CsWRKY33: A Crucial Transcription Factor in the MAPK Pathway Inhibited by Trypsin, Participating in the Suppression of Cucumis sativus Senescence

doi:10.21203/rs.3.rs-3347275/v1

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Research Article

CsWRKY33: A Crucial Transcription Factor in the MAPK Pathway Inhibited by Trypsin, Participating in the Suppression of Cucumis sativus Senescence

https://doi.org/10.21203/rs.3.rs-3347275/v1

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Background

The Mitogen-Activated Protein Kinase (MAPK) cascade pathway extensively participates in the physiological regulation processes of plants. Trypsin, as an inducer of resistance, significantly enhanced the storage quality of Cucumis sativus (C. sativus). However, the mechanism by which trypsin regulated the synthesis of phenylpropanoid compounds through the MAPK pathway to influence fruit resistance remained to be elucidated.

Methods

To investigate the molecular mechanism underlying trypsin-induced C. sativus resistance, we conducted a combined transcriptomic and widely targeted metabolomic analysis, validated through Virus-Induced Gene Silencing (VIGS).

Results

Transcriptomic results revealed that a total of 83 differentially expressed genes (DEGs)were enriched in the MAPK pathway, with 48 genes significantly downregulated and 35 genes significantly upregulated. GSEA analysis further identified the WRKY33 transcription factor from the leading edge subset. Bioinformatics analysis indicated that CsWRKY33 shared high homology with WRKY22 in Arabidopsis. The combined analysis of transcriptomics and widely targeted metabolomics demonstrated significant upregulation in the synthesis of compounds such as vanillin, dihydrocharcone-4'-O-glucoside, and 2-hydroxy-3-phenylpropanoic acid. Co-expression network analysis showed that these key metabolites were negatively regulated by CsWRKY33. VIGS results showed that silencing CsWRKY33 enhanced fruit resistance and extended storage time.

Conclusion

This study revealed that trypsin could downregulate the expression of CsWRKY33 and promote the synthesis of compounds with high antioxidant and antibacterial activity, such as vanillin, dihydrocharcone-4'-O-glucoside, and 2-hydroxy-3-phenylpropanoic acid. This enhancement led to increasing fruit disease resistance and delayed senescence and decay.

CsWRKY33

trypsin

transcriptomics

widely targeted metabolomics

Virus-Induced Gene Silencing (VIGS)

induced resistance

The senescence and decay of fruits and vegetables are intricate physiological processes, influenced by numerous endogenous factors and exogenous influences [1], closely linked to the MAPK signaling pathway [2]. The MAPK cascade pathway consists of three types of serine/threonine protein kinases, transmitting signals through gradual protein phosphorylation to target proteins at the terminal receptor [3]. It not only regulated various processes such as plant growth and development extensively but also maintained a close association with plant immune defense [4].

Early research on the MAPK pathway primarily focused on identifying the environmental signal-responsive MAPK pathway and the isolation and functional analysis of genes in the MAPK cascade pathway [5, 6]. However, in recent years, the interaction between the plant MAPK cascade pathway and other signaling pathways, the expression regulation of genes in the MAPK cascade pathway, and its regulation of downstream transcription factors have gradually become the key aspects for a comprehensive understanding of the mechanistic roles of the plant MAPK cascade pathway [7, 8]. The identification of downstream transcription factors in the MAPK cascade pathway held particular significance in investigating the regulatory network downstream of the MAPK cascade pathway.

Currently, it has been discovered that several transcription factor families, including WRKY, bZIP, ERF, and ICE, have close associations with the MAPK cascade pathway [9, 10, 11, 12]. Among them, the WRKY family is one of the largest transcription factor families in plants [13, 14, 15], and extensive reports have demonstrated its involvement in the MAPK pathway, playing a significant role in plant resistance against pathogenic microorganisms. In cotton, GhWRKY41 could activate the expression of GhC4H and Gh4CL, promoting the accumulation of lignin and flavonoids, and thereby enhancing resistance against Verticillium dahliae [16]. In maize, the transcription factor ZmWRKY83 played a crucial role in conferring resistance against Fusarium graminearum infection [17].

In the preliminary research conducted by our laboratory, it was discovered that trypsin can serve as an effective inducer, enhancing fruit resistance [18, 19, 20]. Due to its ability to scavenge superoxide anions, trypsin could modulate endogenous reactive oxygen species (ROS) levels in dragon fruit peels and inhibit saturated fatty acid levels. It also induced the biosynthesis of compounds involved in the phenylpropanoid pathway, such as lignin, chlorogenic acid [21, 22], and flavonoids [23, 24]. Furthermore, it could influence the activity of flavonoids in scavenging free radicals, such as DPPH and ABTS [25, 26], thereby enhancing fruit resistance. Numerous studies have indicated that MAPK pathway serves as an upstream signaling pathway in the phenylpropanoid pathway, yet the precise mechanism by which trypsin regulated the synthesis of phenylpropanoid compounds through the MAPK pathway, thereby impacting fruit resistance, remained to be elucidated.

C. sativus was known for its rich nutritional contents, but it was prone to postharvest deterioration and decay [27, 28]. In this study, C. sativus was chosen as the experimental material. Through transcriptome data analysis, DEGs regulated by trypsin in the MAPK cascade pathway were identified. WRKY transcription factors were screened through transcriptome analysis methods such as Gene Set Enrichment Analysis (GSEA). Subsequently, widely targeted metabolomics analysis led to the identification of differential metabolites. Finally, through expression correlation analysis and Virus-Induced Gene Silencing (VIGS) technology, preliminary evidence was provided to demonstrate that CsWRKY33 acted as a crucial transcription factor regulated by trypsin in the MAPK pathway, inducing the biosynthesis of phenylpropanoid compounds and enhancing fruit resistance. This finding offered new theoretical insights into the regulatory mechanism of the MAPK pathway in trypsin-mediated preservation.

Experimental materials and reagents

Fresh C. sativus of the same batch (Species: Zhongnong 27) were purchased from a local market. C. sativus with similar size, shape, and color, as well as no mechanical damage or insect contamination, were selected for the experiment. Trypsin (bovine source, 5×10⁵units g^-1) was obtained from Amersco, USA.

C. sativus treatment methods

C. sativus were immersed in a trypsin solution (2.41×10^-6mol/L) for 60 seconds, while the control group was subjected to the same treatment using distilled water. The samples were placed at 25°C. Every 24 hours, observations, photographs, records, and measurements of water loss rates were conducted [29]. After one week of storage, the C. sativus epidermis that had undergone treatment was excised using a surgical blade, mixed thoroughly, and rapidly placed in liquid nitrogen for 3-5 minutes. Subsequently, it was stored at -80°C in preparation for subsequent omics analysis.

Transcriptomic analyses

The Illumina Novaseq 6000 sequencing platform was used for mRNA sequencing. This approach involved sequencing all the mRNA transcribed from specific tissues or cells of eukaryotic organisms at a particular time point. The sequencing protocol employed the Illumina TruSeqTM RNA Sample Prep Kit for the construction of sequencing libraries. Total RNA was extracted, and the RNA Integrity Number (RIN) was quantified using the Agilent 2100 system [30]. Subsequently, the Illumina HiSeq platform was utilized for on-machine sequencing using paired-end sequencing (PE library) with a read length of 2x150 bp.

Co-expression network analysis of MAPK-regulated genes and metabolites

MAPK-related DEGs and differential metabolites regulated by trypsin were screened from the transcriptome data, and the correlations between genes and metabolites were calculated and imported into Cytoscape software for network visualization and analysis [31]. The network diagram illustrated the interactions between genes and metabolites and the key nodes in the interaction network were calculated using Cytoscape's plug-in cytoHubba.

Sequence analysis of the CsWRKY33 gene

The sequence of CsWRKY33was obtained from our RNA-Seq data. Gene-specific primers were designed to clone the open reading frame (ORF) of CsWRKY33. Similar sequences were searched using the NCBI database, and Multiple sequence alignment was executed employing the ClustalW algorithm. Subsequently, a phylogenetic tree was generated through the application of the Neighbor-Joining method using the MEGA6.0 software package. Furthermore, the theoretical isoelectric point and relative molecular weight of CsWRKY33were predicted via the web resource http://web.expasy.org/Compute_pi/ [30].

VIGS vector construction

Total RNA from C. sativus fruit skin was extracted using the Trizol method. cDNA synthesis was performed employing the HiFi-MMLV cDNA Kit. Specific primers for CsWRKY33were used for amplification（Primers were listed in Table S1）. The PCR product and pTRV2 vector, which was digested by EcoRI and BamHI restriction enzymes and recovered, were ligated using T4 DNA ligase. The ligated products were transformed into Escherichia coli Top10, and successfully ligated WRKY33-pTRV2 plasmids were extracted. These plasmids were subsequently transformed into Agrobacterium tumefaciensGV3101 for further experiments [32].

RT-qPCR and determination of indexes

Differential gene expression levels were calculated using the 2^-ΔΔCtmethod, with the experiment being conducted in triplicate [33]. The primer sequences could be found in Table S1. Concurrently, the weight loss rate was periodically assessed and recorded throughout the experimental duration [34].

Statistical analyses

Statistical analysis was performed using the SPSS statistical software package (version 11.0.1). Differences between groups of samples were assessed utilizing non-parametric tests, specifically the Wilcoxon rank-sum test. Paired sample t-tests were utilized to ascertain the significance of differences between samples at specific time points. Significance levels were determined as follows: p < 0.05 denoting significant differences and p < 0.01 representing highly significant differences [35].

Analysis of Differentially Expressed Genes in Transcriptome

Based on the gene expression profiles induced by trypsin treatment, the analysis of expression level differences was completed. First, the results of sample correlation analysis showed that there was a strong correlation between biological duplicate samples (Fig. 1A). PCA analysis showed that the samples were divided into two independent groups (Fig. 1B), with significant differences between the two groups (PC1= 55.58%), while the samples marked with the same color within the group were closely clustered together (PC2= 12.63%). A total of 9061 DEGs were screened from the expression difference analysis, among which 4416 were upregulated and 4645 were downregulated (Figure 1C).

These DEGs were further categorized based on their transcription factor families (Figure 1D), and it was found that they were mainly enriched in the ERF, MYB, bHLH, and WRKY families. Subsequently, we conducted KEGG pathway enrichment analysis on the 9061 significantly DEGs and found that they were distributed across 131 metabolic pathways (Table S2), with 83 genes enriched in the MAPK signaling pathway. We established a gene set for this pathway and conducted further analysis.

GSEA Analysis of MAPK Pathway-Related Genes

By conducting GSEA analysis on the 83 genes enriched in the MAPK signaling pathway, the results indicated that in addition to being annotated in the MAPK pathway itself (MAP04016), they were also annotated in the Plant-Pathogen Interaction pathway (MAP04626) and Plant Hormone Signal Transduction pathway (MAP04075) (Table 1).

Table 1：GSEA Analysis Statistical Table

gene set name	Description	Size	ES	NES	p_value	p adjust	Rank at MAX	Leading edge
MAP04016	MAPK signaling pathway - plant	83	1	1	0	0.146667	82	83
MAP04626	Plant-pathogen interaction	24	-0.26342	-0.79703	0.725191	0.738269	15	8
MAP04075	Plant hormone signal transduction	42	0.230415	0.965639	0.485915	0.9185	11	9

A total of 9 genes were enriched in the leading edge subset of the MAP04075 pathway, among which the screenedMYCtranscription factor (Table S3) has been previously reported by our laboratory [29]. Moreover, from the leading edge subset of the MAP04626 pathway, a total of 8 genes were screened (Table S4). Among these 8 genes, we identified CsaV3_4G006110 as a member of the WRKY transcription factor family, named WRKY33in the study by Chen et al [36]. As an essential transcription factor involved in the MAPK pathway, we hypothesized that CsWRKY33 might influence the synthesis and metabolism of relevant substances, thus enhancing the fruit's disease-resistance capacity.

Co-expression Network Analysis of WRKY33 and Metabolites

Through widely targeted metabolomic analysis, a total of 175 significantly different metabolites were identified (Table S5). We constructed a co-expression network by integrating the transcriptomic data with the metabolomic data to analyze the expression correlations between the selected 83 genes and the metabolites (Figure 3A). The co-expression network, created by using Cytoscape, consisted of 226 nodes and 811 edges.

Furthermore, we employed the "EPC" ranking method using cytoHubba to prioritize the associations between CsWRKY33and the 8 metabolites (Figure 3B). It's noticeable that CsWRKY33 displayed negative correlations with most metabolites from the relationship between genes and metabolites. Among them, the most significant negative correlations were observed with 2-hydroxy-3-phenylpropanoic acid and vanillin. Additionally, other metabolites, such as dihydrocharcone-4'-O-glucoside, were also negatively correlated with CsWRKY33.

Bioinformatics Analysis of the CsWRKY33 Gene

The CsWRKY33gene shares a high similarity of 95.22% with CmWRKY22(The sequences were provided in Table S6). CsWRKY33's open reading frame (ORF) spans a total length of 810 base pairs, encoding a polypeptide comprising 269 amino acids. The calculated molecular weight for this polypeptide was approximately 30.31 kDa, with a theoretical isoelectric point of 6.323. Notably, at its N-terminal region,CsWRKY33harbored a highly conserved WRKYGQK amino acid sequence, which constituted the distinctive WRKY domain characteristic of WRKY transcription factors. Additionally, CsWRKY33featured a putative zinc finger motif (C-X4-5-C-X22-23-H-X1-H) (Figure 4A). Through the utilization of the Blast online alignment tool on NCBI, we conducted multiple sequence alignment involving 11 highly homologous proteins, and subsequently, we constructed an evolutionary tree employing MEGA 6.0 software. The results conclusively indicated that CsWRKY33exhibited the highest homology with CmWRKY22(Figure 4B).

Cloning of CsWRKY33 partial sequence and vector construction

Utilizing C. sativus cDNA as the template, a 249-bp cDNA fragment was amplified with CsWRKY33-specific primers. The agarose gel electrophoresis of the PCR product is shown in Figure 5A. The amplified fragment was excised from the gel and then sent to Sangon Biotech (Shanghai) Co., Ltd. for sequencing. The alignment results confirmed that the fragment is specific to the CsWRKY33gene. The pTRV2-CsWRKY33 vector was constructed (Figure 5B). Subsequently, these plasmids were introduced into the Agrobacterium strainGV3101 for use in the subsequent VIGS validation experiment.

Fruit phenotypic changes and data measurement

During the initial storage period, C. sativus fruits from all groups exhibited good quality with vibrant color (Figure 6A). After 16 days of storage, the control group fruits showed evident yellowing, severe shriveling at the top and near the center, and signs of rot (Figure 6A). In contrast, the fruits treated with trypsin maintained the highest overall freshness, with the least yellowing and shriveling of the skin, and no signs of decay on the surface (Figure 6A). The freshness preservation effect of the silenced group was also superior to the control group, with only slight yellowing at the root and minimal overall yellowing and mild shriveling at the top. As the storage time extended, the weight loss rate of fruits in all groups significantly increased (Figure 6B). The control group exhibited the highest fruit weight loss rate (43.36%), while the trypsin-treated group had the lowest rate (22.55%) (Figure 6B). The weight loss rate of the silenced group's fruits was 30.33%, indicating that VIGS treatment and trypsin treatment slowed down the rate of fruit water loss. Furthermore, verification through RT-qPCR (Figure 6C) revealed thatWRKY33expression was suppressed by trypsin treatment compared to the control group. The silenced group also showed consistent downregulation of WRKY33expression, further confirming the potential role of trypsin in preservation through the inhibition of WRKY33expression.

The MAPK cascade pathway assumed a pivotal role in the regulation of diverse facets of plant growth and development, while also borne considerable importance in orchestrating plant defense mechanisms against pathogen incursions. Abundant research indicated that the MAPK pathway could regulate downstream WRKY family transcription factors and was a key participant in plant immune responses [37]. Our transcriptomic findings also supported this information, revealing that DEGs enriched in the MAPK pathway, as determined through GSEA, led to the identification of the WRKY33 transcription factor from the plant-pathogen interaction pathway (MAP04626).

The results of bioinformatics analysis indicated that this gene possessed a highly conserved WRKYGQK amino acid sequence at its N-terminus. Multiple sequence alignment revealed similarity between this gene and WRKY22/29 from different species, with the highest homology observed with CmWRKY22. In terms of its functional characterization, extensive research suggested that WRKY22/29 served as a significant downstream component of the MAPK mediated signaling pathway. WRKY22 was involved in pathogen-triggered immune responses and actively regulated resistance against bacterial pathogens [38], playing a pivotal role in plant disease-related processes.

However, Qin's research highlighted a different perspective. Their study on sweet orange (Citrus sinensis Osbeck) demonstrated that partial knockout of CsWRKY22 using CRISPR/Cas9 technology enhanced resistance against the Xanthomonas citri subsp. citri (Xcc). Intriguingly, plants overexpressing CsWRKY22 exhibited a dwarfed phenotype with wrinkled and thickened leaves, rendering them more susceptible to Xcc infection. Furthermore, the expression of CsWRKY22 was found to activate the key susceptibility gene CsLOB1, which was associated with citrus canker susceptibility. In the end, CsWRKY22 exacerbated susceptibility to Xcc by fostering host hypertrophy and inducing the expression of CsLOB1 [39].

In this study, Trypsin demonstrated a favorable preservation effect on C. sativus. However, transcriptomic analysis revealed that trypsin reduced the expression of CsWRKY33. The question of whether the reduced expression of CsWRKY33 could enhance fruit resistance, thereby delaying senescence and decay, required further validation. Therefore, we employed VIGS technology to silence CsWRKY33. Experimental results indicated that the overall performance of the C. sativus group with silenced CsWRKY33 exhibited a similar trend to the trypsin-treated C. sativus group. After 16 days of storage, the appearance of the silenced group's C. sativus was notably better than that of the control group, with lower weight loss and extended fruit preservation time.

Furthermore, based on the comprehensive metabolomics analysis of C. sativus, the co-expression network of differentially expressed metabolites and CsWRKY33 revealed that most phenylpropanoid compounds associated with CsWRKY33 exhibited a negative correlation. These substances played a positive role in antioxidant and antibacterial activities, thereby enhancing fruit resistance.

Among the substances showed a strong negative correlation, 2-hydroxy-3-phenylpropanoic acid, also known as phenyllactic acid (PLA), was a broad-spectrum antibacterial compound, exhibiting significant inhibitory effects on most Gram-positive and Gram-negative bacteria as well as fungi [40]. Vanillin possessed a broad-spectrum antifungal action by increasing cell membrane permeability and lipid peroxidation, effectively inhibiting the growth rate of pathogenic fungi, mycelial biomass, and spore germination. Vanillin induced the elevation of defense-related enzyme activities such as phenylalanine ammonia lyase (PAL), chitinase (CHI), and β-1,3-glucanase (β-1,3-GA) in apple fruits, leading to increased levels of total phenols and flavonoids. On the other hand, dihydrocharcone-4'-O-glucoside belonged to the flavonoid class of compounds [33]. Studies have shown that flavonoids possess the ability to enhance antioxidant capacity and free radical scavenging in animal organisms.

Among the metabolites positively correlated with CsWRKY33 expression, the reduction of quercetin-3-O-(6''-malonyl) glucoside could attenuate enzymatic browning caused by the presence of polyphenol oxidase and its substrate phenolic compounds, thus influencing the appearance of the fruit [41].

In conclusion, CsWRKY33 served as a pivotal transcription factor in the trypsin-regulated MAPK pathway, inducing the biosynthesis of phenylpropanoid compounds. It participated in the plant-pathogen interaction pathway, attenuating C. sativus susceptibility under the influence of trypsin. This, in turn, led to an elevation in the levels of antimicrobial and antioxidant flavonoid compounds, enhancing fruit resistance and effectively delaying C. sativus senescence and decay. The results of this investigation provided fresh theoretical substantiation for elucidating the mechanism through which trypsin augmented the preservation of fruits and vegetables.

Trypsin enhanced fruit resistance, reduced fruit moisture loss, and significantly improved C. sativus storage quality. Based on transcriptomic data, a total of 9061 DEGs were screened, with KEGG results showing enrichment of 83 genes in the MAPK pathway. GSEA analysis further identified the key transcription factor WRKY33 (CsaV3_4G006110) from the plant-pathogen interaction (MAP04626) pathway. Multiple sequence alignment results demonstrated a high degree of homology between CsWRKY33 and Arabidopsis WRKY22. Moreover, the results of widely targeted metabolomic analysis indicated that compounds such as vanillin, dihydrocharcone-4'-O-glucoside, and 2-hydroxy-3-phenylpropanoic acid were likely key metabolites regulated by trypsin. Co-expression network analysis revealed a negative correlation between CsWRKY33 and these key metabolites. VIGS and RT-qPCR validation confirmed that silencing CsWRKY33 significantly enhanced C. sativus fruit storage quality. As an inducer of resistance, trypsin could markedly inhibit the expression of CsWRKY33, thereby promoting the synthesis of compounds with high antioxidant and antibacterial activity, such as vanillin, dihydrocharcone-4'-O-glucoside, and 2-hydroxy-3-phenylpropanoic acid. This enhancement results in increased fruit disease resistance and delayed senescence and decay.

Data Availability

All data and materials used in this research were publicly available. Raw sequence data from this study have been submitted to the NCBI sequence read archive under the BioProject accession [PRJNA 728562].

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors

Competing interests

The authors declare that they have no conficts of interest

Authors' contributions

JS contributed to the data analysis and paper writing. JW contributed to the study conception and design, sample collection. XL and XP contributed to the instruction of paper writing. EC, XC and BL contributed to the sample collection. All authors commented on the versions of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2017YFC1600802).

Acknowledgments

We wish to thank Prof. Jianye Chen of South China Agricultural University for providing pTRV1 and pTRV2 VIGS vectors and Agrobacterium strain (GV3101) for this work. We are grateful for the free online platform of Majorbio I-Sanger Cloud Platform (www.i-sanger.com).

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Authors and Affiliations

College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China

Jiaju Sun, Jie Wang, Enyan Chen, Xinxin Chen, Bairu Li & Xin Li

Henan Engineering Research Center of Food Microbiology, Luoyang 471023, China;

Xin Li

National Demonstration Center for Experimental Food Processing and Safety Education, Luoyang 471000,

China

Xin Li

College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang，

471023, China

Xinyue Pang

Corresponding authors

Corresponding author: Email: [email protected] (X Li); [email protected] (XY Pang); Tel.: 86-0379-64282342 (No. 263, Kaiyuan Avenue, Luolong District, Luoyang city, Henan 471023, China)

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Supplementary Information

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Table S1 All primer sequences used in the experiment.

Table S2 List of 131 KEGG enrichment pathways of DEGs.

Table S3 Information of genes in the leading edge of MAP04075 pathway.

Table S4 Information of genes in the leading edge of MAP04626 pathway.

Table S5 Information of 175 significantly different metabolites.

Table S6 Multiple sequences used in bioinformatics analysis.

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No competing interests reported.

TableS1Allprimersequencesusedintheexperiment..xlsx
Table S1 All primer sequences used in the experiment.
TableS2Listof131KEGGenrichmentpathwaysofDEGs..csv
Table S2 List of 131 KEGG enrichment pathways of DEGs.
TableS3InformationofgenesintheleadingedgeofMAP04075pathway.csv
Table S3 Information of genes in the leading edge of MAP04075 pathway.
TableS4InformationofgenesintheleadingedgeofMAP04626pathway.csv
Table S4 Information of genes in the leading edge of MAP04626 pathway.
TableS5Informationof175significantlydifferentmetabolites.csv
Table S5 Information of 175 significantly different metabolites.
TableS6Multiplesequencesusedinbioinformaticsanalysis.fasta
Table S6 Multiple sequences used in bioinformatics analysis.

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CsWRKY33: A Crucial Transcription Factor in the MAPK Pathway Inhibited by Trypsin, Participating in the Suppression of Cucumis sativus Senescence

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Experimental materials and reagents

C. sativus treatment methods

Transcriptomic analyses

Co-expression network analysis of MAPK-regulated genes and metabolites

Sequence analysis of the CsWRKY33 gene

VIGS vector construction

RT-qPCR and determination of indexes

Statistical analyses

Results

Analysis of Differentially Expressed Genes in Transcriptome

GSEA Analysis of MAPK Pathway-Related Genes

Co-expression Network Analysis of WRKY33 and Metabolites

Bioinformatics Analysis of the CsWRKY33 Gene

Cloning of CsWRKY33 partial sequence and vector construction

Fruit phenotypic changes and data measurement

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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