Methods for increasing the biosynthesis efficiency of target proteins in nicotiana benthamiana and advantageous codons obtained by the methods

Abstract

The application provides a method for improving the biosynthesis efficiency of a target protein in Nicotiana benthamiana and an advantageous codon obtained by the method, and relates to the technical field of biotechnology, and the method comprises the following steps: obtaining expression abundance data of tRNA of the Nicotiana benthamiana; determining an advantageous codon with high relative amino acid specificity usage of each amino acid in the Nicotiana benthamiana according to the expression abundance data, wherein the relative amino acid specificity usage is used to represent the degree of resource supply of the isoacceptor tRNA in the host translation system; replacing at least one original codon in an exogenous gene coding the target protein with the advantageous codon to obtain an optimized gene sequence; and introducing the optimized gene sequence into the Nicotiana benthamiana for expression to obtain the target protein.

Description

Technical Field

[0001] This invention relates to the field of biotechnology, and more particularly to a method for improving the biosynthetic efficiency of target proteins in *Nicotiana benthamiana* and the dominant codons obtained by this method. Background Technology

[0002] Nicotiana benthamiana is widely used as a model platform for exogenous protein production due to its high biomass and mature transient expression system. However, in Nicotiana benthamiana heterologous protein expression systems, most existing codon optimization strategies remain at the static genomic level, such as the Codon Adaptation Index (CAI) or Relative Synonymous Codon Usage (RSCU) algorithms based on genomic statistical frequencies.

[0003] However, these static indicators cannot characterize the true dynamic distribution of tRNA resources in *Nicotiana benthamiana* under specific physiological conditions, especially during peak protein synthesis. In fact, tRNA expression abundance is influenced by multiple factors, including transcriptional regulation, post-transcriptional modifications, and cellular metabolic state, and does not exhibit a strictly linear relationship with gene copy number or genome usage frequency. For *Nicotiana benthamiana*, an allotetraploid plant, its genome contains a large number of redundant sequences and pseudogenes resulting from doubling, leading to a more significant discrepancy between static predictions based on the genome and the actual supply capacity of the translation machine. If codon optimization is performed solely based on static indicators, it can easily lead to an imbalance between the supply and demand of specific tRNAs, causing ribosome congestion on the mRNA sequence or even premature translation termination. This has become one of the important factors restricting breakthroughs in the transient expression system yield of *Nicotiana benthamiana*. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for improving the biosynthetic efficiency of target proteins in *Nicotiana benthamiana* and a dominant codon obtained through this method.

[0005] As a first aspect of the present invention, the present invention provides a method for improving the biosynthetic efficiency of a target protein in *Nicotiana benthamiana*, comprising: obtaining expression abundance data of *Nicotiana benthamiana* tRNA; determining, based on the expression abundance data, the dominant codons with high relative amino acid specificity utilization for each amino acid in *Nicotiana benthamiana*, wherein relative amino acid specificity utilization is used to characterize the sufficiency of resource supply of isoform receptor tRNA in the host translation system; replacing at least one original codon in the exogenous gene encoding the target protein with the dominant codon to obtain an optimized gene sequence; and introducing the optimized gene sequence into *Nicotiana benthamiana* for expression to obtain the target protein.

[0006] As a second aspect of the present invention, the present invention provides a set of dominant codons for improving the biosynthetic efficiency of target proteins in *Nicotiana benthamiana*, obtained according to the method described above for improving the biosynthetic efficiency of target proteins in *Nicotiana benthamiana*. The dominant codons include: GCT for alanine; AGA for arginine; AAC for asparagine; GAC for aspartic acid; TGC for cysteine; CAA for glutamine; GAG for glutamic acid; GGC for glycine; CAC for histidine; ATT for isoleucine; CTA for leucine; AAG for lysine; ATG for methionine; TTC for phenylalanine; CCA for proline; AGC for serine; ACC for threonine; TGG for tryptophan; TAC for tyrosine; and GTT for valine.

[0007] This invention optimizes the codons of exogenous genes based on *N. benthamiana* tRNA abundance data. By improving the utilization efficiency of isoform receptor tRNAs, it enhances the protein translation efficiency of target proteins in *N. benthamiana*, thereby improving biosynthetic efficiency. Compared to traditional methods based solely on codon usage characteristics at the genomic sequence level, this invention utilizes the Relative Amino Acid-Specific tRNA Usage (RSAU) index to assess the resource distribution of isoform receptor tRNAs corresponding to different amino acids in *N. benthamiana* from the perspective of tRNA expression resources. This effectively avoids translation bottlenecks caused by insufficient specific tRNA resources. This analytical strategy reduces resource imbalances during translation and lowers the risk of ribosome arrest by improving the matching degree between mRNA codon composition and host tRNA supply, thus potentially improving the expression efficiency of target proteins in the *N. benthamiana* substrate.

[0008] Furthermore, the expression abundance data used in this invention are derived from measured data of *Nicotiana benthamiana*, thus the identified dominant codons contain the species-specific tRNA expression characteristics. As an allotetraploid plant, *Nicotiana benthamiana* exhibits a highly uneven distribution of tRNA gene copy numbers. This invention directly captures the impact of this dynamic imbalance on translation resource allocation through measured tRNA abundance. This allows the codon optimization scheme to adapt to the unique translation resource pattern of *Nicotiana benthamiana*, overcoming the translation bottleneck caused by the lack of species specificity in traditional methods, thereby improving the translation elongation efficiency of exogenous genes within the *Nicotiana benthamiana* genome. Attached Figure Description

[0009] Figure 1 This is an overall flowchart of the method for improving the biosynthetic efficiency of the target protein in *Nicotiana benthamiana* according to the present invention;

[0010] Figure 2 This is a diagram showing the distribution of the number of tRNA genes corresponding to each amino acid in Nicotiana benthamiana.

[0011] Figure 3 A statistical diagram showing the number of tRNAs corresponding to different anticodons in the genome of Nicotiana benthamiana.

[0012] Figure 4 This is a distribution diagram of the alignment results of tRNA sequencing reads from Nicotiana benthamiana.

[0013] Figure 5 Box plot of tRNA expression levels classified based on the physicochemical properties of amino acid side chains;

[0014] Figure 6 A distribution map showing the total expression of isoform receptor tRNAs with different amino acids;

[0015] Figure 7 This is a distribution map of the top ten most abundant tRNAs expressed in Nicotiana benthamiana. Detailed Implementation

[0016] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0017] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The term "comprising" as used herein indicates the presence of features, steps, or operations, but does not exclude the presence or addition of one or more other features.

[0018] When using expressions such as "at least one of A, B, and C," they should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art.

[0019] In realizing the concept of this invention, it was discovered that in Nicotiana benthamiana, the biosynthetic efficiency of exogenous proteins is profoundly affected by the translation process. As a core step in translation, the degree of codon-tRNA fit directly determines the ribosome elongation rate. Currently, codon optimization methods for Nicotiana benthamiana mainly rely on traditional static indicators, and these methods have revealed several limitations in application.

[0020] First, traditional optimization methods are mostly based on metrics such as codon fitness index (CAI) or relative synonymous codon usage (RSCU). These metrics share the characteristic of relying solely on the statistical frequency of the host genome, without considering the actual expression abundance and availability of tRNA in *Nicotiana benthamiana*. Since tRNA is the direct executor of the translation process, the degree of matching between its actual supply capacity and the codon demand of the exogenous gene is the key to determining translation efficiency. Therefore, optimization strategies that rely solely on genome frequency have a mismatch between the resulting sequences and the actual intracellular translation resources (i.e., the whole-cell tRNA pool), resulting in limited optimization effects.

[0021] Secondly, sequences optimized using traditional methods often tend to use high-frequency codons (i.e., the most frequently used codons among synonyms based on genomic frequency statistics). During translation, this can lead to excessive consumption of specific tRNAs in localized regions, causing a supply-demand imbalance. This localized tRNA deficiency can trigger ribosome arrest or even premature translation termination, failing to increase yield and potentially inhibiting further accumulation of the target protein.

[0022] Finally, as a highly complex allotetraploid plant, *Nicotiana benthamiana* possesses a unique genome structure. For example, the copy number distribution of isoform receptor tRNA genes throughout its genome is extremely uneven, with higher copy numbers for tRNA genes corresponding to certain amino acids (such as Met, Ser, and Leu) and lower copy numbers for others (such as Cys). Traditional general-purpose optimization models have failed to be precisely tailored to this species specificity, resulting in blind spots in the design schemes. When using such models to reconstruct exogenous gene sequences, especially under the high translational load of transient expression systems, the frequent use of high-frequency codons can easily exacerbate the supply-demand conflict of local tRNAs, leading to ribosome congestion, stagnation, or premature termination of translation, severely restricting the translational elongation efficiency of exogenous genes in the *Nicotiana benthamiana* genome.

[0023] Therefore, it is necessary to establish a method to improve the biosynthetic efficiency of target proteins in *Nicotiana benthamiana* based on the measured tRNA expression abundance, in order to overcome the problem of imbalance between translation resource supply and demand caused by ignoring the real-time abundance of tRNA in traditional optimization methods, and thus improve the translation efficiency of exogenous target proteins in the *Nicotiana benthamiana* chassis.

[0024] Figure 1 This is an overall flowchart of the method for improving the biosynthetic efficiency of the target protein in *Nicotiana benthamiana* according to the present invention.

[0025] As a first aspect of the present invention, the present invention provides a method for improving the biosynthetic efficiency of a target protein in *Nicotiana benthamiana*, such as... Figure 1 As shown, operations S100 to S400 are included:

[0026] Operation S100: Obtain expression abundance data of tobacco Benzovia tRNA.

[0027] Operation S200: Based on expression abundance data, identify the dominant codons with high relative amino acid specificity utilization for each amino acid in Nicotiana benthamiana. Relative amino acid specificity utilization is used to characterize the sufficiency of resource supply for isoform receptor tRNA in the host translation system.

[0028] Operation S300: Replace at least one original codon in the foreign gene encoding the target protein with a dominant codon to obtain an optimized gene sequence.

[0029] Operation S400: The optimized gene sequence is introduced into Nicotiana benthamiana for expression to obtain the target protein.

[0030] According to embodiments of the present invention, a method for codon optimization of exogenous proteins based on *N. benthamiana* tRNA abundance data is provided. This method improves the protein translation efficiency of target proteins in *N. benthamiana* by increasing the utilization efficiency of isoform receptor tRNAs, thereby enhancing biosynthetic efficiency. Compared to traditional methods based solely on codon usage characteristics at the genomic sequence level, this invention utilizes the RSAU index to assess the resource distribution of isoform receptor tRNAs corresponding to different amino acids in *N. benthamiana* at the tRNA expression resource level. This effectively avoids translation bottlenecks caused by insufficient specific tRNA resources. This strategy reduces resource imbalance during translation, lowers the risk of ribosome arrest, and improves the expression efficiency of target proteins in the *N. benthamiana* substrate by increasing the matching degree between mRNA codon composition and host tRNA supply.

[0031] Furthermore, the expression abundance data used in this invention are derived from measured data of *Nicotiana benthamiana*, thus the identified dominant codons contain the species-specific tRNA expression characteristics. As an allotetraploid plant, *Nicotiana benthamiana* exhibits a highly uneven distribution of tRNA gene copy numbers. This invention directly captures the impact of this dynamic imbalance on translation resource allocation through measured tRNA abundance. This allows the codon optimization scheme to accurately adapt to the unique translation resource pattern of *Nicotiana benthamiana*, overcoming the translation bottleneck caused by the lack of species specificity in traditional methods. It should be noted that the use of a high RSAU strategy for codon optimization has been reported in related studies (including yeast and mammalian systems) to improve protein translation efficiency; therefore, the method of this invention is expected to improve the translation elongation efficiency of exogenous genes in the *Nicotiana benthamiana* chassis.

[0032] According to an embodiment of the present invention, in operation S100, the above-mentioned expression abundance data is obtained by tRNA sequencing. It should be emphasized that this specific data acquisition method does not constitute a limitation of the present invention. In the present invention, the method for obtaining the tRNA expression abundance data of *Nicotiana benthamiana* can employ any method known in the art capable of quantitatively detecting the number of tRNA transcripts. As examples, the above methods include, but are not limited to: high-throughput sequencing, nucleic acid hybridization such as tRNA microarrays, Northern blotting hybridization, mass spectrometry analysis, etc.

[0033] In a preferred embodiment of the present invention, tRNA expression abundance data is obtained using tRNA sequencing. In operation S100, obtaining the expression abundance data of *Nicotiana benthamiana* tRNA includes operations S110 to S140:

[0034] Operation S110: Construct a reference sequence set of tRNA genes from Nicotiana benthamiana.

[0035] According to an embodiment of the present invention, in operation S110, constructing a reference sequence set of tRNA genes of Nicotiana benthamiana includes: based on the whole genome sequence of Nicotiana benthamiana, systematically identifying and annotating it using tRNA prediction software to obtain a reference sequence set containing functional tRNA genes.

[0036] Figure 2 This is a diagram showing the distribution of the number of tRNA genes corresponding to each amino acid in Nicotiana benthamiana.

[0037] Figure 3 This is a statistical graph showing the number of tRNAs corresponding to different anticodons in the Tobacco Bunsenium genome.

[0038] According to embodiments of the present invention, since *Nicotiana benthamiana* is a highly heterozygous tetraploid species, its genome suffers from problems such as tRNA annotation gaps, pseudogene redundancy, and loss of gap region sequences in traditional draft assembly. See also... Figure 2 The distribution of tRNA gene copy numbers within the *Nicotiana benthamiana* genome is highly uneven, with higher copy numbers for the tRNA genes corresponding to Met, Ser, and Leu, and the lowest copy number for the tRNA gene corresponding to Cys. (See also...) Figure 3 The copy number differences at the anticodon level are also significant. CAT has the highest copy number at 218, while ACA, ACC, and GGC each contain only 1 copy. Therefore, this invention conducts species-specific systematic mining and precise reannotation of the tRNA genome. The method for constructing the reference sequence set is described below as an example.

[0039] Specifically, this invention uses a high-quality whole-genome chromosome-level assembled sequence of *Nicotiana benthamiana* reconstructed using telomere-to-telomere (T2T) technology (Zhong et al., *Nat Plants*, 2024, doi:10.1038 / s41477-024-01849-y) as reference genome data. To address the interference from highly repetitive sequences caused by the large and polyploid genome of *Nicotiana benthamiana*, tRNAscan-SE software was used for scanning. To exclude interference from minor variant lines resulting from genome duplication, the analysis mode was set to a eukaryotic search model specifically optimized for complex plant systems. This identification process, combined with a built-in RNA secondary structure thermodynamic free energy minimization model, constructs a multi-dimensional screening mechanism including: nucleotide primary sequence similarity, Hidden Markov Model (HMM), and RNA secondary stem-loop structure free energy. During the candidate sequence identification stage, the software uses its built-in Infernal engine (a tRNA-specific recognition engine based on a covariance model) to perform covariance matrix analysis and filters based on Log-odds score thresholds. This retains atypical tRNA sequences containing long introns while eliminating non-functional pseudogenes lacking complete CCA terminal domains. This achieves low false-positive specificity in the highly repetitive genome of *N. benthamiana*, ensuring the reliability of the annotation library. Using the above methods, this invention precisely located and systematically identified 2150 functional tRNA genes from the entire *N. benthamiana* genome, providing data support for calculating RSAU.

[0040] It should be understood that the above methods are merely preferred examples for ease of understanding and do not constitute a limitation on the technical solution of the present invention.

[0041] The copy number distribution at the genome level described above cannot be directly equated to the actual supply capacity of tRNA during the translation process, and needs to be further corrected by tRNA-seq measured abundance.

[0042] Operation S120: Constructing a tRNA sequencing library of Nicotiana benthamiana.

[0043] According to an embodiment of the present invention, in operation S120, total RNA is extracted from two independent biological replicate samples (D1, D2) of Nicotiana benthamiana, and tRNA sequencing libraries are constructed independently for each sample.

[0044] According to an embodiment of the present invention, in operation S120, constructing the tRNA sequencing library of Nicotiana benthamiana includes operations S121 to S124:

[0045] Operation S121: Extract total RNA from tobacco samples, isolate and enrich small RNA molecules;

[0046] Operation S122: Pre-treat small RNA molecules to eliminate interference from tRNA secondary structure and chemical modifications on reverse transcription;

[0047] Operation S123: Connect the sequencing adapters to both ends of the pretreated small RNA molecules to obtain the ligation product;

[0048] Operation S124: Using the ligation product as a template, reverse transcription is performed to obtain the tRNA sequencing library.

[0049] It should be understood that the above library construction steps are merely preferred examples for ease of understanding and do not constitute a limitation on the technical solution of this invention. Other known tRNA sequencing library construction methods can also be used, as long as a high-quality tRNA sequencing library suitable for high-throughput sequencing can be obtained.

[0050] Operation S130: Perform high-throughput sequencing on the tRNA sequencing library to obtain sequencing read data.

[0051] According to an embodiment of the present invention, in operation S130, the tRNA sequencing libraries constructed by D1 and D2 are subjected to high-throughput sequencing respectively to obtain two sets of independent sequencing read data.

[0052] Operation S140: Align the sequencing read data with the reference sequence set to obtain the expression abundance data of Nicotiana benthamiana tRNA.

[0053] According to an embodiment of the present invention, in operation S140, the alignment of sequencing read data with the reference sequence set specifically includes: first, performing quality control on the sequencing reads to remove low-quality reads and adapter contamination; then, using alignment software (e.g., Bowtie2, STAR, etc.) to map the cleaned reads to the aforementioned constructed Nicotiana benthamiana tRNA reference sequence set; counting the number of uniquely aligned sequencing reads at each tRNA locus, and appropriately allocating multiple aligned reads, such as using the expectation-maximization algorithm or a random allocation strategy, to finally obtain the original count of each tRNA, i.e., expression abundance data.

[0054] According to an embodiment of the present invention, operation S140 further includes quality control and alignment evaluation of the sequencing reads. Specifically, the reads are mapped to the previously constructed *Nicotiana benthamiana* tRNA reference genome using alignment software. The distribution ratios of uniquely mapped reads, multi-mapping reads, and unmapped reads are statistically analyzed to evaluate the fidelity and genome coverage of the sequencing library. The results are as follows: Figure 4 As shown.

[0055] Figure 4 This is a distribution diagram of the alignment results of tRNA sequencing reads from *Tobacco Bengal*.

[0056] according to Figure 4 As can be seen, the unique alignment rate of the samples increased from less than 20% based on traditional public databases to over 50%, and the proportion of multiple aligned sequences and unaligned sequences remained within a reasonable range, demonstrating that the sequencing library has high fidelity and coverage. These results indicate that for the allotetraploid genome of Nicotiana benthamiana, systematic identification and annotation using tRNA prediction software to construct a tRNA reference sequence set can significantly improve the unique alignment rate of the samples, laying a reliable data foundation for subsequent codon optimization based on measured tRNA abundance.

[0057] According to an embodiment of the present invention, after obtaining the expression abundance data, a multi-dimensional statistical analysis is further performed on it to reveal the overall characteristics of tRNA expression in Nicotiana benthamiana.

[0058] Specifically, based on the chemical properties of the amino acid side chains carried by tRNA, tRNAs were classified into five major categories: polar uncharged amino acids, acidic amino acids, basic amino acids, aromatic amino acids, and non-polar amino acids. Box plots and other statistical methods were used to analyze the average expression level and distribution dispersion of tRNAs in different physicochemical groups, and to study the resource allocation of host cells in the translation of amino acids with different chemical properties. The results are as follows: Figure 5 As shown.

[0059] Figure 5 Box plot of tRNA expression levels classified based on the physicochemical properties of amino acid side chains.

[0060] according to Figure 5 It can be seen that the average expression level of tRNAs corresponding to acidic amino acids is high and their distribution is concentrated; while non-polar amino acids contain the most types, but there are large individual differences and highly expressed specific tRNAs.

[0061] Furthermore, statistical analysis was performed based on the types of amino acids carried by the tRNA, and the results are as follows: Figure 6 As shown.

[0062] Figure 6 This is a distribution diagram showing the total expression of isoform receptor tRNAs with different amino acids.

[0063] according to Figure 6 It can be seen that *Nicotiana benthamiana* contains the most abundant total amount of tRNAs carrying glycine (Gly), glutamic acid (Glu), and arginine (Arg). When designing exogenous genes, if the amino acid composition of the target protein matches the distribution of tRNA resources in *Nicotiana benthamiana*, the translation efficiency will be higher. Related studies also indicate that amino acid composition has an effect on translation elongation rate that is as important as codon fit.

[0064] According to an embodiment of the present invention, in operation S200, relative amino acid specificity utilization is used to evaluate the resource share of each tRNA transporting a specific amino acid in the whole-cell tRNA pool, thereby characterizing the specificity of the host translation system in supplying that amino acid for translation. The aforementioned whole-cell tRNA pool refers to the sum of all functional tRNA molecules within *Nicotiana benthamiana* cells.

[0065] According to an embodiment of the present invention, in operation S200, the relative amino acid specificity utilization is determined by the following methods, including operations S210 to S220:

[0066] Operation S210: Standardize the expression abundance data of each tRNA to obtain the standardized expression value of each tRNA. The standardized expression value is the number of transcripts per million (TPM).

[0067] Operation S220: Based on the normalized expression value of tRNA, the normalized expression value of all isoform receptor tRNAs of the amino acid to which the tRNA belongs, and the number of anticodon types of all isoform receptor tRNAs corresponding to the amino acid, the relative amino acid specificity of tRNA is obtained.

[0068] Furthermore, the standardized expression abundance data were sorted in descending order to identify the top ten highly expressed tRNA components. The results are as follows: Figure 7 As shown.

[0069] Figure 7 This is a distribution map of the top ten most abundant tRNAs expressed in Nicotiana benthamiana.

[0070] according to Figure 7 It can be seen that tRNA-Gly-GCC has the highest expression abundance in Nicotiana benthamiana, followed by tRNA-Glu-CTC and tRNA-His-GTG. These analytical results provide a data foundation and theoretical basis for subsequent calculation of RSAU and screening of high RSAU dominant codons.

[0071] According to an embodiment of the present invention, in operation S220, obtaining the relative amino acid specificity utilization of tRNA based on the normalized expression value of tRNA, the normalized expression value of all isoform receptor tRNAs of the amino acid to which the tRNA belongs, and the number of anticodon types of all isoform receptor tRNAs corresponding to the amino acid includes: obtaining an intermediate value based on the ratio of the sum of the normalized expression values ​​of all isoform receptor tRNAs of the amino acid to which the tRNA belongs to to the number of anticodon types of all isoform receptor tRNAs corresponding to the amino acid; and obtaining the relative amino acid specificity utilization of tRNA based on the ratio of the normalized expression value of tRNA to the intermediate value.

[0072] The calculation formula is as follows:

[0073]

[0074] Where RSAU is the relative amino acid specific utilization, and TPM is the total amino acid specific utilization. k The TPM-normalized expression value of the k-th isoform receptor tRNA is given. The sum of the TPM-normalized expression values ​​of all isoform receptor tRNAs for this amino acid, where N is the number of anticodon types corresponding to this amino acid.

[0075] To compare with relative amino acid specificity usage, the relative amino acid codon usage (RSCU) of each tRNA was calculated. RSCU measures the degree of preference for synonymous codons when encoding the same amino acid.

[0076] The calculation formula is as follows:

[0077]

[0078] Among them, RSCU ij E represents the relative synonymous codon usage value of the j-th codon for the i-th amino acid; ij This represents the observed frequency of the j-th codon encoding the i-th amino acid in the complete genome sequence of *Nicotiana benthamiana*; n i This represents the total number of synonymous codons encoding the i-th amino acid.

[0079] According to an embodiment of the present invention, the high RSCU codons and high RSAU codons corresponding to 20 amino acids were calculated respectively, and the sequences are shown in the table below:

[0080] Table 1. Synonymous codons of twenty amino acids and their corresponding high RSCU and high RSAU codons.

[0081]

[0082] Table 1 (continued)

[0083]

[0084] Furthermore, by comparing the genome-level RSCU with the tRNA expression abundance-based index RSAU, this invention found that the two do not entirely agree on the definition of dominant codons. RSCU reflects the nucleotide composition preference formed by the host genome during long-term evolution. Although it is species-specific, it is often affected by mutational pressures such as genomic GC content and may not accurately reflect the real-time dynamics of protein translation. In contrast, RSAU is directly anchored to the actual intracellular abundance of tRNA, the core machine of translation. Since tRNA is the direct limiting factor for amino acid transport, the RSAU index can more realistically reflect the host's resource supply capacity during translation initiation and elongation, thus identifying dominant codons for translation more specifically than RSCU.

[0085] Based on in-depth analysis of the expression profile of *Nicotiana benthamiana* tRNA, this invention screens out a set of dominant codons with high RSAU values ​​as the core replacement targets for sequence optimization. Specifically, according to embodiments of the present invention, the present invention provides a set of dominant codons for improving the biosynthetic efficiency of target proteins in *Nicotiana benthamiana*. These dominant codons include: GCT for alanine; AGA for arginine; AAC for asparagine; GAC for aspartic acid; TGC for cysteine; CAA for glutamine; GAG for glutamic acid; GGC for glycine; CAC for histidine; ATT for isoleucine; CTA for leucine; AAG for lysine; ATG for methionine; TTC for phenylalanine; CCA for proline; AGC for serine; ACC for threonine; TGG for tryptophan; TAC for tyrosine; and GTT for valine.

[0086] According to embodiments of the present invention, the original low-fitness codons in the target gene sequence are replaced with high RSAU codons, enabling the optimized gene sequence to make fuller use of intracellular tRNA resources in *Nicotiana benthamiana*. Specifically, since the isoform receptor tRNAs corresponding to the above codons have high measured expression abundance in *Nicotiana benthamiana*, these codons can obtain a more sufficient supply of tRNA in the expression system, especially under the high translation load of the transient expression system, thereby reducing the probability of ribosome arrest or shedding at the corresponding site and maintaining the continuity of translation elongation. Therefore, based on the principle and existing literature, it is reasonable to expect that using the above-mentioned high RSAU dominant codons for sequence optimization can effectively alleviate the imbalance between the supply and demand of translation resources during the transient expression of exogenous genes in *Nicotiana benthamiana*, and improve the translation elongation efficiency and final yield of the target protein. It should be noted that the use of high RSAU strategies for codon optimization has been reported in related studies to improve protein translation efficiency, further supporting the above reasonable expectation.

[0087] According to an embodiment of the present invention, in operation S300, optionally, by replacing the original low-fitness codons in the target gene sequence with host-specific high RSAU codons, the optimized gene sequence can more fully utilize host tRNA resources during translation. It should be noted that codon optimization using a high RSAU strategy has been reported in relevant studies to improve protein translation efficiency. This indicates that this strategy has certain application potential and lays a solid theoretical foundation for achieving efficient expression of various target proteins in *Nicotiana benthamiana*.

[0088] According to an embodiment of the present invention, in operation S300, the expression of the target protein is performed in a transient expression system of *Nicotiana benthamiana*, and the target protein is a heterologous protein. In a stable expression system, the exogenous protein is continuously expressed at low levels, and the tRNA pool can slowly adapt through cellular homeostasis, tolerating the shortage of rare tRNAs. However, in a transient expression system, the transcription and translation of the exogenous gene reach extremely high intensities in a short period of time, rapidly increasing the consumption of tRNA resources, far exceeding the needs of the intracellular gene. At this time, the tRNA supply bottleneck is amplified, causing ribosomes to stagnate, queue, or even fall off at this codon, resulting in a significant decrease in translation efficiency. Therefore, in a transient expression system, the key to codon optimization lies in further accurately matching the host cell's actual tRNA resource supply capacity during the peak translation period, based on the reference genome static frequency. The RSAU index calculated based on measured tRNA abundance in this invention can directly identify the codon with the most abundant tRNA supply during the peak translation period, thereby effectively avoiding local tRNA depletion during high-load expression of exogenous genes, maintaining a high-efficiency ribosome elongation rate, and thus increasing the yield of the target protein.

[0089] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for improving the biosynthetic efficiency of a target protein in *Nicotiana benthamiana*, characterized in that, include: Obtain expression abundance data of tRNA from Nicotiana benthamiana; Based on the expression abundance data, dominant codons with high relative amino acid specificity utilization for each amino acid in Nicotiana benthamiana were determined. The relative amino acid specificity utilization is used to characterize the sufficiency of resource supply for isoform receptor tRNA in the host translation system. At least one original codon in the foreign gene encoding the target protein is replaced with the dominant codon to obtain an optimized gene sequence; The optimized gene sequence was introduced into *Nicotiana benthamiana* for expression to obtain the target protein.

2. The method according to claim 1, characterized in that, The expression abundance data were obtained through tRNA sequencing.

3. The method according to claim 2, characterized in that, The acquisition of expression abundance data for Nicotiana benthamiana tRNA includes: Construct a reference sequence set for the tRNA gene of Nicotiana benthamiana; Constructing a tRNA sequencing library from Nicotiana benthamiana; The tRNA sequencing library was subjected to high-throughput sequencing to obtain sequencing read data; The sequencing read data were compared with the reference sequence set to obtain the expression abundance data of Nicotiana benthamiana tRNA.

4. The method according to claim 3, characterized in that, The reference sequence set for constructing the tRNA gene of Nicotiana benthamiana includes: Based on the whole genome sequence of Nicotiana benthamiana, tRNA prediction software was used for systematic identification and annotation to obtain the reference sequence set containing functional tRNA genes.

5. The method according to claim 1, characterized in that, The relative amino acid specificity utilization is used to evaluate the resource share of each tRNA that transports a specific amino acid in the whole-cell tRNA pool, in order to characterize the specificity of the host translation system in supplying that amino acid for translation.

6. The method according to claim 1, characterized in that, The relative amino acid specificity utilization was determined by the following method: The expression abundance data of each tRNA were standardized to obtain the standardized expression value of each tRNA, which is the number of transcripts per million. The relative amino acid specificity of tRNA is obtained based on the normalized expression value of tRNA, the normalized expression value of all isoform receptor tRNAs of the amino acid to which the tRNA belongs, and the number of anticodon types of all isoform receptor tRNAs corresponding to the amino acid.

7. The method according to claim 6, characterized in that, The relative amino acid specificity of tRNA is obtained by taking the normalized expression value of tRNA, the normalized expression value of all isoform receptor tRNAs corresponding to the amino acid of that tRNA, and the number of anticodon types of all isoform receptor tRNAs corresponding to that amino acid. An intermediate value is obtained by the ratio of the sum of the normalized expression values ​​of all isoform receptor tRNAs corresponding to the amino acid to which the tRNA belongs to the ratio of the number of anticodon types of all isoform receptor tRNAs corresponding to that amino acid. The relative amino acid specificity of the tRNA is obtained by comparing the normalized expression value of the tRNA with the intermediate value.

8. The method according to claim 3, characterized in that, The tRNA sequencing library constructed from *Nicotiana benthamiana* includes: Total RNA was extracted from tobacco samples, and small RNA molecules were isolated and enriched. The small RNA molecules are pretreated to eliminate interference from tRNA secondary structure and chemical modifications on reverse transcription; Sequencing adapters are ligated to both ends of pretreated small RNA molecules to obtain ligation products; Using the ligation product as a template, a tRNA sequencing library was obtained by reverse transcription.

9. The method according to claim 1, characterized in that, The process of introducing the optimized gene sequence into *Nicotiana benthamiana* to express the target protein is performed in a *Nicotiana benthamiana* transient expression system, and the target protein is a heterologous protein.

10. A set of dominant codons for enhancing the biosynthetic efficiency of target proteins in *Nicotiana benthamiana*, obtained by the method according to any one of claims 1-9, characterized in that, The advantageous codons include: The codon for alanine is GCT; The codon for arginine is AGA; The codon for asparagine is AAC; The codon for aspartic acid is GAC. The codon for cysteine ​​is TGC; The codon for glutamine is CAA; The codon for glutamate is GAG; The codon for glycine is GGC; The codon for histidine is CAC; The codon for isoleucine is ATT; The codon for leucine is CTA; The codon for lysine is AAG; The codon for methionine is ATG; The codon for phenylalanine is TTC; The codon for proline is CCA; The codon for serine is AGC; The codon for threonine is ACC; The codon for tryptophan is TGG; The codon for tyrosine is TAC; The codon for valine is GTT.

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