Comparative Physiological, Proteomic, and Metabolomic Insights into a Promising Low-Pruning Mulberry Cultivar for Silkworm Rearing

Abstract

Mulberry (Morus spp.) is an economically significant plant in the production of silk through feeding leaves to silkworm larvae. Traditional silkworm rearing is heavily labor-intensive, particularly in leaf collection, which leads to low efficiency and impedes the development of sericulture. Here, to assess the feasibility and effectiveness of a novel low-pruning mulberry cultivar, ZJ1, in the silkworm rearing industry, a comprehensive investigation integrating physiological, proteomic, and metabolomic analyses was conducted in comparison with the traditionally high-pruning cultivar, N14. The low-pruning mulberry variety ZJ1 exhibited a notable increase in annual leaf yield of 43.94%, along with a significant enrichment of serine and isoleucine contents, in contrast to those of the high-pruning variety N14. Through iTRAQ proteomics and LC-MS/MS metabolomics analyses, a total of 561 reduced and 803 increased differentially expressed proteins (DEPs), as well as 332 differential expressed metabolites (DEMs) in positive ions and 192 DEMs in negative ions, were identified in the ZJ1 group relative to the N14 group, respectively. The observed features in amino acid profiles and the enrichment of the sucrose-related metabolic pathway provided interesting insights for future endeavors in mulberry variety improvement and the optimization of silkworm diet formulations. Collectively, the low-pruning cultivar ZJ1, characterized by its rapid growth, high leaf productivity, and suitability for mechanized operations, is expected to be an efficient substitute in improving the future sericultural industry, especially in urbanized and industrialized regions.

Keywords: low-pruning cultivation; metabolomics; mulberry; proteomics; sericulture.

Figure 1

Field growth and harvest performance phenotype of different cultivated mulberries. The cultivation of high-pruning mulberry N14 before (A) and after (B) a field harvest. The cultivation of low-pruning mulberry ZJ1 before (C) and after (D) a field harvest. Scale bar = 50 cm.

Figure 2

Comparison of the cocoons produced by silkworms reared on different cultivated mulberry leaves. (A) Phenotypic comparison of the leaves of high-pruning (upper) and low-pruning (bottom) mulberries, respectively. (B) Silkworm cocoons produced by feeding high-pruning mulberry leaves (upper) and low-pruning mulberry leaves (bottom), respectively.

Figure 3

Identification and ontological classification of the differentially expressed proteins in low-pruning mulberry leaves. (A) Volcano plot of differentially expressed proteins, depicting the log2 fold-change (x-axis) versus the −log10 Qvalue (y-axis, representing the probability that the protein is differentially expressed). Qvalue < 0.05 and Foldchange > 1.2 are set as the significant thresholds for differential expression. The red and green dots indicate points of interest that display both large-magnitude fold-changes as well as high statistical significance. Dots in red mean significantly upregulated proteins which passed the screening threshold. Dots in green mean significantly downregulated proteins which passed the screening threshold. And gray dots are non-significantly differentially expressed proteins. (B) Gene ontology analysis of differentially expressed proteins. The x-axis displays the protein count; the y-axis displays the GO term.

Figure 4

Subcellular localization and enriched functional classification of DEPs in low-pruning mulberry leaves based on KEGG pathways. (A) Subcellular localization prediction of DEPs in low-pruning mulberry leaves. (B) Statistics of the top 20 enriched pathways of DEPs in each pairwise comparison.

Figure 5

Metabolomics analysis of low-pruning mulberry leaves and high-pruning mulberry leaves. Volcano plot (A,B), heatmap (C,D), and KEGG enrichment analysis (E,F) showing differently expressed metabolites (DEMs) in low-pruning ZJ1 leaves compared to those in high-pruning N14 leaves. The left line, including panels (A,C,E), shows the DEMs in positive ion mode. On the right panel, including panels (B,D,F), the DEMs in negative ion mode are displayed.

Figure 6

Integrated correlation analyses of proteomics and metabolomics data. (A) Heatmap showing correlation clustering of DEPs and DEMs identified in low-pruning mulberry leaves compared to that in high-pruning mulberry leaves. Each row represents a differential metabolite and each column represents a differential protein, with blue representing a negative correlation and red representing a positive correlation. (B) Splsda analysis of the correlation between differential proteins and differential metabolites in low-pruning mulberry leaves compared to that in high-pruning mulberry leaves. Each dot in the circle represents a protein, and each square represents a metabolite. An acute angle between differential proteins and differential metabolites stands for a positive correlation, while an obtuse angle stands for a negative correlation. The greater the length from the differential metabolites and differential proteins to the center of the circle, the stronger the relationship and vice versa.