment of YFP-Tiam1-FKBP-C2(LACT)/mCherry-FRB-GAIs complex
to the mitochondria, and the output is driven to a low state. (f)
Translocation dynamics of YFP-Tiam1-FKBP-C2(LACT) construct at the
PM upon addition of the inputs. (g) N-IMPLY logic truth table. (h)
Diagram depicting the location of each protein construct. GAIs-YFP-FKBP-C2(LACT)
expresses at the PM, CFP-FRB-Tiam1 is cytoplasmic, and Tom20-mCherry-GID
is mitochondrial bound. Tiam1 translocation to the PM only takes place
once rapamycin (100 nM) alone is present. Presence of GA3-AM (100
μM) obstructs permanent translocation of the Tiam1 to the PM.
(i) Translocation dynamics of CFP-FRB-Tiam1 at the PM. The binary
inputs are denoted as follows: (0,0) for DMSO, (R,0) for rapamycin,
(0,G) for GA3-AM, (R,G) for rapamycin and GA3-AM, both. Time zero
intercept marks the input addition time point. All error bars depict
SEM for n ≥ 12. The scale bars are 10 μm.
|(a) NOR logic
truth table. (b) Schematic of the localization of
the NOR device protein constituents: GAIs-YFP-Tiam1-FKBP-C2(LACT)
is PM-bound, Tom20-CFP-FRB, and Tom20-mCherry-GID are at mitochondria.
PM fluorescence only exists for the DMSO condition (top left panel).
Addition of rapamycin (100 nM), GA3-AM (10 μM), or both, relocalizes
GAIs-YFP-Tiam1-FKBP-C2(LACT) toward the mitochondria. (c) Translocation
dynamics of GAIs-YFP-Tiam1-FKBP-C2(LACT) at PM upon addition of various
combination of inputs. (d) NAND logic truth table. (e) Schematic of
the localization of the NAND device protein constituents: YFP-Tiam1-FKBP-C2(LACT)
is at the PM, Tom20-mCherry-GID is anchored at the mitochondria, FRB-mCherry-GAIs
is cytosolic. DMSO, Rapamycin (100 nM) and GA3-AM (10 μM) alone
fail to sequester YFP-Tiam1-FKBP-C2(LACT) from the PM, and the PM
fluorescence remains high. Rapamycin and GA3-AM together, result in
the recruitment of YFP-Tiam1-FKBP-C2(LACT)/mCherry-FRB-GAIs complex
to the mitochondria, and the output is driven to a low state. (f)
Translocation dynamics of YFP-Tiam1-FKBP-C2(LACT) construct at the
PM upon addition of the inputs. (g) N-IMPLY logic truth table. (h)
Diagram depicting the location of each protein construct. GAIs-YFP-FKBP-C2(LACT)
expresses at the PM, CFP-FRB-Tiam1 is cytoplasmic, and Tom20-mCherry-GID
is mitochondrial bound. Tiam1 translocation to the PM only takes place
once rapamycin (100 nM) alone is present. Presence of GA3-AM (100
μM) obstructs permanent translocation of the Tiam1 to the PM.
(i) Translocation dynamics of CFP-FRB-Tiam1 at the PM. The binary
inputs are denoted as follows: (0,0) for DMSO, (R,0) for rapamycin,
(0,G) for GA3-AM, (R,G) for rapamycin and GA3-AM, both. Time zero
intercept marks the input addition time point. All error bars depict
SEM for n ≥ 12. The scale bars are 10 μm.We then devised the NAND logic
by continuing to employ the two
orthogonal CID systems. For the NAND operation, Tiam1 had to be initially
restricted to the PM, and only upon the presence of both rapamycin
and GA3-AM inputs could the Tiam1 be mobilized away from
the PM (Figure 2d). This constraint suggested
a two-step process: rapamycin attaching an actuation module to PM-localize
Tiam1, and GA3-AM using this module to deliver Tiam1 to
the mitochondria (Supporting Information Figure 3a). To implement this configuration, we expressed YFP-Tiam1-FKBP-C2(LACT),
FRB-mCherry-GAIs, and Tom20-CFP-GID protein constructs in COS-7 cells
(Figure 2e), each of which localized to the
expected intracellular compartments (Supporting
Information Figure 3b). FRB-mCherry-GAIs moved toward mitochondria
in response to the input conditions containing GA3-AM (Supporting Information Figures 3b and c), thus
keeping the PM-bound Tiam1 unperturbed. Rapamycin, on the other hand,
translocated the FRB-mCherry-GAIs to the PM, leaving the Tiam1 localization
intact. Yet, GA3-AM and rapamycin together, facilitated
the translocation of YFP-Tiam1-FKBP-C2(LACT) away from the PM to the
mitochondria. Consequently, the Tiam1 fluorescence signal at the PM
was turned off exclusively in the presence of both inputs (Figure 2f), indicating successful implementation of the
NAND logic expression (Supporting Information Figure 3d). Furthermore, similar to the NOT and NOR gates the device
activation onset was determined to be within 1 min post-input addition
(Supporting Information Figure 3e).We next aimed to extend our technique to accommodate a negating
Boolean logic operator which required the low rather
than the high output to be initially present: the
N-IMPLY function. Contrary to the NAND and NOR gates, the Tiam1 molecules
had to be initially absent from the PM. Therefore, we placed Tiam1
in the cytoplasmic compartment. As the truth table suggests (Figure 2g), rapamycin had to take Tiam1 to the PM, whereas
GA3-AM had to direct it toward the mitochondria. For the
double-input case, GA3-AM had to offset the effect of rapamycin.
This constraint suggested a competitive functionality of the two CID
systems where the direction of Tiam1 motion was favored toward the
GA3-AM-mediated relocalization pathway (Supporting Information Figure 4a). Consequently, we used the
GAIs-YFP-FKBP-C2(LACT), CFP-FRB-Tiam1, and Tom20-mCh-GID for expression
in COS-7 cells (Figure 2h and Supporting Information Figure 4b). To bias the system toward
the gibberellin-mediated translocation pathway, we used a higher concentration
of GA3-AM (100 μM) as compared to the NAND and NOR
devices, while keeping the rapamycin concentration the same (100 nM).
The CFP-FRB-Tiam1 translocation from the cytoplasm toward the PM occurred
optimally only when rapamycin was present (Figure 2i and Supporting Information Figure
4b and c). The cytoplasmic CFP-FRB-Tiam1 signal was also depressed
for the dual input case as GA3-AM mediated the entrapment
of Tiam1 at the mitochondria. Thus, the high PM Tiam1
fluorescence signal was observed exclusively for the rapamycin-only
input case, indicating execution of N-IMPLY logic (Supporting Information Figure 4d). Tiam1 started moving away
from the cytosolic region within 1 min after rapamycin was added (Supporting Information Figure 4c); however, the
change in fluorescence intensity of Tiam1 at the PM was statistically
significant (p = 8.6 × 10–3) 10 min post-rapamycin addition (Supporting
Information Figure 4e), indicating a slower device activation
time relative to the NOT, NOR, and NAND gates devised. However, this
apparent lag was caused by the different quantification applied here;
the fluorescence change was quantified at the PM instead of the cytosol.After successful implementation of the NOT, NAND, NOR, and N-IMPLY
logic expressions we looked into a physiological output likely generated
through networking of the Tiam1 synthetic logic devices to an endogenous
Rac signaling circuit (Figure 3). Tiam1 localization
at the PM should activate Rac and its downstream signaling circuits
that lead to formation of ruffling and lamellipodia.[22] These membrane structures play a crucial role in cell motility
and phagocytosis.[23] The CAAX PM marker
is an apt choice for tracking and quantifying the ruffling extent[24] since in case of ruffling more membrane accumulates
at the cell boundary and consequently the CAAX fluorescent signal
increases. Thus, using this CAAX membrane marker transfected in cells,
we visualized the membrane ruffles in the cell populations that contained
our negating logic devices. For the NOT gate upon addition of the
null DMSO input we observed no change in the extent of membrane ruffles,
whereas the ruffling activity subsided with the rapamycin input (Figure 4a). This implied that the endogenous Rac circuitry
in the cells executed a YES function, yielding the high ruffling output only when Tiam1 was present at the PM. We furthermore
quantified the ruffling extent by analyzing the cells that met the
criteria for expression level of each protein module (Methods). The average values of PM ruffles 4 min after addition
of DMSO or rapamycin were observed to be 24.4 ± 2.3% and 9.5
± 1.4% of the total PM length, respectively (Figure 4b). The magnitude of these values with respect to
the calculated activation threshold (12.6 ± 1.8%) indicated the
robustness of the synthetic NOT logic gate and its efficacy in activating
the endogenous Rac (Figure 4c). At basal level,
on average, 30% of cells’ circumference ruffled. The synthetic
NOT function drove down this ruffling activity to 5% by the end of
the experiment only for the high input case (Figure 4c and Supporting Information Movie 1). We assessed the change in ruffling activity to be statistically
significant (p = 6.7 × 10–6) (Figure 4d) at 1 min post-input addition,
and thus, we deemed the device active at this time point.
Figure 3
|For the synthetic logic device, chemical dimerizers
serve as the binary inputs, and the Tiam1 localization at the plasma
membrane dictates the output. Cascading the device to the endogenous
Rac generates the second output of plasma membrane ruffles.
Figure 4
|NOT gate. (a) Kymograph illustrating the ruffling
extent of ∼15%
of a representative cell’s circumference. The white scale bar
is 10 μm. The time interval in between each two consecutive
frames is 3 min. The white PM curvatures correspond to the PM ruffling
activity visualized by mCherry-CAAX PM marker. (b) The average PM
ruffling activity reported at the fourth minute post-input addition.
The dashed vertical line marks 12.6% device activation cutoff. (c)
PM ruffling activity over the course of 40 min. Average values of
ruffling activity are denoted as the percentage of the circumference
ruffling. Zero on the horizontal axis marks the input addition time
point. The gray shaded region illustrates the time interval when input
was present. The dashed vertical line crosses the time axis at the
device activation onset. The dashed horizontal line is at 12.6% marking
the cutoff defining the device high or low output. The shaded green region defines the device high output. (0) and (R) stand for DMSO and rapamycin, respectively.
(d) Student t test determining the device activation
time. Assessment of significance of ruffling activity change 1 min
pre- and post-input addition (marked with brackets on panel c). NS
is p = 0.04, and *** denotes p =
6.7 × 10–6. This analysis was done for the
rapamycin input case. All average values are reported using n = 12 cells from three independent experiments. All the
error bars represent the standard error of the mean (SEM).
|For the synthetic logic device, chemical dimerizers
serve as the binary inputs, and the Tiam1 localization at the plasma
membrane dictates the output. Cascading the device to the endogenous
Rac generates the second output of plasma membrane ruffles.|NOT gate. (a) Kymograph illustrating the ruffling
extent of ∼15%
of a representative cell’s circumference. The white scale bar
is 10 μm. The time interval in between each two consecutive
frames is 3 min. The white PM curvatures correspond to the PM ruffling
activity visualized by mCherry-CAAX PM marker. (b) The average PM
ruffling activity reported at the fourth minute post-input addition.
The dashed vertical line marks 12.6% device activation cutoff. (c)
PM ruffling activity over the course of 40 min. Average values of
ruffling activity are denoted as the percentage of the circumference
ruffling. Zero on the horizontal axis marks the input addition time
point. The gray shaded region illustrates the time interval when input
was present. The dashed vertical line crosses the time axis at the
device activation onset. The dashed horizontal line is at 12.6% marking
the cutoff defining the device high or low output. The shaded green region defines the device high output. (0) and (R) stand for DMSO and rapamycin, respectively.
(d) Student t test determining the device activation
time. Assessment of significance of ruffling activity change 1 min
pre- and post-input addition (marked with brackets on panel c). NS
is p = 0.04, and *** denotes p =
6.7 × 10–6. This analysis was done for the
rapamycin input case. All average values are reported using n = 12 cells from three independent experiments. All the
error bars represent the standard error of the mean (SEM).Following the same methodology, we evaluated the
ruffling activity
of the binary input gates. Cells containing the synthetic NOR gates
ruffled only for the null input case as expected for NOR expression
(Figure 5a and Supporting
Information Movie 2). The average ruffling extent for each
combination of inputs relative to the activation cutoff value set
for the NOR device (17.1 ± 2.1% cell circumference) was indicative
of the robust operation of this logic device (Figure 5b). For all the input conditions except the null DMSO input,
the PM ruffling extent diminished from an initial average value of
28% PM length to 5% by the end time point (Figure 5c). The output ruffling activity shows a sharp response with
respect to small changes in Tiam1 concentration. For the (0,G) and
(R,G) inputs, Tiam1 translocation away from the PM was not as efficient
as the (0,R) case (Figure 2c), however it was
sufficient to drive the ruffling output to saturation at a comparably
low value, within a similar time scale (Figure 5c). The NOR device responded to the binary input within 1 min (Figure 5d). The synthetic NAND device also induced formation
of ruffles following a NAND pattern (Figure 5e and Supporting Information Movie 3).
The average ruffling activity per input condition with respect to
the 14.7 ± 1.9% device activation cutoff indicated the successful
operation of the NAND logic device cascaded to Rac as a YES operator
(Figure 5f). The PM ruffling activity fell
below the activation threshold, to a final value of 3%, only in the
presence of both inputs (Figure 5g). The NAND
device activation time also remained within 1 min post-input addition
(Figure 5h). Finally the synthetic N-IMPLY
logic networked to the Rac pathway executed the N-IMPLY pattern of
ruffle formation (Figure 5i and Supporting Information Movie 4). The average
length of circumference ruffling was only above the activation threshold
(8.5 ± 1.4%) for the rapamycin input case (18.3 ± 1.4%),
indicating execution of N-IMPLY logic (Figure 5j). We assessed the onset of ruffling suppression to be within a
minute (Figures 5k and 5l). In the cellular context presented, this N-IMPLY functionality
allows for controlling signaling in a reversible manner given the
two dimerizers are added sequentially instead of simultaneously.[24]
Figure 5
|NOR device. (a) Kymograph illustrating the evolution
of the ruffling
activity of ∼15% circumference of a representative cell over
the course of 40 min. Three minutes lapse between two consecutive
frames. (b) Average value of ruffling extent at the fourth minute
post-input addition. The device activation onset evaluated as 17.1%.,
marked by the dashed line. (c) Dynamics of ruffling activity over
the course of 40 min. The dashed horizontal line depicts the cutoff
(17.1%) evaluated based on the ruffling extent of (R,G) case, 1 min
post-input addition. (d) Determination of the NOR device activation
onset considering the (R,G) condition. (NS is p =
0.011 and *** is p = 3.4 ×
10–5). NAND device. (e) Same as panel a. (f) Average
value of ruffling extent at the fourth minute post-input addition.
The device activation threshold at 14.7%. (g) Dynamics of ruffling
activity over the course of 40 min. The 14.7% activation cutoff was
determined based on the extent of ruffling activity of (R,G) case,
1 min post-input addition. (h) Determination of the NAND device activation
onset considering the (R,G) condition (NS is p =
0.3 and *** is p = 1.3 × 10–4). N-IMPLY device. (i) Kymograph illustrating the
evolution of the ruffling activity of ∼15% circumference of
a representative cell over the course of 30 min. Time elapsed between
two consecutive frames is 2 min. (j) Average value of ruffling extent
at 5 min post-input addition. The dashed vertical line represents
the device activation threshold evaluated as 8.8%. (k) Dynamics of
ruffling activity over the course of 30 min. The 8.8% activation threshold
determined based on the extent of ruffling activity of (R,0) case,
1 min post-input addition. (l) Determination of N-MPLY device activation
onset at 1 min post-input addition considering the (R,0) condition.
(NS is p = 0.09 and * is p = 0.7
× 10–2). Binary inputs are denoted as follows:
(0,0) for DMSO, (R,0) for rapamycin, (0,G) for GA3-AM,
(R,G) for rapamycin and GA3-AM. The white scale bar represents
10 μm. Average values presented are calculated considering more
than 12 cells from three independent experiments. All the error bars
represent SEM. Due to the decaying nature of the ruffling activity
over time, p < 0.01 was considered statistically
significant. The gray shaded region illustrates the time interval
within which input was present. The dashed vertical line represents
the device activation onset. The dashed horizontal line depicts the
cutoff for the device high versus low output.
|NOR device. (a) Kymograph illustrating the evolution
of the ruffling
activity of ∼15% circumference of a representative cell over
the course of 40 min. Three minutes lapse between two consecutive
frames. (b) Average value of ruffling extent at the fourth minute
post-input addition. The device activation onset evaluated as 17.1%.,
marked by the dashed line. (c) Dynamics of ruffling activity over
the course of 40 min. The dashed horizontal line depicts the cutoff
(17.1%) evaluated based on the ruffling extent of (R,G) case, 1 min
post-input addition. (d) Determination of the NOR device activation
onset considering the (R,G) condition. (NS is p =
0.011 and *** is p = 3.4 ×
10–5). NAND device. (e) Same as panel a. (f) Average
value of ruffling extent at the fourth minute post-input addition.
The device activation threshold at 14.7%. (g) Dynamics of ruffling
activity over the course of 40 min. The 14.7% activation cutoff was
determined based on the extent of ruffling activity of (R,G) case,
1 min post-input addition. (h) Determination of the NAND device activation
onset considering the (R,G) condition (NS is p =
0.3 and *** is p = 1.3 × 10–4). N-IMPLY device. (i) Kymograph illustrating the
evolution of the ruffling activity of ∼15% circumference of
a representative cell over the course of 30 min. Time elapsed between
two consecutive frames is 2 min. (j) Average value of ruffling extent
at 5 min post-input addition. The dashed vertical line represents
the device activation threshold evaluated as 8.8%. (k) Dynamics of
ruffling activity over the course of 30 min. The 8.8% activation threshold
determined based on the extent of ruffling activity of (R,0) case,
1 min post-input addition. (l) Determination of N-MPLY device activation
onset at 1 min post-input addition considering the (R,0) condition.
(NS is p = 0.09 and * is p = 0.7
× 10–2). Binary inputs are denoted as follows:
(0,0) for DMSO, (R,0) for rapamycin, (0,G) for GA3-AM,
(R,G) for rapamycin and GA3-AM. The white scale bar represents
10 μm. Average values presented are calculated considering more
than 12 cells from three independent experiments. All the error bars
represent SEM. Due to the decaying nature of the ruffling activity
over time, p < 0.01 was considered statistically
significant. The gray shaded region illustrates the time interval
within which input was present. The dashed vertical line represents
the device activation onset. The dashed horizontal line depicts the
cutoff for the device high versus low output.In our study, the Rac signaling
pathway as a whole served as a
YES gate and enabled us to engage a synthetic device with an endogenous
signaling circuit in order to execute a biologically relevant output.
This prompted us to consider examining signal transduction pathways
as biological circuits’ analogues and screen for logic patterns
in endogenous pathways. Specifically, we counted the number of OR,
AND, NOR, NAND, IMPLY, and N-IMPLY logic topologies that do not emerge
as a result of networking (Supporting Information Methods). Such minimal logic configurations were expected to assume
the topology of a three-nodal motif where the two nodes representing
the inputs either both promote the output node (OR/AND) (Supporting Information Figure 5a and b), both
inhibit the output (NOR/NAND) (Supporting Information Figure 5c and d), or one promotes and the other inhibits the output
(IMPLY/N-IMPLY) (Supporting Information Figure 5e and f). We surveyed the prevalence of these logic patterns
in 108 well-annotated signaling pathways (Supporting
Information Data File 1). We found 775 OR/AND, 26 NOR/NAND,
and 198 IMPLY/N-IMPLY logic patterns. Given the total inhibition and
forward reactions available to cells, the calculated expected value
for each of these logic topologies were 765, 16, and 219, respectively
(Supporting Information Data Files 2 and
3).NOR and NAND logic gate patterns are the most efficacious
in the
electronics context as either of these gates alone can be used to
implement any other logic operations, a property known as universality. This overutilization of a single logic element
in electronics does not seem to be a feature used in cell signaling.
We further screened for the number of NOR/NAND patterns cascaded to
each other (Supporting Information Figure
6). Despite the 26 NOR/NAND hits likely being an overestimation of
the number of actual NOR/NAND gates, we did not find any instance
of universal gates cascading (0 out of 405 logic
gate cascades) (Supporting Information Data
File 2). This further suggests that native cell signaling pathways
do not resort to universal logic functions to navigate their finite
resources. Endogenous inhibitory molecules appear in a hub, and disseminate
their signals downstream through suppression of several activator
molecules rather than directly networking. Perhaps repeated use of
inhibitory signal is more costly than a single use of signal activation.
Arguably, not all the conventions in Boolean algebra, in their strict
sense, apply in nature.Further analysis and experiments are
needed to verify that the
three-nodal patterns identified indeed constitute the corresponding
logic function. However, for cases like the regulation of microtubule
associated protein 1B (MAP1B) by two protein phosphatases (PP1 and
PP2A), the current literature confirms the existence of the NOR logic
function.[25] Because of the limited number
of CID systems at hand our synthetic device can only generate a single
output for probing signaling pathways like Rac. Expanding our system
to a binary output device would allow manipulating these signaling
pathways with two inputs to further investigate the true logic identity
of such endogenous networks.In summary, we created logic devices
with physiological outputs
that functioned within a minute in live cells. These devices could
also control the concentration of a gene product within various subcellular
spaces. We accomplished this design by feeding the output of our synthetic
NOT, NOR, NAND, and N-IMPLY logic devices into the Rac signaling pathway.
These synthetic devices themselves executed negation by orchestrating
Tiam1 movement within cells, without utilizing molecular suppressors
usually used to implement the NOT function. Our design consisted of
a three-state movement landscape, where each state represented a subcellular
space, and imposed a distinct degree of freedom in movement on its
resident molecules (Figure 6). By using CID
systems we induced the movement of the activator molecule in between
the spaces, in the direction of increasing constraint, and thus created
negation. The engineered synthetic devices were used to probe signaling
networks in order to create physiological outputs and understand the
dynamics of cell signaling. In the future studying synthetic negating
logic devices with identical inputs/outputs and varied pathway lengths
will be of interest. Because of their fast speed, the networked pathways
composed of cascaded post-translational universal logic gates will also prove useful in biomolecular computation.
Moreover, generating an oscillatory output signal, or implementing
the exclusive negating family of gates (XNOR) are avenues of research
to be explored in the future. Given the higher specificity inherent
in two-input logic gates to environmental variables, emulating the
same negating functions wired to alternative input and output terminals
is valuable for detection of biological molecules, and potentially
medical diagnosis. Such diagnostic devices can take pathogenic substances
or disease biomarkers as inputs, and yield a fast detect-to-protect
response that is crucial for applications in biowarfare or early disease
detection.
Figure 6
|Schematic of the discrete landscape representing the three levels
of freedom in movement of protein modules which govern the output
of each negating logic device. All the devices are depicted at the
initial time-point, representing the (0,0) input case. Rapamycin facilitates
binding of FKBP- and FRB-fusion proteins whereas GA3-AM
mediates pairing of GAI- and GID-containing protein constructs. The
direction of these translocation movements are toward the compartment
with the lower degree of freedom. Tiam1 presence on the plasma membrane
contributes to the high output readout. The spheres
placed adjacent to each other represent a fusion construct that translocates
as a whole. Mitochondria is the location of maximum stability which
hosts the molecules that are no longer free to move.
|Schematic of the discrete landscape representing the three levels
of freedom in movement of protein modules which govern the output
of each negating logic device. All the devices are depicted at the
initial time-point, representing the (0,0) input case. Rapamycin facilitates
binding of FKBP- and FRB-fusion proteins whereas GA3-AM
mediates pairing of GAI- and GID-containing protein constructs. The
direction of these translocation movements are toward the compartment
with the lower degree of freedom. Tiam1 presence on the plasma membrane
contributes to the high output readout. The spheres
placed adjacent to each other represent a fusion construct that translocates
as a whole. Mitochondria is the location of maximum stability which
hosts the molecules that are no longer free to move.
Methods
DNA Constructs
Molecular cloning of mCherry-CAAX, Tom20-mCh-FRB,
Tom20-CFP-FRB, Tom20-CFP-GID, Tom20-mCh-GID, and CFP-FRB-Tiam1 have
been reported elsewhere.[14,24,26] For construction of GAIs-YFP-FKBP-C2(LACT), the PCR product encoding
C2(LACT) using PCR primers (forward, GAGAATTCATGCGCCAATCCCCTGGGC;
reverse, GCTGGATCCGTACAAGAAAGCTGGGTTCTAACAG)
was inserted into GAIs-YFP-FKBP[14] using
the EcoRI and BamHI sites. For the
construction of GAI(s)-YFP-Tiam1-FKBP-C2(LACT), Tiam1 was digested
out from GID-Tiam1-YFP-CAAX and inserted in GAI(s)-YFP-FKBP-C2(LACT)
using the BsrGI sites. For construction of YFP-Tiam1-FKBP-C2(LACT),
the Tiam1 insert obtained from digestion of GAI(s)-YFP-Tiam1-FKBP-C2(LACT)
was ligated into YFP-FKBP-C2(LACT)[24] using
the BsrGI sites. For construction of FRB-mCherry-GAIs,
GAIs was digested out from CFP-GAIs and inserted into FRB-mCherry
using the EcoRI and BamHI sites.
Cell Culture and Transfection
COS-7 cells were cultured
in DMEM (GIBCO) medium supplemented with 10% FBS and 1% PenicillinStreptomycin (Life Technologies) placed in a 5% CO2 incubator.
Cells were split every 2 days. For transfection, coverglass thinly
coated with 1 mg/mL of poly-d-lysine (Sigma) placed in 6-well
plates were used to plate COS-7 cells mixed with 5 μL Turbofect
(Fermentas) and the transfection mixture. The transfection mixture
contained 1 μL of 1 μg/μL of each DNA construct
defined for each logic gate, mixed with 37.5 μL of Opti-MEM
(Life Technologies).
Live Cell Imaging
The transfected
cells were incubated
(5% CO2, 37 °C) for 24 h prior to imaging. Cells were
imaged in DMEM containing 25 mM HEPES (GIBCO). Live cell imaging was
performed using an inverted epi-fluorescence microscope (Axiovert135TV,
ZEISS) using a 40× oil objective. Fluorescence images were collected
by a QIClick charge-coupled device camera (QImaging). Exposure time
per fluorescence channel was 200 ms, and the images were obtained
at a frequency of 1 frame per minute for 30 to 40 min experiment duration,
depending on the logic device. Rapamycin was obtained from LClab and
GA3-AM was prepared as described previously.[14] Rapamycin and GA3-AM both were dissolved
in DMSO. The zero input case consisted of DMSO alone. All of these
inputs were resuspended in DMEM containing HEPES media before they
were added to the sample chamber.
Image Analysis, Fluorescence
Intensity Measurement, and Ruffling
Quantification
The localization of each protein construct
was verified. The intensity of the fluorescent protein signal in the
localization region of interest relative to the background was measured
using Metamorph software (Molecular Devices). To account for photobleaching
the decay in fluorescence signal 10 min prior to input addition was
measured and the data were corrected considering a linear photo bleaching
trend. The fluorescence signal at each time point was normalized by
the average value of fluorescence signal 10 min before the inputs
were added.For the ruffling analysis, the range of ratios within
which each device executed the logic robustly was measured (the performance
was assessed by quantification of the ruffling activity as described
below). On the basis of this, the rubric for acceptable fluorescence
intensity ranges was determined. For all the experiments only cells
which expressed protein within this ratiometric intensity were analyzed.
To quantify the PM ruffles the Trace Region feature in the toolbar
of Metamorph software was used to measure the circumference of each
cell at the initial time point (denoted as L). The
length of PM ruffles for every other time point was measured (denoted
as R where i indicates the time point). The R/L ratio was used to report the circumference
of cell ruffling for any given time point.
Statistical Analysis
Paired, single-tailed, Student’s t-test
(Microsoft Excel) determining the statistical significance
of ruffling activity change 1 min prior to input addition and 1 min
post-input addition was performed. For the NOT gate, this was done
for the rapamycin input condition. For the NOR gate, this analysis
was done for the (rapamycin, GA3-AM) input condition as
the drop in ruffling activity post-input treatment was the least drastic
for this case, marking the worst-case scenario. For the NAND gate,
this analysis was done on the (rapamycin, GA3-AM) condition
since only for this case we expected and observed a change in ruffling
activity. For the N-IMPLY device, this analysis was done for the (rapamycin,
0) condition as only for this case a change is ruffling activity was
expected and observed. Because of the high exposure time, background
decay in ruffling activity was observed over the course of the experiment.
We mainly defined p < 0.01 as statistically significant.
Authors: John M Lambert; Que T Lambert; Gary W Reuther; Angeliki Malliri; David P Siderovski; John Sondek; John G Collard; Channing J Der Journal: Nat Cell Biol Date: 2002-08 Impact factor: 28.824
Authors: Rok Gaber; Tina Lebar; Andreja Majerle; Branko Šter; Andrej Dobnikar; Mojca Benčina; Roman Jerala Journal: Nat Chem Biol Date: 2014-01-12 Impact factor: 15.040
Authors: Benjamin H Weinberg; Jang Hwan Cho; Yash Agarwal; N T Hang Pham; Leidy D Caraballo; Maciej Walkosz; Charina Ortega; Micaela Trexler; Nathan Tague; Billy Law; William K J Benman; Justin Letendre; Jacob Beal; Wilson W Wong Journal: Nat Commun Date: 2019-10-24 Impact factor: 14.919