Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr-Jun;17(2):122-130.
doi: 10.18502/ajmb.v17i2.18563.

Optimization of RfxCas13d Expression in Escherichia coli Host using Response Surface Methodology

Affiliations

Optimization of RfxCas13d Expression in Escherichia coli Host using Response Surface Methodology

Sepideh Abbaszadeh et al. Avicenna J Med Biotechnol. 2025 Apr-Jun.

Abstract

Background: RfxCas13d, a key member of the Cas13 family, plays a vital role in CRISPR-based diagnostics for RNA sequence detection and gene silencing. This study aimed to enhance RfxCas13d expression by optimizing key parameters using Response Surface Methodology (RSM).

Methods: The plasmid pET28b-RfxCas13d-His (Addgene 141322) was introduced into BL21 (DE3) and Rosetta™ (DE3) strains. Initial expression tests were conducted, followed by RSM-guided optimization of factors such as isopropyl β-D-1-thiogalactopyranoside (IPTG) concentration, temperature, cell density at induction, and induction time in BL21 (DE3). Protein expression levels were quantified using ImageJ and AlphaEaseFC software to analyze band intensities.

Results: BL21 (DE3) was selected for further optimization based on preliminary results. Analysis of 26 RSM-designed experiments revealed that temperature, induction time, IPTG concentration, and their interactions significantly influenced RfxCas13d expression. Optimal conditions were identified as 0.25 mM IPTG, an OD600 nm of 0.8 at induction, 37°C, and Overnight (ON) of induction. The regression model exhibited high accuracy, with a correlation coefficient of 0.97 and a p-value less than 0.05, confirming a strong linear relationship between predicted and observed values.

Conclusion: This study highlights the significant impact of the four optimized factors on RfxCas13d expression. Under optimized conditions, a soluble protein concentration of 3.6 mg/100 ml cell culture was achieved after purification. It represents the first application of RSM for optimizing RfxCas13d expression, providing a foundation for further refinement of expression conditions. Continued use of RSM in future research will enhance the efficiency of RfxCas13d production for diagnostic and therapeutic applications.

Keywords: Base sequence; CRISPR-associated proteins; Escherichia coli; Protein biosynthesis.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
A) Displays the results of a Western blot analysis for the RfxCas13d protein. The recombinant RfxCas13d protein has a molecular weight of 113 kilodaltons, which aligns with the band observed in the Western blot. B) Provides a preliminary evaluation of protein expression in BL21 (DE3) and Rosetta™ (DE3) strains. Columns 1 and 2 represent expression in Rosetta™ (DE3) at 3 hr and ON post-induction, respectively, while columns 4 and 5 show expression in BL21™ (DE3) at the same time points. Protein expression levels showed no notable difference between the two strains.
Figure 2.
Figure 2.
Displays RfxCas13d expression in SDS-PAGE under 26 different cultivation conditions as designed by RSM. Lane M features a protein marker, while other lanes represent various experimental conditions. Turbidity values for these experiments were calculated using AlphaEaseFC software.
Figure 3.
Figure 3.
Diagnostic Plots for the Quadratic Models. A) Normal Probability Plot: This plot demonstrates that the residuals—the differences between observed and predicted values—are normally distributed. The alignment of points along the reference line supports the assumption of normality. B) Versus Fits Plot: This plot exhibits an ideal pattern, with residuals randomly dispersed around zero. The absence of any systematic trends or patterns indicates that the model fits the data well. C) Versus Order Plot: This plot was used to detect any time-dependent patterns or autocorrelation. The random scattering of residuals suggests no issues related to the order of observations. D) Matrix Plot of Response and Predictors: This plot presents a strong correlation matrix between the response variable and the predictors. It highlights the relationships and dependencies among the variables, indicating a well-structured model.
Figure 4.
Figure 4.
Evaluation of the effect of the significant parameters on RfxCas13d expression, calculated by the sum of squares index. I (IPTG concentration), Te (temperature), O (OD600 nm before induction), and Ti (post-induction time).
Figure 5.
Figure 5.
A three-dimensional response surface illustrates the expression of RfxCas13d. This figure examines the impact of two variables while maintaining the other two at zero levels. I (IPTG concentration), Te (temperature), O (OD600 nm before induction), and Ti (post-induction time).
Figure 6.
Figure 6.
A) SDS-PAGE under optimal cultivation conditions is shown, induced (I), uninduced (UI), and protein molecular weight marker (M). B) RfxCas13d purification using a Ni-NTA column is shown, with eluted protein fractions (E1, E2, and E3), wash (W), flow-through (FT.), before column (BC) and protein molecular weight marker (M).

Similar articles

References

    1. Makarova KS, Aravind L, Wolf YI, Koonin EV. Unification of Cas protein families and a simple scenario for the origin and evolution of CRISPR-Cas systems. Biology Direct 2011;6:38. - PMC - PubMed
    1. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E. A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science 2012;337(6096):816–21. - PMC - PubMed
    1. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, et al. Multiplex genome engineering using CRISPR/Cas systems. Science 2013;339(6121):819–23. - PMC - PubMed
    1. Mali P, Yang L, Esvelt KM, Aach J, Guell M, DiCarlo JE, et al. RNA-guided human genome engineering via Cas9. Science 2013;339(6121):823–6. - PMC - PubMed
    1. Pardee K, Green AA, Takahashi MK, Braff D, Lambert G, Lee JW, et al. Rapid, low-cost detection of Zika virus using programmable biomolecular components. Cell 2016;165(5):1255–66. - PubMed

LinkOut - more resources