Engineering mammalian cell-based devices that monitor and therapeutically modulate human physiology is a promising and emerging frontier in clinical synthetic biology. However, realizing this vision will require new technologies enabling engineered circuitry to sense and respond to physiologically relevant cues. No existing technology enables an engineered cell to sense exclusively extracellular ligands, including proteins and pathogens, without relying upon native cellular receptors or signal transduction pathways that may be subject to crosstalk with native cellular components. To address this need, we here report a technology we term a Modular Extracellular Sensor Architecture (MESA). This self-contained receptor and signal transduction platform is maximally orthogonal to native cellular processes and comprises independent, tunable protein modules that enable performance optimization and straightforward engineering of novel MESA that recognize novel ligands. We demonstrate ligand-inducible activation of MESA signaling, optimization of receptor performance using design-based approaches, and generation of MESA biosensors that produce outputs in the form of either transcriptional regulation or transcription-independent reconstitution of enzymatic activity. This systematic, quantitative platform characterization provides a framework for engineering MESA to recognize novel ligands and for integrating these sensors into diverse mammalian synthetic biology applications.
Engineering mammalian cell-based devices that monitor and therapeutically modulate human physiology is a promising and emerging frontier in clinical synthetic biology. However, realizing this vision will require new technologies enabling engineered circuitry to sense and respond to physiologically relevant cues. No existing technology enables an engineered cell to sense exclusively extracellular ligands, including proteins and pathogens, without relying upon native cellular receptors or signal transduction pathways that may be subject to crosstalk with native cellular components. To address this need, we here report a technology we term a Modular Extracellular Sensor Architecture (MESA). This self-contained receptor and signal transduction platform is maximally orthogonal to native cellular processes and comprises independent, tunable protein modules that enable performance optimization and straightforward engineering of novel MESA that recognize novel ligands. We demonstrate ligand-inducible activation of MESA signaling, optimization of receptor performance using design-based approaches, and generation of MESA biosensors that produce outputs in the form of either transcriptional regulation or transcription-independent reconstitution of enzymatic activity. This systematic, quantitative platform characterization provides a framework for engineering MESA to recognize novel ligands and for integrating these sensors into diverse mammaliansynthetic biology applications.
The ability
to engineer mammalian
cellular devices that sense and respond to their environment in defined
ways would enable the construction of sophisticated cell-based therapeutics
and transformative tools for fundamental biological research. Such
capabilities could overcome persistent barriers to treatment in applications
ranging from cancer immunotherapy to regenerative medicine. Synthetic
biology provides such an approach for building novel cellular functions
from the bottom up, and the toolbox of biological parts that operate
in mammalian cells is rapidly expanding. In particular, nucleic acid
and protein-based sensors have been developed to recognize diverse
ligands including small biomolecules such as vitamins[1,2] and metabolites,[3] chemical species such
as acetaldehydes and nitric oxide,[4,5] environmental
conditions such as hypoxia,[6,7] and even defined combinations
of small molecules[8] or RNA.[9] Notably, each of these sensing events occurs in the cytoplasm
of the engineered cell, such that these approaches do not enable cell-based
devices to sense many species of biological relevance, including cytokines,
chemokines, cell-surface antigens, and pathogens, which are exclusively
extracellular. Therefore, engineering cell-based devices that interface
robustly with host physiology necessitates new technologies for engineering
cell-surface biosensors that transduce the detection of exclusively
extracellular ligands into changes in cell state.One approach
to building a biosensor for a given ligand is to modify
an existing biosensor protein to recognize a new input. For example,
directed evolution of G-protein coupled receptors (GPCRs) has generated
receptors with novel specificities (receptors activated by solely
synthetic ligands, or RASSLs) for drug-like small molecules.[10,11] In addition, technologies for genetically engineering novel immune
receptors, termed chimeric antigen receptors (CAR), enable programming
T cells to respond to defined ligands, and this approach has recently
demonstrated great promise for cancer immunotherapy in both preclinical[12−14] and clinical investigations.[15−17] A limitation of all these approaches
is that these novel receptors utilize native downstream signaling
mechanisms to transduce a detection event into a change in cell state.
Therefore, signaling downstream from the engineered receptors may
be subject to cross-talk or regulation by native cellular pathways
and components. Moreover, these sensing events may be transduced into
signaling via complex biophysical mechanisms,[18] precluding the straightforward redirection of receptor output into
engineered gene circuits. Thus, integrating such modified receptors
into complex synthetic biology “programs” will require
new engineering strategies.[19]An
alternative approach for coupling ligand-binding to changes
in cell state is to redirect native receptor sensing and signaling
into orthogonal pathways. Most notably, the Tango assay enables one
to detect a ligand binding-induced protein–protein interaction
by transducing this association into the release of an engineered
transcription factor from an inactive state.[20] In this system, the transcription factor is genetically tethered
to a cell surface receptor protein via an amino acid sequence that
is cleaved by the Tobacco Etch Virus protease (TEV), and TEV is genetically
tethered to an adaptor protein that is recruited to the receptor when
the receptor is in the ligand-bound state. Thus, binding of ligand
to the receptor brings TEV into proximity with its target sequence,
resulting in a trans-cleavage event that liberates the transcription
factor to translocate to the nucleus and regulate expression of an
engineered reporter gene. Other approaches for monitoring native protein–protein
interactions include split protein reconstitution, in which a protein
such as GFP[21] or TEV[22] is genetically split, with N- and C terminal domains fused
to each of two interaction partners, such that association between
the interaction partners enables the split GFP or TEV to refold and
reconstitute its activity. While these approaches do redirect ligand
binding-induced receptor signaling into orthogonal signaling pathways,
they nonetheless rely on native interactions and may interact with
native cellular components. Moreover, receptor redirection requires
existing native receptors and adapter proteins, potentially limiting
the generalizability and portability of this approach. Thus, while
several useful tools for biosensing exist, a general approach for
engineering biosensors for exclusively extracellular ligands represents
an important technology gap in mammaliansynthetic biology.To meet this need, we have developed a technology we term a Modular
Extracellular Sensor Architecture (MESA). Here, we describe the design
and development of the MESA platform, comprising independent, tunable
modules, and the optimization of MESA performance using design-based
approaches. We demonstrate ligand-inducible activation of MESA signaling
and adaptation of the MESA platform to generate either transcription-dependent
or transcription-independent outputs. Through the systematic characterization
of this platform, we provide a quantitative framework that should
streamline the adaptation of the MESA system to recognize novel ligands
and the integration of these sensors into various synthetic biology
functional programs.
Results and Discussion
The MESA
design concept (Figure 1) comprises
a fully self-contained sensing and signal transduction system, such
that binding of ligand to the receptor induces signaling via an orthogonal
mechanism to regulate expression of a target gene. In our initial
MESA design, ligand binding-induced receptor dimerization results
in proteolytic trans-cleavage of the target chain (TC) by the protease
chain (PC), releasing a transcription factor (TF) previously sequestered
at the plasma membrane. Such a transcription factor might be either
a native protein or a protein engineered using zinc-finger[23] or TALE[24] DNA-binding
domains to regulate expression of either native or exogenously introduced
genes. The ectodomain (ECD) confers both specificity and affinity
for a ligand. Potential ectodomain sources include ligand-binding
domains from native receptors, short chain variable fragments (scFv)
derived from monoclonal antibodies, or any other protein(s) that dimerizes
upon ligand binding. Ligand binding may be homotypic in the case of
multivalent ligands (e.g., many cytokines exist as homodimers), such
that the ectodomain on each MESA chain recognizes the same epitope.
Ligand binding may also by heterotypic, such that the ectodomain on
each MESA chain binds to a distinct epitope on a given ligand. The
transmembrane domain (TMD) confers cell surface localization.
Figure 1
Modular extracellular
sensor architecture (MESA) design concept.
Proposed general mechanism: ligand binding-induced receptor dimerization
causes the protease on the protease chain (PC) to cleave its cognate
cleavage sequence on the target chain (TC), which releases the transcription
factor (TF) to travel to the nucleus and modulate target gene expression
by binding to a TF binding domain (TFBD) adjacent to a minimal promoter
(Pmin) to drive expression of the output
gene.
Modular extracellular
sensor architecture (MESA) design concept.
Proposed general mechanism: ligand binding-induced receptor dimerization
causes the protease on the protease chain (PC) to cleave its cognate
cleavage sequence on the target chain (TC), which releases the transcription
factor (TF) to travel to the nucleus and modulate target gene expression
by binding to a TF binding domain (TFBD) adjacent to a minimal promoter
(Pmin) to drive expression of the output
gene.A key feature of MESA design is
the use of modular domains to enable
performance optimization by “tuning” receptor biophysics.
Desirable performance characteristics may include low background in
the absence of ligand, a high signal-to-noise ratio, and a large or
small dynamic range (depending on the application), wherein the magnitude
of MESA output depends on analyte concentration. For example, cleavage
kinetics may be directly modulated by modifying either the protease
(PR) on the PC or the protease’s cognate cleavage sequence
(CS) on the TC. Receptor geometry and steric interactions may be tuned
via both the extracellular scaffold (SCF), located between the ectodomain
and transmembrane domain, or the intracellular linker domain (LD),
located between the transmembrane domain and cleavage sequence. Each
of these experimental handles for protein engineering was systematically
explored to map out MESA design space.
Characterization of MESA
Design Space Using Model Receptors
To initially evaluate
the feasibility of the MESA concept, we developed
a strategy enabling us to decouple the two engineering goals required
to build a functional MESA: (1) achieve ligand binding-induced receptor
dimerization and (2) achieve receptor dimerization-induced signaling.
To pursue the latter goal first and identify intracellular receptor
architectures that confer dimerization-inducible signaling, a small
library of model receptors was constructed in which receptor dimerization
was mediated by interactions between receptor ectodomains and did
not involve any ligands (Figure 2a). For these
model receptors, ectodomains were derived from (a) mCherry, a monomeric
fluorescent protein,[25] (b) CD4, which homodimerizes
with a KD of 1 mM (in solution),[26] or (c) dTomato, a fluorescent protein that is
of comparable size to mCherry but that exists as an obligate homodimer,
such that dTomato dimerization is essentially irreversible.[27] Thus, in this model system, the mCherry MESA
represent monomeric receptors, which only encounter one another transiently
due to diffusion within the cell membrane. Similarly, the CD4MESA
represent receptors that weakly dimerize, and the dTomato MESA represent
receptors that strongly dimerize. Therefore, by comparing the amount
of reporter gene activation conferred by mCherry MESA versus dTomato
MESA having identical intracellular architectures, we can assess the
degree to which that particular intracellular architecture confers
dimerization-dependent signaling. Hereafter, this differential activation
of the reporter gene is described as “fold induction”.
We note that such model receptors should be capable of both heterotypic
(TC-PC) and homotypic (PC-PC or TC-TC) dimerization, such that some
dimers will be nonproductive, but this fact should not impair the
use of these model MESA for comparative analysis of intracellular
architectures.
Figure 2
Evaluation of MESA concept using model
receptors. (a) Schematic
of model MESA based upon mCherry, CD4, and dTomato ectodomains. (b)
Cell-surface and permeabilized (total) expression of 6xHis-tagged
mCherry, 6xHis-tagged dTomato, and CD4 MESA was quantified via immunolabeling
and flow cytometry (see Methods). Shaded region
represents isotype control. (c–e) Reporter activity was measured
for (c) target chains (TC) alone, (d) TC coexpressed with free cytosolic
TEV, and (e) TC coexpressed with protease chains (PC). (f) Reporter
activation by dTomato model MESA including a long (23 amino acid)
flexible extracellular scaffold. (g) Relative expression of model
MESA quantified using BFP-tTA fusion system (cartoon on the right).
Experiments were conducted in biological triplicate, mean fluorescence
intensity (MFI) of YFP was measured for each sample after gating on
transfected cells, measurements were normalized relative to the internal
control, and error bars represent the scaled standard deviation. (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001).
The remainder of this initial MESA system was
constructed as follows. To simplify preliminary design evaluations,
no additional extracellular scaffold (SCF) was inserted. Transmembrane
domains derived from CD28 were utilized to mediate cell surface expression
of MESA, which is an approach used extensively for this purpose in
fusion proteins such as chimeric antigen receptors (CAR).[12−16] Linker domains comprised flexible glycine/serine spacers of various
lengths. The autolysis-resistant tobacco etch virus protease S219
V mutant[28] (hereafter, TEV) and its wild
type cleavage sequence (ENLYFQ/G) were selected as trans-cleavage
partners based upon the specificity of this system and its extensive
use in mammalian cells.[20,22,29] As indicated by a forward slash in the protease cleavage sequence
above, cleavage occurs between glutamine and glycine residues, and
the position following the slash is termed P1′. All constructs
utilized the tet transactivator (tTA) as a constitutively active transcription
factor, such that release of tTA from the plasma membrane induced
expression of YFP from a tTA-responsive reporter construct.[30,31] All characterization experiments to follow included samples in which
tTA was expressed from a plasmid to serve as an internal control that
enables quantitative comparisons between independent experiments,
and this “Free tTA” case does not necessarily represent
maximal reporter gene activation.Evaluation of MESA concept using model
receptors. (a) Schematic
of model MESA based upon mCherry, CD4, and dTomato ectodomains. (b)
Cell-surface and permeabilized (total) expression of 6xHis-tagged
mCherry, 6xHis-tagged dTomato, and CD4MESA was quantified via immunolabeling
and flow cytometry (see Methods). Shaded region
represents isotype control. (c–e) Reporter activity was measured
for (c) target chains (TC) alone, (d) TC coexpressed with free cytosolic
TEV, and (e) TC coexpressed with protease chains (PC). (f) Reporter
activation by dTomato model MESA including a long (23 amino acid)
flexible extracellular scaffold. (g) Relative expression of model
MESA quantified using BFP-tTA fusion system (cartoon on the right).
Experiments were conducted in biological triplicate, mean fluorescence
intensity (MFI) of YFP was measured for each sample after gating on
transfected cells, measurements were normalized relative to the internal
control, and error bars represent the scaled standard deviation. (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001).We first investigated whether MESA constructs were expressed,
localized
to the cell surface, and signaled in a cleavage-dependent fashion.
Each model MESA was expressed in HEK293FT cells by transient transfection,
and cell surface expression of MESA was confirmed by flow cytometry
(Figure 2b). When expressed alone, the target
chains did not induce reporter activation (Figure 2c), but when target chains were coexpressed with free cytosolic
TEV, increased reporter activation was detected (Figure 2d). TEV-dependent reporter activation increased when a 6-amino
acid linker domain (LD) was inserted between the transmembrane and
cleavage sequence domains of the target chain, perhaps due to increased
accessibility of the cleavage sequence to TEV. Together, these data
indicate that TEV-mediated cleavage of the target chain conferred
tTA release, as expected.To investigate how intracellular architecture
and dimerization
state impact MESA signaling, the various target chains and protease
chains were coexpressed (Figure 2e). Overall,
reporter activation was greater when target chains were coexpressed
with protease chains rather than with cytosolic TEV, most likely because
localization of TEV to the plasma membrane (as part of a protease
chain) effectively increased the local concentration of TEV near the
target chains. Similarly, dimerization-dependent reporter activation
was observed only when the linker domain on the target chain was omitted;
dTomato MESA induced significantly more reporter activation than did
mCherry MESA (p ≤ 0.05). We hypothesized that
removing these linkers may geometrically constrain TEV and/or induce
some steric hindrance due to proximity of the cleavage sequence to
the plasma membrane, such that these constraints limit the probability
of trans-cleavage during transient diffusive encounters between receptor
chains but do not preclude trans-cleavage when target and protease
chains dimerize. This hypothesis is supported by the observation that
background decreased and fold induction increased when protein expression
levels were decreased by transfecting lower amounts of the relevant
expression vectors (Supporting Information). Importantly, even when dTomato domains were separated from transmembrane
domains by long (23 amino acid) flexible extracellular scaffolds,
reporter activation was not reduced (Figure 2f). Therefore, induction of MESA signaling requires only receptor
dimerization (i.e., high local concentration of receptor chains),
and the observed signaling is not dependent upon geometric peculiarities
of the model MESA receptors. Moreover, this observation supports our
technology development strategy in which intracellular architectures
exhibiting robust dimerization-dependent signaling in model MESA are
subsequently coupled to various mechanisms for conferring ligand-induced
receptor dimerization.Based upon interchain affinities, CD4MESA were predicted to induce
reporter activation intermediate to that conferred by mCherry and
dTomato constructs, but surprisingly, CD4MESA-mediated reporter activation
was lowest of the three (Figure 2e). To investigate
whether this pattern arose due to differences in MESAexpression levels,
BFP was genetically fused to the C-terminus of tTA on each target
chain, enabling estimation of relative expression levels for each
MESA through measurement of mean fluorescence intensity (MFI) of BFP
using flow cytometry (Figure 2g). This analysis
confirmed that CD4MESAexpression was lower than that of mCherry
and dTomato MESA, and moreover, mCherry MESAexpression was higher
than that of dTomato MESA. This suggests that dimerization-dependent
fold induction would be higher if the MESA were expressed at equal
levels, which is most comparable to the target case of ligand-inducible
MESA signaling. Therefore, this BFP fusion approach was used to account
for differences in MESAexpression levels and “correct”
relative reporter activity in subsequent experiments (where indicated).
MESA Performance Optimization through Design-Based Tuning
Having demonstrated dimerization-dependent signaling, we next sought
to improve performance characteristics (i.e., low background and large
fold induction) by tuning MESA kinetics using a design-based approach.
For example, background signaling is due to trans-cleavage during
transient, diffusive receptor encounters. Thus, we hypothesized that
background could be reduced by decreasing the affinity with which
TEV binds its cleavage sequence (i.e., increasing KM) and/or by reducing the rate at which cleavage occurs
once TEV has bound its cleavage sequence (i.e., decreasing kcat), such that the probability of trans-cleavage
occurring during a transient encounter is reduced. Note that interactions
between MESA ectodomains do not impact KM, which is an intrinsic characteristic of the protease–substrate
interaction. However, these modifications might also decrease total
reporter output or decrease the dynamic range, such that various design
objectives might be coupled. To explore these trade-offs, previously
characterized variations in the P1′ residue of the cleavage
sequence were introduced to “scan through” kinetic space.[32] To decouple the effects of modulating KM or kcat, variants
were selected to individually modulate each parameter relative to
a base case, and two such sets of three variants were constructed
(Figure 3b). Varying kcat generated large differences in both background and dimerization-induced
reporter activation, and these trends were not explained by relatively
small differences in MESAexpression levels (Figure 3a,c). Strong reporter activation was only observed for cleavage
sequences with large kcat. Cleavage sequences
with low kcat had low overall reporter
activation whether TEV bound weakly (large KM) or strongly (small KM) to its
cleavage sequence but resulted in a higher fold induction than those
with high kcat. For sequences with large kcat (those with serine (S), glycine (G), or
alanine (A) in the P1′ position), the sequence with lowest KM (the serine sequence) exhibited highest background.
Thus, stronger binding of TEV to its cleavage sequence may increase
the probability of trans-cleavage during transient encounters by stabilizing
the protease–substrate interaction. As was observed with earlier
constructs, fold induction was higher when accounting for differences
in MESAexpression levels (Figure 3d). Finally,
for all cleavage sequences explored, no dimerization-inducible activity
was observed for MESA containing a 6 amino acid linker (Supporting Information), indicating that the
steric occlusion conferred by removing the linker is required to tune
cleavage kinetics to enable robust dimerization-dependent signaling.
Figure 3
Tuning
MESA cleavage kinetics via cleavage sequence variants. (a)
Reporter activity cleavage sequence P1′ position variants.
(b) KM and kcat reported for selected P1′ variants.[32] (c) Fold induction “corrected” for relative MESA expression
levels. (d) BFP expression levels used to generate corrected metrics
in (c). Refer to Figure 2 for measurement details.
(*p ≤ 0.05, **p ≤
0.01, ***p ≤ 0.001).
Tuning
MESA cleavage kinetics via cleavage sequence variants. (a)
Reporter activity cleavage sequence P1′ position variants.
(b) KM and kcat reported for selected P1′ variants.[32] (c) Fold induction “corrected” for relative MESAexpression
levels. (d) BFPexpression levels used to generate corrected metrics
in (c). Refer to Figure 2 for measurement details.
(*p ≤ 0.05, **p ≤
0.01, ***p ≤ 0.001).This kinetic exploration suggested several strategies for
improving
receptor performance. First, we postulated that a cleavage sequence
with large KM and moderate kcat might both decrease background and increase fold induction.
To test this hypothesis, a cleavage sequence with methionine (M) at
P1′ was utilized (Figure 3b). Fold induction
was improved from 1.9 for the wild type (G) cleavage sequence to 2.4
for M cleavage sequence (Figure 4a). When corrected
for variations in MESAexpression levels, fold induction was 3.0 and
5.8 for the G and M cleavage sequences, respectively (Figure 4b, c). We then hypothesized that further increases
in KM without decreasing kcat could further improve MESA performance. Since none
of the cleavage sequences characterized by Kapust et al. combined
high KM with a moderate or high kcat,[32] a previously
reported truncated TEV (tTEV) variant that increases KM without affecting kcat(28) was investigated (Figure 4a,b). Expression-corrected fold induction increased from 3.0 with
full-length TEV to 3.7 with truncated TEV for the G cleavage sequence,
and from 5.8 to 8.3, respectively, for the M cleavage sequence. Notably,
combining the M cleavage sequence with tTEV resulted in large fold
induction but small total reporter activation, again indicating the
existence of design trade-offs that can be weighed and tuned to suit
a particular application. Having thus identified multiple intracellular
MESA architectures that confer dimerization-dependent signaling in
model receptors, we next investigated whether these findings enable
construction of ligand-inducible receptors.
Figure 4
Design-based optimization
of MESA performance. (a) Evaluation of
methionine (M) cleavage sequence and truncated TEV (tTEV) design variants.
(b) Fold induction “corrected” for relative MESA expression
levels. (c) BFP expression levels used to generate corrected metrics
in panel b. Refer to Figure 2 for measurement
details. (*p ≤ 0.05, **p ≤
0.01, ***p ≤ 0.001).
Design-based optimization
of MESA performance. (a) Evaluation of
methionine (M) cleavage sequence and truncated TEV (tTEV) design variants.
(b) Fold induction “corrected” for relative MESAexpression
levels. (c) BFPexpression levels used to generate corrected metrics
in panel b. Refer to Figure 2 for measurement
details. (*p ≤ 0.05, **p ≤
0.01, ***p ≤ 0.001).
Ligand-Inducible MESA Signaling
To test our hypothesis
that the challenge of achieving ligand-induced dimerization may be
decoupled from the challenge of achieving dimerization-induced signaling,
functional intracellular domains identified using model MESA receptors
were genetically fused to extracellular domains that heterodimerize
in the presence of the small molecule rapamycin: FKBP (FK506-binding
protein of 12 kDa) and FRB (FKBP rapamycin-binding).[33] These rapamycin-binding domains have been used for many
applications including ligand-induced protein splicing[34−36] and regulation of gene expression.[37−39] The two domains do not
interact in the absence of rapamycin, and upon the addition of rapamycin,
a stable tertiary complex forms with Kd ≈ 2.5 nM.[33,40] Two sets of MESA were created,
in which either the FRB or FKBP domain was fused to either the protease
chain or the target chain. All receptors included the G protease cleavage
sequence (TC) or full length TEV (PC), and a two amino acid linker
comprising the extracellular scaffold linking the transmembrane domain
to FRB or FKBP. We chose to initially characterize the rapamycinMESA
receptors using the wild type (G) cleavage sequence in order to achieve
a maximal level of reporter activation to facilitate detection, and
we expected that this choice might come at the expense of high background
signaling.As observed with previous receptors (Figure 2c), no single MESA chain induced reporter activity
(± rapamycin) (Figure 5a). Background
was also very low for complementary pairs of MESA (e.g., FRB on TC
and FKBP on PC or vice versa), and after rapamycin addition, reporter
activation was observed within 10 h and increased over 24 h (Figure 5a,b). The concentration of rapamycin used for this
experiment (100 nM) was selected to be consistent with previous work
using rapamycin-binding domains for protein–protein interactions.[34−36] Reporter activation was highest when the FRB domain was on the TC
(fold induction = 10.2), but the background was lowest when the FRB
domain was on the PC, and therefore, the fold induction was greater
(fold induction = 13.4). Given the high background observed for model
MESA using the G cleavage sequence, the low background observed for
the rapamycin binding constructs was surprising and may be partially
explained by the lower expression of rapamycinMESA chains (Supporting Information). The fold induction upon
ligand addition is likely enhanced by the fact that unlike our model
MESA, the rapamycinMESA heterodimerize rather than homodimerize and
therefore do not form nonproductive dimers. This successful generation
of ligand-inducible MESA confirms that this modular receptor architecture
can be coupled with general systems for achieving ligand-induced dimerization
to generate biosensors for exclusively extracellular ligands.
Figure 5
Ligand binding-inducible
MESA signaling. (a) Measurement of reporter
activation for rapamycin MESA constructs with (dark green) and without
(light green) addition of rapamycin. (b) Fluorescent micrographs illustrating
rapamycin-induced MESA reporter activation over time. Yellow (YFP)
represents reporter activation, and red (DsRedExpress2) is a transfection
control. Refer to Figure 2 for measurement
details and see text for abbreviations. (*p ≤
0.05, **p ≤ 0.01, ***p ≤
0.001).
Ligand binding-inducible
MESA signaling. (a) Measurement of reporter
activation for rapamycinMESA constructs with (dark green) and without
(light green) addition of rapamycin. (b) Fluorescent micrographs illustrating
rapamycin-induced MESA reporter activation over time. Yellow (YFP)
represents reporter activation, and red (DsRedExpress2) is a transfection
control. Refer to Figure 2 for measurement
details and see text for abbreviations. (*p ≤
0.05, **p ≤ 0.01, ***p ≤
0.001).
Although the basic MESA mechanism
(Figure 1) is well-suited to coupling MESA
output to the regulation of genetic
circuits, we next designed MESA receptors in which receptor dimerization
alters cell state via a transcription-independent mechanism: reconstitution
of enzymatic activity. In this system, N- and C-terminal fragments
of TEV were each fused to separate MESA chains, such that ligand binding-induced
dimerization should promote reconstitution of split TEV protease (sTEV),
which can be monitored by cleavage of a third “target”
chain (Figure 6a). Split TEV has been used
to monitor protein–protein interactions,[22] and this concept appears to be generalizable to reconstitution
of many proteins, as similar systems using split GFP,[21,41,42] split luciferase,[43] or split beta-lactamase[44,45] have been developed. Hypothetically, MESA–induced activation
of enzymatic activity could couple biosensing to metabolism, could
enable MESA-mediated control of processes in enucleated cells, or
could rapidly induce physiological processes such as caspase-induced
apoptosis. Thus, reconstitution of sTEV serves as a proof of principle
for a wide range of potential MESA outputs. We also hypothesized that
sTEV-MESA might exhibit low background and improved signal-to-noise,
since diffusive encounters between partial TEV fragments and the target
chain would not result in a cleavage event.
Figure 6
MESA-regulated enzyme
reconstitution. (a) Components and proposed
mechanism for the split TEV (sTEV) MESA system. (b) Cleavage of target
chain variants by cytosolic TEV. (c) Individual split TEV fragments
lack proteolytic activity. (d) Geometric and kinetic analysis of contributors
to sTEV background. (e) Contributions of linker length and cleavage
kinetics to dimerization-inducible sTEV MESA signaling. (f) Effects
of receptor stoichiometry on sTEV MESA performance. For target chain
dilutions, fractions are defined relative to the starting amount of
1 μg of target chain plasmid vector DNA per sample, with empty
vector plasmid used to keep the total amount of DNA transfected constant.
For protease chain dilutions, fractions are again defined relative
to the starting amount (1 μg each of PCN and PCC plasmid vectors), and empty vector plasmid was again used
to keep the total amount of DNA transfected constant. Refer to Figure 2 for measurement details. (*p ≤
0.05, **p ≤ 0.01, ***p ≤
0.001).
MESA-regulated enzyme
reconstitution. (a) Components and proposed
mechanism for the split TEV (sTEV) MESA system. (b) Cleavage of target
chain variants by cytosolic TEV. (c) Individual split TEV fragments
lack proteolytic activity. (d) Geometric and kinetic analysis of contributors
to sTEV background. (e) Contributions of linker length and cleavage
kinetics to dimerization-inducible sTEV MESA signaling. (f) Effects
of receptor stoichiometry on sTEV MESA performance. For target chain
dilutions, fractions are defined relative to the starting amount of
1 μg of target chain plasmid vector DNA per sample, with empty
vector plasmid used to keep the total amount of DNA transfected constant.
For protease chain dilutions, fractions are again defined relative
to the starting amount (1 μg each of PCN and PCC plasmid vectors), and empty vector plasmid was again used
to keep the total amount of DNA transfected constant. Refer to Figure 2 for measurement details. (*p ≤
0.05, **p ≤ 0.01, ***p ≤
0.001).Because the sTEV-MESA utilize
a different mechanism of activation
than do the basic MESA, we performed an independent characterization
of this design space. An initial library of sTEV MESA variants was
generated in which dTomato or mCherry ectodomains again served as
model receptors, and 6 or 12 residue intracellular linker domains
were initially included on each chain because we anticipated that
extra flexibility might be required to allow protease reconstitution.
The TEV protease was split into N- and C-terminal fragments to partition
the enzyme’s active site:[22] amino
acid residues 1–118 (NTEV) on the protease chain with NTEV
(PCN) and residues 119–242 (CTEV) on the protease
chain with CTEV (PCC) (Figure 6a).
A library of target chains was also generated in which mCherry served
as the ectodomain and various linkers and cleavage sequences separated
the transmembrane domain from tTA. None of the target chains induced
reporter activation in the absence of TEV, and since the target chain
with G cleavage sequence and 6 amino acid linker signaled most strongly
when coexpressed with soluble TEV (Figure 6b), this construct was initially selected for evaluating the sTEVMESA concept. This target chain was coexpressed with sTEV PCN or PCC individually, confirming that neither sTEV chain
alone induced detectable cleavage of the target chain (Figure 6c). When the target chain was coexpressed with surface-bound
TEV (sb TEV; a mCherry protease chain from the basic MESA system,
Figure 1, with a zero residue LD), reporter
activation was evident. However, when monomeric mCherry-based PCN and PCC were coexpressed, cleavage of target chains
bearing either the most or least kinetically favorable cleavage sequences
(G and L, respectively) was also observed (Figure 6d). These data indicate that diffusive encounters were sufficient
to reconstitute sTEV in these constructs (which we term, “spontaneous
sTEV reconstitution”). Since Wehr et al. did not observe spontaneous
reconstitution of sTEV in membrane-bound constructs,[22] we hypothesized that this difference could be due to expression
level differences or our inclusion of long (6 or 12 amino acid) unstructured
linkers that facilitate sTEV refolding (Wehr et al. omitted such linkers).To investigate strategies for reducing target chain cleavage due
to spontaneous sTEV reconstitution, a library of sTEV variants was
constructed including linkers of 0 or 6 amino acids, and these were
coexpressed with target chains including G or M cleavage sequences
and linkers of 0 or 6 amino acids. For PCC with 0 linkers,
reporter activity was “de-inducible” upon dimerization
for all target chains (Figure 6e). To explain
this phenomenon, we hypothesized that dTomato-mediated dimerization
of ectodomains may cause the protease chains to dimerize in a conformation
that precludes refolding of sTEV fragments, whereas the freely diffusing
mCherry constructs may have sufficient geometric freedom to permit
reconstitution following diffusive encounter. Receptors with 6 residue
linkers on both PCs exhibited dimerization-independent reporter activation,
potentially due to spontaneous sTEV reconstitution during transient
diffusive encounters. However, when the PCN lacking intracellular
linkers and the PCC with 6 residue linkers were coexpressed
with a target with 0 linkers and the G cleavage sequence, a 2.5 fold
induction upon dimerization was observed. Although it is certainly
possible that fold induction could be further increased by refinement
of this scenario (e.g., by considering target chain linker lengths
between 0 and 6 amino acids), optimization of these constructs was
not the objective of this proof of principle investigation, and we
opted to further characterize this functional architecture.Because each sTEV MESA signaling event requires interaction between
three receptor chains, we investigated how varying the stoichiometry
of sTEV MESA components would impact signaling (Figure 6f). While reducing the quantity of target chain transfected
did not appreciably affect fold induction, reducing the quantity of
both PCN and PCC transfected increased fold
induction from 2.5 to 10.6. Similarly, reducing the amount of either PCN or PCC transfected also
increased fold induction to an intermediate degree. Together, these
data demonstrate that this mechanism for achieving dimerization-dependent
signaling is robust to variations in relative MESAexpression levels,
and fold induction may be optimized by tuning the expression of protease
chains to limit spontaneous sTEV reconstitution. Thus, reconstitution
of enzymatic activity provides an additional modality for coupling
MESA biosensing to regulation of cell state.
Ligand-Inducible Enzyme
Reconstitution
We next investigated
whether the sTEV MESA mechanism could be harnessed to achieve ligand-inducible
enzyme reconstitution. Thus, sTEV MESA chains were constructed in
which the heterodimeric rapamycin binding domains (FRB and FKBP) were
utilized as ectodomains for the protease chains. Based upon results
from model sTEV MESA (Figure 6), we evaluated
PCN with 0 and 6 linkers and PCC with 6 linkers,
since PCC with 0 linkers appeared incompatible with sTEV
reconstitution. A flexible scaffold (2 or 6 amino acids) was also
inserted between transmembrane and rapamycin-binding domains on the
protease chains, because we hypothesized that some flexibility would
be required to enable simultaneous dimerization of rapamycin-binding
domains and reconstitution of sTEV fragments. Since the geometric
constraints governing the mobility of reconstituted sTEV may differ
when protease chain dimerization is mediated by rapamycin-binding
domains vs dTomato domains (used in Figure 5), we investigated target chains including either 0 or 6 amino acid
intracellular linkers and a G cleavage sequence. In control experiments,
rapamycin-sTEV MESA performed similarly to model sTEV MESA—no
signaling was observed when the target chain was expressed alone or
paired with only PCC or PCN (Supporting Information).Ligand-inducible enzyme reconstitution.
Reporter activation was
measured for rapamycinsTEV MESA expressed transiently in cells cultured
without rapamycin (light green) or with rapamycin (dark green). Refer
to Figure 2 for measurement details. (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001).When this small library of potential receptors was functionally
evaluated, several configurations exhibited significant rapamycin-inducible
signaling (Figure 7). The highest fold induction
(7.4) was observed for receptors with 2 extracellular scaffold linkers,
and 6 intracellular linkers on both the PCN (FKBP) and
PCC (FRB). However, no rapamycin-inducible signaling was
observed when these protease chains were expressed with target chains
lacking an intracellular linker (Supporting Information). This suggests that rapamycin-mediated sTEV reconstitution resulted
in protease chain complexes to which the linker-less target chain
was sterically or geometrically inaccessible. Although the number
of design variations considered in this experiment was limited, one
general trend may be that inducible receptor configurations involved
a combination of protease chain linker lengths that somewhat constrained
receptor flexibility and potentially limited spontaneous sTEV reconstitution.
Figure 7
Ligand-inducible enzyme reconstitution.
Reporter activation was
measured for rapamycin sTEV MESA expressed transiently in cells cultured
without rapamycin (light green) or with rapamycin (dark green). Refer
to Figure 2 for measurement details. (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001).
It may well be possible to further optimize receptor performance
by modifying the promising constructs reported here (e.g., by considering
intermediate linker lengths). Importantly, this design space may be
explored by making such rational changes to the initial constructs
characterized here. Overall, this proof of principle experiment demonstrates
that the MESA platform may be adapted to engineer novel ligand-inducible
receptor output modalities.
Conclusions and Future Prospects
The MESA platform
addresses a key technological gap in the mammaliansynthetic biology
toolbox and will enable robust interfacing of engineered cell-based
devices with host physiology. Moreover, this investigation demonstrates
the feasibility of engineering integrated receptors and signal transduction
systems from the ground up using modular components, and this novel
approach may well be extended to engineering biosensor systems in
other cellular contexts, potentially including microbial hosts.Although the initial MESA development described here relied upon
design-based methods, it is certainly possible that these functional
designs may serve as starting points for further optimization using
approaches such as directed evolution or computation-guided protein
engineering. In general, the MESA platform enables design-based receptor
engineering because it is possible to tune specific biophysical parameters
by modifying the sequence of specific receptor domains. In this investigation,
we made use of this property to identify functional receptor designs
via limited trial-and-error searches. In the future, this property
of tunability may be further leveraged to develop predictive design
tools. MESA development was conducted using transient transfection
in order to identify architectures that are likely to signal robustly
in many contexts and over various expression levels. In particular,
our data suggest that stable receptor expression via lentiviral transduction
or stable integration of expression vectors into safe harbors in host
chromosomal DNA should result in both lower background and greater
fold induction (Supporting Information).The quantitative exploration of design space presented here also
provides a framework for readily adapting MESA technology to novel
inputs (ligands), outputs (transcription factors or enzymes), and
applications of interest. For example, MESA output may be amplified
by coupling it to gene circuits such as positive feedback amplifiers.[46] Because MESA signaling is self-contained, it
should also be possible to multiplex MESA receptors (e.g., using multiple
engineered transcription factors as outputs). Coupling multiplexed
receptors to novel or existing logic-based gene circuits[6,8,47] should enable novel capabilities
including multiparametric evaluation of extracellular ligands. MESA
could be used in combination with other sensor-effector systems such
as CAR technologies to increase the safety and efficacy of cell-based
immunotherapy.[19] As mammaliansynthetic
biology plays an increasingly important role in clinical applications,
platform technologies such as MESA are needed to construct complex
and customizable cell-based devices that enable new and effective
therapeutic strategies.
Methods
DNA Constructs
Constructs encoding MESA fusion proteins
were assembled by PCR amplification and standard molecular cloning.
MESA constructs were cloned into the adeno-associated virusexpression
vector plasmid pAAV GFP SN,[48,49] although expression
was achieved by transient transfection (not viral packaging). pDSRedExpress2
was included as a transfection control. Source plasmids for MESA components
included pCL-CTIG (Addgene plasmid 14901),[50] pRK1043 (Addgene plasmid 8835),[28] pBI-MCS-EGFP
(Addgene plasmid 16542),[31] pBSmCD4 (Addgene
plasmid 14613),[51] AAV-FLEX-rev-ChR2-tdtomato
(Addgene plasmid 18917),[52] pEBFP2-Nuc (Addgene
plasmid 14893),[53] YFP-FKBP (Addgene plasmid
20175)[54] and YFP-tagged FRB (YR) (Addgene
plasmid 20148),[54] pmCherry-C1 (Clontech
632524).[27] A complete list of DNA constructs
as well as plasmids and primers used for cloning can be found in Supporting Information.
Cell Culture and Transfection
HEK293FT cells (Life
Technologies) were maintained at 37 °C in 5% CO2 in
growth medium (Dulbecco’s modified growth medium supplemented
with 10% FBS, 1% penicillin–streptomycin, and 4 mM l-glutamine). Transfections were performed in 10 cm plates seeded
with 6 × 106 cells in 10 mL media (for immunochemistry)
or in 24 well plates seeded with 1.5 × 105 cells in
0.5–0.75 mL media (for receptor signaling experiments). Cells
were seeded 8–12 h before transfection by the CaCl2–HEPES-buffered saline (HeBS) method. For rapamycin-induced
signaling experiments, media change occurred 16 h post-transfection
at which time rapamycin (Santa Cruz Biotechnology Inc., 100 nM with
0.5% DMSO, final concentrations) or DMSO (0.5% final concentration)
was added to culture media, and cells were incubated for 24 h before
analysis.
Flow cytometry
Approximately 1 × 104 live cells from each transfected well were analyzed using an LSRII
flow cytometer (BD Bioscience) running FACSDiva software. Cells were
harvested 36 h post-transfection by trypsinization with 0.15 mL trypsin-EDTA
or PBS with 0.5 mM EDTA and resuspended in phosphate buffered saline
(PBS) with 5% bovine serum albumin (BSA) and 0.5 mM EDTA to prevent
formation of aggregates. Data were electronically compensated and
analyzed using FlowJo software (Tree Star). Live single cells were
gated based on scatter, and DsRedExpress2+ cells were gated as “transfected,”
and reporter activity (YFP) was quantified and normalized with respect
to the internal control (reporter plasmid + constitutively expressed
tTA). Example gating is included in Supporting
Information. Samples were collected and analyzed in biological
triplicate, and data points and error bars represent the mean and
standard deviation, respectively, of the mean fluorescent intensity
measured for each biological replicate.
Immunolabeling
Cells transfected with CD4MESA or N-terminal
6xHis-tagged mCherry or dTomato MESA (no reporter plasmid) were harvested
as previously described, fixed in 2% paraformaldehyde in PBS, and
either left intact for surface labeling or permeabilized in PWB buffer
(0.5% saponin, 0.2% BSA in PBS) for whole-cell labeling. Cells transfected
with 6xHis-tagged constructs were incubated with fluorescein isothiocyanate
(FITC)-conjugated rabbit polyclonal antibodies against the 6xHis tag
(ab1206 from Abcam), or a FITC-conjugated rabbit IgG isotype control
(ab37406 from Abcam) to control for nonspecific binding. FITCexpression
was quantified by flow cytometry and analyzed as previously described,
with mCherry or dTomato on MESA chains serving as the transfection
control for gating. CD4 construct-transfected cells were incubated
with phycoerythrin (PE) conjugated rat antimouse CD4 antibodies (#100408
from BioLegend) or PE-conjugated isotype control (#400607 from BioLegend).
Authors: Tom Wehrman; Benjamin Kleaveland; Jeng-Horng Her; Robert F Balint; Helen M Blau Journal: Proc Natl Acad Sci U S A Date: 2002-03-19 Impact factor: 11.205
Authors: Morgan L Maeder; Stacey Thibodeau-Beganny; Jeffry D Sander; Daniel F Voytas; J Keith Joung Journal: Nat Protoc Date: 2009-09-17 Impact factor: 13.491
Authors: Rachel M Hartfield; Kelly A Schwarz; Joseph J Muldoon; Neda Bagheri; Joshua N Leonard Journal: ACS Synth Biol Date: 2017-08-23 Impact factor: 5.110
Authors: Leonard Katz; Yvonne Y Chen; Ramon Gonzalez; Todd C Peterson; Huimin Zhao; Richard H Baltz Journal: J Ind Microbiol Biotechnol Date: 2018-06-18 Impact factor: 3.346