High Throughput Screening with SAMDI Mass Spectrometry for Directed Evolution

Article abstract of DOI:10.1021/jacs.0c07828

Advances in directed evolution have led to an exploration of new and important chemical transformations; however, many of these efforts still rely on the use of low-throughput chromatography-based screening methods. We present a high-throughput strategy for screening libraries of enzyme variants for improved activity. Unpurified reaction products are immobilized to a self-assembled monolayer and analyzed by mass spectrometry, allowing for direct evaluation of thousands of variants in under an hour. The method was demonstrated with libraries of randomly mutated cytochrome P411 variants to identify improved catalysts for C-H alkylation. The technique may be tailored to evolve enzymatic activity for a variety of transformations where higher throughput is needed.

Full text of DOI:10.1021/jacs.0c07828

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High Throughput Screening with SAMDI Mass Spectrometry for
Directed Evolution
Adam J. Pluchinsky,∥ Daniel J. Wackelin,∥ Xiongyi Huang, Frances H. Arnold, and Milan Mrksich*
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ABSTRACT: Advances in directed evolution have led to an exploration of new and important chemical transformations; however,
many of these efforts still rely on the use of low-throughput chromatography-based screening methods. We present a high-
throughput strategy for screening libraries of enzyme variants for improved activity. Unpurified reaction products are immobilized to
a self-assembled monolayer and analyzed by mass spectrometry, allowing for direct evaluation of thousands of variants in under an
hour. The method was demonstrated with libraries of randomly mutated cytochrome P411 variants to identify improved catalysts for
C−H alkylation. The technique may be tailored to evolve enzymatic activity for a variety of transformations where higher throughput
is needed.
irected evolution represents a viable route to developing
biocatalysts for synthetic organic chemistry,1−4 including
linked to the viability of the cell, coupled to a measurable
coproduct, or make use of a biological reporter system.
To evolve enzymes for this reaction, we generate libraries
containing cytochrome P411 variants in well plates and allow
the variants to catalyze the reaction on an acetate-protected
substrate (Figure 1A). With our approach, we then use self-
assembled monolayers to selectively immobilize the substrate
and reaction product directly from cell suspensions (Figure
1B). Based on the chemistry available on the reaction products,
we chose to engineer the surface to present maleimide groups
against a background of tri(ethylene glycol) groups. We can
treat the reaction products with acid to reveal the thiol, which
allows immobilization to the monolayer via a Michael addition.
We then use SAMDI MS to measure the masses of the analyte-
alkanethiolate conjugates by matrix-assisted laser-desorption
ionization mass spectrometry (MALDI-MS).34,35 In this way,
we need only identify the products by a corresponding change
in mass and integrate the peaks of the substrate and product to
provide a yield for the reaction (Figure 1C).
D
many non-natural transformations.5−10 With substantial
advances in our ability to generate genetic diversity11 and
prepare libraries exceeding thousands of variants,12 the
screening of activity remains a significant bottleneck for
many reactions. Conventional screening efforts largely rely on
optical methods, which oftentimes have a defined reaction
scope13,14 as they usually require a suitable chromophore on
the molecule of interest15−17 or are based on the detection of a
coupled coproduct.18 While methods employing mass
spectrometry (MS) have the advantage that they are label-
free and therefore quite general, a chromatographic separation
step is often necessary, which can limit throughput.12,19−22
These methods limit both the rate at which evolution is
performed and the sequence space explored, often with only
several hundred variants screened per round of evolution in a
suitable time frame.23,24 This constraint has prompted the
development of alternative MS-based assays.16,25−29 Here, we
describe the first application of self-assembled monolayers for
matrix-assisted laser desorption ionization (SAMDI) as a high-
throughput assay that provides a generalizable platform to
enable screening in directed evolution campaigns.
In this study, the peak corresponding to substrate capture
was present at 1033 Da, and the product peak was shifted by
+86 Da (Figure 1C, right). For each spectrum acquired, we
calculated relative product yields from the area under the curve
In recent work, we evolved a cytochrome P411 to perform
alkylation of sp3 C−H bonds through carbene C−H insertion,
providing an efficient biocatalytic route for this highly
challenging and valuable transformation.12 However, each of
the reactions reported required the use of chromatography to
detect the reaction products. Leveraging SAMDI’s abilities to
assay enzyme activity30,31 and rapidly analyze thousands of
small molecule reactions directly from complex solutions,32,33
we sought to continue evolving this catalyst for C−H insertion
activity in high throughput. We chose an allylic substrate which
was among the most challenging to detect12 (Figure 1A);
developing a screen for this reaction is difficult because the
products are not easily ionizable, do not possess a significant
chromophore or generate a fluorescent signal, and cannot be
(AUC) of each peak using AUCproduct/(AUCsubstrate
+
AUCproduct). Each variant was screened in quadruplicate to
acquire an average yield and account for variability in the
deprotection and immobilization steps. We then normalized
the values by the average value of parent activity on each
respective plate to acquire a fold improvement. For each
Received: July 20, 2020
https://dx.doi.org/10.1021/jacs.0c07828
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© XXXX American Chemical Society
A

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Figure 1. Use of the SAMDI screening assay in a cycle of directed evolution. (A) Libraries of cytochrome P411 are expressed in 96-well plates and
allowed to react with the substrate (purple) and ethyl diazoacetate to form the ester product (orange). (B) Reaction products are deprotected and
transferred directly to a SAMDI plate where they immobilize to a maleimide-presenting monolayer. (C) The array is analyzed by MS, and results
are displayed as a heat map where each variant is shaded by fold improvement measured over its parent.
library, we generated heat maps to visualize the relative
activities of each variant (Figure 1C, left). Variants were
shaded by their fold improvement where orange represents
increased activity and purple, decreased activity relative to
parent-like activity (white). The most promising library
members were run at analytical scale and validated using gas
chromatography mass spectrometry (GCMS). We then
selected the best variant to be the parent of the next round
of evolution.
To identify the best starting variant for the first round of
evolution, we screened a diverse panel of heme proteins (see SI
methods) and chose a variant with one mutation (P74T) from
P411-CHF identified by Zhang et al.12 With P411-CHF-
(P74T) as the initial parent, we first used SAMDI to measure
the retention of function of enzymes in libraries generated by
error-prone PCR at various manganese chloride concentrations
(Figure S1). From these data, we found that SAMDI was able
Figure 2. Scatterplot of screening results collected via GCMS and
SAMDI from a library of 70 mutants. Values were calculated as a
fraction of product over the total of the remaining starting material
and product formed. Correlation was determined using least-squares
linear regression.
to rank variants with a least-squares correlation of R2 = 0.96 to
data collected by GCMS (Figure 2). While both techniques
identified one variant in this library as having potentially
improved activity, further validation confirmed this hit to be a
false positive (Figure S2).
In order to identify biocatalysts with increased activity, we
performed iterative rounds of mutagenesis and screening in
whole E. coli cells. Because SAMDI can handle the large
sequence space of random libraries, we opted to generate
mutations throughout the entire gene using error-prone PCR.
Over the course of three rounds of evolution, we acquired data
for nearly 5000 variants (Figure S3) approximately 140-fold
more rapidly than what would be expected with GCMS (Table
1). Here, data generation for each round required only a few
hours, reducing the total analysis time from 24 days (for 1
replicate) to 17 h (for 4 replicates). In the third round we
Table 1. Comparison of Throughput and Total Screening
Effort of SAMDI to Conventional Screening Methodology
round 1 round 2
round 3
total
4956
# of variants
540
1920
2496
time GCMS 7 min/sample
time SAMDI 3 s/sample
x4 replicates
63 h
27 min
1.8 h
224 h
96 min
6.4 h
291 h
125 min
8.3 h
24 days
248 min
∼17 h
screened nearly 2500 variants and did not find a significantly
improved enzyme, suggesting that the enzyme may be
B
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approaching a local maximum in activity or may need
stabilizing mutations before further activating mutations can
be found. Experimental procedure may also need to be
reworked to avoid possible limitations in dynamic range as
enzymes improve. As we sought to evolve on this platform as a
proof of principle and managed to do so, we decided to end
the campaign.
To acquire the fold improvement of each parent over their
predecessor, we ran the top variants from each round at
analytical scale and measured their activities against their
parents by GCMS. The final variant displayed a 2-fold
improvement (1300 total turnovers (TTNs)) (Figure 3).
The use of a thiol-tagged reactant to allow immobilization of
the product was a convenient choice in this work but would
not be compatible with many reactions. Hence, we repeated
the C−H insertion reactions using a molecule that lacked a
thiol group and that could be immobilized to a monolayer
using a “traceless” immobilization method (Figure S7). In this
scheme, a monolayer presenting a diazirine group reveals a
carbene on irradiation, which reacts nonselectively to
immobilize nearly all molecules.37,38 We performed reactions
for five additional substrates and used the traceless
immobilization scheme to analyze products and, in each
case, observed peaks in the mass spectra that corresponded to
reactant and product (Figure S8). This example demonstrates
that reactants need not be functionalized for immobilization
and, in turn, suggests that this method will have a very broad
relevance in directed evolution.
Throughout the course of this study, 22 944 spectra were
generated and processed. With each plate requiring only 30
min per run, SAMDI collected data more than 100-fold faster
than classic GCMS and approximately 10-fold faster than
recent developments in the state-of-the-art thereof.20,39 If
higher throughput is desired, the method may be accelerated
by approximately 2-fold by working with groups of 16 96-well
plates in 50 min per run, with each sample requiring only 0.5
μL from each well.33
SAMDI-MS has been used extensively to profile enzymatic
activity both in biochemical reactions and from complex
lysates, while permitting the analysis of up to thousands of
samples per hour and more than 30 000 experiments per
day.31,32,36,40−42 Hence, it is clear that the throughput in this
study was not limited by the number of variants that could be
screened.
The approach described here has the benefits that it is high-
throughput, compatible with all library diversification techni-
ques performed in multiwell plates and may be applied to any
reaction that produces a shift in mass.33 While epPCR allowed
SAMDI to find modest fold improvements in the present work,
we expect that utilizing other diversification techniques will
result in greater improvements.
Figure 3. We used GCMS to characterize the hits and obtain the total
turnover (TTN) for each variant. The evolutionary lineage of P411
for C−H alkylation is displayed. Bars represent mean yields
(performed from two independent cell cultures, each used for
duplicate reactions). Reaction conditions were as follows: cytochrome
P411 in E. coli whole cells (optical density at 600 nm, OD600, of 1), 5
mM substrate, 5 mM ethyl diazoacetate, 5 vol % EtOH in M9-N
buffer at room temperature under anaerobic conditions for 18 h. The
asterisk symbol represents the introduction of a stop codon. See the
SI for details.
SAMDI-MS can accommodate a wide variety of chemical
transformationswithout sacrificing throughputas other
immobilization strategies have been demonstrated and are
readily available.35,37,38,40,43 In this way, the assay is not limited
to certain classes of reactions but can be adapted to many
organic transformations. We note that this method cannot be
applied to reactions where the product and substrate share the
same massincluding stereoisomeric and tautomeric struc-
turesand would in those cases require a second reaction step
(that is selective for one of the molecules), tandem mass
spectrometry, or a separation step.
As directed evolution continues to add new chemistries to
Nature’s repertoire, generating small molecules with increasing
complexity,44 the need for high-throughput and generalizable
screening tools is paramount. It is the use of immobilization
chemistry that distinguishes SAMDI’s throughput and
substantiates the method to be well suited for evaluating
variants in applications of directed evolution. This platform
enables directed evolution efforts to evolve enzymes for
improved activity and interrogate wider areas of protein space.
We anticipate that further use of this method will lead to
exploring larger areas of chemical space in high throughput and
help uncover unexpected solutions for creating better enzymes.
Interestingly, none of the beneficial mutations were in the
active site of the enzyme or at sites previously mutated in
rational approaches (Figure S4). By not restricting the
sequence space explored, we were able to identify potential
allosteric effects and provide new sites that may be investigated
in targeted evolution.
To demonstrate the reproducibility of the SAMDI
technique, we selected and scaled up one variant from the
final round to be screened repeatedly with SAMDI. Here we
found a standard deviation of 2.3% with a resolving power of
0.1 m/z (Figure S5). The primary source of variability about
the mean is likely due to application of matrix, which leads to
modest differences in signal strength from spot to spot.34 We
also note that while the SAMDI technique is able to accurately
quantitate the extent of each reaction,36 we only required
relative product yields to proceed with evolution, and thus,
accurate yields were determined only for the variants validated
by GCMS. Experimental reproducibility at-large was shown by
inducing multiple colonies of the same clone for the initial
variant. Here, we found a coefficient of variation (CV) of 14%
(Figure S6).
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(4) Yu, H.; Lopez, R. I. H.; Steadman, D.; Mendez-Sanchez, D.;
ASSOCIATED CONTENT
* Supporting Information
The Supporting Information is available free of charge at
https://pubs.acs.org/doi/10.1021/jacs.0c07828.
■
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AUTHOR INFORMATION
Corresponding Author
Milan Mrksich − Department of Biomedical Engineering and
Department of Chemistry and Department of Cell and
Developmental Biology, Northwestern University, Evanston,
Illinois 60208, United States; orcid.org/0000-0002-
4964-796X; Email: milan.mrksich@northwestern.edu
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Authors
Adam J. Pluchinsky − Department of Biomedical Engineering,
Northwestern University, Evanston, Illinois 60208, United
States
Daniel J. Wackelin − Division of Chemistry and Chemical
Engineering MC 210-41, California Institute of Technology,
Pasadena, California 91125, United States
Xiongyi Huang − Division of Chemistry and Chemical
Engineering MC 210-41, California Institute of Technology,
Pasadena, California 91125, United States; orcid.org/
0000-0001-7156-8881
Frances H. Arnold − Division of Chemistry and Chemical
Engineering MC 210-41, California Institute of Technology,
Pasadena, California 91125, United States; orcid.org/
0000-0002-4027-364X
Complete contact information is available at:
https://pubs.acs.org/10.1021/jacs.0c07828
Author Contributions
∥A.J.P. and D.J.W. contributed equally to this work.
Notes
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A.; Turner, N. J.; Flitsch, S. L.; Barran, P. E. Real-Time Screening of
Biocatalysts in Live Bacterial Colonies. J. Am. Chem. Soc. 2017, 139
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The authors declare no competing financial interest.
ACKNOWLEDGMENTS
■
We thank Dr. Ruijie Zhang for initial discussions and Dr.
Sabine-Brinkmann-Chen for critical review of the manuscript.
A.J.P. and D.J.W. are supported by the National Science
Foundation Graduate Research Fellowship under Grant Nos.
DGE-1842165 and DGE-174530. Research reported in this
publication was supported by the Department of Defense,
Defense Threat Reduction Agency, under award HDTRA1-15-
1-0052 (to M.M.) and by the US Army Research Office
Institute for Collaborative Biotechnologies cooperative agree-
ment W911NF-19-2-0026 (to F.H.A. and X.H.).
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