Saccharides Create a Crowding Environment for Gene Expression in

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Biological and Environmental Phenomena at the Interface

Saccharides create crowding environment for gene expression in cell-free systems Lihui Bai, Xiaocui Guo, Xue Zhang, Wenting Yu, and Dayong Yang Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b03744 • Publication Date (Web): 08 Apr 2019 Downloaded from http://pubs.acs.org on April 10, 2019

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Saccharides create crowding environment for gene expression in cell-free systems Lihui Bai#, Xiaocui Guo#, Xue Zhang, Wenting Yu, Dayong Yang*

School of Chemical Engineering and Technology, Key Laboratory of Systems

Bioengineering (Ministry of Education), Collaborative Innovation Center of Chemical

Science and Engineering (Tianjin), Tianjin University, Tianjin, 300072, P. R. China

*E-mail: [email protected] (Dayong Yang)

Keywords: crowding effect, saccharides, cell-free system, synthetic biology

ACS Paragon Plus Environment

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ABSTRACT

Cellular physical microenvironment such as crowding shows great influence on

enzymatic reactions. Herein, we report a new finding that saccharides with low-

molecular-weight create effective crowding microenvironment for gene expression in

cell-free protein synthesis (CFPS) which provides valuable implication for living

systems. Four saccharides including sorbose, galactose, sucrose and cellobiose are

screened out as effective crowders. At low concentration range of saccharides, both the

mRNA and protein amounts present an upward trend with the concentration increment

of saccharides; when the concentrations exceed a critical value, mRNA and protein

amounts turn to decrease. A mechanism is proposed that at low concentrations of

saccharides, the effective concentrations of reactants increase due to the coexistence

of crowders and reactants in a finite volume; when the concentrations exceed a critical

value, the molecular diffusion of reactants is dominantly restricted due to the increased

viscosity. Our finding opens a new view that saccharides with low-molecular-weight


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could be crowders and provides new insight that substances with low-molecular-weight

in cells would produce crowding effect on biochemical reactions in living systems.


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Introduction

Cellular physical environment has significant impacts on its internal reaction

networks. From a physicochemical point of view, all cells are concentrated in small

volumes and filled with high concentration of biomolecules (proteins, nucleic acids,

ribosomes and saccharides, etc.), which makes crowding phenomenon an ubiquitous

and significant feature of cellular environment1, 2. For instance, the macromolecular content of E. coli was calculated to be 300-400 g/L, which generally occupied 20-30% cell volume3, 4. Therefore, investigation of crowding effect will provide a more

comprehensive understanding of cellular physical environment. Crowding effect on

reaction networks mainly includes two aspects. Each of the crowding agents and

reactants has a finite molecular volume and cannot occupy the same space at one

time3. The effective volume for reactants decreases when the crowding agents and

reactants coexist. As a result, the association of the enzymes and substrates is

facilitated owing to the increased effective concentration of these biomolecules5, 6. For

example, it has been demonstrated that the crowding agents could increase the

association between DNA and enzymes7, 8. Besides, crowding molecules increase


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viscosity of solutions, which slows down the rates of diffusion-controlled reactions3, 9.

For example, Klumpp and coworkers found that the slow diffusion of the tRNA

complexes in the cytoplasm generated a physical limit on the speed of translation10.

Kapral and coworkers found that small molecule diffusion and reaction rate coefficients

decreased in crowded environment11. Zhao and colleagues found that the rotational

diffusion of protein was influenced by bulk concentration and the polymer structure12.

However, it’s challenging to study the crowding effect inside cells due to the

extremely complex reaction networks and sophisticated intracellular environments.

Instead, CFPS allow activating biological protein expression without using living cells, and provide a simplified and well-controlled in vitro model for studying the physicochemical basis of cells and even constructing artificial cells13-15. Crowding effect

has been extensively studied in CFPS, in which crowders were macromolecules such

as polyethylene glycol (PEG) and ficoll. For example, Yamane and colleagues added

PEG in CFPS and protein expression was enhanced16. Huck and coworkers reported

that diffusion coefficient of RNA and protein decreased due to the macromolecular

crowding caused by ficoll 70 in cell-free system17. Xu and coworkers found that cell-free


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transcription was improved by the addition of PEG-8000, ficoll-70 or ficoll-400, but

translation was inhibited18.

Crowding molecules inside cells not only include macromolecules such as proteins

and nucleic acids, but also comprise substances with low-molecular-weight. For

example, Sharp found that the crowding effect was weakly dependent on crowder size

and medium-sized molecules had the same effect as much larger macromolecules,

such as proteins and RNA19. Li and coworkers employed sucrose and ficoll as crowders

to investigate the crowding effect on I4%

structure20. These two studies

suggested that small molecules might create crowding environment via excluded

volume effect. In this study, we report a new finding that saccharides with lowmolecular-weight create effective crowding microenvironment in E. coli extract-based

CFPS. Ten typical monosaccharides and disaccharides were tested and four

saccharides were screened out as crowders. A mechanism figure is proposed to

elucidate the crowding effect of saccharides. The experimental results are in

accordance with our mechanism diagram.


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Experimental Section

Construction of in vitro transcription and translation Transcription and translation were carried out by mixing 25 J feeding buffer, 15 J E.

coli extract, 200 ng pRset-eGFP plasmid or 200ng pRset-YFP plasmid and nucleasefree water and crowding agents to a final volume of 50 J 2 Unless stated otherwise, the

reaction volume was kept at 50 J 2 The feeding buffer contained 50 mM hepes, 90 mM

potassium glutamate, 15 mM magnesium glutamate, 1.5 mM amino acid mixture, 20

mM 3-phosphoglycerate, 5 mM cyclic adenosine monophosphate, 2.5 mM nicotinamide

adenine dinucleotide, 2.5 mM coenzyme A, 0.5 mM folinic acid, 3 mg/mL tRNA, 0.66

mM spermidine, 1 mM UTP, 1 mM CTP, 1 mM ATP, 1 mM GTP. Then the

measurement of fluorescence intensity was obtained from microplate reader at 30°C.

The timescale is 12 h. mRNA measurement After the reaction, total RNA was first isolated from CFPS reactions using RNAprep Pure Cell/Bacteria Kit (TIANGEN) according to the manufacturer’s instructions. The quantity and quality (A260/A280 value) of RNA samples were determined using a Uv-Vs spectrophotometer Q5000 (Quawell). For cDNA synthesis, about 200 ng of total RNA was used to a reverse


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transcription reaction using the FastKing RT Kit (TIANGEN) according to the manufacturer’s instructions. For qPCR analysis, cDNA samples were diluted 10 times with nuclease-free water. 1 µL of the diluted sample was combined with 10 µL of 2x SuperReal PreMix Plus (with SYBR Green

),

0.5

µL

of

10

µM

eGFP

gene

specific

forward

primer

(5'-

GAGCTTTTCACTGGCGTTG-3'), 0.5 µL of 10 µM eGFP gene specific reverse primer (5'TGGTGCAGATGAACTTCAGG-3') and 8 µL RNase-free water. A no reverse transcription control (RNA) was prepared for each sample. All samples were conducted in 96-well plate (Roche) and reactions were run on a LightCycler 480 (Roche). The amplification cycling conditions consisted of an initial incubation at 95°C for 10 min, then 40 cycles of denaturation at 95°C for 20 s followed by annealing at 55°C for 20 s, and then extended at 72°C for 20 s. The standard curve was prepared from serial dilutions of the purified eGFP PCR products. Viscosity measurements The viscosity measurements were carried out on an AR-G2 rheometer (TA Instruments). Experiments were performed in the parallel plate using 400 µL saccharide solutions. The temperature is 25°C and the time scale is 1 min.


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Results and discussion

Control 3% Glucose 3% Fructose 3% Mannose 3% Galactose 3% Sorbose

b) 12

10 8 6 4 2 0

eGFP ( 104 a.u.)

eGFP ( 104 a.u.)

a) 12 10 8 6 4 2 0

0 2 4 6 8 10 12 Time (h) c)

Control 3% Maltosemonohydrate 3% Trehalose 3% Melibiose 3% Sucrose 3% Cellobiose

0 2 4 6 8 10 12 Time (h) d)

6

6

5

5

eGFP ( 104 a.u.)

eGFP ( 104 a.u.)

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4 3 2 1 0

Saccharides

4 3 2 1 0

Saccharides

Figure 1. Effect of 3% five monosaccharides (a, c) and five disaccharides (b, d) on

eGFP amount in CFPS. The dots in figure c and d represented eGFP amounts at 12 h.

We chose five typical monosaccharides (glucose, mannose, fructose, galactose

and sorbose) and five disaccharides (maltosemonohydrate, melibiose, trehalose,

sucrose and cellobiose) as crowder candidates and added to CFPS. In CFPS, cell

lysates contained basic protein synthesis machineries, energy regeneration substrates,

amino acids, nucleotides and cofactors21-23. The process of gene expression in CFPS is

shown in Figure S1a: DNA is transcribed into mRNA by RNA polymerase, and


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afterwards mRNA is translated to polypeptides which are then fold into mature proteins.

mRNA and protein amounts in the system are dynamic. In this study, we focused on

studying the crowding effect of saccharides on the mRNA and protein amounts in

CFPS. Unless stated otherwise, the reaction volume was kept at 50 J and the reaction

time was set at 12 h. The experimental group without addition of saccharides was set as

the benchmark. Enhanced green fluorescent protein (eGFP) was used as the reporter

protein. The plasmid profile of pRset-eGFP was presented in Figure S2. The

concentrations of 1%, 2% and 3% (w/v) of saccharides were tested in order to screen

out saccharides which have no obvious inhibitory effect on protein expression at low

concentrations. Unexpectedly, we found that protein amounts presented two different

trends in different saccharides (Figure S3and Figure S4). For example, with 3%

saccharides, protein amounts were partially inhibited in fructose, mannose, trehalose

and melibiose; were inhibited completely in glucose and maltosemonohydrate.

However, in galactose, sorbose, sucrose and cellobiose, no inhibitory effect was

observed, which suggested they could be used as crowders in CFPS (Figure 1). We

further examined the effects of glucose, mannose, fructose, sorbose and galactose on


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pure eGFP and found that there was no obvious difference in these five saccharides

systems (Figure S5). The inhibitions of some saccharides to protein expression still

remained unclear and we speculated it was related to enzyme activity involved in

protein synthesis. We therefore employed saccharides which had no inhibitory effect on

protein expression for the following studies, including galactose, sorbose, sucrose and

cellobiose. The chemical structures are shown in Figure S1b.

Next, we varied the concentration range of sorbose, galactose and sucrose from

4% to 20% and cellobiose from 2% to 10% and measured mRNA and protein amounts

in these crowding environments. It was noted that the cellobiose concentration was

lower than other saccharides, because cellobiose was less soluble than the other three

saccharides.


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Figure 2. Effect of sorbose (a), galactose (b), sucrose (c) and cellbiose (d) on eGFP

mRNA amounts in CFPS. Error bars represent standard deviations from three

measurements.

We first tested the effect of different concentrations of sorbose, galactose, sucrose

and cellobiose on mRNA amount in CFPS. The results show that eGFP mRNA amount

presented an increasing trend first and then declining in the presence of saccharides

(Figure2). In detail, at low concentrations of sorbose, such as 4% and 8%, mRNA

amount was higher than that of the control group (without sorbose); when the


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concentrations exceeded 8%, mRNA amount turned to decline (Figure 2a). In galactose

and sucrose systems, when the concentrations are less than 12%, mRNA amount

increased with the increment of saccharides concentration; when the concentrations

exceeded 12%, mRNA amount turned to decrease (Figure 2b and Figure 2c). Among

them, the increase of mRNA amount resulting from galactose was more obvious than

sucrose. mRNA amount was higher than the control group at 4% cellobiose; when the

concentrations exceeded 4%, mRNA amount turned to descend (Figure 2d). On the

whole, mRNA amount reached highest at 12% galactose, and copy numbers of mRNA increased from 3.3( × 106CJ ( to 16 ( × 106CJ (2 The optimal concentration of four saccharides for mRNA output was different which could be caused by the structure

difference of saccharides24. Basing on the above results, we speculated that at low

concentration of saccharides, crowding effect facilitated mRNA production due to the

increased effective concentrations of T7 RNA polymerase and reactants; however,

when the concentration reached a higher level, mRNA amount decreased because that

the diffusions of T7 RNA polymerase and other reactants were restricted in the relatively

high concentration of saccharides.


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Figure 3. Effect of sorbose (a), galactose (b), sucrose (c) and cellobiose (d) on eGFP

amount in CFPS. Error bars represent standard deviations from three measurements.

We next investigated the effect of different concentrations of sorbose, galactose,

sucrose and cellobiose on eGFP amount in CFPS. Similar tendency of protein amount

was observed as compared to mRNA amount. At low concentrations of sorbose, such

as 4% and 8%, protein amount was higher than that of the control group (without

sorbose); when the concentrations exceeded 8%, protein amount turned to decrease

(Figure 3a). When the concentrations of galactose and sucrose were less than 12%,


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protein amount increased with the increment of saccharides concentration; when the

concentrations exceeded 12%, protein amount turned to descend (Figure 3b and Figure

3c). Besides, protein amount was higher than that of the control group at 2% cellobiose;

when the concentrations exceeded 2%, protein amount turned to descend (Figure 3d).

Meanwhile, it was worth noting that eGFP expression and mRNA yield were not

consistent, completely. For example, in cellobiose system, mRNA amount reached

highest at 4% concentration of cellobiose, but eGFP expression reached highest at 2%

concentration of cellobiose (Figure 2d and Figure 3d). This inconsistency demonstrated

that the crowding effect created by saccharides also influenced the translation process

rather than just the transcription process.


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b) 4.0 3.2 2.4 1.6 0.8 0

4

c)

8 12 16 20 Csorbose(%)

4.0

4

sucrose 3.2 2.4 1.6 0.8 0.0

0

4

8 12 16 20 Csucrose(%)

4.0

galactose 3.2 2.4 1.6 0.8 0.0

0

d)

4 8 12 16 20 Cgalactose(%)

4.0

cellobiose

4

0.0

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4

sorbose

Initial expression rate ( 10 a.u./h)

4


a)


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3.2 2.4 1.6 0.8 0.0

0

2 4 6 8 Ccellobiose(%)

10

Figure 4. Effect of sorbose (a), galactose (b), sucrose (c), cellobiose (d) on initial protein

expression rates. Error bars represent standard deviations from three measurements.

Meanwhile, we calculated the initial reaction rates of protein production by the

following formula:

Initial reaction rates (a.u./h) = (I-I0)/t The initial reaction rates were defined the change of fluorescence intensity in initial unit time (t represented the first 1 h). The fluorescence intensity of protein in our study increased linearly in the first one hour, as presented in Figure S6. I was the eGFP


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fluorescence intensity at 1 h. I0 was the initial eGFP fluorescence intensity. We found that in sorbose and sucrose systems, initial expression rates of protein increased when

the concentration of saccharides increased from 4% to 12%; when the concentrations

exceeded 12%, initial protein expression rates turned to decrease (Figure 4a and Figure

4c). At 4% galactose, initial expression rate was higher than that of the control group;

when the concentrations exceeded 4%, initial expression rates turned to decrease

(Figure 4b). In cellobiose system, when the concentration was 2%, the initial expression

rate was higher than that of the control group (without cellobiose); when the

concentrations exceeded 2%, initial protein expression rates turned to descend (Figure

4d). Basing on the results of protein amount and initial expression rates of protien, we

proposed that when the concentration of saccharides was relatively low, crowding effect

promoted protein formation; as the concentration continued to increase and exceeded a

certain value, crowding effect inhibited protein production.

We next studied the mechanisms for the crowding effect of saccharides. We

speculated that the viscosity of saccharide solutions played critical roles in regulating

diffusion-controlled reactions according to previous studies9,

18.

The effects of


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saccharides with different concentrations on mRNA and protein amounts were related to

the viscosity and diffusion coefficients of solution. Therefore, we determined the viscosity of saccharides, and calculated the diffusion coefficients (D) of solution by Einstein stokes equations17, 25:

DAB = A"CGN AJB=2.2×10—4/rAJB. Where k is the boltzmann constant, T is absolute temperature, rA is the radius of the target molecule, JB is the viscosity of solution (the average value of three measurements). At a certain temperature, diffusion coefficient is inverse relation with

the viscosity of solution for any molecule. So the variation trend of diffusion coefficient is

theoretically the same for different molecules. To illustrate more clearly, we calculated diffusion coefficients with T7 RNA polymerase as an example (rA is 5 nm). The results were shown in Figure S8.


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trend for each saccharide (Figure S7 and Figure S8). Basing on the above experimental

results, we propose that saccharides generally create two effects: increasing the

effective concentration of reactants and thus enhancing reaction rates (Effect 1); and

limiting the diffusion of the reactants and thus slowing down the reaction rates (Effect 2).

We define the initial state as the dilute solution without saccharides in CFPS (Scheme

1a). In initial state, reactants (enzymes and substrates) can diffuse and shuttle freely

and synthesize proteins. When saccharides are added in CFPS, the viscosity of solution

increases with concentration increment of saccharides. At low concentrations of

saccharides, the reactants diffusion is not greatly restricted due to the relatively low

solution viscosity, while the effective concentrations of reactants increase owing to the

coexistence of crowders and reactants in a finite volume. As a consequence, Effect 1 is

dominant as compared to Effect 2, which results in incremental amounts of m RNA and

protein (Scheme 1b). At high concentrations of saccharides, the viscosity of solution is

relatively high due to the enhanced quantity of hydrogen bonds between saccharides

and water. The diffusion of reactants is restricted and Effect 2 is dominant, leading to

down-regulation of mRNA and protein amounts (Scheme 1c). When the viscosity of


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solution reaches a critical value, Effect 1 is comparable to Effect 2, mRNA and protein

amounts would be the highest. Overall, with the increase of saccharides concentrations

in CFPS, mRNA and protein amounts first increase and then decline when the

concentration of saccharides exceeds a critical value. Our experimental results are in

full agreement with proposed mechanism and model.

Figure 5. Crowding effect of sorbose (a), galactose (b), sucrose (c) and cellobiose (d)

on YFP amount. At low concentration range of saccharides, YFP amount presented an

upward trend with the increment concentration of saccharides; when the concentration

exceeded the critical level, YFP amount turned to descend. Error bars represent

standard deviations from three measurements.


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To verify the crowding effect of saccharides on CFPS, we further employed yellow

fluorescent protein (YFP) as the reporter protein and studied protein amount in four

saccharide systems (Figure 5). Trend of YFP amount was similar to that of eGFP in

saccharide solutions. At 4% sorbose, YFP amount was higher than that of the control

group (without sorbose); when the concentrations exceeded 4%, YFP amount turned to

decline (Figure 5a). YFP amount gradually increased as the concentration of galactose

increased from 4% to 12%; when the concentrations exceeded 12%, YFP amount

turned to decrease (Figure 5b). In sucrose system, YFP amount reached the highest

level when the concentration was 16% (Figure 5c). When the concentration of

cellobiose was less than 6%, YFP amount increased with the increased concentration of

cellobiose; when the concentrations exceeded 6%, YFP amount turned to descend

(Figure 5d).


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Conclusion

In conclusion, we have demonstrated that saccharides could create crowding

microenvironment in CFPS and studied the crowding effect of saccharides on mRNA

and protein amounts. At low concentration range of saccharides, both the mRNA

amount and protein amount present an upward trend with the concentration increment

of saccharides; when the concentrations exceed a critical value, mRNA and protein

amounts turn to decrease. Basing on the experimental results, we proposed a

mechanism that at low concentration of saccharides, the effective concentrations of

reactants increase due to the coexistence of crowders and reactants in a finite volume;

when the concentrations exceed the critical value, the molecular diffusion of reactants is

dominantly restricted due to the increased viscosity. We envision that our work offers

new insights that substances with low-molecular-weight in cells would produce crowding

effect on biochemical reactions in living systems.


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ASSOCIATED CONTENT

The supporting information is available free of charge on the ACS Publications website.

Supplementary materials and methods, Figure S1-S4 (PDF).

AUTHOR INFORMATION

Corresponding author *E-mail: [email protected]; [email protected]

Author Contributions

Lihui bai and Xiaocui guo contributed equally to this work.

Notes The authors declare no competing interests.

ACKNOWLEDGMENT

This work was in part supported by National Natural Science Foundation of China (grant

no. 21621004, 21575101 and 21622404). We thank Ms. Yang Liu, Mr. Yi Jiao, Ms. Liyi

Xu and Ms. Qing Sun at Tianjin University for their kind help on experiments and


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discussion. We are highly grateful to Dr. Xiaohui Li at Tianjin University for viscosity test

and Dr. Shaolan Zou at Tianjin University for qPCR measurement.

ABBREVIATIONS PEG, polyethylene glycol; CFPS, cell-free protein synthesis; GFP, green fluorescent

protein; YFP, yellow fluorescent protein.

REFERENCES (1) Ellis, R J; Minton, A P, Cell biology: join the crowd. Nature 2003, 425 (6953), 27-28. (2) Zhou, H X; Rivas, G; Minton, A P, Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Ann. Rev. Biophys. 2007, 37 (37), 375-397. (3) Sokolova, E, Effects of macromolecular crowding on gene expression studied in protocell models. Physical Organic Chemistry 2015. (4) Zimmerman, S B; Trach, S O, Estimation of macromolecule concentrations and excluded volume effects for the cytoplasm of Escherichia coli. J. Mol. Biol. 1991, 222 (3), 599-620. (5) Ellis, R J, Macromolecular crowding: obvious but underappreciated. Trends Biochem. Sci 2001, 26 (10), 597-604. (6) Minton, A P, The influence of macromolecular crowding and macromolecular confinement on biochemical reactions in physiological media. J. Biol. Chem. 2001, 276 (14), 1057710580. (7) Sasaki, Y; Miyoshi, D; Sugimoto, N, Effect of molecular crowding on DNA polymerase activity. Biotech. J. 2006, 1 (4), 440-446. (8) Sasaki, Y; Miyoshi, D; Sugimoto, N, Regulation of DNA nucleases by molecular crowding. Nucleic Acids Res. 2007, 35 (12), 4086-4093. (9) Ellis, R J, Macromolecular crowding: an important but neglected aspect of the intracellular environment. Curr. Opin. Struct. Biol. 2001, 11 (1), 114-119. (10) Klumpp, S; Scott, M; Pedersen, S; Hwa, T, Molecular crowding limits translation and cell growth. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (42), 16754-16759. (11) Echevera, C; Tucci, K; Kapral, R, Diffusion and reaction in crowded environments. Journal of Physics Condensed Matter 2007, 19 (19), 65146-65112. (12) Jing, Q; Chen, A; Zhao, N, A new scaling for rotational diffusion of molecular probes in polymer solutions. PCCP 2017, 19 (48), 32687-32697. (13) Carlson, E D; Gan, R; Hodgman, C E; Jewett, M C, Cell-Free Protein Synthesis: Applications Come of Age. Biotechnol. Adv. 2012, 30 (5), 1185-1194. (14) Shimizu, Y; Inoue, A; Tomari, Y; Suzuki, T; Yokogawa, T; Nishikawa, K; Ueda, T, Cell-


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free translation reconstituted with purified components. Nat. Biotechnol. 2001, 19 (8), 751755. (15) Oza, J P; Aerni, H R; Pirman, N L; Barber, K W; Haar, C M T; Rogulina, S; Amrofell, M B; Isaacs, F J; Rinehart, J; Jewett, M C, Robust production of recombinant phosphoproteins using cell-free protein synthesis. Nat. Commun. 2015, 6, 8168. (16) Nakano, H; Tanaka, T; Kawarasaki, Y; Yamane, T, Highly productive cell-free protein synthesis system using condensed wheat-germ extract. J. Biotechnol. 1996, 46 (3), 275-282. (17) Hansen, M M K; Meijer, L H H; Spruijt, E; Maas, R J M; Rosquelles, M V; Groen, J; Heus, H A; Huck, W T S, Macromolecular crowding creates heterogeneous environments of gene expression in picolitre droplets. Nat. Nanotechnol. 2016, 11 (2), 191-197. (18) Ge, X; Luo, D; Xu, J, Cell-Free Protein Expression under Macromolecular Crowding Conditions. PLoS One 2011, 6 (12), e28707. (19) Sharp, K A, Analysis of the size dependence of macromolecular crowding shows that smaller is better. Proc. Natl. Acad. Sci. U. S. A. 2015, 112 (26), 7990-7995. (20) Bai, J; Liu, M; Pielak, G J; Li, C, Macromolecular and Small Molecular Crowding Have Similar Effects on L ) Structure. Chemphyschem 2016, 18 (1), 55-58. (21) Murray, C J; Baliga, R, Cell-free translation of peptides and proteins:from high throughput screening to clinical production. Curr. Opin. Chem. Biol. 2013, 17 (3), 420-426. (22) Jewett, M C; Calhoun, K A; Voloshin, A; Wuu, J J; Swartz, J R, An integrated cell-free metabolic platform for protein production and synthetic biology. Mol. Syst. Biol. 2008, 4 (1), 220-220. (23) Pedersen, A; Hellberg, K; Enberg, J; Karlsson, B G, Rational improvement of cell-free protein synthesis. New Biotechnol. 2011, 28 (3), 218-224. (24) Lee, J K; Pachtman, E A; Frumin, A M, Structural configuration of sugars and their ability to inhibit fava bean hemagglutination. Ann. N. Y. Acad. Sci. 2010, 234 (1), 161-169. (25) Nenninger, A; Mastroianni, G; Mullineaux, C W, Size dependence of protein diffusion in the cytoplasm of Escherichia coli. J. Bacteriol. 2010, 192 (18), 4535-4540.


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Langmuir

TOF Figure

1 0 0

Diluted solution

Low-viscosity solution

High-viscosity solution


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Saccharides Create a Crowding Environment for Gene Expression in

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