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\begin{document}

\title{Implementing strategies in synthetic biology to maximize membrane
protein production}



\author[1]{Monica D. Rieth}%
\affil[1]{Southern Illinois University Edwardsville Department of Chemistry}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Membrane proteins represent a class of proteins that are difficult
targets to characterize. Their structural and functional
characterization requires that they first be produced at quantities that
enable their biophysical and biochemical analysis. Because they are
natively produced at levels much lower than their soluble counterparts,
extraction from their natural sources is not sufficient to produce
enough material for these studies. Recombinant protein expression and
production has become a popular method to produce large amounts of
proteins for research and industrial purposes. Significant effort has
been spent finding new ways to optimize and increase protein expression.
As cutting edge techniques in synthetic biology continue to advance they
offer a potential well of opportunities to tune expression through
better control of the transcription and translation processes. Many
techniques being developed are geared toward the production of soluble
proteins, but in the following review, a focus on effective strategies
to maximize membrane protein production in yeast is presented and
includes many of the most innovative approaches to maximize expression
using synthetic biology. Synthetic biology utilizes modern techniques in
molecular biology and genetic engineering to optimize the production of
compounds produced in microbes by altering gene elements required for
transcription and translation of critical genes responsible for their
synthesis. Compounds include natural products, hydrocarbon-based
compounds for biofuels, and therapeutic proteins. Producing membrane
proteins recombinantly using similar methods to increase expression
yields is described in this review along with cutting edge techniques
like cell-free expression, which circumvents many of the common problems
that plague overexpression of membrane proteins microbial-based
platforms.%
\end{abstract}%



\sloppy


\textbf{Title:} Implementing strategies in synthetic biology to maximize
membrane protein production

\textbf{Running Title:} Strategies to maximize membrane protein
production

\textbf{Author:} Monica D. Rieth*\textsuperscript{+} ~

\textbf{Address:} Department of Chemistry, Southern Illinois University
Edwardsville, 44 S. Circle Drive, Box 1652, Edwardsville, IL, 62026,
U.S.A.

*Corresponding author

Phone: 1-618-650-3561

Email: \href{mailto:mrieth@siue.edu}{\nolinkurl{mrieth@siue.edu}}

\textsuperscript{+} The author's former institutional affiliation and
contact information is listed above. Updated contact information
including new affiliation is pending. All correspondence should be
directed
to~\href{mailto:monica.rieth1@gmail.com}{\nolinkurl{monica.rieth1@gmail.com}}.

\textbf{Keywords} : proteins, synthetic biology, membranes, yeast,
engineering, recombinant expression

\textbf{Take Aways}

\begin{itemize}
\tightlist
\item
  Membrane proteins are challenging targets for recombinant expression
\item
  Overexpression results in misfolding, aggregation, degradation and
  apoptosis
\item
  Synthetic biology helps tune protein expression and increase yields
\end{itemize}

\textbf{Abstract}

\textbf{}Membrane proteins represent a class of proteins that are
difficult targets to characterize. Their structural and functional
characterization requires that they first be produced at quantities that
enable their biophysical and biochemical analysis. Because they are
natively produced at levels much lower than their soluble counterparts,
extraction from their natural sources is not sufficient to produce
enough material for these studies. Recombinant protein expression and
production has become a popular method to produce large amounts of
proteins for research and industrial purposes. Significant effort has
been spent finding new ways to optimize and increase protein expression.
As cutting edge techniques in synthetic biology continue to advance they
offer a potential well of opportunities to tune expression through
better control of the transcription and translation processes. Many
techniques being developed are geared toward the production of soluble
proteins, but in the following review, a focus on effective strategies
to maximize membrane protein production in yeast is presented and
includes many of the most innovative approaches to maximize expression
using synthetic biology. Synthetic biology utilizes modern techniques in
molecular biology and genetic engineering to optimize the production of
compounds produced in microbes by altering gene elements required for
transcription and translation of critical genes responsible for their
synthesis. Compounds include natural products, hydrocarbon-based
compounds for biofuels, and therapeutic proteins. Producing membrane
proteins recombinantly using similar methods to increase expression
yields is described in this review along with cutting edge techniques
like cell-free expression, which circumvents many of the common problems
that plague overexpression of membrane proteins microbial-based
platforms.

\textbf{Introduction}

Membrane proteins (MPs) represent an important class of biomolecules
that either closely associate with or almost completely reside within
the membranes of cells. They are crucially important in cellular
processes ranging from signaling, trafficking, and more recently,
scaffolding and shaping of the plasma membrane. Regions of exposed
hydrophobic amino acid residues form intimate contacts with membranes
that help to stabilize their structure and function (Levental \& Lyman,
2022). They also render these proteins remarkably challenging to study.
Many biochemical and biophysical techniques used in the preparation of
their soluble counterparts must often be adapted through the addition of
detergents and lipid mimetic complexes that provide a membrane-like
environment. One major obstacle to their study is producing quantities
of biologically active proteins for structural characterization and
other downstream analyses.

MPs can be divided into three broad classes: peripheral, integral, and
lipid-anchored. Peripheral MPs interact with the plasma membrane
superficially wherein only a small portion or region of exposed
hydrophobic amino acid residues are in contact with the lipid bilayer.
These proteins can typically be extracted using biochemical techniques
suitable for soluble proteins and do not necessitate the addition of
detergents or lipids to increase their solubility in aqueous buffers.
Similarly, lipid-anchored proteins are mostly soluble in aqueous buffers
and rely on the covalent attachment of a lipid (e.g. palmitoylation) or
a glycolipid (e.g. glycophosphatidylinositol) to one or more residues to
interact with membranes. Integral membrane proteins (IMPs), which will
be primarily referred to in this article, are almost entirely,
\textgreater{} 50\% amino acid composition, embedded in the lipid
bilayer of the plasma membrane of cells rendering them extremely
insoluble. \emph{In vitro} , a suitable detergent or lipid complex must
be used to keep them soluble and functionally active (Czerski \&
Sanders, 2000; Levental \& Lyman, 2022; Lin \& Guidotti, 2009; Whiles et
al., 2002). Methods used to obtain proteinaceous material for \emph{in
vitro} analyses can rarely be universally applied across the entire
spectrum of IMPs. Efforts to optimize experimental conditions is
resource and labor-intensive and hampers progress toward
characterization. As a result, relatively few IMPs have known solved
structures compared to soluble proteins (Carpenter et al., 2008; Pan \&
Vachet, 2022). G-protein coupled receptors (GPCRs), for example, are one
of the largest classes of IMPs (Errey \& Fiez-Vandal, 2020). They are a
key player in signal transduction and are responsible for processing
extracellular signals across cell membranes leading to a downstream
response. They are nearly ubiquitous across all kingdoms of life, but
their importance in critical cellular processes, specifically in humans,
makes them popular targets for drug therapy. Elucidating the structure
of GPCRs has direct implications for rational drug design. Until 2007,
the three-dimensional structure of nearly all GPCRs remained
uncharacterized (Cherezov et al., 2010; Qu et al., 2020). Fortunately,
critical advances in experimental methods such as the advent of
cryo-electron microscopy (cryo-EM) have enabled significant achievements
to be made. Although, high-yield production and purification still
remains a formidable challenge to their understanding and
behavior\emph{in vivo} .

Synthetic biology is a field uniquely poised to address the expression
problem in membrane protein research. In this review, techniques used in
the field of synthetic biology are explored presenting potentially the
most effective ways to fine-tune expression and production to maximize
yields. Recombinant expression methods serve as the basis for this
discussion to provide a background for understanding the underlying
challenges associated with current methods in MP expression. Along these
lines, the molecular biology steps that govern critical intracellular
processes in yeast is described to highlight important areas that might
be targeted to address some of the most difficult challenges.
Transcription and translation are two processes that lie at the center
of protein expression and production. They affect intracellular
conditions in yeast that ultimately effect cell viability and final
yields. Many of the synthetic biology strategies discussed take into
account regulatory features involved in transcription such as choice of
gene promoters, terminators and other genetic elements that provide a
greater level of control, which affects the viability of yeast during
expression as well as the quantity and potential quality of the protein
produced.

\textbf{Current challenges in recombinant membrane protein production}

Determining the optimal expression cassette and culture conditions for
maximum MP yield is largely an empirical process. Finding a singular,
universal approach is far from realistic when considering the nuances of
expression in any microbial platform including yeast. Yeast is the most
commonly used eukaryotic system for recombinant protein expression.
Prior knowledge of structural features of the target protein is
primarily what drives the decision to use yeast over its common
prokaryotic counterpart, \emph{E. coli} . Bacterial and yeast strains,
are selected for their well-characterized and robust
transcription-translation machinery, ease of culturing and genetic
alteration, and their ability to be scaled up to industrial levels. High
culture densities can be attained while having direct implications for
high-yield protein production. Protein expression targets that have
posttranslational modifications (PTMs) critical to their structure and
function may benefit from heterologous expression in eukaryotic yeast
species. Yeasts are phenotypically better equipped to handle proteins
that require PTMs as they are mostly unable to be carried out in
prokaryotes. Eukaryotic yeast species such as \emph{Saccharomyces
cerevisiae} (\emph{S. cerevisiae} ) are equipped with a developed
secretory pathway that carries out posttranslational processing such as
the addition of sugar residues at asparagine within the consensus motif,
Asn-X-Ser/Thr (\emph{N} -linked glycosylation) and serine and threonine
residues (\emph{O} -linked glycosylation). Glycosylation occurs both
during (co-translation) and after (post-translation) synthesis of the
polypeptide chain. It can have important ramifications for proper
structure and function. Glycosylation is often required for proper
protein folding and transport of MPs through the secretory pathway. In
some circumstances, glycosylation reportedly increases protein secretion
leading to enhanced expression, and it facilitates proper folding by
destabilizing the unfolded polypeptide state (Han \& Yu, 2015;
Shental-Bechor \& Levy, 2008). Further, glycosylation reportedly
enhances the stability, function and resistance to proteolytic
degradation in cellulases (Greene et al., 2015). When MPs are not
properly glycosylated and folding is negatively affected, proteins may
become prematurely degraded through the ER-associated degradative
pathway (Han \& Yu, 2015). In \emph{S. cerevisiae} , improper
glycosylation can lead to irreversible misfolding, aggregation and
degradation, impacting protein yields. This commonly occurs in \emph{S.
cerevisiae} where proteins often suffer from hyperglycosylation through
the addition of excess mannose residues (Conde et al., 2004; Kastberg et
al., 2022; Nakamura et al., 1993). Differences in glycosylation between
mammalian and yeast cells give rise to changes in glycosylation
patterning through differences in the identity of sugar residues
attached. This can also impact protein yield through misfolding and
premature degradation. Hyperglycosylation can be avoided altogether
through site-directed mutagenesis of glycosylated residues, however,
amino acid substitutions also introduce some risk of improper folding
and degradation (Han \& Yu, 2015). Other yeast species have been
explored as an alternative to \emph{S. cerevisiae} since they do not
suffer from the same hyperglycosylation effects. Species such as
methylotrophic, \emph{Pichia pastoris} (\emph{P. pastoris, syn.
Komagataella phaffii} ), have been used successfully for high-yield
expression. \emph{Yarrowia lipolytica} (\emph{Y. lipolytica} ) is an
emerging species with potential for industrial applications due to its
ability to produce commodity compounds and hydrocarbon-based compounds
for biofuels, among others. Though, it has not been extensively studied
for its MP production potential. The secretory pathway is considered the
rate-limiting step in protein synthesis in yeast. During expression, if
proteins become misfolded, they accumulate in the ER and impede the
synthesis of new proteins triggering a stress-related response called
the unfolded protein response (UPR). When this happens it can induce
premature degradation and cell death. These are just some of the factors
that must be considered when deciding on the best expression platform
when maximum yields are required. \emph{E. coli} , \emph{S. cerevisiae}
, and \emph{P. pastoris} (syn. \emph{K. phaffii} ) are among the best
characterized organism genomes reported enabling different recombinant
expression conditions to be tested and optimized.

Disulfide bonding is another type of PTM important for the stabilization
of tertiary structural contacts in some IMPs. Bacterial expression
systems lack an oxidative intracellular environment where disulfide
bonds form\emph{. S. cerevisiae} provides a better platform to support
this type of PTM. Where certain PTMs are critical for structure
formation and stabilization, \emph{S. cereivisiae} is principally the
better choice. Mammalian proteins are often post-translationally
modified compared to prokaryotic proteins, reinforcing the importance of
selecting the proper host (Macek et al., 2019).

Another challenge to successful MP expression is establishing optimal
cell growth and culture conditions. High-yield recombinant protein
production is achieved by applying rigorous growth conditions to coax
the host into producing as much protein as possible. Under such
conditions, deleterious effects can lead to truncated, misfolded, or
degraded protein. For IMPs, overexpression also leads to an
overabundance of the target protein in the plasma membrane after
trafficking from the secretory pathway. This results in molecular
crowding and alters both protein conformation and the morphology of the
membrane itself (Chen et al., 2016; Guigas \& Weiss, 2016; L\selectlanguage{ngerman}öwe et al.,
2020; H.-X. Zhou, 2009). The latter can have serious destabilizing
effects and potentially lead to premature cell death (Figure 1).

The goals of synthetic biology are directly aimed at addressing
challenges in expression and other compounds of industrial importance.
It is for this reason that the next section is devoted to discussing
techniques that have gained traction in the field. It is meant to
suggest a practical set of parameters that can be used to guide the
design of gene expression constructs to increase MP yields in yeast.

\textbf{3. Strategies to modulate expression using synthetic biology}

Synthetic biology encompasses a broad curation of methods aimed at
reprogramming different cell types including microbial and mammalian
cells for the purposes of producing compounds used in biofuels,
pharmaceuticals, and materials-based applications. The synthetic
processes necessary to produce these compounds requires the introduction
of metabolic pathways not native to the original host species in many
cases. One challenge synthetic biology has the potential to address is
producing high-quality MPs for structural characterization and other
biochemical analyses. Progress in MP research is often stymied by a lack
of high-throughput, robust methods to produce high-quality material. The
following summarizes and highlights some of the most effective tools
available that can be used to tune MP expression and production
in\emph{S. cerevisiae} , Much of the progress made in synthetic biology
has been possible using \emph{E. coli} and \emph{S. cerevisiae} -- two
of the best studied microbes. Application of these tools is slowly being
introduced into other microbes. Processes in yeast will be the focus for
the remainder of the review. The intracellular processes involved in
protein production include transcriptional regulation through adaptation
of genetic elements such as gene promoters, terminator regions, and
other mechanisms of transcriptional control including transcription
factors. A brief discussion on the use of fusion tags to boost protein
yields follows along with whole genome editing strategies to generate
selective knockout (KO) strains and down-regulate undesired proteolytic
pathways. Conversely, metabolic engineering methods are discussed as a
way of introducing novel pathways and genes identified to support MP
production along with future insights into how this technology can be
used to tune processes involved in expression. Innovative culturing
methods that include comparative insights into differential protein
induction methods, constitutive versus inductive, are discussed. Lastly,
the latest developments in cell-free (CF) expression, a field that has
seen significant advances in protein production applications, is
presented with an emphasis on advantages over whole cell expression and
future directions.

\emph{\textbf{Tuning protein expression and yield in yeast using genetic
elements and fusion tags}}

High-yield protein expression often employs rigorous expression
conditions to achieve the highest yields possible for a target
construct. Under these conditions, the rate of protein synthesis exceeds
the capacity of the intracellular protein quality control machinery
leading to misfolding and premature protein degradation. In the case of
the former, protein misfolding leads to the accumulation of aggregated
material that collects inside the expression host called inclusion
bodies. Inclusion bodies (IBs) are insoluble and resistant to
proteolytic degradation. This can be advantageous if a target IMP is
susceptible to premature degradation during expression or if
overexpression leads to premature cell death, which is common in the
case of MPs (Kesidis et al., 2020). Proteins can be coaxed into IBs by
incorporating certain fusion tags into the gene expression construct
(Esposito \& Chatterjee, 2006). The use of fusion tags has seen much use
in high-yield protein expression primarily as a handle for
post-production purification. These Include the common hexahistidine tag
(His6), Myc, thioredoxin (Trx), and maltose binding protein (MBP).
Including either solubility or IB-directing tags within the gene
expression cassette also has substantial effects on protein yields
(Costa et al., 2014; Ki \& Pack, 2020). Most reports of IB formation
occur in \emph{E. coli} and it is generally considered an undesired
outcome of protein aggregation that results from poor expression
conditions and the lack of PTMs. Where \emph{E. coli} falls short in
expression efforts, yeast has proved to be more successful (Cai et al.,
2019; Duman-Özdamar \& Binay, 2021). Taking advantage of IB formation
can be used to effectively increase expression yields and is useful when
a feasible refolding procedure has been established (Bhatwa et al.,
2021). The use of IB tags for \emph{S. cerevisiae} expression is not as
well described, but there is evidence of IB formation under specific
conditions depending on the expression target (Binder et al., 1991;
Rueda et al., 2016). Interestingly, two identified prionogenic proteins
which originated in yeast, were shown to form inclusion bodies when
expressed in \emph{E coli.} (Espargaró et al., 2012). Re-purposing these
proteins, Sup35 and Ure2, may provide one possible strategy to initiate
IB formation when used as a fusion tag for proteins expressed in\emph{E.
coli} and \emph{S. cerevisiae} .

Directing protein expression, primarily MPs, into IBs increases yield,
but does little to preserve protein structure and function. Solubilizing
and refolding aggregated protein in the absence of chaperones can be
complicated as protein size increases (molecular weight) due to the
increasing number of associated protein folding intermediates that can
be assumed (Kiefhaber et al., 1991; Mitraki \& King, 1989; Silow \&
Oliveberg, 1997). Again, this is further complicated by any native PTMs
required for proper structure and function (Roth et al., 2010;
Shental-Bechor \& Levy, 2008). In \emph{S. cerevisiae} , the presence of
the secretory pathway is accompanied by the unfolded protein response
(UPR) that is triggered under stress-induced conditions (Gardner et al.,
2013; Ng et al., 2000; Walter \& Ron, 2011). High-level expression
conditions can create an environment where protein misfolding is more
likely to occur. A cascade of intracellular events results that can
either increase the expression of molecular folding chaperones or it can
lead to premature death through activation of apoptotic pathways (Hetz
et al., 2020; Walter \& Ron, 2011). Finding alternate ways to relieve
cell-induced stress is necessary to avoid these unwanted outcomes and
achieve maximum yields. Toward this end, attenuating induced expression
conditions are required, which can be accomplished by choosing a
compatible expression plasmid and tailoring incorporated genetic
elements to optimize this process through better control.

Protein expression plasmids comprised of small circular pieces of DNA
that are introduced to either bacterial or yeast organisms and are
incorporated into the phenotype of the host expression system. The
native transcription and translation machinery of the host is hijacked
to produce the product of the target genes included within the plasmid
DNA, usually at levels higher than the homeostatic levels of the native
genes in the host genome. When successful conditions have been
established, this results in high protein yields. Predicting optimal
expression conditions \emph{ab initio} is nearly impossible considering
the intricate interplay of multiple processes involved. Rigorous
expression conditions are usually employed, but this can lead to
undesired outcomes including premature cell death. The use of genetic
elements such as promoters to induce protein expression and impose more
control on the process is one way to potentially mitigate this effect.
Choice of plasmid also influences protein expression levels by their
copy number within a cell and mitotic stability, which affects their
ability to replicate through cell division during propagation. Plasmid
copy number also affects protein expression levels and it has been
suggested that when coupled with a strong constitutive promoter, plasmid
copy number is reduced along with plasmid stability, which is enough to
offset expression ``gains'' achieved by a strong promoter (Stueber \&
Bujard, 1982). Although, the use of auxotrophic selection markers has a
much greater effect on plasmid copy number (Karim et al., 2013). A
variety of commonly used plasmids are readily available for protein
expression in yeast. These include pRS plasmids and their variants,
pYES, pESC and many others which are summarized by Da Silva and
Srikrishnan (Da Silva \& Srikrishnan, 2012; Fang et al., 2011). Many of
the plasmids in these series spawned from the popular pRS plasmids and
differ by slight variations in their promoter regions as well as other
features including various selection markers and incorporated tags for
assaying expression and intracellular trafficking or for purification.
Promoters can be classified as either constitutive or inducible. While
constitutive promoters; TEF1, ADH1, and GDP, offer a greater dynamic
range of expression, inducible promoters, FIG1 and GAL, enable greater
control over timing and transcriptional regulation of expression, which
is especially useful when expressing targets that are inherently toxic
to the host. MPs fall into this category. When they are overexpressed
and trafficked to the plasma membrane, this can lead to membrane
overcrowding causing destabilizing effects (Guigas \& Weiss, 2016; Löwe
et al., 2020; H.-X. Zhou, 2009). Waiting to induce expression until
higher cell densities are achieved is a way to ensure expression will
not trigger premature cell death before higher yields can be obtained.

Efforts continue to be directed toward engineering new synthetic
promoters to optimize expression by incorporating elements that allow
for greater transcriptional control (Alper et al., 2005). Synthetic
promoters usually include hybrid features of the native promoter along
with a tunable site upstream of the core promoter that can act to
suppress its activity. This is effective particularly for a strong
promoter such as GAL1 (Mazumder \& McMillen, 2014). Including repressor
sites can also change a constitutive promoter, PFY1, to an inducible one
using a similar approach, by incorporating regulatory elements upstream
of the main promoter. Alternatively, hybrid promoters take elements from
at least two different promoters, combining them into a single new
promoter with altered activity and regulation (Blazeck et al., 2012).
Recombining promoter regions requires a detailed understanding of
different native yeast promoters and regulatory elements. Some
promoters, the tightly-regulated \emph{HO} promoter for example, are
only active in certain cell types and respond to transcription factor
initiation under specific conditions. The \emph{HO} promoter is
activated only in mother-type yeast cells in response to the SWI5
transcription factor during G1 phase of cell cycle division (Nasmyth et
al., 1990). This adds an additional layer of protein expression control
through the use of transcription factors, which interact with promoter
and repressor regions to up- or down-regulate expression. This further
expands the capacity for fine tuning. Transcription factors are native
to all organisms and their identification has traditionally encompassed
experimental characterization (Ian A. Taylor et al., 2000; Vachon et
al., 2013). These methods have largely been supplanted using genome
sequencing and mapping methods along with bioinformatics to help
identify conserved regulatory regions across species (Hahn \& Young,
2011; Yu, 2006). To understand transcription activation or repression of
a specific promoter region requires \emph{a priori} knowledge of their
native function, which genome mapping has helped elucidate. These
efforts have resulted in the curation of libraries of promoters enabling
high-throughput screening and the construction of synthetic promoters
(Gordân et al., 2011). Beyond that, functional assessment is needed to
assay transcription factor and regulatory motif compatibility with the
host organism expression machinery. This can be accomplished using a
fluorescence reporter gene to measure expression levels or by measuring
mRNA (Blazeck et al., 2012). Using a repressor in conjunction with a
promoter provides a means of tighter control over inducing expression
and could help to avoid the negative effects that result from
overwhelming the intracellular expression machinery under rigorous
expression conditions, this includes when using a strong promoter.
Coupled with an in-depth analysis of expression for a target construct,
a linked repressor can be activated at different time points throughout
the period of expression to avoid aggravating the UPR or inducing
apoptosis (Kaneko \& Nomura, 2003).

Another strategy to allow for better control over protein expression is
by engineering non-native terminator sequences. Though, perhaps not as
commonly addressed as a means of tailoring protein expression, adjusting
terminator sequences can impact the completion of transcription,
dissociation and recycling of transcription machinery and other
important parameters such as mRNA half-life. They can be versatility
introduced across different yeast expression platforms like
industrial,\emph{Y. lipolytica} , and they can be completely
synthetically constructed resembling few to no features of any native
terminator sequences (Curran et al., 2015). Short terminator sequences
have been engineered for yeast and showed increased protein expression
levels by 3.7-fold when compared with the commonly used \emph{CYC1}
terminator in yeast. A weak terminator can lead to transcriptional
read-through and delayed dissociation of RNA polymerase. In \emph{E.
coli} , it has been suggested lower transcription efficiency can lead to
slowed expression, reducing the chance of overwhelming the translation
machinery (Swartz, 2001). Using similar rationale, this may be necessary
to attenuate the effects of a strong promoter and avoid triggering a
stress-related cellular response such as misfolding, degradation (mRNA
and protein) and cell death. One other approach that has been used in
\emph{P. pastoris}(syn. \emph{K. phaffii} ) using hybrid promoters that
contain both bacterial and yeast derived elements (Liu et al., n.d.).
The purpose is to employ a yeast species that could produce proteins
with desired PTMs rather than the hyperglycosylation \emph{S.
cerevisiae} is known for, while adapting it to high-level expression by
introducing promoter features from a related high-producing species.
Using a synthetic hybrid promoter along with a transactivator enabled
methanol-free activation of protein production and increased the yield
of a recombinant \selectlanguage{greek}α-\selectlanguage{english}amylase expression target produced in \emph{P.
pastoris (} syn. \emph{K. phaffii} ). This avoided the need to use toxic
methanol to induce expression.

Metabolic and genome engineering efforts to increase membrane protein
yield

In recent years, whole genome methods to increase recombinant protein
production have emerged. This has been mostly reported for \emph{E.
coli} . However, \emph{S. cerevisiae} still remains one of the more
popular eukaryotic expression platforms. Both model microbe systems are
well-characterized and contain reasonably-sized genomes that enable
genetic manipulation to be feasible. As our understanding of the
interplay between multiple intracellular processes continues to evolve,
this has shed light on additional indirect factors that influence the
outcome of protein expression. This requires a top-down systems level
analysis of simultaneous cell processes that take place under specific
environmental conditions. Metabolic engineering aims to address these
challenges. To look at how this approach can be applied to MP expression
requires a recognition and understanding of the processes not only
directly involved in but also those affected downstream by their
synthesis, folding, PTM, and translocation. Transcriptomics and
metabolomics analyses are two ways that the effects of growth conditions
can be assessed by looking at changes in transcript levels, mRNA, of
genes involved in certain metabolic pathways (R. Carlson et al., 2002;
Chae et al., 2017; Dromms \& Styczynski, 2012; Guan et al., 2018; Park
et al., 2005; Trethewey, 2004; Yuan et al., 2018). Similarly,
metabolomics is used to assess signature metabolites and their relative
quantities, which are by-products from these pathways and interconnected
processes. Information can be gleaned from these studies about the
pathways that are most affected by expression conditions. Metabolic
engineering aims to divert resources that support identified systems
away from non-essential pathways and redirecting them toward recombinant
expression. The rationale is that this results in prolonged expression
leading toward increased production levels. Employing a rational
approach to achieve this requires a systems level understanding of the
host metabolism including those involved in transcription, translation
and flux of metabolites, which also includes proteins. An analysis of
the host expression platform helps in deciding which pathways are
critically effected during protein expression. As a result of these
analyses one strategy is to engineer KO yeast strains that are lacking
pathways least critical for survival of the organism. Also, targeting
genes responsible for the translation bottleneck created when strong
promoters generate higher rates of mRNA synthesis helps alleviate this
stress and associated degradation of mRNA. This was successfully
demonstrated in \emph{E. coli} when 36 genes responsible for
non-essential functions were selectively knocked out (Sharma et al.,
2020; L. Zhou et al., 2022). The results showed that protein expression
could be increased by 1.5-fold when carried out at lower temperatures,
25 \selectlanguage{ngerman}°C.

Alternatively, knockin (KI) strains also show promise as a means of
increasing production. In this way, strains are engineered to carry out
important processes that lead to proper protein function. This is a
common strategy employed in the latest gene editing technologies such as
CRISPR/Cas9. This allows for targeted gene insertion to coax the host
into producing gene products that are either non-native to the host
organism or to restore gene function that has been lost (Giuliano et
al., 2019; Ye et al., 2021). Recently, CRISPR/Cas9 technology was used
successfully to introduce the T7 RNA polymerase gene, an established
robust expression system, into a strain of \emph{E. coli} naturally
lacking this system (Ye et al., 2021). While some genome-wide strategies
have been used successfully in \emph{E. coli} , an extensive exploration
of these methods in \emph{S. cerevisiae} has not yet been reported. The
addition of folding chaperones such as Hsp150 and PDI1 has seen some
success, mostly for the recombinant expression of soluble proteins (Kim
et al., 2014). Yeast strains deficient in lysosomal compartment
proteases along with other organellar proteases is another strategy that
has been implemented to circumvent protein degradation, truncation and
increase yields by at least 10-fold (Tomimoto et al., 2013). Processes
such as glycosylation also have significant effects on protein yield and
quality control. Mutagenesis efforts have been directed toward
humanizing yeast strains to produce glycosylation patterns on
recombinantly expressed proteins similar to those produced in humans
(Hamilton \& Gerngross, 2007) (Figure 2). As proof of concept, humans,
for example, lack the ability to produce sialic acid,~\emph{N}
-glycolylneuraminic acid, while other mammals can produce it. This leads
to aberrant sialylation. Knocking out its production in mammalian and
other cell lines can potentially alleviate this problem. This is an
important consideration in the design and production of therapeutic
proteins where posttranslational differences in the resulting protein
can have severe immunological effects. For MPs along with other
non-therapeutic proteins, glycosylation affects folding, stability,
half-life and function (Helenius \& Aebi, 2001; Mitra et al., 2006). All
of which are important considerations for high-yield, high-quality
recombinant expression.

Changing culture conditions to tune expression

Before some of the cloning and engineering strategies previously
discussed, ``simpler'' approaches may also prove helpful. High-yields
and high-quality are not necessarily linked and higher-yields may, in
fact, produce large quantities of unfolded, non-functional protein. When
this outcome is not intended, for example, if avoiding inclusion body
formation is desired, lowering the culture temperature during protein
induction can lead to higher yields of functional, high-quality material
(Francis \& Page, 2010; Li et al., 2001; San-Miguel et al., 2013;
Weickert et al., 1997). This has mostly been explored in E. coli,
however, and little is reported on low temperature cultivation effects
in yeast. The use of synthetic media also facilitates slowed expression
and production compared to nutrient-rich media. Lastly, like strong
promoters, growth conditions can also affect plasmid copy number
(Stueber \& Bujard, 1982).

A promising field that has gained much traction over the last decade is
the use of CF systems for high-yield expression. Once used primarily as
a research tool to understand transcription and translation has now been
adapted to produce protein products at scale for synthetic biology
(Garenne et al., 2021; Silverman et al., 2020). CF systems do not suffer
from the production bottlenecks presented by their whole-cell
counterparts, but there are other important considerations. The
intracellular systems and processes that accompany traditional \emph{in
vivo} expression have effectively been removed, leaving only the
essential protein expression and production machinery. Prokaryotic CF
systems emerged using components isolated from \emph{E. coli} where
recombinantly expressed, purified, components have been used
successfully -- ``Protein synthesis Using Recombinant Elements'' (PURE
system) (E. D. Carlson et al., 2012; Klammt et al., 2006; Ohashi et al.,
2010). Success has also been met using crude cell lysis extract (Kigawa
et al., 2004). Eukaryotic CF expression has been developed from a
variety of sources ranging from wheat germ to Chinese hamster ovary
(CHO) cells to HeLa cells (Anderson et al., 1989; Brödel et al., 2014;
Harbers, 2014; Weber et al., 1975). There are only a few reports of CF
systems using expression machinery isolated from yeast and most utilize
soluble proteins to demonstrate feasibility of the system (Hodgman \&
Jewett, 2013). Extracts from \emph{E. coli} have been utilized
successfully in CF expression on a multi-liter scale (Figure 3). The
reactions are stable for several hours and can be scaled to produce
gram-level quantities of material (E. D. Carlson et al., 2012). CF yeast
systems have also been utilized successfully to produce active firefly
luciferase at \selectlanguage{greek}µ\selectlanguage{english}g-scale (Hodgman \& Jewett, 2013). While most of the
large-scale production efforts described utilize soluble proteins,
strategies to adapt this technique to MPs are summarized nicely in
several reviews (Klammt et al., 2006; Sachse et al., 2014). CF In Vitro
Transcription/Translation reaction (IVTT) systems provide a solution to
the potentially limited space available at the plasma membrane that is
necessary to support properly folded, functional MPs. Arguably, it also
leaves proteins less susceptible to the structural and conformational
defects that arise from overcrowding in the membrane during
overexpression. Rather, in the absence of the native cell-membrane, CF
systems rely on artificially supplemented media to support MP
solubility. Mild detergents and other lipids that assume a bilayered
morphological structure are added to the synthetic milieu to keep newly
synthesized hydrophobic MPs soluble and conformationally active (Klammt
et al., 2006). CF systems streamline the production process by omitting
the need for any additional protein refolding protocols to be
established prior to characterization. One important consideration is
the compatibility of detergent and lipid additives not only to the
target protein, but also their effects, if any, on the viability of the
IVTT reaction components. Also, the concentration of detergent and
lipids required to maintain protein solubility and active reaction
components must be determined as well. Detergents must be maintained at
a concentration above their critical micelle concentration, CMC, to
maintain effective solubility properties (Kalipatnapu \& Chattopadhyay,
2005; Sachse et al., 2014). Though this is perhaps a slight
simplification of the complex biophysical interactions between MPs and
solubilizing detergents and lipids. At any given time during the course
of the reaction, the concentration of freely available detergent and
associated micelles fluctuates during expression as proteins are
synthesized and occupy micelle aggregates. Further complicating this
process are the changes in by-product accumulation accompanying the
reaction. These are important considerations when optimizing the
synthesis reaction, but advantageously, carrying this out in a CF system
also provides flexibility in the amount of detergent that can be added,
changing the solubilizing capacity of the reaction mixture. Generally,
nonionic detergents such as Brij and Triton X-100 detergents can be
scaled at minimal cost. Other proprietary detergent mixtures such as
Empigen BB\selectlanguage{ngerman}\textsuperscript{®}, which is comprised of a heterogeneous
distribution of varying chain length molecules, is also mild and
nondenaturing (Lowthert et al., 1995). These types of detergents are
least likely to cripple the functionality of the components in the
reaction mixture leading to longer reaction times and increased protein
yields. Further, orchestrating a system to remove reaction by-products
as they accumulate and adding substrates can facilitate longer reaction
times and improve yields (Schoborg et al., 2014). Detergent solubilized
proteins can be later reconstituted into bilayered systems for
downstream analysis (Rieth et al., 2020).

\textbf{Conclusions and Future Directions}

A plethora of strategies along with synthetic biology tools for
high-yield recombinant MP production is described. Integral MPs remain
one of the most challenging expression targets due to their extreme
hydrophobicity, which presents challenges to most host organisms when
expressed at high levels. Overexpression often involves recruiting
rigorous gene expression conditions that lead to activation of
stress-related intracellular pathways in yeast that can thwart efforts
to achieve high yields. Engineering native and nonnative hybrid
promoters can help alleviate these problems as well as coupling
activator and repressor sites upstream of the target protein.
Consideration of terminator sequences provides another way to fine-tune
expression and slow the coupled transcription-translation process to
help avoid overwhelming the intracellular translation machinery. Many of
the strategies summarized in this regard relate to the use of expression
plasmids to achieve maximum yields. Indirect approaches have also been
described using metabolic engineering and other genome engineering
techniques to generate KO and KI strains with the aim of redirecting
yeast metabolism and nutrient resources toward producing the target
protein. The use of metabolic/genome engineering to halt non-essential
processes has been demonstrably successful in some cases for soluble
proteins and has yet to be applied to MP expression. Generating KOs to
remove unwanted protease activity can also help increase yields,
although increasing yields is not always coupled with high-quality,
functional proteins. This review is intended to summarize the tools
available to MP researchers looking to produce proteins for
characterization. It describes best approaches that can be applied to
maximize yields, which is often a bottleneck to progress in areas of
structural biology and other types of analyses. It is also intended to
help define areas in need of further development and where future
efforts could be beneficially directed so that more can be learned about
the processes critical to expression. While still somewhat a new
methodology, CF expression for MPs holds tremendous promise as an
alternative to heterologous expression in microbes by removing some of
the critical barriers to overexpression and maximizing yields. Further,
similar strategies used for synthetic biology in microbial systems have
been attempted in CF systems with some success. Genetic components;
transcription/translation, promoters, regulatory elements are beginning
to be explored in CF systems and already make use of well-characterized,
robust systems such as the \emph{E. coli} -based T7 transcription system
(Garenne et al., 2021). Much of the progress seen with CF systems has
been derived from \emph{E. coli} . However, the same limitations present
in \emph{E. coli} expression still plagues its CF counterpart. Namely,
the ability to carry out PTMs. Although, less is known about CF systems
using yeast-derived components much of its progress has been pioneered
by Jewett and co-workers and could potentially complement \emph{E. coli}
-derived systems for this reason, but without the limitations of the
finite space in the plasma membrane. Along these lines, it may be
advantageous to use CF in tandem with microbial systems by testing an
expression system \emph{in vitro} prior to transferring the genetic
components to a cell-based system. CF systems are amenable to laboratory
automation and potential scale-up making high-throughput testing
possible, which can help supplement arduous efforts to screen single
expression conditions at one time. CF also makes incorporation of
unnatural amino acids possible for biophysical and other downstream
analysis.

\textbf{Acknowledgement}

I would like to acknowledge the ongoing encouragement from colleagues
near and far, and I want to thank them for their continued support.
Figures 2 and 3 were created using Biorender.com.

\textbf{Figures}

\textbf{Hosted file}

\verb`image1.emf`  available at \url{https://authorea.com/users/581605/articles/622112-implementing-strategies-in-synthetic-biology-to-maximize-membrane-protein-production}

\textbf{Hosted file}

\verb`image2.emf`  available at \url{https://authorea.com/users/581605/articles/622112-implementing-strategies-in-synthetic-biology-to-maximize-membrane-protein-production}

\textbf{Hosted file}

\verb`image3.emf`  available at \url{https://authorea.com/users/581605/articles/622112-implementing-strategies-in-synthetic-biology-to-maximize-membrane-protein-production}



\textbf{References}

Alper, H., Fischer, C., Nevoigt, E., \& Stephanopoulos, G. (2005).
Tuning genetic control through promoter engineering. \emph{Proc.Natl.
Acad. Sci.} , \emph{102} (36), 12678--12683.

Anderson, C. W., Straus, J. W., \& Dudock, B. S. (1989). Preparation of
a cell-free protein-synthesizing system from wheat
germ.\emph{Recombinant DNA Methodology,} (pp. 677--685). Elsevier.

Bhatwa, A., Wang, W., Hassan, Y. I., Abraham, N., Li, X.-Z., \& Zhou, T.
(2021). Challenges Associated With the Formation of Recombinant Protein
Inclusion Bodies in Escherichia coli and Strategies to Address Them for
Industrial Applications. \emph{Front. Bioeng.Biotechnol.} , \emph{9} .
https://www.frontiersin.org/articles/10.3389/fbioe.2021.630551

Binder, M., Schanz, M., \& Hartig, A. (1991). Vector-mediated
overexpression of catalase A in the yeast Saccharomyces cerevisiae
induces inclusion body formation. \emph{Eur. J. Cell Biol.} ,\emph{54}
(2), 305--312.

Blazeck, J., Garg, R., Reed, B., \& Alper, H. S. (2012). Controlling
promoter strength and regulation in Saccharomyces cerevisiae using
synthetic hybrid promoters. \emph{Biotechnol. Bioeng.} , \emph{109}
(11), 2884--2895. https://doi.org/10.1002/bit.24552

Brödel, A. K., Sonnabend, A., \& Kubick, S. (2014). Cell-free protein
expression based on extracts from CHO cells. \emph{Biotechnol. Bioeng.}
,\emph{111} (1), 25--36.

Cai, H., Yao, H., Li, T., Tang, Y., \& Li, D. (2019). High-level
heterologous expression of the human transmembrane sterol
\selectlanguage{greek}Δ\selectlanguage{english}8,\selectlanguage{greek}Δ\selectlanguage{english}7-isomerase in Pichia pastoris. \emph{Protein Expr. Purif.}
,\emph{164} , 105463. https://doi.org/10.1016/j.pep.2019.105463

Carlson, E. D., Gan, R., Hodgman, C. E., \& Jewett, M. C. (2012).
Cell-free protein synthesis: Applications come of age. \emph{Biotechnol.
Adv.} , \emph{30} (5), 1185--1194.
https://doi.org/10.1016/j.biotechadv.2011.09.016

Carlson, R., Fell, D., \& Srienc, F. (2002). Metabolic pathway analysis
of a recombinant yeast for rational strain development.\emph{Biotechnol.
Bioeng.} , \emph{79} (2), 121--134. https://doi.org/10.1002/bit.10305

Carpenter, E. P., Beis, K., Cameron, A. D., \& Iwata, S. (2008).
Overcoming the challenges of membrane protein
crystallography.\emph{Curr. Opin. Struct. Biol.} , \emph{18} (5),
581--586. https://doi.org/10.1016/j.sbi.2008.07.001

Chae, T. U., Choi, S. Y., Kim, J. W., Ko, Y.-S., \& Lee, S. Y. (2017).
Recent advances in systems metabolic engineering tools and
strategies.\emph{Curr. Opin. Biotechnol.} , \emph{47} , 67--82.

Chen, Z., Atefi, E., \& Baumgart, T. (2016). Membrane Shape Instability
Induced by Protein Crowding. \emph{Biophys. J.} , \emph{111} (9),
1823--1826. https://doi.org/10.1016/j.bpj.2016.09.039

Cherezov, V., Abola, E., \& Stevens, R. C. (2010). Recent Progress in
the Structure Determination of GPCRs, a Membrane Protein Family with
High Potential as Pharmaceutical Targets. In J.-J. Lacap\selectlanguage{ngerman}ère
(Ed.),\emph{Membrane Protein Structure Determination: Methods and
Protocols}(pp. 141--168). Humana Press.
https://doi.org/10.1007/978-1-60761-762-4\_8

Conde, R., Cueva, R., Pablo, G., Polaina, J., \& Larriba, G. (2004). A
search for hyperglycosylation signals in yeast glycoproteins. \emph{J.
Biol. Chem.} , \emph{279} (42), 43789--43798.
https://doi.org/10.1074/jbc.M406678200

Costa, S., Almeida, A., Castro, A., \& Domingues, L. (2014). Fusion tags
for protein solubility, purification and immunogenicity in Escherichia
coli: The novel Fh8 system. \emph{Front. Microbiol.} , \emph{5} .
https://www.frontiersin.org/articles/10.3389/fmicb.2014.00063

Curran, K. A., Morse, N. J., Markham, K. A., Wagman, A. M., Gupta, A.,
\& Alper, H. S. (2015). Short Synthetic Terminators for Improved
Heterologous Gene Expression in Yeast. \emph{ACS Synth. Biol.} ,\emph{4}
(7), 824--832. https://doi.org/10.1021/sb5003357

Czerski, L., \& Sanders, C. R. (2000). Functionality of a membrane
protein in bicelles. \emph{Anal. Biochem.} , \emph{284} (2), 327--333.
https://doi.org/10.1006/abio.2000.4720

Da Silva, N. A., \& Srikrishnan, S. (2012). Introduction and expression
of genes for metabolic engineering applications in Saccharomyces
cerevisiae. \emph{FEMS Yeast Res.} , \emph{12} (2), 197--214.
https://doi.org/10.1111/j.1567-1364.2011.00769.x

Dromms, R. A., \& Styczynski, M. P. (2012). Systematic applications of
metabolomics in metabolic engineering. \emph{Metabolites} , \emph{2}
(4), 1090--1122.

Duman-Özdamar, Z. E., \& Binay, B. (2021). Production of Industrial
Enzymes via Pichia pastoris as a Cell Factory in Bioreactor: Current
Status and Future Aspects. \emph{Protein J.} , \emph{40} (3), 367--376.
https://doi.org/10.1007/s10930-021-09968-7

Errey, J. C., \& Fiez-Vandal, C. (2020). Production of membrane proteins
in industry: The example of GPCRs. \emph{Protein Expr. Purif.}
,\emph{169} , 105569. https://doi.org/10.1016/j.pep.2020.105569

Espargaró, A., Villar-Piqué, A., Sabaté, R., \& Ventura, S. (2012).
Yeast prions form infectious amyloid inclusion bodies in
bacteria.\emph{Microb. Cell Factories} , \emph{11} (1), 89.
https://doi.org/10.1186/1475-2859-11-89

Esposito, D., \& Chatterjee, D. K. (2006). Enhancement of soluble
protein expression through the use of fusion tags. \emph{Curr. Opin.
Biotechnol.} , \emph{17} (4), 353--358.
https://doi.org/10.1016/j.copbio.2006.06.003

Fang, F., Salmon, K., Shen, M. W. Y., Aeling, K. A., Ito, E., Irwin, B.,
Tran, U. P. C., Hatfield, G. W., Da Silva, N. A., \& Sandmeyer, S.
(2011). A vector set for systematic metabolic engineering in
Saccharomyces cerevisiae. \emph{Yeast} , \emph{28} (2), 123--136.
https://doi.org/10.1002/yea.1824

Francis, D. M., \& Page, R. (2010). Strategies to Optimize Protein
Expression in E. coli. \emph{Curr. Protoc. Protein Sci.} , \emph{61}
(1), 5.24.1-5.24.29. https://doi.org/10.1002/0471140864.ps0524s61

Gardner, B. M., Pincus, D., Gotthardt, K., Gallagher, C. M., \& Walter,
P. (2013). Endoplasmic reticulum stress sensing in the unfolded protein
response. \emph{Cold Spring Harbor Perspectives in Biology} .
https://doi.org/10.1101/cshperspect.a013169

Garenne, D., Haines, M. C., Romantseva, E. F., Freemont, P.,
Strychalski, E. A., \& Noireaux, V. (2021). Cell-free gene
expression.\emph{Nat. Rev. Methods Primers} , \emph{1} (1), Article 1.
https://doi.org/10.1038/s43586-021-00046-x

Giuliano, C. J., Lin, A., Girish, V., \& Sheltzer, J. M. (2019).
Generating Single Cell--Derived Knockout Clones in Mammalian Cells with
CRISPR/Cas9. \emph{Curr. Protoc. Mol. Biol.} , \emph{128} (1), e100.
https://doi.org/10.1002/cpmb.100

Gordân, R., Murphy, K. F., McCord, R. P., Zhu, C., Vedenko, A., \&
Bulyk, M. L. (2011). Curated collection of yeast transcription factor
DNA binding specificity data reveals novel structural and gene
regulatory insights. \emph{Genome Biol.} , \emph{12} (12), R125.
https://doi.org/10.1186/gb-2011-12-12-r125

Greene, E. R., Himmel, M. E., Beckham, G. T., \& Tan, Z. (2015). Chapter
Three - Glycosylation of Cellulases: Engineering Better Enzymes for
Biofuels. In D. C. Baker \& D. Horton (Eds.), \emph{Adv. Carbohydr.
Chem. Biochem.} (Vol. 72, pp. 63--112). Academic Press.
https://doi.org/10.1016/bs.accb.2015.08.001

Guan, N., Du, B., Li, J., Shin, H., Chen, R. R., Du, G., Chen, J., \&
Liu, L. (2018). Comparative genomics and transcriptomics analysis-guided
metabolic engineering of Propionibacterium acidipropionici for improved
propionic acid production. \emph{Biotechnol. Bioeng.} , \emph{115} (2),
483--494.

Guigas, G., \& Weiss, M. (2016). Effects of protein crowding on membrane
systems. \emph{Biochim. Biophys. Acta - Biomembr.} , \emph{1858} (10),
2441--2450. https://doi.org/10.1016/j.bbamem.2015.12.021

Hahn, S., \& Young, E. T. (2011). Transcriptional Regulation in
Saccharomyces cerevisiae: Transcription Factor Regulation and Function,
Mechanisms of Initiation, and Roles of Activators and
Coactivators.\emph{Genetics} , \emph{189} (3), 705--736.
https://doi.org/10.1534/genetics.111.127019

Hamilton, S. R., \& Gerngross, T. U. (2007). Glycosylation engineering
in yeast: The advent of fully humanized yeast. \emph{Curr. Opin.
Biotechnol.} , \emph{18} (5), 387--392.
https://doi.org/10.1016/j.copbio.2007.09.001

Han, M., \& Yu, X. (2015). Enhanced expression of heterologous proteins
in yeast cells via the modification of N-glycosylation
sites.\emph{Bioengineered} , \emph{6} (2), 115--118.
https://doi.org/10.1080/21655979.2015.1011031

Harbers, M. (2014). Wheat germ systems for cell-free protein
expression.\emph{FEBS Lett.} , \emph{588} (17), 2762--2773.

Helenius, A., \& Aebi, and M. (2001). Intracellular Functions of
N-Linked Glycans. \emph{Science} , \emph{291} (5512), 2364--2369.
https://doi.org/10.1126/science.291.5512.2364

Hetz, C., Zhang, K., \& Kaufman, R. J. (2020). Mechanisms, regulation
and functions of the unfolded protein response. \emph{Nat. Rev. Mol.
Cell Biol.} , \emph{21} (8), Article 8.
https://doi.org/10.1038/s41580-020-0250-z

Hodgman, C. E., \& Jewett, M. C. (2013). Optimized extract preparation
methods and reaction conditions for improved yeast cell-free protein
synthesis. \emph{Biotechnol. Bioeng.} , \emph{110} (10), 2643--2654.
https://doi.org/10.1002/bit.24942

Ian A. Taylor, Pauline B. McIntosh, Preshna Pala, Monika K. Treiber,
Steven Howell, Andrew N. Lane, \& Stephen J. Smerdon. (2000, March
11).\emph{Characterization of the DNA-Binding Domains from the Yeast
Cell-Cycle Transcription Factors Mbp1 and Swi4} (world)
{[}Research-article{]}. ACS Publications; American Chemical Society.
https://doi.org/10.1021/bi992212i

Kalipatnapu, S., \& Chattopadhyay, A. (2005). Membrane Protein
Solubilization: Recent Advances and Challenges in Solubilization of
Serotonin1A Receptors. \emph{IUBMB Life} , \emph{57} (7), 505--512.
https://doi.org/10.1080/15216540500167237

Kaneko, M., \& Nomura, Y. (2003). ER signaling in unfolded protein
response. \emph{Life Sci.} , \emph{74} (2), 199--205.
https://doi.org/10.1016/j.lfs.2003.09.007

Karim, A. S., Curran, K. A., \& Alper, H. S. (2013). Characterization of
plasmid burden and copy number in \emph{Saccharomyces cerevisiae} for
optimization of metabolic engineering applications. \emph{FEMS Yeast
Res.} , \emph{13} (1), 107--116. https://doi.org/10.1111/1567-1364.12016

Kastberg, L. L. B., Ard, R., Jensen, M. K., \& Workman, C. T. (2022).
Burden Imposed by Heterologous Protein Production in Two Major
Industrial Yeast Cell Factories: Identifying Sources and Mitigation
Strategies. \emph{Front Fungal Biol.} \emph{3} . https://www.Front
Fungal Biol.iersin.org/articles/10.3389/ffunb.2022.827704

Kesidis, A., Depping, P., Lodé, A., Vaitsopoulou, A., Bill, R. M.,
Goddard, A. D., \& Rothnie, A. J. (2020). Expression of eukaryotic
membrane proteins in eukaryotic and prokaryotic hosts. \emph{Methods}
,\emph{180} , 3--18. https://doi.org/10.1016/j.ymeth.2020.06.006

Ki, M.-R., \& Pack, S. P. (2020). Fusion tags to enhance heterologous
protein expression. \emph{Appl. Microbiol. Biotechnol.} , \emph{104}
(6), 2411--2425. https://doi.org/10.1007/s00253-020-10402-8

Kiefhaber, T., Rudolph, R., Kohler, H.-H., \& Buchner, J. (1991).
Protein Aggregation in vitro and in vivo: A Quantitative Model of the
Kinetic Competition between Folding and Aggregation. \emph{Nat.
Biotechnol.} , \emph{9} (9), Article 9.
https://doi.org/10.1038/nbt0991-825

Kigawa, T., Yabuki, T., Matsuda, N., Matsuda, T., Nakajima, R., Tanaka,
A., \& Yokoyama, S. (2004). Preparation of Escherichia coli cell extract
for highly productive cell-free protein expression.J. Struct. Funct.
Genomics, \emph{5} , 63--68.

Kim, H., Yoo, S. J., \& Kang, H. A. (2014). Yeast synthetic biology for
the production of recombinant therapeutic proteins. \emph{FEMS Yeast
Res.} , n/a-n/a. https://doi.org/10.1111/1567-1364.12195

Klammt, C., Schwarz, D., Löhr, F., Schneider, B., Dötsch, V., \&
Bernhard, F. (2006). Cell-free expression as an emerging technique for
the large scale production of integral membrane protein. \emph{FEBS J}
,\emph{273} (18), 4141--4153.
https://doi.org/10.1111/j.1742-4658.2006.05432.x

Levental, I., \& Lyman, E. (2022). Regulation of membrane protein
structure and function by their lipid nano-environment. \emph{Nat. Rev.
Mol. Cell Biol.} , 1--16. https://doi.org/10.1038/s41580-022-00524-4

Li, Z., Xiong, F., Lin, Q., d'Anjou, M., Daugulis, A. J., Yang, D. S.,
\& Hew, C. L. (2001). Low-temperature increases the yield of
biologically active herring antifreeze protein in Pichia
pastoris.\emph{Protein Expr. Purif.} , \emph{21} (3), 438--445.

Lin, S.-H., \& Guidotti, G. (2009). Chapter 35 Purification of Membrane
Proteins. In R. R. Burgess \& M. P. Deutscher (Eds.), \emph{Meth.
Enzymol.} (Vol. 463, pp. 619--629). Academic Press.
https://doi.org/10.1016/S0076-6879(09)63035-4

Liu, Q., Song, L., Peng, Q., Zhu, Q., Shi, X., Xu, M., Wang, Q., Zhang,
Y., \& Cai, M. (n.d.). A programmable high-expression yeast platform
responsive to user-defined signals. \emph{Sci. Adv.} , \emph{8} (6),
eabl5166. https://doi.org/10.1126/sciadv.abl5166

Löwe, M., Kalacheva, M., Boersma, A. J., \& Kedrov, A. (2020). The more
the merrier: Effects of macromolecular crowding on the structure and
dynamics of biological membranes. \emph{FEBS J.} , \emph{287} (23),
5039--5067. https://doi.org/10.1111/febs.15429

Lowthert, L. A., Ku, N. O., Liao, J., Coulombe, P. A., \& Omary, M. B.
(1995). Empigen BB: A Useful Detergent for Solubilization and
Biochemical Analysis of Keratins.Biochem. Biophys. Res.
Commun.,\emph{206} (1), 370--379. https://doi.org/10.1006/bbrc.1995.1051

Macek, B., Forchhammer, K., Hardouin, J., Weber-Ban, E., Grangeasse, C.,
\& Mijakovic, I. (2019). Protein post-translational modifications in
bacteria. \emph{Nat. Rev. Microbiol.} , \emph{17} (11), 651--664.
https://doi.org/10.1038/s41579-019-0243-0

Mazumder, M., \& McMillen, D. R. (2014). Design and characterization of
a dual-mode promoter with activation and repression capability for
tuning gene expression in yeast. \emph{Nucleic Acids Res.} ,\emph{42}
(14), 9514--9522. https://doi.org/10.1093/nar/gku651

Mitra, N., Sinha, S., Ramya, T. N. C., \& Surolia, A. (2006). N-linked
oligosaccharides as outfitters for glycoprotein folding, form and
function. \emph{Trends Biochem. Sci.} , \emph{31} (3), 156--163.
https://doi.org/10.1016/j.tibs.2006.01.003

Mitraki, A., \& King, J. (1989). Protein Folding Intermediates and
Inclusion Body Formation. \emph{Nat. Biotechnol.} , \emph{7} (7),
Article 7. https://doi.org/10.1038/nbt0789-690

Nakamura, S., Takasaki, H., Kobayashi, K., \& Kato, A. (1993).
Hyperglycosylation of hen egg white lysozyme in yeast. \emph{The J.
Biol. Chem.} , \emph{268} (17), 12706--12712.

Nasmyth, K., Adolf, G., Lydall, D., \& Seddon, A. (1990). The
identification of a second cell cycle control on the HO promoter in
yeast: Cell cycle regulation of SWI5 nuclear entry. \emph{Cell}
,\emph{62} (4), 631--647. https://doi.org/10.1016/0092-8674(90)90110-Z

Ng, D. T., Spear, E. D., \& Walter, P. (2000). The unfolded protein
response regulates multiple aspects of secretory and membrane protein
biogenesis and endoplasmic reticulum quality control. \emph{J. Cell
Biol.} , \emph{150} (1), 77--88.

Ohashi, H., Kanamori, T., Shimizu, Y., \& Ueda, T. (2010). A Highly
Controllable Reconstituted Cell-Free System -a Breakthrough in Protein
Synthesis Research. \emph{Curr. Pharm. Biotechnol.} , \emph{11} (3),
267--271. https://doi.org/10.2174/138920110791111889

Pan, X., \& Vachet, R. W. (2022). Membrane Protein Structures and
Interactions From Covalent Labeling Coupled with Mass
Spectrometry.\emph{Mass Spectrom. Rev.} , \emph{41} (1), 51--69.
https://doi.org/10.1002/mas.21667

Park, S. J., Lee, S., Cho, J., Kim, T. Y., Lee, J. W., Park, J. H., \&
Han, M.-J. (2005). Global physiological understanding and metabolic
engineering of microorganisms based on omics studies. \emph{Appl.
Microbiol. Biotechnol.} , \emph{68} , 567--579.

Qu, X., Wang, D., \& Wu, B. (2020). Chapter 1---Progress in GPCR
structure determination. In B. Jastrzebska \& P. S.-H. Park
(Eds.),\emph{GPCRs} (pp. 3--22). Academic Press.
https://doi.org/10.1016/B978-0-12-816228-6.00001-5

Rieth, M. D., Root, K. T., \& Glover, K. J. (2020). Reconstitution of
full-length human caveolin-1 into phospholipid bicelles: Validation by
analytical ultracentrifugation. \emph{Biophys. Chem.} , \emph{259} ,
106339. https://doi.org/10.1016/j.bpc.2020.106339

Roth, J., Zuber, C., Park, S., Jang, I., Lee, Y., Kysela, K. G., Fourn,
V., Santimaria, R., Guhl, B., \& Cho, J. W. (2010). Protein
N-glycosylation, protein folding, and protein quality control.\emph{Mol.
Cell} , \emph{30} (6), 497--506.
https://doi.org/10.1007/s10059-010-0159-z

Rueda, F., Gasser, B., Sánchez-Chardi, A., Roldán, M., Villegas, S.,
Puxbaum, V., Ferrer-Miralles, N., Unzueta, U., Vázquez, E.,
Garcia-Fruitós, E., Mattanovich, D., \& Villaverde, A. (2016).
Functional inclusion bodies produced in the yeast Pichia
pastoris.\emph{Microb. Cell Factories} , \emph{15} (1), 166.
https://doi.org/10.1186/s12934-016-0565-9

Sachse, R., Dondapati, S. K., Fenz, S. F., Schmidt, T., \& Kubick, S.
(2014). Membrane protein synthesis in cell-free systems: From
bio-mimetic systems to bio-membranes. \emph{FEBS Lett.} , \emph{588}
(17), 2774--2781. https://doi.org/10.1016/j.febslet.2014.06.007

San-Miguel, T., Pérez-Bermúdez, P., \& Gavidia, I. (2013). Production of
soluble eukaryotic recombinant proteins in E. coli is favoured in early
log-phase cultures induced at low temperature. \emph{Springerplus}
,\emph{2} , 1--4.

Schoborg, J. A., Hodgman, C. E., Anderson, M. J., \& Jewett, M. C.
(2014). Substrate replenishment and byproduct removal improve yeast
cell-free protein synthesis. \emph{Biotechnol. J.} , \emph{9} (5),
630--640. https://doi.org/10.1002/biot.201300383

Sharma, A. K., Shukla, E., Janoti, D. S., Mukherjee, K. J., \& Shiloach,
J. (2020). A novel knock out strategy to enhance recombinant protein
expression in Escherichia coli. \emph{Microb. Cell Factories} ,\emph{19}
(1), 148. https://doi.org/10.1186/s12934-020-01407-z

Shental-Bechor, D., \& Levy, Y. (2008). Effect of glycosylation on
protein folding: A close look at thermodynamic
stabilization.\emph{Proceed. Natl. Acad. Sci. USA} .
https://doi.org/10.1073/pnas.0801340105

Silow, M., \& Oliveberg, M. (1997). Transient aggregates in protein
folding are easily mistaken for folding intermediates.\emph{Proceed.
Natl. Acad. Sci.,} \emph{94} (12), 6084--6086.
https://doi.org/10.1073/pnas.94.12.6084

Silverman, A. D., Karim, A. S., \& Jewett, M. C. (2020). Cell-free gene
expression: An expanded repertoire of applications. \emph{Nat. Rev.
Genet.} , \emph{21} (3), Article 3.
https://doi.org/10.1038/s41576-019-0186-3

Stueber, D., \& Bujard, H. (1982). Transcription from efficient
promoters can interfere with plasmid replication and diminish expression
of plasmid specified genes. \emph{EMBO J.} , \emph{1} (11), 1399--1404.
https://doi.org/10.1002/j.1460-2075.1982.tb01329.x

Swartz, J. R. (2001). Advances in Escherichia coli production of
therapeutic proteins. \emph{Curr. Opin. Biotechnol.} , \emph{12} (2),
195--201. https://doi.org/10.1016/S0958-1669(00)00199-3

Tomimoto, K., Fujita, Y., Iwaki, T., Chiba, Y., Jigami, Y., Nakayama,
K., Nakajima, Y., \& Abe, H. (2013). Protease-Deficient Saccharomyces
cerevisiae Strains for the Synthesis of Human-Compatible
Glycoproteins.\emph{Biosci. Biotechnol. Biochem.} , \emph{77} (12),
2461--2466. https://doi.org/10.1271/bbb.130588

Trethewey, R. N. (2004). Metabolite profiling as an aid to metabolic
engineering in plants. \emph{Curr. Opin. Plant Biol.} , \emph{7} (2),
196--201.

Vachon, L., Wood, J., Kwon, E.-J. G., Laderoute, A., Chatfield-Reed, K.,
Karagiannis, J., \& Chua, G. (2013). Functional Characterization of
Fission Yeast Transcription Factors by Overexpression
Analysis.\emph{Genetics} , \emph{194} (4), 873--884.
https://doi.org/10.1534/genetics.113.150870

Walter, P., \& Ron, D. (2011). The unfolded protein response: From
stress pathway to homeostatic regulation. \emph{Science} .
https://doi.org/10.1126/science.1209038

Weber, L. A., Feman, E. R., \& Baglioni, C. (1975). Cell free system
from HeLa cells active in initiation of protein
synthesis.\emph{Biochemistry} , \emph{14} (24), 5315--5321.

Weickert, M. J., Pagratis, M., Curry, S. R., \& Blackmore, R. (1997).
Stabilization of apoglobin by low temperature increases yield of soluble
recombinant hemoglobin in Escherichia coli. \emph{Appl. Environ.
Microbiol.} , \emph{63} (11), 4313--4320.

Whiles, J. A., Deems, R., Vold, R. R., \& Dennis, E. A. (2002). Bicelles
in structure-function studies of membrane-associated
proteins.\emph{Bioorgan. Chem.} , \emph{30} (6), 431--442.
https://doi.org/10.1016/S0045-2068(02)00527-8

Ye, C., Chen, X., Yang, M., Zeng, X., \& Qiao, S. (2021). CRISPR/Cas9
mediated T7 RNA polymerase gene knock-in in E. coli BW25113 makes T7
expression system work efficiently.J. Biol. Eng., \emph{15} , 22.
https://doi.org/10.1186/s13036-021-00270-9

Yu, X. (2006). Genome-wide prediction and characterization of
interactions between transcription factors in Saccharomyces
cerevisiae.\emph{Nucleic Acids Res.} , \emph{34} (3), 917--927.
https://doi.org/10.1093/nar/gkj487

Yuan, H., Liu, Y., Li, J., Shin, H., Du, G., Shi, Z., Chen, J., \& Liu,
L. (2018). Combinatorial synthetic pathway fine-tuning and comparative
transcriptomics for metabolic engineering of Raoultella ornithinolytica
BF60 to efficiently synthesize 2, 5-furandicarboxylic
acid.\emph{Biotechnol. Bioeng.} , \emph{115} (9), 2148--2155.

Zhou, H.-X. (2009). Crowding effects of membrane proteins. \emph{J.
Phys. Chem. B.} , \emph{113} (23), 7995--8005.

Zhou, L., Ma, Y., Wang, K., Chen, T., Huang, Y., Liu, L., Li, Y., Sun,
J., Hu, Y., Li, T., Kong, Z., Wang, Y., Zheng, Q., Zhao, Q., Zhang, J.,
Gu, Y., Yu, H., Xia, N., \& Li, S. (2022). Omics-guided bacterial
engineering of Escherichia coli ER2566 for recombinant protein
expression. \emph{Appl. Microbiol. Biotechnol.} .
https://doi.org/10.1007/s00253-022-12339-6

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