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Biotechnology of Microbial Enzymes.
© 2017 Elsevier Inc. All rights reserved.2017
Chapter 8
The Pocket Manual of Directed 
Evolution: Tips and Tricks
Diana M. Mate1, David Gonzalez-Perez2, Ivan Mateljak2, 
Patricia Gomez de Santos2, Ana Isabel Vicente2 and Miguel Alcalde2
1DWI-Leibniz Institute for Interactive Materials, Aachen, Germany 2Department of Biocatalysis, 
Institute of Catalysis, CSIC, Cantoblanco, Madrid, Spain
8.1 INTRODUCTION
Directed molecular evolution is a powerful engineering strategy to obtain 
enzymes that are tailor-made for specific biotechnological processes, ranging 
from industrial and environmental applications to drug discovery. Similarly, 
such studies offer insights into protein structure-function relationships and nat-
ural protein evolution (Bloom and Arnold, 2009; Tracewell and Arnold, 2009; 
Bornscheuer et al., 2012; Goldsmith and Tawfik, 2012). This methodology rec-
reates the Darwinian principles of mutation, recombination, and selection in 
the laboratory, but collapsing the evolutionary timeline from thousands of years 
to months or even days. For more than two decades now, members of the six 
enzyme classes have been engineered by directed evolution (Jackel and Hilvert, 
2010; Cobb et al., 2013; Martínez and Schwaneberg, 2013). Indeed, the limits 
of directed evolution are now being pushed beyond those imposed by nature, as 
proven by enzymes evolved to catalyze chemical reactions that have no known 
natural counterparts (Renata et al., 2015) or those that act in nonnatural envi-
ronments (Zumarraga et al., 2007; Lehmann et al., 2012; Mate et al., 2013a,b; 
Alvizo et al., 2014).
In recent years, excellent protocols for library creation and screening have 
been published in comprehensive directed evolution handbooks (Brakmann and 
Johnson, 2002; Arnold and Georgiou, 2003a,b; Brakmann and Schwienhorst, 
2004; Gillan et al., 2014). Thus, the purpose of this pocket manual on directed 
evolution is to provide a quick but wide glance at the most common techniques 
and methods used in protein evolution, as well as to mention new research 
trends in this groundbreaking field of biotechnology. Throughout this guide, 
DOI: http://dx.doi.org/10.1016/B978-0-12-803725-6.00008-X
186 Biotechnology of Microbial Enzymes
you will find our own personal views on how to perform directed evolution 
in the most efficient manner. We will pay special attention to the evolutionary 
methods developed by laboratories elsewhere, while offering tips and tricks to 
overcome bottlenecks during the step of library construction and exploration, all 
of which can help carry out more productive directed evolution studies.
The first section of the guide deals with the variety of techniques used to 
construct mutant libraries in order to generate DNA diversity. The second sec-
tion discusses the use of computational tools in laboratory evolution, while the 
third part details the most representative host organisms employed for directed 
evolution. The fourth section describes the selection and screening technologies 
currently used to evaluate mutant libraries, and finally, the last section high-
lights the new trends in this thrilling research field (Fig. 8.1).
8.2 METHODS TO GENERATE DNA DIVERSITY
All directed evolution experiments involve the creation of mutant libraries 
using one or more parental DNA sequences encoding the enzyme/s of interest 
as the starting point. The target gene(s) is subjected to random mutation and/or 
recombination, although the fidelity with which these in vitro processes mimic 
nature remains unknown. While the mutagenesis process can be performed with 
mutagenic strains, the undesired introduction of mutations in regions outside of 
the gene frontiers (eg, promoters, terminators, selection markers) compromise 
the quality of the mutant libraries, discouraging their use (Wong et al., 2006a). 
Accordingly, most of the in vitro or in vivo methods used to generate DNA 
diversity only target the gene under study.
The success of a directed evolution experiment not only depends on the 
quality of the gene library but also, on the availability of an efficient cloning 
system. For years, cloning strategies have relied on restriction enzymes to cre-
ate sticky ends in target sequences, digesting the cloning vector with the same 
enzymes and then ligating the fragments using DNA ligases. In directed evolu-
tion experiments, poor ligation efficiency, incomplete digestion, or the lack of 
unique restriction sites can hamper standard cloning and diminish transforma-
tion efficiencies. To overcome these drawbacks, a series of commercial kits has 
been released that are based on the use of homologous sequences followed by 
in vitro or in vivo recombination, overlapping PCR or the use of megaprimers 
(Tee and Wong, 2013), as well as the joining of multiple overlapping DNA frag-
ments in a single-tube reaction (Gibson et al., 2009, 2010).
8.2.1 Mutagenic Methods
8.2.1.1 Random Mutagenesis
Irrespective of the cloning strategy chosen for your directed evolution experi-
ment, there are two key issues to be considered when incorporating random 
mutations into the target DNA sequence: the quantity and the quality of the 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 187
mutations. On the one hand, the quantity (referred to as mutational load or 
frequency) reflects the number of mutations per kilobase pair. Although the 
sequence of each protein has different tolerance to mutations, the mutational load 
suitable for directed evolution studies generally ranges from 2 to 7 nucleotide 
FIGURE 8.1 The process of directed evolution. The methods employed to generate diversity 
are highlighted in green, the host organisms for directed evolution are shown in orange, and the 
screening and selection methods are shown in blue: epPCR, error-prone PCR; SeSaM, Sequence 
Saturation Mutagenesis; IvAM, In vivo Assembly of Mutant libraries; CSM, Combinatorial 
Saturation Mutagenesis; StEP, Staggered Extension Process; RACHITT, RAndom CHimeragenesIs 
on Transient Templates; DOGS, Degenerate Oligonucleotide Gene Shuffling; ITCHY, Incremental 
Truncation for the Creation of HYbrid enzymes; SCRATCHY, ITCHY+ DNA Shuffling; SHIPREC, 
Sequence Homology-Independent Protein RECombination; USERec, USER friendly DNA 
Recombination; RM-PCR, Random Multi-recombinant PCR; SISDC, Sequence-Independent 
Site-Directed Chimeragenesis; CLERY: Combinatorial Libraries Enhanced by Recombination 
in Yeast; IVOE, In vivo Overlap Extension; MORPHING, Mutagenic Organized Recombination 
Process by Homologous IN vivo Grouping; OSCARR, One-pot, Simple methodology for CAssette 
Randomisation and Recombination; MAP, Mutagenesis Assistant Program; PROSAR, Protein 
Sequence Activity Relationship; 3DM, 3-Dimensional Matching; ConSurf, Conservation Surface-
mapping; PELE, Protein Energy Landscape Exploration; FoldX, Force field; CASTER, Combinatorial 
Active-site Saturation Test aid software; CASTp, Computed Atlas of Surface Topography of pro-
teins; HTS, High-Throughput Screening; MTP, MicroTiter Plate; GFP, Green Fluorescent Protein; 
IVC, In vitro Compartmentalization; FACS, Fluorescence Assisted Cell Sorting.
188 Biotechnology of Microbial Enzymes
substitutions per gene (Wong et al., 2006a). A good trick to estimate the muta-
tional load is to construct small mutant libraries with different mutational loads 
(one or two 96-well plates), evaluating the mutational landscape by counting 
the number of clones with less than 10% of the parental activity. Typically, a 
landscape in which 35–50% of the total clones screened have less than 10% 
of the parental activity is suitable for directed evolution campaigns, although 
this figure varies in function of the target protein and its activity (Arnold and 
Georgiou, 2003b). Conversely, the quality of the mutations is determined by 
the mutational bias, which is strictly dependent on the mutagenic method. For 
instance, mutagenesis based onDNA polymerases is strongly biased towards 
a higher rate of transitions (Ts; change from purine to purine or pyrimidine to 
pyrimidine) over transversions (Tv; change from purine to pyrimidine or vice 
versa). Some mutagenic methods (see below) have been developed to equili-
brate the Ts/Tv ratio or to make them independent of the DNA polymerase bias. 
As a general tip, we suggest combining different polymerases by alternating 
between them in consecutive generations of evolution.
Leaving aside the expensive synthetic chemistry-based methods for mutagen-
esis and the use of nonreliable mutator strains, PCR-based methods (also known 
as error-prone PCR or epPCR methods) are the most commonly employed for 
random mutagenesis. They are based on the use of low fidelity DNA polymer-
ases and chemicals that interfere with the activity of the DNA polymerase. The 
DNA polymerase from the thermophilic bacterium Thermus aquaticus (Taq 
DNA polymerase) is frequently used in these experiments due to its high error 
rate, which is linked to the lack of 3´→5´proofreading exonuclease activity. 
Moreover, the mutational loads in Taq libraries can be altered by the addition 
of MnCl2, the use of unbalanced dNTP concentrations and the reduction in the 
concentration of gene template. The GeneMorph II random mutagenesis kit is 
a valuable alternative to the standard Taq libraries as it minimizes the muta-
tional bias by using the Mutazyme II, which is a blend of the Mutazyme I DNA 
polymerase and a Taq polymerase mutant (Strategene, 2004). Alternative meth-
ods to produce a less biased mutational spectrum include SeSaM and IvAM. 
Sequence Saturation Mutagenesis (SeSaM) is a protocol to modify each nucleo-
tide position of the target gene independent of polymerase bias (Wong et al., 
2004). It is a process based on the random introduction of α-phosphorothioate 
nucleotides that are ultimately replaced by universal bases. The mutational 
spectrum is dependent on the concentration of α-phosphorothioate nucleotides, 
the combination of two or more of them, and the preference of the universal 
base for different base-pairings. Among other examples, the utility of SeSaM 
has been proven in directed evolution studies on phytases (Shivange et  al., 
2012), proteases (Li et al., 2012; Martinez et al., 2013), and DNA polymerases 
(Kardashliev et al., 2014). In vivo Assembly of Mutant libraries with different 
mutational spectra (IvAM) involves the recombination of two or more muta-
genic libraries created by different epPCR-based methods in Saccharomyces 
cerevisiae (Zumárraga et al., 2008). The libraries can be mixed in different pro-
portions to adjust the mutational bias and their mutagenic loads. Thus, IvAM 
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represents a good alternative when the host organism is S. cerevisiae, this yeast 
having been used comprehensively during the evolution of ligninases (Maté 
et al., 2010; Garcia-Ruiz et al., 2012; Molina-Espeja et al., 2014).
8.2.1.2 Saturation Mutagenesis
Since epPCR methods are not useful to introduce consecutive mutations (ie, 
they only produce a single nucleotide substitution per codon), on average we 
can only access 5.6 residues of the 20 amino acids in the protein alphabet. 
Moreover, the degeneracy of the genetic code (with four letters, there are 64 
possible codons: 61 codons for the 20 amino acids plus 3 stop codons), along 
with the mutational bias of DNA polymerases, generate amino acid changes of 
similar chemical nature. A recent study demonstrated that in low load epPCR 
libraries, around 45% of the library explored is wasted due to: (1) the pres-
ence of the parental type (33%), (2) mutants with identical substitutions (9%), 
and (3) mutational errors (3%) (Zhao et al., 2014). All these shortcomings can 
be alleviated by using saturation mutagenesis (SM) methods, whereby single 
codons are replaced by all the codons that will generate the 20 naturally occur-
ring amino acids (Georgescu et al., 2003; Martínez and Schwaneberg, 2013). 
SM methods can be used as a fine-tuning step on residues of particular interest, 
such as those revealed by conventional epPCR. As SM methods involve the 
rational selection of the site/s to be mutated and screened, they are considered 
to be so-called semirational approaches (Chica et al., 2005; Lutz, 2010). In fact, 
the residues subjected to SM are typically identified by molecular modeling 
assisted by the resolution of protein crystal structures, together with a range of 
computational tools (see Section 8.2).
When several codons are simultaneously subjected to SM the process is 
referred as to combinatorial saturation mutagenesis (CSM), which is often a 
useful approach to unmask optimal interactions and synergies between resi-
dues. Iterative saturation mutagenesis (ISM) is a CSM approach performed in 
consecutive cycles (Reetz and Carballeira, 2007). In ISM, several positions are 
targeted for SM in the initial and in independent rounds, where the best hit of 
the offspring is then chosen as the parental type for a new ISM cycle, which 
also includes the second best hit. The process is repeated for as many rounds as 
necessary until the desired trait is obtained. More recently, Omnichange, was 
described as a versatile method for multiple SM (Dennis et al., 2011), a proto-
col that permits up to five independent codons to be saturated simultaneously. 
Unlike ISM, this strategy does not require a minimum distance to be maintained 
between the mutated codons while permitting a combinatorial assembly of the 
positions subjected to mutagenesis in a simple manner (ie, it is a restriction 
enzyme-free method).
In CSM experiments, it is very important to pay attention to the size of the 
library to be screened. For example, when using NNK or NNS degenerate prim-
ers (N = A, T, C or G; K = G or T; S = G or C; codon coverage 32; coded amino 
acids 20), exploration of three positions simultaneously implies screening 
190 Biotechnology of Microbial Enzymes
libraries of approximately 100,000 clones. Unless ultrahigh-throughput assays 
are available, we strongly suggest using NDT primers (N = A, T, C or G; and D = 
A, G, or T) for two or more positions (Currin et al., 2014). These degenerate oli-
gos provide a good variety of polar, nonpolar, aliphatic, aromatic, negative and 
positive charged residues, notably reducing the demand for screening (eg, three 
positions can be easily handled in libraries of only 5184 clones for a coverage 
of 95%). Indeed, one good option is to construct couple-NDT libraries for the 
rapid analysis of synergies between two positions with minimal experimental 
effort (432 clones per library). Another clever trick involves a mixture of three 
primers (NDT, VHG (where V = no T, H = no G) and nondegenerate TGG = 
tryptophan) that allows a degeneracy of 22 unique codons for the 20 natural 
amino acids to be created. With this approach, codon redundancy and screen-
ing effort are decreased (eg, to saturate two positions with NNK primers, 3068 
clones must be screened while using the three primer trick only 1450 clones are 
needed for a library coverage of 95%) (Kille et al., 2013).
8.2.2 DNA Recombination Methods
DNA recombination is fundamental to harness the selected mutant offspring 
from epPCR libraries or to create a complete set of chimeric proteins from dis-
tant parental types. Since the invention of in vitro DNA shuffling by Stemmer 
in 1994, many DNA recombination protocols have been reported, fostering the 
rapid growth of directed enzyme evolution. Here, we will only refer to the most 
common methods and to some protocols developed in our laboratory that are 
supported by the machinery of S. cerevisiae.
8.2.2.1 In Vitro Methods
8.2.2.1.1 Homology-Dependent Recombination Methods
Due to their extreme simplicity in terms of structural requirements and the ease 
of library construction, homology-dependent recombination methods are the 
most frequentlyemployed protocols for switching two or more templates (eg, 
DNA shuffling (Stemmer, 1994); StEP (Zhao et al., 1998); RACHITT (Coco 
et al., 2001); DOGS (Gibbs et al., 2001)).
1. In vitro DNA shuffling: this method allows the recombination of parental 
genes with only 63% sequence identity (Stemmer, 1994). It takes advantage 
of the random fragmentation of parental genes by DNase I and their reas-
sembly in a primer-free PCR reaction. DNA shuffling is commonly used to 
recombine highly distant parental types (DNA family shuffling) or to com-
plement other in vitro recombination protocols (see below).
2. StEP (Staggered Extension Process): this method involves iterative cycles 
of denaturing and priming/extension from two or more parental genes in 
the absence of primers (Zhao et al., 1998). In all PCR cycles, each ampli-
fied fragment will anneal to a different parental template due to sequence 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 191
complementarity, and it will continue the extension process giving rise to a 
full collection of chimeric products. It is useful to recombine the best mutant 
offspring from a round of directed evolution, as well as to mix different 
genes from the same family with sequence identities above 80%.
8.2.2.1.2 Homology-Independent Recombination Methods
Distinct homology-independent recombination methods have emerged to fill 
the gap when attempting to recombine structural related enzymes but with 
weak DNA identity (eg, ITCHY (Ostermeier et al., 1999); SCRATCHY (Lutz 
et al., 2001a); SHIPREC (Sieber et al., 2001); USERec (Villiers et al., 2010); 
RM-PCR (Tsuji et al., 2001); SISDC (Hiraga and Arnold, 2003)).
1. ITCHY (Incremental Truncation for the Creation of HYbrid enzymes): 
ITCHY allows chimeric libraries to be designed between two distant paren-
tal types (even those that have a sequence identity below 50%). Firstly, the 
two parental types are cloned in tandem (ie, in a single vector), followed by 
the vector linearization between them. Subsequently, exonuclease III from 
Escherichia coli incrementally truncates one parental gene from its 3´ end 
and the other from its 5´ terminus, which is followed by intramolecular liga-
tion of random truncated fragments to yield a full set of chimeric products 
(Ostermeier et al., 1999). New versions of this method include thio-ITCHY, 
which uses α-phosphorothioate dNTPs to avoid inaccuracies during time-
dependent exonuclease III digestion (Lutz et al., 2001b).
2. SHIPREC (Sequence Homology-Independent Protein RECombination): 
Like ITCHY, SHIPREC is employed to design chimeras irrespective of 
their relative sequence identity (Sieber et al., 2001). In this case, a fusion 
gene is created that is comprised of the two parental types by linking the 
C- and N-termini with a small linker containing a unique restriction site. 
This fusion construct can then be fragmented randomly by DNase I and S1 
nuclease, yielding a library of blunt end-fusion constructs. Upon circular-
izing the library by intramolecular blunt-end ligation and by introducing a 
cleavage step using the restriction site, a library enriched in chimeric genes 
is produced that can be cloned into a suitable expression vector.
8.2.2.2 In Vivo Methods
Since its discovery in 1981, the homologous recombination in S. cerevisiae has 
generated great interest among cell and molecular biologists (Orr-Weaver et al., 
1981), and it has since then become the model of choice to study homologous 
recombination. It is well known that homologous sequences of 40 to 50 base 
pairs are sufficient to drive in vivo splicing of DNA fragments, one to another 
(Oldenburg et al., 1997). This principle can be applied to the in vivo cloning 
of mutant libraries together with a linearized plasmid, as well as to perform 
DNA shuffling of parental genes (Gonzalez-Perez et al., 2012). Homologous 
recombination in vivo is independent of cleavage sites since it neither requires 
192 Biotechnology of Microbial Enzymes
restriction enzymes nor in vitro ligation. The sequence generated after recombi-
nation is similar to that obtained by in vitro methods but without the disruptions 
due to the insertion of restriction sites or linker sequences. All the protocols 
described in this section are based on the high frequency of homologous recom-
bination in S. cerevisiae. As an important tip for the methods described below, 
the design of overlapping overhangs to favor the in vivo splicing and recombina-
tion between fragments is crucial for rapid and efficient mutant library creation.
1. In vivo DNA shuffling: Full parental genes (unfragmented) with DNA 
sequence identities as low as approximately 50% can be in vivo shuffled at 
the same time that they are cloned into a linearized plasmid with overhangs 
complementary to the ends of target genes. This simple method is extremely 
useful when evolving eukaryotic genes in yeast, permitting the recombina-
tion of several parental types and their cloning in one-pot (Cherry et  al., 
1999). In our experience, mutations at a distance of ≥20 residues from one 
another can be shuffled by the yeast’s in vivo gap repair mechanism. We 
have used this method as the main recombination protocol in the evolution 
of different ligninolytic genes (Garcia-Ruiz et al., 2014; Alcalde, 2015).
2. CLERY (Combinational Libraries Enhanced by Recombination in Yeast): 
CLERY combines in vitro and in vivo DNA shuffling in a single round of 
evolution. This method was validated for the creation of chimeric human 
cytochrome P450 with 74% nucleotide sequence identity (Abecassis et al., 
2000), and more recently, to design chimeric laccases with only 51% nucle-
otide sequence identity (Pardo et al., 2012).
3. Mutagenic StEP + in vivo DNA shuffling: We recently modified the StEP 
method to introduce point mutations during amplification (mutagenic StEP). 
The chimeric library obtained in this way was subjected to further recom-
bination through in vivo shuffling in order to design thermostable versatile 
peroxidases (Garcia-Ruiz et  al., 2010, 2012) and blood tolerant laccases 
(Mate et al., 2013a,b). Both CLERY and this method are useful when trying 
to increase the number of crossover events in chimeric libraries.
4. IVOE (In Vivo Overlap Extension): This is a fast and reliable method that 
mimics classic sequence overlap extension (SOE, also known as double 
PCR). By transforming the PCR fragments containing homologous over-
hangs along with the linearized plasmid into yeast, several amplification 
and ligation steps are avoided, while the proof-reading apparatus of S. cer-
evisiae prevents the inclusion of undesired mutations. This approach can be 
efficiently used for site-directed mutagenesis (including insertion and dele-
tion mutagenesis), CSM, site-directed recombination, and gene assembly 
(Alcalde, 2010). IVOE has been exploited exhaustively in our laboratory for 
the directed evolution of ligninases (Garcia-Ruiz et al., 2014; Alcalde, 2015; 
Mate and Alcalde, 2015).
5. MORPHING (Mutagenic Organized Recombination Process by Homologous 
IN vivo Grouping): We designed MORPHING as a random domain 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 193
mutagenesis method to focus mutational loads and recombination events on 
specific protein segments while the remaining protein regions keep unaltered 
(Gonzalez-Perez et al., 2014a). Mutant segments as short as 30 amino acids 
are subjected to epPCR while the remaining fragments are amplified with 
high-fidelity polymerases. The DNA fragments are flanked with homolo-
gous overhangs at their 5´ and 3´ ends, and they are spliced in vivo along 
with the linearized vector in a one-pot step. MORPHING has been used to 
improve the oxidative stability of a versatile peroxidase (Gonzalez-Perez 
et al., 2014b), to enhance secretion of an unspecific peroxygenase (Molina-
Espeja et al., 2014) and to find consensus-ancestor mutations in aryl alcohol 
oxidases (Viña-Gonzalezet al., 2015).
6. DNA puzzle: This method was developed recently in our lab to recover 
putative beneficial mutations that are lost through the evolution process 
(Gonzalez-Perez et al., 2014b). With DNA puzzle, mutations discarded by 
regular recombination approaches are relocated in independent sequence 
blocks that can be amplified and recombined with each other to identify 
epistatic effects in new mutational environments.
As a final reflection, the combination of random mutagenesis and DNA 
recombination methods with rational and semirational approaches has proved 
to be effective in directed evolution experiments (Fig. 8.2). Such strategies 
not only compensate the mutational bias of each method but they also permit 
sequence diversity to be enriched, increasing the fraction of functional enzymes 
in the mutant library. As a rule of thumb, a thorough analysis of each round of 
evolution gives clues and directions about which approaches should be followed 
in successive rounds. Given that there are very few chances to find beneficial 
mutations in a directed evolution experiment (generally less than 0.5% of ran-
dom mutations are beneficial (Bloom and Arnold, 2009)), it is much easier to 
damage an enzyme than to improve it. Therefore, the subtle incorporation of 
mutations and their recombination in consecutive generations, analyzing the 
synergies and interactions between the mutations carried by the offspring of 
interest, is our preferred approach.
8.3 COMPUTATIONAL TOOLS
Combining computational algorithms with directed evolution allows CSM, 
DNA recombination or epPCR methods to be performed in a more effective 
way, leading to biocatalysts with strong biotechnological potential while reduc-
ing notably the demands on screening. Indeed, the courtship between in silico 
computational approaches and directed evolution reduces the time to construct 
smart mutant libraries. In recent years, different computational methods have 
emerged that take advantage of the thousands of sequences and structures 
deposited in gene and protein databases (Verma et  al., 2012a,b). Compre-
hensive reviews of these computational tools have been recently published 
FIGURE 8.2 Some representative methods used to mutagenize/recombine target gene(s). epPCR: error-prone PCR; MORPHING: Mutagenic Organized 
Recombination by Homologous IN vivo Grouping; ISM: Iterative Saturation Mutagenesis; StEP: Staggered Extension Process.
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 195
(Damborsky and Brezovsky, 2014; Sebestova et al., 2014), so here we will sim-
ply mention a few representative examples of the most common computational 
algorithms used to date.
1. SCHEMA: This computational method allows libraries to be designed by 
recombination of several homologous sequences (with as little as 55 % iden-
tity) while maximizing the number of folded proteins (Voigt et al., 2002). 
SCHEMA predicts the fragments that must be inherited in the same parent, 
thereby allowing the computational selection of blocks from which novel 
proteins (chimeras) can be assembled. The selection of crossover locations 
is based on a metric for disruption, defined as the number of interactions of 
a hybrid protein that are broken when a given pattern of fragments is inher-
ited from each of the parents (ie, the pairs of residues within 4.5 Å of each 
other that are not present as the same pair in any of the parents—defined as 
SCHEMA energy <E>). This method requires a multiple sequence align-
ment of the parental sequences, a PDB file, and a UNIX-based computer. 
While SCHEMA can be combined with the RASSP algorithm for sequence 
elements that are contiguous along the polypeptide chain (Endelman 
et al., 2004), the swapping of elements that are not contiguous in primary 
sequence can be performed by using the NCR algorithm in combination 
with SCHEMA (Smith et al., 2013).
2. MAP (Mutagenesis Assistant Program): MAP compares the different ran-
dom mutagenesis methods available and their consequences in terms of 
mutational bias at the level of amino acid substitution (Wong et al., 2006b). 
MAP is used to predict the quality of the mutant library based on the epPCR 
method chosen and the nucleotide composition of the target gene. It works 
at three levels of information using three distinct indicators: (1) the protein 
structure indicator provides data about the likelihood of introducing stop 
codons and residues that destabilize the helical structure (Pro, Gly), (2) the 
amino acid diversity indicator shows the proportion of variants with pre-
served amino acids (ie, amino acids that do not change with a single nucleo-
tide substitution—silent mutations—) and the average number of amino acid 
substitutions after a single nucleotide change, and (3) the chemical diversity 
indicator provides the chemical diversity generated in terms of amino acid 
substitution (aliphatic, aromatic, neutral, charged). The new version of the 
server (MAP2.0 3D) permits further mapping of the sequence indicators onto 
the target protein’s 3D structure, correlating the pattern of amino acid substi-
tution with structural information regarding local interactions solvent acces-
sibility, residual motility, and secondary elements (Verma et  al., 2012a,b, 
2014). To work, MAP2.0 3D requires only the target gene sequence and a 
PDB file (or a homology model) of the protein.
3. HOT-SPOT WIZARD: This algorithm predicts hot-spot residues for CSM 
to modify activities and stability, precluding catalytic determinants from 
mutagenesis (Pavelka et al., 2009). For each individual amino acid, the tool 
196 Biotechnology of Microbial Enzymes
gives information about the degree of mutability (and possible amino acid 
substitution at that position), functional and structural significance, and 
similar residues in related enzymes. The server integrates data from several 
bioinformatics databases allowing structural and evolutionary previews to 
be performed. The requirements to run HotSpot Wizard are minimal, only 
the PDB file of the target protein.
4. 3DM: The 3DM protein superfamily platform is a commercial database that 
is useful to explore sequence-function relationships (Kuipers et al., 2010). 
By superimposing protein family structures from different sources (includ-
ing mutations reported in the literature), a structure sequence alignment 
provides valuable information about conserved residues and more mutable 
amino acids to create CSM libraries.
5. ProSAR (Protein Sequence Activity Relationship): This computational plat-
form unmasks beneficial mutations from experimental mutant libraries (even 
from mutants with reduced function) to be incorporated into new iterative 
rounds of directed evolution. ProSAR follows the same principles that rule 
QSAR (an algorithm used for drug design) but applied to protein engineer-
ing to sort out beneficial, neutral, and detrimental mutations from a given 
mutant library in order to find new epistatic effects within a given protein 
scaffold (Fox et al., 2007).
8.4 FUNCTIONAL EXPRESSION SYSTEMS
The choice of a suitable host to functionally express a target enzyme is critical 
in directed evolution. The main organisms used include bacteria (E. coli and 
Bacillus sp.), yeast (S. cerevisiae, Pichia pastoris), and to a much lesser extent 
mammalian and insect cell lines. Gene expression in heterologous systems may 
imply differences in codon usage, chaperones, and posttranslational modifica-
tions, all of which must be taken into account before starting a directed evolu-
tion process. Depending on the host, the directed evolution timeline can vary 
notably due to the different growth rates of the organisms. For example, the 
doubling time for a prokaryotic host like E. coli is between 0.25–0.33 hours, 
whereas it takes from 2 to 3 days in the insect cell line Spodoptera frugiperda 
Sf9 (Pourmir and Johannes, 2012). For all these reasons, the bacteria E. coli and 
the brewing yeast S. cerevisiae areby far the most common hosts for directed 
evolution of prokaryotic and eukaryotic genes, respectively.
Since its discovery in 1886 by Theodor Escherich, E. coli has been widely 
studied and hence, dozens of standardized protocols exist for its genetic manip-
ulation. Due to its ease of handling and biological attributes (fast growth, 
high transformation efficiency), E. coli leads the list of host organisms used 
in directed evolution. However, in vitro library creation is often complicated 
and more significantly, E. coli lacks essential posttranslational modification and 
specific chaperones needed when expressing eukaryotic genes. Thereby, many 
attempts to produce eukaryotic proteins in E. coli result in the accumulation of 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 197
proteins in inclusion bodies and/or misfolding (Khow and Suntrarachun, 2012). 
In such cases, the organism of choice is S. cerevisiae as it offers similar process-
ing machinery to higher eukaryotic cells. Moreover, although S. cerevisiae has 
a slower growth rate (with a doubling time of 1.25–2 hours) and its transforma-
tion efficiency is approximately 2 orders of magnitude lower than that of E. coli 
(107–108 and 108–1010 transformants per μg of DNA, respectively), it does pos-
sess a high frequency of homologous DNA recombination with proof-reading 
activity that is very convenient to create mutant libraries, as described above 
(Gonzalez-Perez et al., 2012). Another attractive advantage of this host is that it 
can secrete heterologous proteins to the culture broth, avoiding tedious lysis steps 
and cumbersome interactions during screening assays. However, what is prob-
ably the main pitfall of using S. cerevisiae relates with its poor level of secretion 
when compared to other industrial hosts (eg, Aspergillus oryzae, P. pastoris). 
Unfortunately, the latter are far from ideal for directed evolution due to the lack 
of episomal vectors, their low transformation efficiencies and complex plasmid 
recovery. Thus, using tandem-expression systems (ie, S. cerevisiae for evolution 
and P. pastoris or A. oryzae for overproduction) can help to circumvent these 
hurdles, as long as the evolved enzyme properties are maintained in the produc-
tion host (Mate et al., 2013b; Molina-Espeja et al., 2015).
8.5 MUTANT LIBRARY EXPLORATION
Along with the creation of genetic diversity and the functional expression of 
mutant libraries, the success of directed evolution experiments depends on the 
development of reliable and robust methods to explore the desired enzyme prop-
erty (Arnold and Georgiou, 2003b; Martínez and Schwaneberg, 2013). Ideally, 
such methods must be robust, reliable, sensitive, and reproducible. The tech-
niques available to explore mutant libraries can be classified as genetic selec-
tion methods, or as high-throughput and ultrahigh-throughput screening assays 
(Table 8.1).
8.5.1 Genetic Selection Methods
Genetic selection methods allow very large libraries (~109 clones per round) 
to be explored and they do not require special instrumentation. They are spe-
cifically designed to detect enzyme features linked to the survival of the host 
(Leemhuis et al., 2009) and therefore, these selection methods are mainly lim-
ited to explore detoxifying enzymes or enzymes associated to host metabolism 
(Boersma et al., 2008; Reetz et al., 2008). For this reason they are complicated 
to use when attempting to improve nonnatural functions, such as activity on 
nonnatural substrates or in harsh environments (eg, high temperature, extreme 
pH, or in the presence of nonconventional media like organic cosolvents and 
ionic liquids).
TABLE 8.1 Selection and Screening Methods Used in Directed Evolution
Approach Library size Advantages Limitations References
Selection ∼109 Yields desirable variants. No special 
instrumentation required
Only possible for detoxifying 
enzymes or enzymes that 
synthesize essential nutrients for 
cell growth and survival
Leemhuis et al. (2009)
Agar plate-based 
screening
∼105 Easy manipulation. Useful as 
prescreening method
Low sensitivity. Substrate must 
be supplemented as part of the 
growth medium
Tobias and Joern 
(2003)
Microtiter plate 
screening
∼103–104 Availability of a wide range of analytical 
tools and robotic automation
Relatively low screening 
capacity
Salazar and Sun (2003)
Cell surface display ∼109 Large libraries Fluorescence detection Lane and Seelig (2014)
Liposome display ∼107 Rapid and efficient evolution of various 
proteins, including pore-forming proteins, 
transporters and receptors
Fluorescence detection Fujii et al. (2013) and 
Fujii et al. (2014)
Megavalent bead 
display
∼109 Up to 106 copies of the DNA and the 
protein or peptide of interest are 
displayed on the beads
Fluorescence detection Diamante et al. (2013)
Cell as microreactor ∼109 Large libraries. No compartmentalization 
needed. Femtoliter scale (not much 
reagent needed)
Product should stay in the 
cell. Differences in catalytic 
performance depending on the 
metabolic state of cells
Martínez and 
Schwaneberg (2013)
GFP and its variants 
as reporters
∼107–108 No need of fluorescent substrate Desired function or enzyme 
activity must be linked to GFP 
expression
Yang and Withers 
(2009)
TABLE 8.1 Selection and Screening Methods Used in Directed Evolution
Approach Library size Advantages Limitations References
Ligand-mediated 
eGFP expression 
system 
(LiMEx)
∼107 No need of fluorescent substrate. 
Allows the detection of subtle differences 
in intracellular concentrations of 
metabolites
Desired function or enzyme 
activity must be linked to GFP 
expression
Cheng et al. (2015)
Cell-in-droplet 
screening
∼109 Large libraries. Femtoliter scale 
(not much reagent needed)
Substrates and products that 
do not cross the oil-phase 
barrier of the droplets are 
needed. Differences in catalytic 
performance depending on the 
metabolic state of cells
van Rossum et al. 
(2013)
Cellular High-
Throughput 
Encapsulation 
Solubilization and 
Screening (CHESS)
∼108 Applicable for directed evolution of 
both soluble and membrane proteins
Proteins lower than 70 kDa 
can diffuse out of the capsules. 
Capsules are not resistant 
to highly basic solutions. A 
fluorescent read-out of protein 
integrity is required for FACS
Scott and Plückthum 
(2013) and Yong and 
Scott (2015)
Fur-shell technology ∼107 Adaptable to other hydrolytic enzymes 
that use substrates in which β-D-glucose 
is released upon hydrolysis
Differences in catalytic 
performance depending on the 
metabolic state of cells
Pitzler et al. (2014)
In vitro 
compartmentalization 
(IVC)
∼1010 Large libraries. No cloning and 
transformation steps. Femtoliter scale 
(not much reagent needed)
Substrates and products that do 
not cross the oil-phase barrier 
of the droplets are needed
Griffiths and Tawfik 
(2006)
Phage-assisted 
continuous evolution 
(PACE)
n.r. Dozens of rounds of evolution in one 
day with minimal researcher intervention. 
It does not require the manufacture of 
specialized components
The gene encoding the protein 
target of evolution must be 
linked to pIII production in 
E. coli
Esvelt et al. (2011) and 
Dickinson et al. (2014)
n.r.: not reported.
200 Biotechnology of Microbial Enzymes
8.5.2 High-Throughput Screening (HTS) Assays
Although with a weaker capacity for exploration than selection methods, 
HTS assays allow enzyme function to be uncoupled from host survival. These 
methods are generally based on changes in absorbance or fluorescence emis-
sion, such that small improvements derived from single amino acid substitu-
tions can be detected. HTS assays can be performed in solid or liquid phase.
1. Solid phase screening assays: Agar plate-based screening involves visual 
changes after substrate conversion (ie, qualitative measurements in terms 
of color, fluorescence, or halo formation around the colonies), changes that 
can be detected withthe naked eye or by digital image analysis (Tobias 
and Joern, 2003). The main advantages of these solid phase assays are their 
relatively easy of handling and medium throughput capacity (~105 clones 
per round) (Leemhuis et  al., 2009). Nevertheless, they are often limited 
by: (1) their poor sensitivity since soluble products diffuse away from the 
colony and only very active mutants can be detected and (2) interference 
with cell growth provoked by the chromogenic or fluorogenic substrates that 
are added as supplements to the agar medium (although the use of transfer 
membranes can help alleviate this problem (Aharoni et al., 2005)).
2. Liquid phase screening assays: Known as microtiter plate (MTP) based 
screening methods, are the most common format used. They offer a low 
to medium screening capacity (~103–104 clones per round) but they permit 
the individual analysis of each component of the mutant library and their 
comparison with the parental type (Leemhuis et al., 2009). Typically, single 
colonies from a mutant library are inoculated into 96-well plates (master 
plates), grown until stationary phase (biomass production), and replicated 
into a second 96-well plate for enzyme expression. All the protein variants 
are then extracted, either by cell lysis (intracellular enzymes) or by remov-
ing the biomass (extracellular enzymes), and screened in microtiter plate 
format to quantify the changes in absorbance or fluorescence (van Rossum 
et al., 2013).
The optimization and validation of MTP-based screening methods is typi-
cally performed by evaluating the linearity of the assay and the coefficient of 
variance (CV). In practice, CV values below 15% are acceptable for directed 
evolution experiments. It is also important to adjust the conditions of the assay so 
that the activity of the wild-type/parental enzyme is close to the detection limit 
of the assay (never below). The use of special equipment helps to achieve good 
CV values (humidity shakers, colony pickers, liquid handlers, pipetting robots, 
etc.), avoiding the abundant generation of false positives. If available, solid-phase 
assays can be used for prescreening before the selected clones are further sub-
jected to MTP-based screening. In MTP assays, it is wise to include a full column 
in each plate with the parental type (internal standard) in order to estimate the 
improvements achieved for each individual mutant in each single plate.
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 201
8.5.3 Ultrahigh-Throughput Screening Assays
Next in the throughput scale are the fluorescence-activated cell sorting (FACS)-
based screening methods. FACS cytometers are complex instruments that 
can analyze the fluorescent characteristics of individual “particles” (eg, cells, 
liposomes, beads, emulsion droplets, or polymer shells) at extremely high event 
rates (~107 per hour), isolating those with the strongest signal for the desired 
trait (Yang and Withers, 2009; Pitzler et al., 2014). The main bottleneck in the 
use of these systems is that they are not generally applicable since they require 
linking the genotype (a nucleic acid that can be replicated) and phenotype (a 
functional feature like binding or catalytic activity) in an ultrahigh-throughput 
context (Griffiths and Tawfik, 2006). In other words, active enzyme mutants 
should only label the particle in which they are produced. This can be attempted 
through the accumulation of a fluorescent product in the particle, permitting the 
identification and recovery of the active variants, although this is not always 
an easy task (Martínez and Schwaneberg, 2013). FACS-based screening tech-
niques can be classified into five distinct categories according to the methods 
used to link the genotype and phenotype: (1) cell surface display (or in vivo 
display) of active enzymes, (2) in vitro display, (3) green fluorescent protein 
(GFP) methods, (4) entrapment of the product inside the cells, and (5) in vitro 
compartmentalization.
1. Cell surface display: This involves the attachment of heterologous enzymes 
to the surface of bacteria (bacterial surface display (van Bloois et al., 2011)), 
yeast (yeast surface display (Boder and Wittrup, 1997)) or phages (phage 
surface display (Fernandez-Gacio et  al., 2003)). Cell display offers ultra-
high-throughput capacity of up to 109 clones per round and allows direct 
contact between the enzyme and the added substrate, without requiring dif-
fusion through the cell membrane. However, this accessibility is at the same 
time a major drawback as the product is also freely diffusible.
2. In vitro display: This method is based on the synthesis of the target protein 
for evolution through an in vitro translation system so that the genotype-
phenotype linkage is achieved using molecules like ribosomes (ribosome 
display), puromycin (mRNA display), and the DNA replication initiator pro-
tein RepA (CIS display). More recently, novel in vitro display approaches 
have been reported that include liposome and megavalent bead display. 
Liposome display enables membrane proteins to be engineered, and it relies 
on their display on liposome membranes through the transcription and trans-
lation of a single DNA molecule using an encapsulated cell-free transla-
tion system (Fujii et al., 2014). Megavalent bead surface display allows to 
tailor-made protein binders by laboratory evolution. In this method, the gene 
that encodes the protein of interest is attached to a bead by strong noncova-
lent interactions and the corresponding protein is displayed via a covalent 
thioether bond on the DNA (Diamante et al., 2013).
202 Biotechnology of Microbial Enzymes
3. Green fluorescent protein (GFP) methods: Due to their autofluorescent 
properties, GFP and its variants are ideal candidates for single-cell fluores-
cence analysis and, therefore, they can be used in flow cytometry screening 
(Yang and Withers, 2009). The main advantages of GFP-based screening 
methods are their very high-throughput (∼107–108 clones per round) and the 
lack of expensive fluorescent substrates. Nonetheless, the enzymatic func-
tion or activity of interest must be linked to GFP expression, a requirement 
that cannot always be met by all protein systems.
4. Entrapment of the product inside the cells: An alternative to cell surface dis-
play strategies and GFP-based screening methods are in vivo FACS-based 
screening approaches in which the fluorescent product is trapped within the 
cell (Yang and Withers, 2009). This approach, also known as a cell microre-
actor, must overcome the challenge of designing substrates that are accessi-
ble to the enzyme inside the cell and ensuring that the diffusible fluorescent 
products stay within the cell. This can be readily achieved if the enzyme 
catalyzes reactions in which the size, polarity, or other chemical proper-
ties of the substrate are modified, resulting in the retention of the product 
within the cell. The drawback of substrate/product entrapment in the cell 
has been overcome by developing cell microencapsulation techniques that 
imitate natural cell compartmentalization eg, including the target enzyme 
in microemulsion droplets along with the substrate and products (Griffiths 
and Tawfik, 2006). The main advantages of the cell-in-droplet approach are 
its ultrahigh-throughput capacity (~109 clones per round) and the reduced 
volume of the microemulsions (typically ~5 femtoliters), such that little 
substrate is needed (Aharoni et  al., 2005). Very recently, novel screening 
platforms using polymer encapsulated cells have been developed like: (1) 
the cellular high-throughput encapsulation, solubilization and screening 
(CHESS) method to allow the encapsulation of libraries of approximately 
108 mutants in a polymer to form cell-like microcapsules (Yong and Scott, 
2015) and (2) the polymer shell (fur-shell) method that relies on fluorescent 
hydrogel formation around E. coli cells (Pitzler et al., 2014).
5.In vitro compartmentalization (IVC): Microencapsulation can be performed 
in the absence of cells, directly producing the enzyme from the DNA library 
by in vitro protein translation. Such IVC offers the advantage of generating a 
large number of droplets per emulsion volume unit (>1010 in 1 mL of emul-
sion), coupled to the ease of preparing emulsions and their high stability to 
changes in temperature, pH, and salt concentrations (Aharoni et al., 2005). 
Additionally, IVC prevents the gene diversity loss derived from the cloning 
and transformation steps by in vitro protein translation of the DNA used 
to generate the mutant library; moreover, it reduces experimental time by 
skipping the cell growth steps associated with cloning, transformation, and 
protein production (Martínez and Schwaneberg, 2013).
For all the strategies described above, a single round of directed evolu-
tion involves mutation, gene expression, screening, or selection, all of which 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 203
typically requires weeks with frequent researcher involvement. In order to 
speed up the overall process, the phage-assisted continuous evolution (PACE) 
platform was recently developed, which enables extremely rapid evolution of 
biomolecules with minimal human intervention (Esvelt et al., 2011). The PACE 
system is based on a fixed-volume vessel (a “lagoon”) where a continuously 
replicating phage carries an evolving gene of interest. Phage-free host E. coli 
cells are constantly supplied to the lagoon and as the infection ability of phage 
is linked to the function of the target gene, phage-encoding inactive mutants 
produce non-infectious host cells that are diluted out of the lagoon, permitting 
hundreds of rounds of evolution to be carried out in a few days.
In summary, there are a variety of screening and selection techniques cur-
rently available for laboratory evolution. The choice of one method or another 
depends on the convergence of several factors, which include the nature of the 
enzyme target, the feature to be engineered, and the facilities that are available 
in a given laboratory. Current MTP-based screening methods are those most 
often used in directed evolution, thanks to their easy set-up and the wide avail-
ability of compatible instruments. Although the number of sophisticated ultra-
HTS platforms has grown significantly in recent years, there is still a long way 
to go before they can be implemented as a routine approach to screen mutant 
libraries.
8.6 FORTHCOMING TRENDS IN DIRECTED EVOLUTION
In this last section we will briefly discuss some emergent methods and new 
strategies in directed enzyme evolution.
1. Neutral genetic drift: Neutral drift is an evolutionary approach that emulates 
neutral natural evolution, whereby many different genotypes can lead to the 
same phenotype. Neutral drift in the laboratory is based on the accumulation 
of neutral mutations by iterative cycles of epPCR and screening to maintain 
the protein's native function (Peisajovich and Tawfik, 2007). Libraries cre-
ated by this technique are characterized by their high diversity and quality, 
that is, they are enriched in folded and active variants. This contrasts with 
conventional directed evolution where the library is mostly comprised of 
inactive variants due to the accumulation of deleterious mutations, espe-
cially when using high mutational loads (Gupta and Tawfik, 2008).
Repeated rounds of random mutation and purifying selection generate 
highly polymorphic networks, which if expanded sufficiently can generate 
different genotypes with a similar functional phenotype (ie, natural activity), 
while unmasking hidden properties in terms of stability and substrate prom-
iscuity (Bloom et al., 2007a,b; Bershtein and Tawfik, 2008; Tokuriki et al., 
2008; Romero and Arnold, 2009; Tokuriki and Tawfik, 2009). Neutral drift 
can be utilized when searching for activity on novel substrates to which the 
parental protein displayed weak (latent activity) or no activity. Furthermore, 
it can be applied to further enhance an activity that appears to have reached 
204 Biotechnology of Microbial Enzymes
an activity plateau (ie, after several rounds of directed evolution the improve-
ments in activity are barely detectable (Tokuriki et al., 2012)). Neutral drift 
is also useful to increase stability, even by drifting the protein network closer 
to the consensus/ancestral sequence (Bershtein and Tawfik, 2008). In addi-
tion, it can be used prior to the start of an evolution campaign to enhance 
stability or the promiscuous activity of the parental type.
The critical point in neutral drift is to determine the selection cut-off 
which is dependent on the final objective of the experiment. When search-
ing for high stability variants, suggestions include the use of low mutational 
loads while strictly purging the library to retain a high level of native activity 
(over 75% of the parental activity). On the other hand, when pursuing latent 
activities, the advice is to use higher mutational loads and milder cut-offs to 
generate a very diverse population (over 30% of the parental activity). If the 
cut-off is set too high, the library will become too uniform and promiscuity 
will be very difficult to achieve (Kaltenbach and Tokuriki, 2014) (Fig. 8.3).
2. Circular permutation: In nature, this consists in the relocation of the N- and 
C-termini of a given protein, which possibly commences through the tandem 
duplication of a precursor gene. The evolutionary advantages of circular per-
mutation in nature are not fully understood, yet in the laboratory circular 
permutation is providing a new twist to directed evolution experiments as 
FIGURE 8.3 Combination of neutral drift and adaptive evolution to pursue novel functions. 
After employing neutral drift on the wild-type protein (represented as the small circle in dark orange) 
and expanding the neutral polymorphic network (enclosed in the large black circle), latent promis-
cuous activities are detected and can be defined by the sequences in the intersecting regions (small 
circles in light orange). Those sequences, although retaining some or all native activity (depending 
on the threshold selected), represent ideal starting points for adaptive evolution towards promiscu-
ous activity 1, 2, 3, or 4 (arrows and small circles in red, dark blue, green, and grey, respectively).
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 205
it can modify activities, specificities and stabilities (Yu and Lutz, 2011). 
Through in vitro circular permutation, the amino acid composition of the 
target enzyme is not altered but rather, the structural reorganization of the 
whole protein simply gives rise to new topologies with unexpected func-
tions. Circular permutation protocols include: (1) the covalent connection 
of the native N- and C-termini of the target gene with the help of a short 
peptide linker, (2) random DNase I cleavage of a peptide bond in the primary 
sequence, and (3) screening of the circular permutation library. Among the 
most important issues to consider when creating circular permutation librar-
ies are: (1) the peptide linker length and composition, (2) that the native 
C- and N-terminus of the protein lie within 20 Å of each other (as is the case 
for most natural proteins), and (3) the inclusion of start and stop codons 
preceding the cloning site in the linearized vector.
3. De novo enzyme design: In recent years, the development of quantum 
mechanics/molecular mechanics (QM/MM), molecular dynamics and Monte 
Carlo algorithms has permitted their implementation in directed evolution 
and in rational studies to evaluate protein–substrate interactions, catalytic 
determinants, and stability (Kiss et al., 2013; Carvalho et al., 2014). Taking 
advantage of computational simulations, the engineering of de novo enzymes 
has generated significant scientific interest as it allows artificial biocatalyststo be tailor-made using algorithms like ROSSETA or ORBIT, mimicking 
enzyme function (Golynskiy and Seelig, 2010; Kries et al., 2013). The pro-
cess involves four essential steps: (1) selection of the target reaction, includ-
ing the catalytic mechanism and the functional groups involved, (2) modeling 
of the most stable structure of the rate limiting transition state (theozyme), 
(3) docking of the theozyme into a palette of protein scaffolds from PDB, and 
(4) production of the de novo enzyme in a heterologous host. Nonetheless, 
these types of enzymes show often poor catalytic rates, an inconvenience that 
can subsequently be surpassed by directed evolution (Blomberg et al., 2013).
4. Metagenomics: The exploitation of the vast genetic reservoir of bacteria and 
fungi from extreme environments can be useful to isolate more robust genes/
enzymes. As such, metagenomics offers a great potential for industrial bio-
catalysis due to its access to the limits of natural biological and molecular 
diversity (Lorenz and Jürgen, 2005; Chistoserdova, 2014). Indeed, the com-
bination of metagenomics and directed evolution can aid the pursuit of more 
potent biocatalysts for numerous applications where processing conditions 
are severe. Verenium, the successor of Diversa, is a biotech company whose 
old slogan “evolve the best from nature” anticipated this approach almost 
two decades ago. Nevertheless, there are only a few examples of academic 
groups that apply directed evolution to enzymes that have emerged from 
metagenomic environments, among them: a metagenome-derived thermo-
philic lipase from a hot spring engineered to enhance its catalytic efficiency 
(Kumar et al., 2013); an alkaline laccase from mangrove soil to decolorize 
textile dyes (Liu et al., 2011); and a metagenome-derived epoxide hydrolase 
206 Biotechnology of Microbial Enzymes
from a microbial biofilter community to improve enantioselectivity (Kotik 
et al., 2013). Even though enzymes from metagenomics sources are ideal 
starting points for directed evolution due to their implicit stability, the lack 
of suitable hosts for library construction and exploration (especially in the 
case of fungi) has precluded faster development. Hence, the identification 
and engineering of suitable heterologous hosts is being actively pursued to 
enhance the efficiency of metagenomic gene expression and directed evolu-
tion (Yang and Ding, 2014).
5. Resurrection of ancestral proteins: The increasing growth of sequence data-
bases, DNA synthesis techniques, and phylogenetic evolutionary methods are 
helping us to understand the origin of the proteins on our planet and of life as 
we know it (Benner et al., 2007). Indeed, paleoenzymology allows us to travel 
back in time to recover ancestral proteins at the molecular level of organisms 
that are already extinct. This approach is very valuable to create ancestral and 
ancestral-like proteins whose activities and stabilities extend beyond those of 
their extant counterparts (Gaucher et al., 2008; Arnaud, 2013). While enzyme 
reconstruction and resurrection has been used over the years to discern the 
principles behind natural protein evolution, its combination with directed 
evolution could lead to a new generation of biocatalysts. We can already 
find solid examples of highly thermostable and promiscuous resurrected 
Precambrian enzymes in the literature, such as thioredoxins and β-lactamases 
(Perez-Jimenez et al., 2011; Risso et al., 2013), many of which could be now 
evolved in vitro to further exploit their rediscovered traits. Our laboratory is 
devoted to evolve different resurrected enzymes with strong tolerance to high 
mutational loads (due to the mutational robustness linked to their stability) 
and wide substrate promiscuity. Indeed, the combined directed evolution of 
modern and ancestral enzymes will provide a deeper understanding of protein 
evolution while driving the engineering of superior biocatalysts.
8.7 CONCLUDING REMARKS
Directed evolution has opened several avenues for protein engineers and molec-
ular biologists that only existed in our dreams some years ago. The rapid pro-
gress in synthetic biology and metabolic engineering has led to a new way of 
making biocatalysts, which has had a strong impact on each of the four colors in 
biotechnology (white, industrial; green, agricultural; red, biopharmaceuticals; 
and blue, marine biotechnologies (Alcalde, 2015)).
Still, there are several challenges to be overcome regarding directed evolution: 
(1) the need to implement sophisticated ultra-high-throughput screening assays 
as routine and universal tools for library exploration, (2) the restricted DNA 
diversity covering the full spectrum of the protein alphabet, which may be pos-
sibly dealt with new random codon mutagenesis strategies, and (3) the demand 
for more reliable computational algorithms to reduce the resources required for 
screening. In the near future, solutions to these problems will accelerate the 
The Pocket Manual of Directed Evolution: Tips and Tricks Chapter | 8 207
design of enzymes, metabolic pathways, or even whole microorganisms that can 
be used in the production of chemicals, biofuels, medicines, and foodstuffs.
ACKNOWLEDGMENTS
This work was supported by the European Commission projects Indox-FP7-
KBBE-2013-7-613549 and Cost-Action CM1303-Systems Biocatalysis, and the National 
Projects Dewry [BIO201343407-R] and Cambios [RTC-2014-1777-3].
ABBREVIATIONS
CLERY Combinatorial Libraries Enhanced by Recombination in Yeast
CHESS Cellular High-throughput Encapsulation, Solubilization and Screening
CSM Combinatorial Saturation Mutagenesis
CV Coefficient of Variance
GFP Green Fluorescent Protein
epPCR Error prone PCR
FACS Fluorescence-Activated Cell Sorting
GFP Green Fluorescent Protein
HTS High-Throughput Screening
IvAM In Vivo Assembly of Mutant libraries with different mutation spectra
IVC In Vitro Compartmentalization
IVOE In Vivo Overlap Extension
ISM Iterative Saturation Mutagenesis
ITCHY Incremental Truncation for the Creation of HYbrid enzymes
MAP Mutagenesis Assistant Program
MORPHING Mutagenic Organized Recombination Process by Homologous IN vivo 
Grouping
MTP MicroTiter Plate
PCR Polymerase Chain Reaction
PACE Phage-Assisted Continuous Evolution
ProSAR Protein Sequence Activity Relationship
QM/MM Quantum Mechanics/Molecular Mechanics
SeSaM Sequence Saturation Mutagenesis
SHIPREC Sequence Homology-Independent Protein RECombination
SM Saturation Mutagenesis
SOE Sequence Overlap Extension
StEP Staggered Extension Process
Ts Transition
Tv Transversion
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