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=== Construction of bacteria expression vectors === | === Construction of bacteria expression vectors === | ||
Revision as of 13:21, 2 October 2024
amiR-CHS1
Contents
- 1 Management of Spodoptera litura using RNA interference technology
- 2 RESULTS
- 2.1 Selection of target gene and pre-amiRNA backbone
- 2.2 Construction of bacteria expression vectors
- 2.3 Determination of amiRNA and VLP expression in bacteria
- 2.4 VLP improved RNAi efficiency in S. litura
- 2.5 Supression of CHS1 attenuatead the pupation and molting of S. litura larvae
- 2.6 VLP improved amiRNA stability in the intestinal fluid of S. litura
- 3 Reference
DDDD Sequence and Features
- 10INCOMPATIBLE WITH RFC[10]Illegal EcoRI site found at 4
- 12INCOMPATIBLE WITH RFC[12]Illegal EcoRI site found at 4
- 21INCOMPATIBLE WITH RFC[21]Illegal EcoRI site found at 4
- 23INCOMPATIBLE WITH RFC[23]Illegal EcoRI site found at 4
- 25INCOMPATIBLE WITH RFC[25]Illegal EcoRI site found at 4
- 1000COMPATIBLE WITH RFC[1000]
amiR-CHS1, an artificial microRNA targeting the chitin synthase 1 of Spodoptera litura
Management of Spodoptera litura using RNA interference technology
Spodoptera litura (common cutworm) is a polyphagous agricultural pest worldwide and causes enormous losses to a myriad of economical crops. It has evolved high resistance to multiple chemical insecticides [1]. It poses a necessity for development of alternative strategies for S. litura control. Recently, RNA interference (RNAi) technology has emerging as a promising strategy for pest insect management [2].
RESULTS
Selection of target gene and pre-amiRNA backbone
Chitin is one the main components of the insect cuticle, and chitin synthase (CHS) is a vital enzyme required for chitin formation. It has been reported that the SlCHS1 gene is associated the pupation and molting of S. litura larvae. To control S. litura, an artificial microRNA (amiRNA) targeting the SlCHS1 was designed.
The sequence of SlCHS1 (accession No. XM_022964624.1) [3] was retrieved from NCBI, and submitted to the online tool Web MicroRNA Design 3 (WMD3) (http://wmd3.weigelworld.org/cgi-bin/webapp.cgi) to obtain amiRNA candidates for targeting SlCHS1 (amiR-CHS1). A 21-nucleotide target sequence (5′-GATGACAACGTCATGAAGAAG-3′) of SlCHS1 was selected. Although the plant precursor backbones are more frequently used for amiRNA expression, the amiRNAs modified using insect pre-miRNA backbones caused stronger RNA responses in Helicoverpa armigera than plant pre-miRNA constructs. The reason is that the insect pre-miRNA constructs bypass the plant miRNA machinery and consequently act as effective templates for processing into miRNAs in the insect following ingestion (Figure 1) [4]. In our project, the Tribolium castaneum bantam (Tc-ba) scaffold [4] was chosen as the backbone for the generation of amiR-CHS1. Growing evidence indicates that the presence of highly active nucleases in body fluids is the major factor responsible for the limited RNAi efficiency against lepidopteran insects, due to their exclusive abilities in RNAi molecules degradation [5, 6]. To improve RNAi efficiency in S. litura, we attempted to deliver RNAi molecules using a bacteriophage MS2 virus-like particle (VLP)-based delivery system [7].
Figure 1 Comparison of miRNA biogenesis in plants and animals [4]. Plant pre-miRs processed in nucleus either by top-down or bottom-up cleavage by Dicer-like 1 (DCL1). Animal pri-miR cleaved by Drosha in nucleus to form pre-miR which is then exported to cytoplasm where it is processed by Dicer 1 (DCR1). Note longer upper and lower stems in plant precursors than in animal structures.
Construction of bacteria expression vectors
The bacteria expression vectors were constructed based on pET28a. Three vectors were designed for expressing amiR-CHS1, VLP ( HIV TAT-conjugated coat protein (CP) dimer), and VLP plus amiR-CHS1 ( VLP-amiR-CHS1, Figure 3) in Escherichia coli.
Figure 3 Vector design for expressing amiR-CHS1 and MS2-amiRCHS1 in bacteria.
Determination of amiRNA and VLP expression in bacteria
Three bacteria expression vectors were expressed in E.coli BL21(DE3) that lacks RNase III activity (BL21Δrnc). Northern blot showed the expression amiR-CHS1 in BL21Δrnc that expresses amiR-CHS1 and VLP-amiR-CHS1 (Figure 4A). Successful expression of VLP was determined by SDS-PAGE in bacteria expressing VLP and VLP-amiR-CHS1 (Figures 4B).
Figure 4 Analyses of amiRNA and VLP expression in engineered bacteria BL21Δrnc. (A) Detection of amiR-CHS1 expression by northern blott using a DIG-labeled amiRCHS1-specific probe. Samples of 5µg total cellular RNA were loaded in each lane of the RNA blot. The Gelview-stained gel before blotting is shown below the blot as a loading control. (B) Protein samples were separated by 10% SDS-PAGE, and the gel was stained with Coomassie Brilliant Blue R-250. Samples of 5 µg total protein were loaded in each lane.
VLP improved RNAi efficiency in S. litura
Bioassay was conducted via feeding S. litura larvae with an artificial diet supplemented with the engineered bacteria. Only the VLP-amiR-CHS1 markedly suppressed the target gene expression and reduced the larval weight gain (Figure 5).
Figure 5 Bioassay of S. litura larvae 7 days after feeding (DAF). (A) Larval weight of S. litura. Data are means ± SE (n ≥ 30). (B) Analysis of S. litura CHS1 expression quantified by qRT-PCR. Data are means ± SE (N ≥ 5). Different lowercase letters above the columns indicate significant differences (P < 0.05, one-way ANOVA with Tukey’s multiple range test). (C) Representative examples of S. litura larvae.
Supression of CHS1 attenuatead the pupation and molting of S. litura larvae
Bioassay of S. litura was performed till the molting stage. As shown in Figure 6, the pupation and molting of S. litura larvae were significantly inhibited by feeding the VLP-amiR-CHS1.
Figure 6 Effects on pupation and molting of S. litura after silencing SlCHS1. (A,B) Phenotype of S. litura 25 and 32 DAF. (C) Representation (%) of developmental and mortality rates of S. litura larvae until molting stage after feeding on engineered bacteria.
VLP improved amiRNA stability in the intestinal fluid of S. litura
To test whether the MS2 VLP could reduce the degradation of amiRNA by nuclerase in the midgut of S. litura, RNA from different BL21Δrnc strains was extracted and digested with intestinal fluid. The results showed that naked amiR-CHS1 was quickly degraded after 5 min of incubation and completely degraded after 10 min. By contrast, the amiCHS1 encapsulated by the MS2 VLP could be detected even after 10 minutes of incubation. These results indicate that the MS2 VLP could protect amiRNA from degradation in the intestinal fluid of S. litura.
Figure 7 Stability test of S. litura’s intestinal fluid against amiRNAs. Northern blotting of amiR-CHS1 in engineered BL21Δrnc extract after incubation with intestinal fluid (15-fold dilution) of tobacco cutworms at room temperature. Naked amiR-CHS1 is strongly degraded after 5 minutes and completely degraded after 10 minutes. In contrast, amR-CHS1 filled with VLP is relatively stable. Sample loading, 5 μg.
Reference
- L. Xu et al., Transcriptome analysis of Spodoptera litura reveals the molecular mechanism to pyrethroids resistance. Pestic. Biochem. Physiol. 169, 104649 (2020).
- K. Y. Zhu, S. R. Palli, Mechanisms, applications, and challenges of insect RNA interference. Annu. Rev. Entomol. 65, 293–311 (2020).
- H. Z. Yu et al., Identification and functional analysis of two chitin synthase genes in the common cutworm, Spodoptera litura. Insects 11 (2020).
- J. Bally et al., Plin-amiR, a pre-microRNA-based technology for controlling herbivorous insect pests. Plant Biotechnol. J. 18, 1925–1932 (2020).
- R. B. Guan et al., A nuclease specific to lepidopteran insects suppresses RNAi. J. Biol. Chem. 293, 6011–6021 (2018).
- J. N. Shukla et al., Reduced stability and intracellular transport of dsRNA contribute to poor RNAi response in lepidopteran insects. RNA Biol. 13, 656–669 (2016).
- G. Wang et al., Novel miR-122 delivery system based on MS2 virus like particle surface displaying cell-penetrating peptide TAT for hepatocellular carcinoma. Oncotarget 7, 59402–59416 (2016).