Aakash Saha1, Pablo R Arantes1, Rohaine V Hsu1, Yogesh B Narkhede1, Martin Jinek2, Giulia Palermo1,3. 1. Department of Bioengineering, University of California, Riverside, 900 University Avenue, Riverside, California 92521, United States. 2. Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland. 3. Department of Chemistry, University of California, Riverside, 900 University Avenue, Riverside, California 92521, United States.
Abstract
CRISPR-Cas12a is a genome-editing system, recently also harnessed for nucleic acid detection, which is promising for the diagnosis of the SARS-CoV-2 coronavirus through the DETECTR technology. Here, a collective ensemble of multimicrosecond molecular dynamics characterizes the key dynamic determinants allowing nucleic acid processing in CRISPR-Cas12a. We show that DNA binding induces a switch in the conformational dynamics of Cas12a, which results in the activation of the peripheral REC2 and Nuc domains to enable cleavage of nucleic acids. The simulations reveal that large-amplitude motions of the Nuc domain could favor the conformational activation of the system toward DNA cleavages. In this process, the REC lobe plays a critical role. Accordingly, the joint dynamics of REC and Nuc shows the tendency to prime the conformational transition of the DNA target strand toward the catalytic site. Most notably, the highly coupled dynamics of the REC2 region and Nuc domain suggests that REC2 could act as a regulator of the Nuc function, similar to what was observed previously for the HNH domain in the CRISPR-associated nuclease Cas9. These mutual domain dynamics could be critical for the nonspecific binding of DNA and thereby for the underlying mechanistic functioning of the DETECTR technology. Considering that REC is a key determinant in the system's specificity, our findings provide a rational basis for future biophysical studies aimed at characterizing its function in CRISPR-Cas12a. Overall, our outcomes advance our mechanistic understanding of CRISPR-Cas12a and provide grounds for novel engineering efforts to improve genome editing and viral detection.
CRISPR-Cas12a is a genome-editing system, recently also harnessed for nucleic acid detection, which is promising for the diagnosis of the SARS-CoV-2coronavirus through the DETECTR technology. Here, a collective ensemble of multimicrosecond molecular dynamics characterizes the key dynamic determinants allowing nucleic acid processing in CRISPR-Cas12a. We show that DNA binding induces a switch in the conformational dynamics of Cas12a, which results in the activation of the peripheral REC2 and Nuc domains to enable cleavage of nucleic acids. The simulations reveal that large-amplitude motions of the Nuc domain could favor the conformational activation of the system toward DNA cleavages. In this process, the REC lobe plays a critical role. Accordingly, the joint dynamics of REC and Nuc shows the tendency to prime the conformational transition of the DNA target strand toward the catalytic site. Most notably, the highly coupled dynamics of the REC2 region and Nuc domain suggests that REC2 could act as a regulator of the Nuc function, similar to what was observed previously for the HNH domain in the CRISPR-associated nuclease Cas9. These mutual domain dynamics could be critical for the nonspecific binding of DNA and thereby for the underlying mechanistic functioning of the DETECTR technology. Considering that REC is a key determinant in the system's specificity, our findings provide a rational basis for future biophysical studies aimed at characterizing its function in CRISPR-Cas12a. Overall, our outcomes advance our mechanistic understanding of CRISPR-Cas12a and provide grounds for novel engineering efforts to improve genome editing and viral detection.
CRISPR-Cas (clustered
regularly interspaced short palindromic repeats
and CRISPR-associated proteins) is a part of the bacterial immune
system that confers protection against invading viruses. In 2012,
the discovery that the CRISPR-associated protein Cas9 is an RNA-programmable
endonuclease[1] enabled precise manipulation
of nucleic acids, launching an unprecedented genome editing revolution.[2] Recently, a novel CRISPR protein, Cas12a,[3] emerged as a promising tool for innovative applications
of the CRISPR technology, such as nucleic acid detection.[4] The CRISPR-Cas12a system is the basis of the
DETECTR technology,[5] which allows rapid
detection of viruses including SARS-CoV-2, which is spreading across
multiple countries.At the molecular level, the CRISPR-Cas9
and CRISPR-Cas12a systems
confer precise double-stranded DNA (dsDNA) breaks by using CRISPR
RNAs (crRNA) as a guide for molecular recognition of substrate DNA.[2] Thanks to a short protospacer adjacent motif
(PAM) sequence in the viral DNA, these systems can be programmed to
recognize any DNA sequence of interest, therefore enabling genome
editing.[6] Despite sharing functional similarities
with CRISPR-Cas9, Cas12a has a distinct evolutionary history and intriguing
mechanistic properties.[7−9] Structural and biochemical studies of Cas12a have
revealed a bilobed architecture, similar to what was observed in Cas9.
It comprises a recognition (REC) lobe and a nuclease (NUC) lobe connected
by a wedge domain (WED (Figure ).[10−16] The REC lobe includes two α-helical domains (REC1 and REC2),
which mediate nucleic acid binding. The NUC lobe consists of the RuvC
and Nuc domains, flanked by the PAM-interacting (PI) domain, which
binds to the PAM sequence in the DNA. The guide RNA forms a heteroduplex
with one DNA strand (the target strand TS), while the other nontarget
strand (NTS) is accommodated within a cleft formed by the RuvC and
Nuc domains (Figure b,c). Unlike Cas9, which cleaves the TS and NTS using two specific
catalytic domains, HNH and RuvC, respectively, Cas12a performs cleavage
of both the DNA strands using a single active site located within
the RuvC domain.[13] This has raised questions
on the role of the additional Nuc domain, which was initially thought
to cleave the DNA TS, enacting the role of HNH in Cas9.[12] More recent studies have implied that the Nuc
domain instead plays a role in NTS and DNA binding.[13,15,16] However, it is unclear how conformational
changes of the Nuc domain would activate DNA cleavages or facilitate
the exchange of the TS and NTS within the RuvC active site to achieve
a dsDNA break.
Figure 1
Overview of CRISPR-Cas12a. X-ray structures of Cas12a
proteins
in complexes with guide RNA (a) or guide RNA and target DNA (b, c)
across different species, viz. Lachnospiraceae bacterium
Cas12a (LbCas12a),[10]Acidaminococcus
sp. Cas12a (AsCas12a),[11,12] and Francisella
novicida Cas12a (FnCas12a).[13−16] Cas12a proteins are shown in
cartoon format, highlighting individual protein domains in different
colors. The guide RNA (orange), the DNA target strand (TS, cyan),
and the DNA nontarget strand (NTS, violet) are shown as ribbons. The
DNA-bound states include a cleaved NTS (a) and a complete NTS (b).
Overview of CRISPR-Cas12a. X-ray structures of Cas12a
proteins
in complexes with guide RNA (a) or guide RNA and target DNA (b, c)
across different species, viz. Lachnospiraceae bacterium
Cas12a (LbCas12a),[10]Acidaminococcus
sp. Cas12a (AsCas12a),[11,12] and Francisella
novicida Cas12a (FnCas12a).[13−16] Cas12a proteins are shown in
cartoon format, highlighting individual protein domains in different
colors. The guide RNA (orange), the DNA target strand (TS, cyan),
and the DNA nontarget strand (NTS, violet) are shown as ribbons. The
DNA-bound states include a cleaved NTS (a) and a complete NTS (b).Atomic resolution structures have captured Cas12a
bound to guide
RNA alone (for Lachnospiraceae bacterium LbCas12a[10] and Francisella novicida FnCas12a[13]) and guide RNA and a target dsDNA (for Acidaminococcus sp. AsCas12a[12] and FnCas12a,[13]Figure ). For the DNA-bound states, both AsCas12a
and FnCas12a have been determined in complex with a cleaved NTS (Figure b),[12−14,16] while FnCas12a has also been
obtained including a longer NTS that binds within RuvC and reconciles
with the TS (Figure c, hereafter referred to as FnCas12a′).[15] Collectively, these atomic-resolution structures offered
intricate details about the Cas12a ribonucleoprotein complex, suggesting
extensive conformational plasticity. However, it is unclear how this
structural plasticity could contribute to the “open-to-closed”
conformational change of the protein, which is thought to facilitate
substrate DNA binding and subsequent cleavage.[16] In light of these experimental findings, investigating
the protein structural plasticity at the atomic level through Molecular
Dynamics (MD) is critical for understanding its biological functions
and rational engineering of novel Cas12a-based tools for genome editing
and viral nucleic acid detection.Molecular simulations have
previously contributed in the understanding
of fundamental biophysical aspects of the CRISPR-Cas9 system,[17−22] revealing a striking plasticity of the ribonucleoprotein complex.[17−21] These studies provided predictive insights into the dynamic behavior
of Cas9, many of which have been corroborated by single-molecule FRET
experiments[23] and cryoEM,[24] providing also a framework for rational design of Cas9
for improved genome editing.[25,26]Here, we present
a multimicrosecond length MD study of CRISPR-Cas12a,
to characterize conformational plasticity of the protein and its interplay
with the nucleic acids over long time-scales. We collected an overall
ensemble of ∼20 μs, carried out in multiple replicates,
considering different states and across species. The simulations reveal
a “switch” in the conformational dynamics of Cas12a
upon DNA binding that results in the activating motions of the peripheral
REC2 and Nuc domains. In agreement with previous structural[13,14] and single-molecule experiments,[16] this
increased mobility of REC2 and Nuc upon DNA binding could enable the
conformational changes associated with DNA cleavage. The simulations
also reveal an important role of the Nuc domain, whose large-amplitude
motions could enable the conformational activation of the system for
completing DNA cleavages. In this process, the REC lobe is critical
in aiding the conformational dynamics of Nuc. Indeed, highly coupled
dynamical motions of REC2 and Nuc suggest that REC2 could act as a
regulator of the Nuc function, as previously observed for the HNH
domain in CRISPR-Cas9.[19,23−25,27] Considering the key role of the REC lobe for the
specificity of Cas9,[25,28,29] and as recently found in Cas12a,[30] our
outcomes now call for future studies aimed at characterizing the functional
role of REC and Nuc in CRISPR-Cas12a.
Results
Conformational
Flexibility of Cas12a Bound to RNA and DNA
Building on the
available structures of Cas12a (Figure ), we collected ensembles of
μs-length MD simulations. We examined LbCas12a, AsCas12a, and
FnCas12a to assess differences and similarities in the dynamics across
various species and states (i.e., crRNA-bound vs DNA-bound). For each
model system of Cas12a, MD simulations were carried out in explicit
solvent, obtaining multiple μs-length trajectories (i.e., 4
replicates of ∼1 μs each) and reaching an overall sampling
of ∼20 μs. The choice of simulating multiple and independent
μs-length trajectories was motivated by the need to achieve
solid statistics for the purpose of our analysis and by our previous
theoretical investigations of the parent CRISPR-Cas9.[17−19] Those studies had shown that multiple ns-to-μs MD trajectories
are critical for describing the interdependent dynamics of the protein
domains and their interplay with the nucleic acids. Notably, in the
present work, data analysis was performed in analogy to our early
multimicrosecond MD investigations of CRISPR-Cas9.[17] This enabled a fair comparison of the dynamical properties
between the two CRISPR-Cas systems.To develop an initial understanding
of the overall flexibility of the system when bound to RNA and DNA,
we employed root-mean-square fluctuation (RMSF) analysis, which is
a traditional mode of measuring protein flexibility (Figure S1). Additionally, to investigate whether the observed
changes in fluctuations are maintained across the ns-to-μs runs,
we computed a time-dependent RMSF (t-RMSF, Figure a). As a result,
the t-RMSF reveals high fluctuations of the PI domain
in the RNA-bound LbCas12a and FnCas12a (Figure a) complexes, which are conserved along the
simulated runs. Upon DNA binding, the flexibility of the PI region
is remarkably reduced for both AsCas12a and FnCas12a, as stabilized
by the binding of DNA. Simultaneously, the flexibility of REC2 and
Nuc shows a remarkable increase. The change in flexibility of the
PI, REC2, and Nuc domains upon DNA binding is shown in the 3D structure
of FnCas12a, indicating regions of high fluctuations using thicker
tubes (Figure b).
Interestingly, a high flexibility of REC2 and Nuc is preserved in
the FnCas12a′ complex, where a dsDNA locates in between REC2
and Nuc (Figure b,
lower panel). This is notable because the binding of a dsDNA commonly
stabilizes the surrounding protein scaffold, as observed at the level
of the PI domain. On the other hand, the RMSF of the RuvC domain,
which is responsible for both NTS and TS cleavages, reveals low fluctuations
(Figure S1). This is in agreement with
high structural stability of this conserved domain,[31] also observed in MD simulations of CRISPR-Cas9.[17] The remaining protein domains do not show significant
flexibility upon DNA binding. Analysis of the root-mean-square deviation
(RMSD) of the protein Cα atoms reveals that the protein backbone
reaches a similar stability in both RNA- and DNA-bound states (i.e.,
the RMSD reaches ∼4–5 Å, Figure S2). This indicates that upon DNA binding, the overall stability
of the protein is preserved, but the flexibility of different protein
domains changes, as shown by the analysis of the t-RMSF (Figure a).
Figure 2
Cas12a
flexibility along the dynamics. (a) Time-dependent Root
Mean Square Fluctuations (t-RMSF, in Å), computed
for the PI (top), Nuc (center), and REC2 (bottom) domains of the LbCas12a
(Lb.), AsCas12a (As.), and FnCas12a
(Fn.) systems. The RNA-bound and DNA-bound systems
are indicated using black and blue bars, respectively. t-RMSF values are colored from white (low fluctuations) to magenta
(high fluctuations), accordingly to the scale on the bottom right.
(b) The averaged RMSF values are plotted on the 3D structures of the
RNA-bound FnCas12a (top) and DNA-bound FnCas12a′ (bottom),
indicating protein regions of high fluctuations using thicker tubes
(color-coded according to the t-RMSF scale). The
RNA (orange) and the DNA TS (cyan) and NTS (violet) are shown as a
cartoon.
Cas12a
flexibility along the dynamics. (a) Time-dependent Root
Mean Square Fluctuations (t-RMSF, in Å), computed
for the PI (top), Nuc (center), and REC2 (bottom) domains of the LbCas12a
(Lb.), AsCas12a (As.), and FnCas12a
(Fn.) systems. The RNA-bound and DNA-bound systems
are indicated using black and blue bars, respectively. t-RMSF values are colored from white (low fluctuations) to magenta
(high fluctuations), accordingly to the scale on the bottom right.
(b) The averaged RMSF values are plotted on the 3D structures of the
RNA-bound FnCas12a (top) and DNA-bound FnCas12a′ (bottom),
indicating protein regions of high fluctuations using thicker tubes
(color-coded according to the t-RMSF scale). The
RNA (orange) and the DNA TS (cyan) and NTS (violet) are shown as a
cartoon.
Large-Amplitude Motions
and Conformational Ensemble
Aiming to dissect the large-scale
collective motions of the Cas12a-nucleic
acid complexes and characterize its essential degrees of freedom,
we performed Principal Component Analysis (PCA). With this analysis,
the “essential dynamics”[32] of the system is described along the first principal mode of motion
(i.e., principal component 1, PC1), providing information on the large-amplitude
motions of the complexes and, in turn, on their functional dynamics.
PCA has been performed considering all the FnCas12a systems (i.e.,
the RNA-bound FnCas12a, DNA-bound FnCas12a, and FnCas12a′).
In detail, we combined the collected ensembles arising from the compared
systems and subjected to RMS-fit to the same reference configuration,
ensuring consistency of the eigenbasis and motions of the PCs (details
are reported in the Methods section).In Figure a, PC1
is plotted over the 3D structures of FnCas12a in the RNA- and DNA-bound
states, where the arrows indicate the direction and relative amplitude
of motions. In the RNA-bound state, the PI domain displays large-amplitude
motions, which are directed toward the cleft that accommodates the
PAM of the DNA. These motions agree well with previous structural
analyses, suggesting that the inward movement of the PI domain would
accompany PAM binding.[11,14] Upon binding of DNA, the PI domain
remarkably reduces the amplitude of its motions, while REC2 and Nuc
display substantially increased amplitude motions. The large-amplitude
of the motions of REC2 and Nuc is preserved in all DNA-bound states,
in the presence of a cleaved NTS (i.e., in the FnCas12a system) and
in the FnCas12a′ system, where a complete NTS rehybridizes
with the TS to form a duplex in the vicinity of REC2 and Nuc (Figures c and 3a). As previously suggested by Stella and co-workers based
on single-molecule FRET,[16] an increased
flexibility of REC2 and Nuc upon binding of DNA could have a functional
role. Indeed, the mobility of these regions could favor the exchange
of the NTS and TS, as well as to attain the 5′-3′ polarity
of the TS required for cleavage within the RuvC active site.[16] In this respect, the catalytic RuvC domain displays
short-amplitude motions, in agreement with the high structural stability
of this conserved protein domain.[17,31] Interestingly,
REC1 shows motions of smaller amplitude, which arise from strong interactions
with the RNA:DNA hybrid and reflect the function of this domain in
anchoring the target DNA strand.[14]
Figure 3
Large-amplitude
motions and conformational space adopted by CRISPR-Cas12a.
(a) “Essential dynamics”, derived from the first principal
component (PC1) of the individual protein domains of FnCas12a bound
to RNA (left) and DNA (right), shown using arrows of sizes proportional
to the amplitude of motions. For the DNA-bound states, the “essential
dynamics” is shown for the presence of a cleaved NTS (FnCas12)
and complete NTS (FnCas12a′). (b) Projections of the first
and second principal components (PC1 vs PC2) from MD simulations of
the RNA- and DNA-bound FnCas12a systems. The PC1 vs PC2 plots characterize
the conformational space sampled by the FnCas12a into regions in which
the protein is “open” (red cloud) and “closed”
(blue cloud). A cartoon of FnCas12a indicating the “open-to-closed”
conformational transition is shown on the right.
Large-amplitude
motions and conformational space adopted by CRISPR-Cas12a.
(a) “Essential dynamics”, derived from the first principal
component (PC1) of the individual protein domains of FnCas12a bound
to RNA (left) and DNA (right), shown using arrows of sizes proportional
to the amplitude of motions. For the DNA-bound states, the “essential
dynamics” is shown for the presence of a cleaved NTS (FnCas12)
and complete NTS (FnCas12a′). (b) Projections of the first
and second principal components (PC1 vs PC2) from MD simulations of
the RNA- and DNA-bound FnCas12a systems. The PC1 vs PC2 plots characterize
the conformational space sampled by the FnCas12a into regions in which
the protein is “open” (red cloud) and “closed”
(blue cloud). A cartoon of FnCas12a indicating the “open-to-closed”
conformational transition is shown on the right.The direction of FnCas12a principal motions upon DNA binding is
of particular interest, as differences are observed in the presence
of a complete NTS, as opposed to cleaved NTS. In FnCas12a, in which
the NTS is cleaved, REC2 and Nuc move toward each other (Figure a), and REC1 also
moves toward RuvC and Nuc. In the FnCas12a′ system (including
a complete NTS), REC1-2 and Nuc preserve opposite motions but directed
away from each other. Nuc points its motions out of the protein framework,
as also observed for REC1-2. To gain further insights on this observation,
we performed volumetric analysis on the equilibrium trajectories (details
are reported in the SI). We measured the
volume of the cavity between the REC and NUC lobes, which forms the
RuvC binding groove. This revealed a contraction of the groove in
the FnCas12a system (Figure S6). On the
other hand, in the FnCas12a′ system, an expansion of the groove
is observed. Considering that Cas12a cuts the NTS first,[13,16,33] the dynamical differences observed
in the presence and absence of a complete NTS suggest possible conformational
rearrangements of Nuc and REC1-2 upon NTS cleavage, which could allow
the subsequent processing of the TS.[16]Overall, the direction of the motions of these domains (as opposite
to each other) indicates the tendency toward the “opening”
and “closure” of the protein to accommodate and cleave
the nucleic acids.[11,14,16] This is a functional feature shared with CRISPR-Cas9, as observed
in previous simulation studies and through structural analyses.[17,34,35] To characterize the conformational
space adopted by the ribonucleoprotein, we plotted the first versus
the second principal components (i.e., PC1 vs PC2, Figure b). As a result, the PC1 vs
PC2 plots identify two states, which depict the “open”
and “closed” conformations of the protein well (schematically
drawn using a cartoon of FnCas12a in Figure b), observed in both the RNA-bound and DNA-bound
forms of FnCas12a. Notably, a range of conformational states from
“open” to “closed” was also observed through
PCA of multimicrosecond MD runs on CRISPR-Cas9.[17,35] This indicates that both ribonucleoprotein complexes have a general
tendency toward an “open-to-closed” breathing to allow
nucleic acid association. In this respect, it is worth noting that
DNA binding-induced conformational changes occur at remarkably slower
rates than what is possible to simulate using classical MD.[36,37] Yet, our data show a good coverage of the conformational landscape
(Figures b and S7), implying that the PCA well-represented the
large-scale dynamics of the system. It is also notable that in the
DNA-bound states, the conformational space explored by the protein
is slightly restricted as a result of global stabilization due to
the binding of the DNA (FnCas12a) and a complete NTS (FnCas12a′).
This also agrees well with previous PCA of the CRISPR-Cas9 complex.[17] In summary, the Cas12a protein preserves a general
tendency toward an “open-to-closed” conformational transition
in both the RNA-bound and DNA-bound states. However, as described
above, prior to DNA binding, large-amplitude motions and high flexibility
are observed at the level of the PI domain. On the other hand, upon
DNA binding, the largest motions shift to REC2 and Nuc.Finally,
it is noteworthy that the PCs arising from the LbCas12a,
AsCas12a, and all FnCas12a systems cannot be directly compared owing
to the inconsistency in the eigenbasis. Acknowledging this fact, two
independent PCAs have been performed for the RNA-bound LbCas12a and
DNA-bound AsCas12a systems to gain insights into their “essential
dynamics”. We observed that the RNA-bound LbCas12a displays
large amplitude motions in the PI domain directed inward. On the other
hand, AsCas12a bound to a cleaved NTS exhibits the largest motions
in the REC2 and Nuc domains, moving toward each other (Figure S7). This is qualitatively consistent
with the switch in the “essential dynamics” observed
in the FnCas12a systems upon DNA binding.
Coupled Motions of Protein
Domains
To investigate the
interdependent conformational dynamics among spatially distant protein
domains, we performed dynamic correlation analysis. This analysis
was performed and averaged over multiple MD trajectories using two
different methods. We computed the traditional Pearson cross-correlation
(CC) coefficients, which measure the
collinear correlation between two Cα atoms (i and j), determining whether they tend to move in
lockstep (positive CC) or show opposed
motions (negative CC). The CC analysis only detects correlations that are collinear
with each other, neglecting correlated motions occurring out of phase.
Hence, we also employed a generalized correlation (GC) scheme.[38] This measures
the degree of correlation between Cα atoms based on their mutual
information, providing a normalized measure of how much information
on one atom’s position is provided by that of another atom.
The method, however, does not distinguish positive vs negative correlations,
neglecting the description of opposite atom’s motions. Hence,
when employed together, the CC and GC schemes are powerful in describing the
interdependent dynamics of proteins.The CC matrix (i.e., a two-by-two plot of the Cα CC coefficients) of FnCas12a shows a conserved pattern
of correlated/anticorrelated motions in both RNA- and DNA-bound states
(Figure , upper triangles),
which are also found in the other Cas12a systems (Figures S8–S12). The REC lobe (i.e., REC1-2) preserves
anticorrelated motions with the NUC lobe (including RuvC, Nuc, PI,
and WED). This indicates the tendency of REC to move in an opposite
way with respect to NUC, thereby favoring the “open-to-closed”
conformational transition underlying nucleic acid binding.[11,14,16] The GC matrix, which goes beyond the reach of a Pearson-like CC analysis, captures the overall dependencies
of the protein motions (Figure , lower triangles). In the RNA-bound state of FnCas12a (Figure a), coupled motions
are only detected among REC1-2 and PI. On the other hand, in the DNA-bound
FnCas12a (Figure b)
correlated motions of REC2 and Nuc become prominent, while REC1 also
displays correlations with Nuc (although at a lower extent). In the
presence of a complete NTS (i.e., in the FnCas12a′, Figure c), the overall system’s
GC becomes more intense, preserving
a high degree of coupling between REC1-2 and Nuc. We note that intense
correlations between REC2 and Nuc are found in all simulated replicas
of each DNA-bound system (Figures S8–S10). This indicates a shift in the correlated motions from one region
of the GC matrix (corresponding to REC1-2
and PI, in the RNA-bound state) to the REC1-2/Nuc domains upon DNA
binding, finally encompassing the entire protein when bound to a complete
NTS. To further evaluate the interdependent coupling between protein
domains, we computed the per-domain GC scores (Cs), which accumulate (and normalize) the GC for each protein domain with each other (details
are reported in the SI).[39] As a result, the per-domain Cs matrices highlight the high
degree of coupling between Nuc and REC2 upon DNA binding (Figure S13). AsCas12a, which has been simulated
only in the DNA-bound state, also shows high GC between REC1-2 and Nuc (Figure S11). The RNA-bound LbCas12a preserves a pattern of highly correlated
motions (Figure S12). However, for these
species, a direct comparison between the RNA- and DNA-bound states
is not possible due to the lack of structural information. Finally,
it is interesting to note that only in the presence of complete nucleic
acids (i.e., in the FnCas12a′, Figure c), highly correlated motions are observed
across the entire protein. This has also been established through
MD simulations of the DNA-bound Cas9,[19,35,40] indicating a mechanism of interdomain allosteric
communication.[41,42] This novel hypothesis in CRISPR-Cas12a
arising from our data now warrants further computational investigations
of protein allostery that are currently being pursued in our laboratory.
This will likely also clarify the most important residues sustaining
the functional motions and the communication mechanism.[43,44]
Figure 4
Correlated
motions of CRISPR-Cas12a. Cross-Correlation (CC, upper triangles) and Generalized Correlations
(GC, lower triangles) matrices, computed
for FnCas12a in the RNA-bound state (a) and upon DNA binding, in the
presence of a cleaved NTS (b) and a complete NTS (c). Data are averaged
over 4 simulation replicas of ∼1 μs each. The strength
of the CC is colored blue (for CC ≥ 0, lockstep motions) to violet
(for CC ≤ 0, anticorrelated motions),
while the GC are green (correlated)
to magenta (not correlated). Color scales are at the bottom. The protein
sequence is also shown. Boxes are used to highlight anticorrelated
CC motions between the REC and NUC lobes
and highly coupled GC between REC &
Nuc, also depicted in the cartoon of FnCas12a (bottom right).
Correlated
motions of CRISPR-Cas12a. Cross-Correlation (CC, upper triangles) and Generalized Correlations
(GC, lower triangles) matrices, computed
for FnCas12a in the RNA-bound state (a) and upon DNA binding, in the
presence of a cleaved NTS (b) and a complete NTS (c). Data are averaged
over 4 simulation replicas of ∼1 μs each. The strength
of the CC is colored blue (for CC ≥ 0, lockstep motions) to violet
(for CC ≤ 0, anticorrelated motions),
while the GC are green (correlated)
to magenta (not correlated). Color scales are at the bottom. The protein
sequence is also shown. Boxes are used to highlight anticorrelated
CC motions between the REC and NUC lobes
and highly coupled GC between REC &
Nuc, also depicted in the cartoon of FnCas12a (bottom right).
Discussion
Dynamic “Switch”
upon DNA Binding
MD
simulations of Cas12a indicate a change in the structural flexibility
and in the conformational dynamics of the protein upon DNA binding.
In the RNA-bound states, the PI region displays high flexibility (Figure ) and large-amplitude
motions directed toward the cleft that accommodates the PAM of the
substrate DNA (Figure a). Upon DNA binding, the flexibility of the PI region is notably
reduced, while the flexibility of REC2 and Nuc increases. Furthermore,
the PI domain reduces the extent of its motions, while REC2 and Nuc
display the largest amplitude motions. This suggests that the binding
of DNA, which is initiated at the level of the PI domain in Cas12a,
quenches the conformational flexibility of PI and induces the activation
of peripheral large-scale motions at the level of REC2 and Nuc. This
high flexibility and large-scale breathings of REC2 and Nuc upon DNA
binding are also observed in the FnCas12a′ complex, where REC2
and Nuc directly interact with a duplex region of the DNA substrate
(Figure c). Taken
together, analysis of the protein fluctuations (Figure ) and large-amplitude motions (Figure ) indicates a switch in the
Cas12a dynamics upon DNA binding, which results in quenching of PI
domain mobility and activating motions of the peripheral REC2 and
Nuc domains. This switch in the Cas12a dynamics rationalizes some
functional aspects and previous observations. Indeed, the high flexibility
of the PI domain prior to DNA binding could favor its inward conformational
change for accommodating the PAM.[11,14] Subsequent
DNA binding, which is initiated at the level of the PI region, results
in curtailment of the PI domain dynamics. On the other hand, REC2
and Nuc increase in flexibility, also when binding to a complete NTS
(as in FnCas12a′, Figures and 3). This is notable because
the binding of dsDNA commonly induces the stabilization of the surrounding
protein framework, which is indeed observed at the level of the PI
domain. The high flexibility of REC2 and Nuc in the presence of complete
nucleic acids also agrees with a very recent study revealing that
the DNA in this region is intrinsically highly flexible.[45] Moreover, a high degree of flexibility of these
regions upon DNA binding and during the formation of an RNA:DNA hybrid
has also been observed through cryoEM and single-molecule experiments.[16,46] This increase in flexibility upon DNA binding is possibly a consequence
of the need to cleave both DNA strands by a single active site located
within the RuvC domain. This requires an exchange of the NTS and TS
within the active site, which in turn necessitates conformational
changes (and increased mobility) of the interacting protein domains,
namely the REC lobe and Nuc.[16,47] Moreover, high conformational
plasticity of REC and Nuc is also needed for the release of the product,[48] as well as for enabling the nonspecific cleavage
of single-stranded DNA (ssDNA) accessing the RuvC–Nuc interface.[4,15,49] This is a critical property that
allows leveraging of Cas12a for the diagnosis of viral nucleic acids
in the DETECTR technology.[5]The switch
in the conformational dynamics of Cas12a is also reflected by the
analysis of the generalized correlations (GC), which capture the overall dependencies of the protein motions.
This analysis shows a change in the correlated motions of FnCas12a
domains, revealing that correlations between REC1-2 and Nuc increase
upon DNA binding (Figure , lower triangles). Notably, correlated motions of REC2 and
Nuc are preserved across the DNA-bound Cas12a systems (Figures S8–S12), suggesting a coupled
dynamical function, where the motions of REC2 allow conformational
changes in Nuc. This observation is particularly interesting in light
of similar observations previously reported for the Cas9 enzyme. Indeed,
in the DNA-bound form of Cas9, REC2 has been shown to play a critical
role in regulating the conformational activation of the HNH domain
for TS cleavage. Specifically, single-molecule experiments[23,25,27] and recent cryo-EM structures[24] have shown reciprocal conformational changes
of REC2 and HNH domains to allow the latter to dock at the TS for
cleavage. Accordingly, MD simulations have revealed that the HNH domain
approaches the TS in concert with a transition of REC2,[19] while displaying correlated motions similar
to what is observed for REC2 and Nuc in Cas12a. This suggests that
despite being evolutionarily different than Cas9,[9] REC2 of Cas12a could play a similar regulatory function
on the conformational activation of Nuc to allow the cleavage of the
TS.
Conformational Activation for TS Processing
Cas12a
uses the single RuvC domain to cleave both DNA strands, differing
from Cas9, which cleaves the NTS and the TS using the RuvC and HNH
nuclease domains, respectively. This has questioned the role and function
of the additional Nuc domain, which was initially thought to cleave
the DNA TS.[12] It is unclear, in fact, whether
and how conformational changes of Nuc would activate DNA cleavages
or facilitate the exchange of the TS and NTS within the RuvC active
site for cleavage.Here, molecular simulations of Cas12a upon
DNA binding offer interesting insights on the dynamic role of Nuc.
We observed significant differences in the direction of the essential
motions of Cas12a in the presence/absence of the DNA NTS (Figure A). Indeed, in the
presence of a complete NTS (i.e., in FnCas12a′), REC1-2 and
Nuc display overall outward motions, leading to an expansion of the
RuvC binding groove (Figure A). On the other hand, upon cleavage of the NTS (i.e., in
AsCas12a and FnCas12a), REC1-2 and Nuc point inward (Figure B). This results in a contraction
of the groove between the TS and the RuvC active site after NTS cleavage,
which is also confirmed through volumetric analysis performed on the
equilibrium trajectories (Figure S6). This
observation is of particular interest. Considering that Cas12a cuts
the NTS first,[13,16,33] this reinforces the outcomes of single-molecule FRET,[16] suggesting that Nuc and REC2 are highly dynamic
and could allow the cleavage of the TS. Indeed, given the presence
of a single catalytic site within the RuvC domain, after initial cleavage
of the NTS, the TS should access the active site with conformational
changes of the interacting protein domains. In light of this fact,
our atomistic simulations indicate the tendency of Nuc to bend toward
REC2, suggesting the narrowing of the groove between the TS and the
RuvC active site. Concurrently, the motion of REC2, nearing Nuc and
RuvC, shows its propensity to push the DNA TS toward the RuvC active
site. REC1 also points toward RuvC, aiding the RuvC active site to
access the TS. Hence, the REC lobe and Nuc would cooperate in the
activation of the system toward TS cleavage.
Figure 5
Changes in the RuvC binding
groove of CRISPR-Cas12a before and
after NTS cleavage. (a) Before NTS cleavage, an expansion in the RuvC
binding groove is observed as mediated by outward motions of REC1-2
and Nuc. (b) After NTS cleavage, inward motions of REC1-2 and Nuc
dynamics lead to a contraction of the RuvC binding groove. The outward/inward
motions of the REC1-2 and Nuc domains are shown in transparent-to-mat
colors. Arrows are also used to indicate the conformational transitions.
The RuvC binding groove, which is located in between the REC and NUC
lobes, is also highlighted.
Changes in the RuvC binding
groove of CRISPR-Cas12a before and
after NTS cleavage. (a) Before NTS cleavage, an expansion in the RuvC
binding groove is observed as mediated by outward motions of REC1-2
and Nuc. (b) After NTS cleavage, inward motions of REC1-2 and Nuc
dynamics lead to a contraction of the RuvC binding groove. The outward/inward
motions of the REC1-2 and Nuc domains are shown in transparent-to-mat
colors. Arrows are also used to indicate the conformational transitions.
The RuvC binding groove, which is located in between the REC and NUC
lobes, is also highlighted.Correlation analyses have indicated highly coupled motions between
REC2 and Nuc (Figure ). This suggests a coupled dynamical function, where the motions
of REC2 are fundamental to allow the conformational changes of Nuc.
This resembles the reciprocal dynamical role of REC2 and HNH in Cas9,
where REC2 regulates conformational changes of the catalytic HNH domain
to allow TS cleavage.[19,23−25] In light of
these observations, the dynamics of REC2 in Cas12a could assist the
conformational changes of Nuc and acts as a “regulator”
of its function. In support of this hypothesis, single-molecule studies
of Cas12a have shown that the REC2 and Nuc domains show the largest
conformational rearrangements.[16] Hence,
the coupled dynamics observed here between REC2 and Nuc now calls
for new biophysical experiments to assess the role of the REC lobe
in the conformational activation of CRISPR-Cas12a. In this respect,
we note that in the case of Cas9, biophysical studies have shown that
conformational changes of the REC lobe are also critical for the enzyme’s
specificity,[25,27] and mutations in the REC domain
can reduce its off-target activity.[25,28,29] Moreover, a recent study has shown that point mutations
in the REC lobe of AsCas12a can reduce off-target effects.[30] These findings and the results of the current
study thus motivate further investigation on the functional role of
REC and Nuc in CRISPR-Cas12a.
Conclusions
Here,
all-atom MD simulations characterize the structural plasticity
of CRISPR-Cas12a and the dynamic determinants underlying nucleic acid
association. On a collective sampling of ∼20 μs, carried
out over multiple states and across different species, we reveal that
DNA binding induces a switch in the conformational dynamics of Cas12a,
which results in quenching motions of the PAM interacting domain and
activating motions of the peripheral REC2 and Nuc domains. This switch
in the Cas12a dynamics rationalizes crucial functional aspects. Indeed,
the increased flexibility of REC2 and Nuc upon DNA binding could enable
the conformational changes associated with DNA cleavage.[16] Considering that the core of the RuvC catalytic
domain is highly rigid,[17,31] the observed flexibility
of the adjacent Nuc domain and REC2 could contribute to the exchange
of the DNA strands within the Cas12a active site for sequential cleavage,[16] rapid release,[48] and
subsequent nonspecific cleavage of ssDNAs.[4] This property is at the core of the DETECTR technology for rapid
viral nucleic acid detection, especially that of SARS-CoV-2.[5] This suggests that the mutual dynamics of REC2
and Nuc observed here could be critical for the nonspecific binding
of ssDNAs and thereby for the underlying mechanistic functioning of
the DETECTR technology.In-depth analysis of the dynamics upon
DNA binding also offers
mechanistic insights into the role of Nuc, whose function is incompletely
understood. Accordingly, the joint dynamics of REC and Nuc shows the
tendency to promote the conformational transition of the DNA TS toward
the RuvC active site through opposite and concerted motions. REC2
and Nuc also display highly coupled dynamics, suggesting that REC2
could act as a regulator of the Nuc function, as previously observed
for the HNH domain in Cas9.[19,23−25,27] In the case of Cas9, the REC
lobe plays a critical role in the enzyme’s activation and specificity.[25,28,29] Moreover, point mutations in
REC of AsCas12a can reduce off-target effects,[30] which limit the applicability of the CRISPR technology.
In light of these results, our outcomes motivate future investigations
to characterize the functional role of REC and Nuc in CRISPR-Cas12a.
It is also notable that our data suggest an unforeseen allosteric
communication in CRISPR-Cas12a, which we have previously described
in CRISPR-Cas9,[35,40,41] in agreement with experimental data.[6,25] This hypothesis
grants now in-depth investigations, which we are currently pursuing
building on our interests in the computational determination of protein
allostery.Overall, our work provides an atomic-level characterization
of
the CRISPR-Cas12a conformational dynamics, with insights into substrate
DNA binding and cleavage. The mechanistic understandings arising from
molecular simulations are of fundamental importance for further experimental
studies aimed at a full characterization of the dynamic features of
Cas12a. These outcomes can contribute to engineering efforts aimed
at improving the CRISPR-Cas12a technology toward more efficient and
specific genome editing and viral detection.
Materials and Methods
Structural
Models
Molecular simulations have been performed
on five model systems of CRISPR-Cas12a, based on the available X-ray
structures. The RNA-bound states have been based on two X-ray structures: Lachnospiraceae bacterium Cas12a (LbCas12a) solved at 2.38
Å resolution (5id6.pdb)[10] and Francisella novicida Cas12a (FnCas12a) solved at 3.34 Å resolution (5ng6.pdb).[13] The DNA-bound states have been based on three
X-ray structures. We considered the structures of Acidaminococcus
sp. Cas12a (AsCas12a) and FnCas12a, in which the NTS is partially
cleaved (i.e., 5b43.pdb at 2.38 Å resolution[12] and 5nfv.pdb at 2.50 Å
resolution,[13] respectively). The third
DNA-bound state has been based on a recent structure of the FnCas12a,
including a longer NTS that binds within the RuvC cleft and reconciles
with the TS (6I1K.pdb at 2.65 Å resolution).[15] These
systems have been embedded in explicit waters, and Na+ ions
were added to neutralize the total charge, leading to orthorhombic
periodic cells comprising on average a total number of ∼210,000
atoms, for each system. Full details are reported in the Supporting Information (SI).
Molecular Dynamics
(MD) Simulations
MD simulations
have been performed employing the Amber ff12SB force field, which
includes the ff99bsc0[50] corrections for
DNA and the ff99bsc0+χOL3[51,52] corrections for RNA. The Allnér force field[53] has been employed for Mg2+ ions, and the TIP3P
model[54] has been employed for waters. These
force field parameters and the simulation protocol have also been
employed in our recent studies of CRISPR-Cas9,[40,55,56] corroborated by NMR experiments and quantum
mechanical calculations, enabling a fair comparison. An integration
time step of 2 fs has been employed. All bond lengths involving hydrogen
atoms were constrained using the SHAKE algorithm. Temperature control
(300 K) has been performed via Langevin dynamics, with a collision
frequency γ = 1/ps. Pressure control was accomplished by coupling
the system to a Berendsen barostat,[57] at
a reference pressure of 1 atm and with a relaxation time of 2 ps.
The systems have been subjected to energy minimization to relax water
molecules and counterions, keeping the protein, RNA, DNA, and Mg2+ ions fixed with harmonic position restraints of 300 kcal/mol·Å2, and then, the systems have been heated up from 0 to 100
K in the canonical ensemble (NVT), by running two simulations of 5
ps each, imposing position restraints of 100 kcal/mol·Å2 on the above-mentioned elements of each system. The temperature
was further increased up to 200 K in ∼100 ps of MD runs in
the isothermal–isobaric ensemble (NPT), reducing the restraint
to 25 kcal/mol Å2. Subsequently, all restraints were
released, and the temperature of the systems was raised to 300 K in
a single NPT simulation of 500 ps. After ∼1.1 ns of equilibration,
∼10 ns of NPT runs were carried out allowing the density of
the system to stabilize around 1.01 g/cm–3. Finally,
∼1 μs of MD simulations has been carried out in an NVT
ensemble for each system, which has also been simulated in 4 replicates.
Independent MD simulation replicas have been obtained starting from
different configurations and velocities, initialized accordingly to
the Maxwell–Boltzmann distribution at physiological temperature.
This approach enabled us to obtain solid statistics for the analysis
in our purposes. Considering five simulation systems, we collected
a total of ∼20 μs of aggregate sampling (i.e., 5 systems
* 4 replicas * ∼1 μs = ∼20 μs). Molecular
simulations have been performed using the GPU version of AMBER 18.[58] The analysis of the results has been performed
on each simulated MD replica and the ensemble obtained averaging independent
ns-to-μs trajectories (details are in the SI). This enabled assessing the reproducibility of our results
across independent simulations and also providing a solid statistical
ensemble.
Principal Component Analysis (PCA)
PCA is a statistical
method that can report large-scale collective motions occurring in
biological macromolecules undergoing MD simulations. Through this
statistical technique, it is possible to reduce the large number of
degrees of freedom to an essential subspace set, which captures large-amplitude
motions of the system. In PCA, the covariance matrix of the protein
Cα atoms is calculated and diagonalized to obtain a new set
of coordinates (eigenvectors) to describe the system motions. Each
eigenvector–also called Principal Component (PC)–is
associated with an eigenvalue corresponding to the mean square fluctuation
contained in the system’s trajectory projected along that eigenvector.
By sorting the eigenvectors according to their eigenvalues, the first
PC (i.e., PC1) corresponds to the system’s largest amplitude
motion, and the dynamics of the system along PC1 is usually referred
to as “essential dynamics”.[32]In this work, the principal motions of
the protein were captured starting from the mass-weighted covariance
matrix of the Cα atoms. In detail, PCA has been performed considering
the FnCas12a systems, whereby the collected ensembles (i.e., arising
from the compared RNA-bound FnCas12a, DNA-bound FnCas12a, and FnCas12a′
systems; Figure )
were combined and subjected to RMS-fit to the same reference configuration,
removing the rotational and translational motions. This was performed
to ensure a consistent eigenbasis and motions of the PCs on all compared
systems and to construct the covariance matrices from the atoms’
positions. We also performed two independent PCA on the LbCas12a and
AsCas12a systems, providing insights into their essential motions.
Each element in the covariance matrix is the covariance between atoms i and j, defining the i, j position of the matrix. The covariance C is defined aswhere and are the position
vectors of atoms i and j, and the
brackets denote an average over the sampled time period. The two terms
in eq represent the
displacement vectors for atoms i and j. The covariance matrix was then diagonalized, leading to a complete
set of orthogonal collective eigenvectors, each associated with a
corresponding eigenvalue. The eigenvalues denote how much each eigenvector
is representative of the system dynamics, thus giving a measure of
the contribution of each eigenvector to the total variance. Indeed,
the eigenvectors with the largest eigenvalues correspond to the most
relevant motions. By projecting the displacements vectors of each
atom along the trajectory onto the eigenvectors (i.e., by taking the
dot product between the two vectors at each frame), the PCs were then
obtained. The cumulative variance accounted by all the PCs was calculated
for all systems, revealing that the first PCs account for the major
contribution (Figures S5 and S6). Full
details on the application of this statistical technique on MD simulations
of CRISPR-Cas12a are in the SI.
Cross-Correlation
Analysis
Correlation analysis has
been performed in order to identify the dynamical coupling of the
motions between Cα atoms (i and j) in the simulated systems. “Pearson-like” cross-correlation
(CC) analysis provides a measure of
the collinear correlations between the atoms i and j. The CC matrix can be computed
as a normalization of the covariance matrixwhere and are the position
vectors of atoms i and j, considered
over the sampled time period (denoted using brackets). Positive values
of the CC coefficients indicate lockstep
motions between atoms i and j, while
negative CC values are indicative of
anticorrelated motions. CC values equal
to zero evince that the atoms’ displacements are independent
from each other. The magnitude of CC coefficients (i.e., ranging from 0–>1 for lockstep motions
and from −1–>0 for anticorrelated motions) indicates
strength of the correlation. As noted above, the CC neglects the nonlinear contributions between atoms i and j and does not capture correlated
motions occurring out of phase with each other. To capture more broadly
the dependency of the atomic motions, we also employed a generalized
correlation method described below.
Generalized Correlations
Analysis Based on Mutual Information
This approach relies
on information theory and uses the mutual
information (MI) measure to obtain the generalized
correlation (GC) coefficients.[38] In information theory, two variables, such as
the such as the and position vectors,
can be considered correlated when their joint probability distribution, p(,), is smaller
than the product of their marginal distributions, p() · p(). The MI is a measure of the degree of correlation between and defined as
a function of p(,) and p()·p() accordingly
toNotably, MI is closely
related to the definition of the Shannon entropy and can be computed
aswhere H[] and H[] are the marginal
Shannon entropies, and H[,] is the joint
entropy, providing a link between motions’ correlations and
information content. Based on this definition, and considering that MI varies from 0 to + ∞, the normalized GC coefficients, ranging from 0 (independent variables)
to 1 (fully correlated variables), can be defined aswhere d is
the dimensionality of and . This approach
has been originally introduced by Lange and Grubmüller,[38] who developed a computationally efficient algorithm.
Overall, a GC analysis is powerful in
capturing nonlinear coupled motions in biomolecular systems. However,
the GC coefficients do not distinguish
positive vs negative motions, giving a normalized measure of how much
information on one atom’s position is provided by that of another
atom. Hence, when employed together, the CC and GC schemes can provide a
more comprehensive understanding of the interdependent dynamics of
proteins, with information on whether protein regions move in lockstep
or through opposite motions (through CC), and provide also more general information on the atoms’
interdependence (through GC). In the
present work, the GC coefficients have
been computed using the positions vectors of Cα atoms along
the simulated trajectories. For each model system, all correlation
analyses have been performed over independent MD trajectories and
have also been averaged over the aggregate sampling arising from 4
ns-to-μs MD replicas (details are in the SI). To further spotlight relevant correlations among spatially
distant domains, the averaged GC matrices
of the FnCas12a system have also been further processed to compute
per-domain GC scores (Cs). This measure
accumulates and normalizes the GC coefficients
over each protein domain, resulting in per-domain GC matrices that help in identifying the most relevant coupled
motions in large biomolecular systems (details are in the SI).[17,39]
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