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\begin{document}

\title{Advances in cell-free biosensors: Principle, mechanism and applications}



\author[1]{Liyuan Zhang}%
\author[2]{Wei Guo}%
\author[1]{Yuan Lu}%
\affil[1]{Tsinghua University}%
\affil[2]{Shenyang Agricultural University}%


\vspace{-1em}



  
  \date{June 09, 2024}


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\selectlanguage{english}
\begin{abstract}
Synthetic biology has promoted the development of biosensors as tools
for detecting trace substances. In the past, biosensors based on
synthetic biology have been designed on living cells, but the
development of cell biosensors has been greatly limited by defects such
as the obstruction of cell membrane. However, the advent of cell-free
synthetic biology addresses these limitations. Biosensors based on the
cell-free protein synthesis system have the advantages of higher safety,
higher sensitivity, and faster response time over cell biosensors, which
makes cell-free biosensors have a broader application prospect. This
review summarizes the workflow of various cell-free biosensors,
including the identification of analytes and signal output. The
detection range of cell-free biosensors is greatly enlarged by different
recognition mechanisms and output methods. In addition, the review also
discusses the applications of cell-free biosensors in environmental
monitoring and health diagnosis, as well as existing deficiencies and
aspects that should be improved. In the future, through continuous
improvement and optimization, the potential of cell-free biosensors will
be stimulated, and their application fields will be expanded.%
\end{abstract}%



\sloppy


\textbf{1 Introduction}

Biosensors are analysis tools that take biological components as the
main functional elements and used for rapid detection of various
trace-level analytes. They generally consist of sensitive biorecognition
elements, transducers, and signal analysis systems {[}1{]}. The
sensitive element (enzyme, antibody, cell, \emph{etc.} ) identifies and
binds the analytes, and then the transducer captures the interaction
between the sensitive material and the analyte and converts the analyte
into an identifiable signal (e.g., electricity signal). The quantity of
the analyte is further calculated through the signal analysis system.
Compared with traditional instrument-based analytical chemistry such as
gas chromatography (GC), high-performance liquid chromatography (HPLC),
biosensors are less costly, more specific, faster, easier to operate,
capable of on-line analysis, real-time identification, and simultaneous
output of results. So they are more sensitive and more convenient. With
the advantages of biosensors, they have been widely used in
environmental detection, food safety inspection, disease diagnosis,
biochemical analysis, and other fields {[}2-4{]}.

Meanwhile, synthetic biology has propelled the development of biological
sensors. Synthetic biology has great potential in the application of
biosensors by designing genetic circuits and logic operations for
biological components, resulting in a variety of genetic devices and
biological modules {[}5{]}. It has promoted the construction of
customized biological function system, which can finally realize sensors
with customized programming sensitivity, specificity and dynamic range,
and expand the scope of sensor detection target {[}6, 7{]}, providing
transformative tools for improving the performance of biosensors.

The design of synthetic biology is mainly dependent on living cells in
recent decades, which leads to the rapid development of cell biosensors.
Cell biosensors can use animal and plant cells, especially microbial
cells as basal cells (sensitive element). Cells can metabolize a variety
of compounds using intracellular enzymes with high stability and
activity. Cell biosensors have a long service life and high
reproducibility of experimental results {[}8{]}. Moreover, the
sensitivity and specificity of biosensors can be improved by the
introduction of corresponding genetic modules. Heavy metals, pesticides,
vitamins, and some macromolecules can be detected using cell biosensors.
For example, Hou \emph{et al.} {[}9{]} specifically detected
bioavailability of cadmium, lead, and arsenic in contaminated soil using
a customized suite of multiple whole-cell \emph{Escherichia
coli}sensors. Nevertheless, there are some shortcomings in cell
biosensors that need to be addressed. Since cell biosensors use live
genetically modified microorganisms (GMOs), if they are released into
the environment, there are certain unsafe factors. In order to prevent
the occurrence of this situation, it is usually impossible to apply
these GMO biosensors {[}10, 11{]}. Furthermore, the response time of
biosensors is prolonged because some analytes are hard to cross over the
cell membrane. Moreover, some analytes may be toxic to living cells, so
some cell-based biosensors are not suitable for detecting cytotoxic or
impermeable membrane analytes, such as organophosphates. They may also
be influenced by actual environmental samples as well as their own
physiological and chemical conditions {[}12{]}. The above disadvantages
lead to significant limitations for cell biosensors in applications.

However, the emergence of cell-free synthetic biology not only promotes
the construction of cell-free biosensors in synthetic biology but also
solves the limitations described above. Currently, the biosensor
platform based on cell-free protein synthesis (CFPS) system has been
developed {[}13{]}. The CFPS system is a mixed system of DNA templates,
transcriptional machinery, translational machinery, the necessary
substrates (including amino acids, energy substrates, cofactors, and
salts), and water{[}14{]}. CFPS system can be divided into crude extract
system and PURE system. The main difference between the two systems is
the source of the translational machinery. As the name implies, one is
from the crude extract, and the other one is from purified components.
Compared with the crude extract system, the PURE system is more stable;
however, the cost is higher, and the yield is also lower. The CFPS
system and DNA template can be assembled into a mature cell-free
biosensor. CFPS systems perform biological transcription and translation
in an open environment, exhibiting a variety of unique functions
superior to cellular systems and laying the foundation for biosensors to
introduce more complex genetic circuits. Due to the uniqueness of the
cell-free system, the biosensors based on the cell-free system have
obvious advantages, which are reflected in the aspects of higher safety,
higher tolerance, shorter response time, higher sensitivity, higher
stability, and higher selectivity. These advantages are summarized in
Table 1. Therefore, given these significant advantages, the application
of cell-free systems in biosensor engineering is growing rapidly. The
following contents focus on the design principle and workflow of
cell-free biosensors, as well as the development of cell-free biosensors
in environmental monitoring and biomedical applications.

\textbf{2 Principle and workflow of cell-free biosensors}

The design principle of most cell-free biosensors is to select the
appropriate recognition mechanism and reporter gene based on the
analytes, and then clone the encoded gene into the cell-free expression
vector. Furthermore, select the appropriate cell-free protein synthesis
system to constitute a mature cell-free biosensor with the coding
template DNA. Cell-free biosensors can detect a variety of analytes,
including ions, antibiotics, amino acids as well as nucleic acids of
viral pathogens. The workflow of cell-free biosensor (Fig. 1) can be
divided into two parts, the recognition and response of analytes by
specific identification mechanisms, and the output of readable signals
through reporter gene expression. First, accurate recognition of
analytes is the key to cell-free biosensors. When analytes are added to
the cell-free system, the sensor's recognition mechanism is regulated by
specific molecular structure and binding {[}15, 16{]}. Second, the
downstream reporter gene is activated to be transcribed and translated
into reporter proteins in a cell-free system. According to the
presentation mode of different reporting proteins, the detection results
are output by optical and other readable signals {[}17{]}.

\subsection*{}

{\label{section}}

\subsection*{2.1 Recognition-response
mechanisms}

{\label{recognition-response-mechanisms}}

With the emergence of multiple analytes, some analytes are difficult to
be recognized and detected by traditional recognition mechanisms (such
as enzymes, antibodies, and PCR technology), which has led to the
development of recognition mechanisms to use diversified molecular
structures as recognition elements. The following contents mainly
introduce the recognition mechanism of cell-free biosensors based on
different molecular structures, including transcription factors,
CRISPR-Cas, toehold switches, and adaptors {[}18{]}.

\textbf{2.1.1 Transcription factor activation/repression}

A transcription factor (TF) is a protein molecule with a specific
structure that binds to a specific gene and regulates gene expression at
a specific intensity at a specific time and place. Therefore, the
sensitivity and specificity of TFs can be used to design the sensor as a
recognition element. TF-based cell-free biosensors have been used to
identify specific small molecules, such as inorganic ions and organic
molecules (bacterial quorum sensing molecules) {[}19{]}, and they are
also used in high-throughput screening and metabolic engineering
{[}20{]}. Specific correct TFs or natural conformational TFs are
selected by detecting different analytes, such as TF in response to
aromatic compounds (XylS-AraC,XylR-NtrC, and LysR), metal ions (MerR,
ArsR, DtxR, Fur, and NikR), or antibiotics (TetR and MarR) {[}21{]}.
When analytes (ligands) are present in a cell-free environment, the
response of TFs is immediately obtained, and binding of ligands to their
activated TFs or the release of ligand-bound inhibitory TFs can lead to
the reporter gene expression (Fig. 2A). For unknown ligands, they can be
converted into detectable ligands by using metabolic enzymes {[}12{]}.

To avoid the reaction of TFs to substances other than detection targets,
TFs with enhanced specificity and sensitivity should be further
expanded. Alternatively, a directed evolutionary strategy can be used to
screen and select specific TFs {[}22{]}. Due to the known limitations of
TFs, not all analytes can be identified, so there are other
identification mechanisms {[}23, 24{]}.

\textbf{2.1.2 Toehold switch and CRISPER-Cas recognition}

Cell-free biosensors based on toehold switch and CRISPER-Cas are mainly
designed to detect genomic DNA or viral RNA of some pathogens. The
toehold switch system is a programmable ribosome regulator, and it
consists of two strands of RNA, called a switch or a trigger. The
toehold switch sensor controls the translation of genes by triggering
the binding of RNA through a trans effect. The switch contains a salient
loop structure-forming in the upstream of the gene, which blocks gene
translation in cis by blocking the ribosome binding site (RBS) {[}25{]}.
After binding to the complementary trigger RNA, the sequestration is
released, and the gene translation is activated {[}26{]}. The target
nucleic acid is used as a trigger RNA to activate the expression of the
reporter gene in cell-free system. Finally, the detection of the target
can be determined directly by the expression of the reporter gene.

The cell-free biosensors based on CRISPER-Cas mainly rely on the cut
principle of CRISPER-Cas to identify targets. CFPS system can express
many kinds of active CRISPR machinery from plasmids or linear DNAs, and
it can further output quantitative dynamics of gene cleavage or
repression without the protein purification {[}27{]}. According to
different Cas effectors (Cas9, Cas12a, and Cas13a), CRISPR biosensor
systems have different shear cleavage principles {[}28{]}. For example,
the CRISPER-Cas13a system can detect analytes that can directly cleave
captured targets using the Cas13-crRNA complex {[}29{]}, and then the
lateral cracks of the complex are activated to cleave nearby
non-targeted RNA (quenched fluorescent RNA). As a reporter, the quenched
fluorescent RNA is cleaved and displays a fluorescence signal to respond
to the results.

In addition, toehold switch and CRISPER-Cas can cooperate to detect
analytes. For example, Pardee \emph{et al} . {[}30{]} identified two
strains by NASBA- CRISPER /Cas9 cleavage method (Fig. 2B). The nucleic
acid sequence of a strain can be used as the target sequence. With the
participation of reverse transcriptase and T7 RNA polymerase, the
proto-spacer adjacent motifs (PAM) and trigger sequence (lacZ trigger)
can be introduced in target sequence by isothermal amplification
{[}31{]}. Cas endonuclease is mediated by sgRNA to recognize the PAM of
the target sequence for fixed-point cutting. The uncut sequence contains
the trigger RNA, which can be detected by the paper-based toehold switch
sensor and finally identified as the strain type by the color change
{[}32{]}.

Nevertheless, there are some challenges to this method. The isothermal
amplification process is susceptible to contamination, which could lead
to off-target products and false positives. However, this phenomenon can
be minimized by using sequentially specific fulcrum switch sensors, and
CRISPR-Cas mediated amplification of downstream selection {[}33{]}.
Multiplexing for CRISPR-Cas systems is also a considerable challenge
{[}34, 35{]}.

\textbf{2.1.3 Aptamer recognition}

Due to its small size, high stability, high affinity, and high
specificity, aptamers can not only separate and combine with any
selected molecule (including metal ions, small molecules, peptides,
proteins, and even materials surfaces), but also can be easily modified
in any position. Therefore, they are suitable for use as recognition
elements of sensors {[}36, 37{]}. Aptamers are single-stranded DNA or
RNA molecules, most of which are obtained by a combinatorial biology
technique called SELEX. In the cell-free environment, the
single-stranded region of the aptamer is easily regulated by phage
polymerase, which regulates the transcription and translation of the
aptamer sequence through the T7 promoter. For example, Iyer \emph{et al}
. used nucleic acid aptamers to identify thrombin. They inserted
thrombin-bound ssDNA aptamers in the downstream of the T7 promoter,
creating a ''bubble'' structure downstream that binds to the aptamers in
the presence of thrombin, blocking transcription of the T7 RNA
polymerase (Fig. 2C). Finally, the presence of thrombin can be detected
by the expression of the reporter gene {[}38, 39{]}.

Although this method has high stability and specificity, its sensitivity
needs to be further improved. In addition, the identification mechanism
lacks high-quality aptamers for clinically important targets in medical
applications. The aptamer technology must be extensively tested in
clinical sample substrates to establish the reliability and accuracy.

\textbf{2.1.4 CFPS component identification}

In addition to the recognition mechanism mentioned above, there is
another recognition mechanism that utilizes the cell-free translation
system. So far, this mechanism has only been applied to amino acid
detection. The design of a cell-free system selectively removes a
specific amino acid, and it then adds the sample, which contains missing
components from the system, such as amino acids in the patient's plasma
sample {[}40{]} (Fig. 2D). Aminoacyl-tRNA synthase can be used as a
recognition element to identify the amino acid in the sample and then
produce aminoacyl tRNA. After the CFPS system is complete, the
translation machinery is activated to produce protein output.
Jang\emph{et al} . {[}41{]} used this principle to design cell-free
biosensors to detect amino acids. This cell-free biosensor not only can
accurately detect the amino acid content in the sample but also has a
high sensitivity.

In addition to using the recognition mechanism of the cell-free
translation system, most of the recognition mechanisms are encoded in
the genetic circuit and then added to the cell-free hybrid system for
characterization. Because the CFPS system can regulate the complex
genetic circuits, it is possible to design a variety of recognition
mechanisms for the detection of cell-free biosensors. This extends the
types, levels, and ranges of target analytes to be detected.

\textbf{2.2 Signal output}

The signal of cell-free biosensors is mainly output in the form of
optical or electrochemical signals. According to statistics, the optical
reporter genes mainly include \emph{lux} (bacterial
luciferase),\emph{luc} (firefly luciferase), \emph{gfp} (green
fluorescent protein), and \emph{lacZ} (\selectlanguage{greek}β-\selectlanguage{english}galactosidase) {[}42{]}. After
the identification, the downstream reporter gene is activated and
expressed in the cell-free system. Various output methods are available
for monitoring the proteins expressed by the reporter genes, including
fluorescence, luminescence, visible color changes, \emph{etc.}

The most common method is to report the fluorescence of proteins based
on GFP which is a simple, convenient and intuitive signal output method
in laboratory operation, and it does not require reaction substrates
(Fig. 3A). GFP expressed by the cell-free system could not glow by
itself, and the fluorescence only can be generated by the light
excitation. Therefore, the fluorescence output representing the gene
expression level needs to be measured by means of absorbance detection.
However, the obvious disadvantage of GFP is that the background signal
is high, which makes the sensitivity of GFP low.

In addition, the signal can be output by the luciferase gene
(\emph{lux/luc} ) (Fig. 3B). The luciferase experiment is extremely
sensitive. It has no signal background and has a wide linear range (up
to 7-8 orders of magnitude). Luciferase needs to be mixed with luciferin
and other required chemicals to produce fluorescence. Generally,
luciferase assay reagent is added to the test system, and the luciferase
level is measured in the plate reader after the reactant mixing.
Moreover, the application of luciferase also has certain limitations,
such as short half-life, poor repeatability, and certain requirements on
oxygen, \emph{etc.}

Enzymes catalyze substrate molecules that can produce strong exponential
signals than fluorescent proteins. \selectlanguage{greek}β-\selectlanguage{english}galactosidase (\selectlanguage{greek}β-\selectlanguage{english}gal) can lyse
synthetic substrates, resulting in color changes, fluorescence, or
chemiluminescence, which allows the output of LacZ-based sensors to be
adjusted for different conditions. However, \selectlanguage{greek}β-\selectlanguage{english}gal has some dependence on
the substrate. The colorimetric method based on the enzyme activity of
\selectlanguage{greek}β-\selectlanguage{english}gal can directly observe the color changes with the naked eye, and the
most common substrate for colorimetric detection
is\emph{O-nitrophenyl-d-pyrine} galactoside. This signal output method
is suitable for paper-based cell-free biosensors (Fig. 3C). Because the
cell-free biosensors based on luciferases and \selectlanguage{greek}β-\selectlanguage{english}gal have high
sensitivity and short response time, so \emph{luc} and \emph{lacZ} are
preferred reporter genes.

Except for the optical signal output, cell-free biosensors can also be
output by electrochemical measurement. A variety of material electrodes
combined with cell-free system and electrochemical signals can be
generated, while the electrodes can capture the target.
Capacitance-voltage and constant-capacitance measurements are employed
to monitor the capacitance changes induced by surface modification steps
for sensor preparation as well as interactions between receptor and its
ligands {[}43{]}. Mousavi \emph{et al} . {[}44{]} designed an extensible
reporter enzyme system, in which a sensor based on a cell-free gene
circuit cleaves specific DNA sequences in solution, generating
electrochemical signals when the newly released strands are trapped on
the surface of nanostructured microelectrodes (Fig. 3D). This method is
in sharp contrast to the traditional optical reporter, which not only
has limited multiplexing ability but also has a dependence on
ventilation and reduced sensitivity in turbid solutions {[}45{]}. These
limitations can be overcome by electrochemical measurements. The
electrochemical system will enable the multiplexing of gene-based
circuits for portable detection and will facilitate the development of
electronic devices related to synthetic biology.

\textbf{3 Improvement of cell-free biosensors in practical application}

To keep up with the development of practical applications, the cell-free
biosensor is required to be more portable, stable, and cost-efficient.
These requirements have led to continuous improvement of cell-free
biosensors. Generally, cell-free biosensor reagents are often
refrigerated or frozen during storage or transportation. This method of
storage is not convenient, which may hinder the field deployment.
Therefore, the researchers develop the lyophilization technology to
improve the storage stability of cell-free biosensors. The cell-free
system ensures that it remains active after lyophilization and does not
adversely affect the efficiency. By freeze-drying, the cold-chain
storage problems can be overcome to stabilize the long-term and higher
temperature storage of the cell extract, which can last up to three
months to a year and reduce the necessary storage space. Moreover, the
stability of cell-free biosensors can be improved in other ways. For
example, Karig \emph{et al.} {[}46{]} also investigated using the
non-reducing disaccharide trehalose to protect cell-free components
during oven drying. Moreover, components can be encapsulated in the
liposomes {[}47{]} or polymer substrates to maintain the system
stability {[}48{]}. However, the decrease of the activity of the
cell-free system after lyophilization is the main improvement target
that needs to be developed in the future.

To facilitate the field monitoring, biosensors need improving the
portability. Cell-free systems can be freeze-dried with appropriate
supports (e.g., microtubules and microporous plates). Beyond that, the
cell-free system also can be introduced onto a cheap matrix simple paper
{[}26{]}, where the freeze-drying and the signal amplification can
reduce the chance of contamination and false positives. Because of the
small size of the freeze-dried reagent required for the paper-based
cell-free biosensor, this greatly reduces the cost and facilitates the
field testing.

Furthermore, there may be some differences in the cell-free systems
prepared in different batches, so it is necessary to standardize the
cell-free systems. PURE systems can be developed to improve sensor
standards. The PURE system for cell-free protein synthesis reduces the
level of contaminated proteases, nucleases, and phosphatases, and
provides a more precise method of preparation, a higher reproducibility,
and better flexibility of the modular system. Because there is no
metabolic side effect of amino acid library like in crude extract-based
cell-free system, so the PURE system is more stable {[}49{]}. The PURE
system has been commercialized to make them available for a variety of
applications, with strict quality control. However, the commercial PURE
system is expensive, and the production cost of the PURE system is very
high, so the general sensor design still uses the crude extract system.
Therefore, in order to standardize the cell-free biosensors, more time
and energy should be spent on the development of the PURE system to
improve the efficiency and reduce the cost in the future. At present,
there is some lag in commercial applications of cell-free biosensors,
which will be the focus of future development.

\textbf{4 Applications}

At present, we are all faced with the situation of frequent
environmental pollution and human diseases. All kinds of environmental
pollutants and diseases seriously threaten the living environment and
health of human beings. To detect these hazards more quickly and
accurately, biosensors with low cost and high efficiency are urgently
needed. In this context, cell-free biosensors have made remarkable
achievements in the rapid detection of environmental pollutants and
disease pathogens (Fig. 4).

\textbf{4.1 Environmental detection}

Many chemical pollutants exist in the environment, which pose some
serious threats because they are invisible or hard to spot. The most
common harmful substances are heavy metals, such as arsenic and
mercury{[}50{]}, as well as toxic small molecules and antibiotics {[}51,
52{]}. The environmental protection agency (EPA) stipulates that some
harmful pollutants cannot exceed a certain level in the environment, so
it is necessary to test the present level of these substances in the
environment. A number of cell-free biosensors have been developed and
designed to detect the presence or content of hazardous substances in
environmental samples.

When inorganic heavy metals enter the body from the environment, they
accumulate in certain organs of the body, cause chronic poisoning, and
harm health. Researchers have designed a number of cell-free biosensors
for detecting heavy metals. For example, a paper-based mercury biosensor
was designed by the iGEM team Peking 2010 {[}53{]}. By adjusting the
plasmid concentrations and adding new translation enhancement sequences
to optimize the cell-free mercury sensor, it increased the yield of the
CFPS reaction and enabled accurate quantification of the analytes. It
can detect 6 \selectlanguage{greek}µ\selectlanguage{english}g/L of mercury concentration. The paper-based cell-free
biosensor has a low cost and is convenient for detection. In addition,
the team built a 3D-printed box that can be connected to a phone for
real-time readings, extending the detection platform to real-time
applications.

There are also some cell-free biosensors designed to detect toxic
organic molecules. For instance, Khalid\emph{et al} . {[}53{]} developed
a cell-free biosensor platform, a ligand-induced activated RNA output
sensor (ROSALIND), which uses a variety of TFs to detect harmful
pollutants in water samples, such as toxic PPCP compounds (salicylate,
benzalkonium chloride and uric acid). However, when testing
non-laboratory samples (e.g., drinking water and lake water), the
sensitivity of the sensor may be reduced due to the interference of the
molecular components in the samples. Therefore, the matrix effect of
these test samples needs to be further explored in future work.

The presence of antibiotics in the environment is harmful to the
ecological balance and human health. Therefore, its presence in the
environment needs to be monitored in a timely manner. Duyen \emph{et al}
. {[}54{]} have developed a simple biological sensor based on color
paper, inhibition of bacteria used in the detection of protein synthesis
of antibiotics. The detection limits of paramycin, tetracycline,
erythromycin, and chloramphenicol were further estimated to be 0.5, 2.1,
0.8, and 6.1 \selectlanguage{greek}μ\selectlanguage{english}g/mL. Pellinen \emph{et al} . {[}55{]} designed a novel
cell-free biosensor for the detection of tetracycline hydrochloride
(Tc-HCl). Tc-HCl has been detected at concentrations below 10 ng/ml. The
maximum residue limit for Tc-HCl in EU milk samples is 100 ng/ml, and
the limit for Tc-HCl in commercial microbial inhibition tests is 30 to
500 ng/ml. It can be seen that the detection limit of cell-free
biosensors can reach the ppt level, which has reached the environmental
standard level for the detection of some pollutants. The test results
can be used to judge whether the samples under test meet the standards
or not. Although the sensitivity of current cell-free biosensors can
reach a certain level, some substances with lower detection limits still
exist or will appear in the future, which requires us to continuously
improve and optimize the cell-free biosensors.

These examples demonstrate that cell-free biosensors have been
successfully applied to the detection of toxic substances in the
environment. Due to its low detection limit and fast and convenient
characteristics, cell-free biosensors can quickly detect pollutants,
determine the safety limit of analysis samples, and timely monitor the
environment for timely prevention or repair. Through the continuous
optimization of cell-free biosensors, it has a broad prospect in
environmental monitoring.

\textbf{4.2 Clinical biomedical applications}

Because of the high sensitivity and fast response time of cell-free
biosensors, they can quickly judge the diagnosis result, which occupies
an important position in biomedicine. The existing cell-free biosensors
mainly focus on the detection of clinically relevant carcinogens,
bacteria, and pathogens (e.g., EDCs, AA, and AHL) {[}17, 56-58{]}. These
sensors can be used to screen pathogens that can be detected in blood,
urine, and sputum samples from clinical patients.

The well-known chemicals called endocrine-disrupting chemicals (EDCs)
{[}59, 60{]}, widely exist in the environment, food, and personal care
products. Exposure to EDCs can lead to acute and chronic diseases,
including cancer and diabetes. Salehi \emph{et al} . {[}61{]} designed a
hER\selectlanguage{greek}β-\selectlanguage{english}CFPS biosensor to detect endocrine xenoestrogens (XEs, one kind of
the EDCs) in human blood and urine. Because these test samples (blood,
urine, and sputum samples from clinical patients) are complex, they can
interfere with the cell-free system to a certain degree and may alter
the delicate calibration of protein synthesis reactions, making the test
process less smooth. In order to solve this problem, some measurements
can be taken to pretreat the sample. They added RNA enzyme inhibitors to
the samples, which can reduce the impact of urine or blood samples on
the CFPS system. This can simplify the detection process, which can be
used for more complex analytes and expand the application range of
cell-free biosensors.

The virus is rapidly pathogenic, and some are highly infectious. The
severity of the virus infection and its unknown complications make
timely diagnosis of the virus critical to the human health, which also
can limit the rapid spread of the virus. In this context, some cell-free
biosensors are designed to detect viruses. Gootenberg \emph{et al} .
{[}62{]} developed a rapid diagnostic cell-free biosensor (SHERLOCK)
based on CRISPR-Cas13a to detect Zika virus in human serum samples. The
sensitivity of the sensor is similar to that of ddPCR and qPCR, but with
less variation. To improve the specificity of the sensor, they
synthesized mismatched crRNA, which allowed them to distinguish between
different strains (Zika virus and dengue fever). Cell-free biosensors
can also be used to detect other viruses, such as Ebola virus. Now there
is a kind of electrochemical DNA biosensor for detecting examples of
this kind of virus {[}63{]}. In a word, cell-free biosensors can detect
not only the presence or absence of a single virus but also different
types of viruses.

The content of amino acids also has a great impact on human health. The
lack of amino acids can lead to abnormal physiological functions, affect
the normal progress of antibody metabolism, and lead to diseases. It can
be used as an early detection method for several types of cancer.
Jang\emph{et al} . {[}41, 64{]} designed a CFPS biosensor to detect
amino acids in fetal bovine serum (FBS) samples. The amino acid content
was successfully detected, and the detection limit was less than 100 nM.
However, the types of amino acids detected by cell-free sensors based on
crude extracts are limited, so they suggested using the PURE system for
cell-free biosensors. It can detect more kinds of amino acids (Asp, Asn,
Glu, and Gln) than the crude extract system, and the detection threshold
is lower {[}65{]}.

These examples show that cell-free biosensors have significant
advantages in medical diagnosis and clinical sample testing. They can be
used for early detection of disease and also can respond quickly to
virus outbreaks or the occurrence of genetic variations and mutations to
help monitor the spread of disease.

\textbf{5 Conclusion}

The cell-free system with unique advantages provides a novel design
platform for the development of biosensors. Considering the openness and
rapid prototyping capability of CFPS, the CFPS system can open up more
design space for the construction and optimization of biosensors and
genetic circuits. Cell-free biosensors based on TF, RNA, and toehold
switch can reduce the number of cycles required to design and help build
complex genetic networks. CFPS system can also be integrated with
mathematical modeling and high technologies (e.g., automation and
microfluidics) to unlock the potential of cell-free biosensors.

In the practical applications of cell-free biosensors, the
lyophilization technology based on the portable paper platform can
maintain the stability of the system, which promotes its portable use
and reduces the cost. However, there are still many challenges to be
addressed. The decline of the activity after the storage is a problem
that needs to be further improved. To improve in situ detection,
multiplexing functions, the sensitivity, and the specificity of
cell-free biosensors need to be further optimized.

In addition, cell-free biosensors can use CFPS systems other than
\emph{E. coli} , such as yeast and mammalian cells, to develop more
sophisticated biosensors. By improving the sensor recognition mechanisms
and combining cell-free systems with other materials (e.g., silicon),
more types of functional cell-free biosensors can be developed. It might
expand the detection range of cell-free biosensors to sense the odor,
air, temperature, light, and osmotic pressure. With further evolution of
cell-free biosensors, besides environmental monitoring and human health
diagnosis, they will increasingly expand their applications to food
testing, classroom education, and others, making them more practical and
commercial.

\textbf{Acknowledgment}

This work was supported by the National Key R\&D Program of China (Grant
No. 2018YFA0901700), the Institute for Guo Qiang, Tsinghua University
(Grant No. 2019GQG1016), and the Laboratory Innovation Fund of Tsinghua
University.

\textbf{Conflict of interest}

The authors declare no financial or commercial conflict of interest.

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\textbf{Table 1.} The advantages of cell-free biosensors\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Features\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Advantages\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Reference\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Safety\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
No GMOs will be released, and therefore there is no biosafety
issue.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
{[}48, 66{]}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Toxicity tolerance\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
The system can operate in the presence of toxins.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
{[}67{]}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Response time\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
The tested materials can react directly with the sensors in a cell-free
environment to generate signals more quickly.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Selectivity\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
It has the selectivity based on biosensor elements, which can reduce the
interference with other signals.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
{[}51{]}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Stability\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Cell-free systems have high long-term storage stability by the
freeze-drying technology.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Sensitivity (Detection limit)\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
The detection sensitivity is high; the detection limit is low and can
even reach the nanomole level.\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
{[}68{]}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Robustness\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Cell-free system can keep its structure and function stable when it is
disturbed by uncertain factors.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
{[}69{]}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Engineering operation\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Metabolic pathways can be simplified and optimized by adding different
concentrations of DNA components or by mixing different cell
extracts.\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
{[}55{]}\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Figure legends}

\textbf{Fig. 1. The workflow of cell-free biosensors.}

\textbf{Fig. 2. Recognition-response mechanisms of cell-free biosensor
systems.} (A) After the ligand is identified, reporter genes can be
activated by binding activated transcription factors or releasing
inhibitory transcription factors. Unknown ligands can be converted into
detectable ligands by using metabolic enzymes before the identification.
(B) Cell-free biosensors use NASBA-CRISPR/Cas9 cleavage system to
identify different strains of virus. (C) Nucleic acid ligands are used
to identify thrombin. When thrombin is absent, the reporter protein is
successfully expressed, but the translation is blocked in the presence
of thrombin. (D) When samples containing amino acids are added,
incomplete CFPS is activated, leading to successful expression of the
reporter protein.

\textbf{Fig. 3. Signal output of cell-free biosensor systems.} (A) The
reporter gene \emph{gfp} is expressed in the CFPS system and output in
the form of optical signal. (B) The reporter gene \emph{luc} is
expressed in the CFPS system and output in the form of optical signal.
(C) The reporter gene \emph{lacZ} is expressed in a paper-based
cell-free system, and the color change on the measured paper can be
easily detected by the naked eye. (D) The biosensor based on the
cell-free genetic circuit captures the analyte through the
nanostructured microelectrode to generate the electrochemical signal
output.

\textbf{Fig. 4. The applications of cell-free biosensors.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig/Fig}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fih/Fih}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fii/Fii}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fij/Fij}

\end{center}
\end{figure}

\selectlanguage{english}
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