
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00787-9
10.1016/j.psj.2024.104208
104208
GENETICS AND MOLECULAR BIOLOGY
Research Note: Metabolomics revealed the causes of the formation of chicken structural blue earlobes
Li Shiru ⁎1
Wang Zhijun ⁎1
Li Shicheng *
Ding Xiangying †
Fang Qiaoyu *
Pan Xinjie *
Gao Guangtang *
Du Xue *
Zhao Ayong zay503@zafu.edu.cn
*2
⁎ Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Department of Animal Science and Technology, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
† Department of Jiangshan Livestock Development Service Center, Jiangshan Agriculture and Rural Bureau, Zhejiang, Quzhou 324100, China
2 Corresponding author: zay503@zafu.edu.cn
1 These authors contributed equally to this work.

10 8 2024
11 2024
10 8 2024
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© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The earlobes of chickens exhibit a range of colors, but there has been relatively little research on the formation of structural blue earlobes. Previous results showed that the structural color earlobes were related to the interplay between melanin and collagen in light reflection. To investigate the metabolic differences in these earlobe colors, we conducted nontargeted liquid chromatograph mass spectrometer (LC-MS) for metabolomic sequencing on structural blue (Green and Blue groups) and nonstructural color (Black group) earlobes tissue of Jiangshan black-bone chickens. The content detection in earlobe tissues of different groups shows that there were significant differences in melanin and collagen content between the Black and Green group. The metabolome identified a total of 6,102 mass spectroscopic peaks and ultimately identified 919 annotated metabolites. Variable importance in the projection (VIP) analysis identified the common differential expressed metabolites (DMs) “Tyr Thr Ala Glu” among the 3 groups. By combining those DMs with differentially expressed genes (DEGs) in our previous transcriptome data from the same sample, and associated with KEGG pathway analysis, multiple pathways related to melanogenesis and collagen metabolism were enriched across the 3 groups. By analyzing the metabolites and genes in these pathways, as well as the interaction network diagram of DEGs, we identified some key genes, Wnt Family Member 6 (WNT6), Transcription Factor 7 (TCF7), Proopiomelanocortin (POMC) and Calcium/Calmodulin Dependent Protein Kinase II Alpha (CAMK2A), and some key DMs like DG (11M3/9M5/0:0) and gentisic acid. The differential gene expression and metabolic levels affect the production of melanin and collagen, leading to differences in the content in melanin and the thickness of the collagen layer between earlobe colors, while the thickness of the collagen layer could affect light scattering, ultimately resulting in different colored earlobes in Jiangshan black-bone chickens.

Key words

Jiangshan black-bone chicken
earlobe color
metabolome
transcriptome
melanin
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pmcINTRODUCTION

Chickens exhibit diverse earlobe colors, which often exhibit significant differences from adjacent feathers. The formation of earlobe coloration is likely influenced by epidermal structure, pigmentation, and vascular distribution. Research has shown that red earlobes arise from vascular color penetration; white earlobes result from purine base deposition under the epidermis; yellow earlobes result from deposition of yellow pigments, such as carotenoids and bilirubin; and black earlobes result from large amounts of melanin or melanocyte deposition (Prum and Torres, 2004).

However, the blue and green colors observed in biological systems are primarily produced through structural coloration, which involves the refraction, diffuse reflection, diffraction, or interference of light waves caused by subtle structures on the surface of organisms (Thayer and Patel, 2023). In the blue skin of fish, amphibians, reptiles, and mammals, for example, studies have found that structural blue color is created by the combination of melanin and collagen, with melanin serving as a background plate that absorbs light waves transmitted by collagen nanostructures (Pillay et al., 2014).

Some breeds of black-bone chickens, such as Jiangshan black-bone chickens and Silk-feathered black-bone chickens, exhibit blue-structured earlobes (Liu et al., 2022). However, there is a dearth of research on the blue earlobes of chickens, particularly about epigenetic and metabolic components. We found that the earlobes of Jiangshan black-bone chickens exhibit 3 color types: dark reddish-purple earlobes (Black group) similar to skin color, dark peacock green earlobes (Blue group) with a bright, slightly bluish hue, and light peacock green earlobes (Green group) with a slightly yellowish tint. The Blue and Green groups are traditionally considered structural blue and are also the common earlobe colors “Peacock Green” of Jiangshan black-bone chickens.

In our previous research, we found that the color of the earlobes of Jiangshan black-bone chickens is produced by the combined action of melanin and collagen, but the total content of melanin and collagen between the earlobes were not determined (Li et al., 2024). The presentation and saturation of structural color are influenced by melanin pigmentation, which has been found to have the ability to absorb visible light and form nanoscale structures (Prum and Torres, 2004). Consequently, we propose that the content, deposition, and metabolism of melanin may also contribute to the differences in the 3 earlobe colors of Jiangshan black-bone chickens.

In this study, we employed nontargeted liquid chromatograph mass spectrometer (LC-MS) metabolomics combined with previously transcriptome to analyze the 3 earlobe color differences in Jiangshan black-bone chicken, hoping to provide new insights into the metabolic level for the formation of structural color earlobe in Jiangshan black-bone chicken.

MATERIALS AND METHODS

Animal Materials and Earlobe Collection

Twelve 360-day-old Jiangshan black-bone chickens were used as experimental subjects, and divided into 3 groups (Black, Blue, and Green) based on earlobe color, with 4 chickens in each group. Earlobe tissue samples were collected from each chicken for subsequent experiments. The euthanasia protocol and tissue collection procedures employed in this study were approved by the Animal Health Committee of Zhejiang Agricultural and Forestry University (Hangzhou, China), under approval number ZAFUAC202401.

Determination of Melanin and Total Collagen Content

Utilize PBS (pH 7.2 - 7.4, 0.01 mol/L) as the homogenizing buffer and grind the earlobe tissue samples at a centrifugation speed of 3,000 rpm for 20 min, maintaining a 10% homogenate-to-tissue ratio. Collect the supernatant and measure melanin and total collagen content using the Chicken Melanin and Col ELISA kit (BSN-C0648B, BSN-C0642B, HangZhoubaseniao Biotechnology, Hangzhou, China) respectively, following the manufacturer's instructions. Perform at least 3 independent replicates and generate a standard curve. Measure the OD value at 450 nm using a Thermo Scientific Fluoroskan (Thermo Fisher, Waltham, MA) and calculate the sample concentration.

All concentration results are presented as mean ± S.E.M. We used independent sample T tests to compare 2 groups and One-way ANOVA to compare 3 groups. The following notation is used to indicate levels of significance: *P < 0.05.

LC-MS Metabolome

The LC-MS/MS analysis of sample was conducted on a UHPLC-Q Exactive HF-X system (Thermo Fisher, Waltham, MA) equipped with an ACQUITY HSS T3 column (Waters, MA, USA) at Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). And LC/MS raw data were preprocessed using Proggenesis QI (Waters Corporation, Milford) and baseline filtering, peak identification, integration, retention time correction, and peak alignment. Metabolite identification was performed using the metabolic public databases HMDB (Human Metabolome Database, http://www.hmdb.ca/), Metlin (https://metlin.scripps.edu/), and Majorbio Database. Use the 80% rule (retain at least 80% of the nonzero variables in a sample set) to remove missing values. Normalize the response intensity of the sample mass spectrum peaks and perform log10 transformation.

Perform data conversion using Pareto conversion and perform partial least squares discriminant analysis (PLS-DA) analysis with a 95% confidence level. The threshold for differential metabolites (DM) was Variable importance in the projection (VIP) >1 and P < 0.05.

KEGG Annotation and Enrichment

The metabolites detected this time and the genes previously sequenced by transcriptome (Li et al., 2024) were functionally annotated using Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg) databases. We performed enrichment analysis using the Python's scipy package (v1.0.0). Pathways with P < 0.05 were considered significantly enriched.

Protein-Protein Interaction Analysis

We analyzed protein-protein interactions (PPI) using String (v11.5) and visualized the results with Cytoscape (v3.10.1) to create a protein-protein interaction network map.

RESULTS AND DISCUSSION

The Content of Melanin and Total Collagen

The total content of melanin and collagen content of 3 types of earlobes were tested and observed significant differences (P < 0.05) between the Black and Green groups, with Black group exhibiting higher levels. No significant differences (P > 0.05) were observed between Blue vs. Black group or Green vs Blue group, although Blue group showed slightly higher levels (Figure 1A, B). Previous study found that the collagen fiber layer in the dermal tissue of the green and blue groups was thicker, indicating that there exist an increasing thickness but reduced collagen fiber production in the peacock green earlobes (Li et al., 2024).Figure 1 The content of melanin and total collagen and differentially metabolites (DM) of Jiangshan black-bone chickens with different earlobe colors. (A) The melanin content of earlobes between groups; (B) The total collagen content of earlobes between groups. Data were presented as means ± SEM. *P < 0.05 as indicated by 1-way ANOVA; (C, E and G) VIP value analysis of Green_vs_Black (C), Blue_vs_Black (E) and Green_vs_Blue (G). The color of the bar indicates the P value of the metabolite. *P < 0.05, **P < 0.01, and ***P < 0.001; (D) PLS-DA shows the classification effect of the model; (F) Venn Diagram shows common and unique DMs between groups. The length of the VIP bar indicates the contribution of the metabolite.

Figure 1

Differential Metabolites and VIP Value Analysis

Nontargeted LC-MS was employed to investigate the differences in metabolite levels between the earlobe tissues of black, blue, and green groups. All raw data were deposited in the CNCB OMIX database (accession number OMIX006456). The PLS-DA analysis showed that the intra-group and inter-group differences met the requirements, and the degree of inter-group separation was relatively high (Figure 1D). We identified a total of 6,102 mass spectrometry peaks and ultimately identified 981 annotated metabolites and 919 metabolites after sum normalization. The DMs between groups were screened under VIP > 1 and P < 0.05 conditions. A total of 251 DMs were differential expressed between groups, among which 3 DMs were common, namely “Tyr Thr Ala Glu”, “Galactoarabinan” (carbohydrates and carbohydrate conjugates of HMDB), and “PE (18:2/0:0)”, and all of them were highest expressed in Black group (Figure 1F). In Green_vs_Black, 22 DMs were up-regulated and 128 were down-regulated; 26 were up-regulated and 148 were down-regulated in Blue_vs._Black; 10 were up-regulated and 10 were down-regulated in Green_vs_Blue.

We screened the top 30 DMs with VIP values and found that “Tyr Thr Ala Glu” (red underlined) was present in Green_vs_Black (Figure 1C), Blue_vs_Black (Figure 1E) and Green_vs_Blue (Figure 1G) with high differential contribution values. Additionally, the VIP value analysis between groups also revealed many common DMs (colored underline), which may affect the formation of different earlobe colors (Figure 1C, E, G). This suggests that “Tyr Thr Ala Glu” is an important metabolite contributing to the differences observed among the 3 earlobe types. “Tyr Thr Ala Glu” is a polypeptide sequence consisting of 4 amino acids: tyrosine (Tyr), threonine (Thr), alanine (Ala), and glutamic acid (Glu). Tyr is a substrate of the enzyme tyrosinase, which is involved in the key steps of melanin synthesis and is a crucial precursor for melanin production (Li et al., 2023). Therefore, the DM “Tyr Thr Ala Glu” is related to melanin metabolism and affects the regulation of melanin synthesis among the 3 earlobe types through signal transduction pathways.

Conjoint Analysis of DM and DEG and PPI Network

KEGG enrichment heatmap analysis reveals the KEGG pathways of all DEG and DM, including 12 pathways related to melanin and collagen production, and 6 of the 12 pathways highlighted in red were significantly enriched in our results (Figure 2A). We conducted PPI analysis on the annotated DEGs involved in these 12 pathways, among which 77 DEGs collectively formed the PPI network, with CXCR5 located at the core (Figure 2B). Among them, collagen related DEGs including Collagen Type IV Alpha 3 Chain (COL4A3), Collagen Type IV Alpha 4 Chain (COL4A4), Collagen Type VI Alpha 1 Chain (COL6A1), Collagen Type VI Alpha 2 Chain (COL6A2), Collagen Type VI Alpha 3 Chain (COL6A3), and Collagen Type IX Alpha 1 Chain (COL9A1), as well as melanin related DEGs such as Pro-opiomelanocortin (POMC), Wnt Family Member 6 (WNT6), Calcium/Calmodulin Dependent Protein Kinase II Alpha (CAMK2A), and Transcription Factor 7 (TCF7), were also present in the PPI network (Figure 2B). This indicates potential differences in gene expression related to melanin and collagen among the 3 earlobe colors in Jiangshan black-bone chickens, and the DEGs in the PPI network are likely the key regulatory genes.Figure 2 Correlation analysis between differentially expressed genes (DEG) and DM. (A) KEGG enrichment heatmap analysis of DM and DEG; (B) PPI analysis of 77 DEGs of the common 12 KEGG pathway of Green_vs_Black, Blue_vs_Black and Green_vs_Blue; (C and D) The bubble plot shows the DMs and DEGs in Green_vs_Black (C) and Blue_vs_Black (D); (E) The regulatory network of melanogenesis in Jiangshan black-bone chicken earlobes.

Figure 2

Ten widely studied common pathways for DEGs and DMs were used to create bubble plots in Green_vs_Black and Blue_vs_Black group as shown in Figure 2C-D. Notably, the “Melanogenesis” pathway was associated with DMs such as DG (11M3/9M5/0:0) and DEGs such as POMC, CAMK2A, and WNT6 (Figure 2C). And the “Tyrosine metabolism” pathway was associated with DMs such as Gentisic acid and DEGs such as Alcohol Dehydrogenase 6 (ADH6) and Phenylethanolamine N-Methyltransferase (PNMT) (Figure 2C). Tyrosine generates dopamine under the action of tyrosinase, and then undergoes a series of steps to ultimately produce melanin (Riley, 1997). This indicates genetic and metabolic differences in melanin production between the peacock green and dark reddish-purple earlobes, providing more reliable evidence than a single omics approach alone. This also suggests the differences in melanin metabolism between the structurally colored and nonstructurally colored earlobes of Jiangshan black-bone chickens. These DMs and DEGs may be key regulatory substances for earlobe color.

Regulatory Network of Melanogenesis in Chicken Earlobes

Melanin is a pigment molecule synthesized within melanosomes, which are specialized organelles found in melanocytes (Figure 2E). Melanin production is controlled by multiple factors. Specifically, ETB-R induces the production of the second messengers Inositol Triphosphate (IP3) and Diacyl Glycerol (DG), leading to melanin synthesis. Frizzled is involved in the Wnt signaling pathway, and MC1R activates the cAMP responsive element binding protein (CREB). The increased expression and phosphorylation-mediated activation of Melanocyte Inducing Transcription Factor (MITF) then stimulates the transcription of key melanogenic enzymes such as tyrosinase (TYR), tyrosinase-related protein 1 (TYRP1), and dopachrome tautomerase (DCT), thereby promoting tyrosine metabolism to produce melanin (Videira et al., 2013; Zhou et al., 2021). However, in addition to being converted into melanin, tyrosine can also participate in other metabolic pathways by synthesizing gentisic acid (Ito and Wakamatsu, 2008).

We have found that DM (DG [11M3/9M5/0:0]) and DEGs (POMC, CAMK2A, WNT6, and TCF7) were involved in the “melanogenesis (map04916)” pathway, and they participated in 3 paths in the “melanogenesis” pathway (Figure 2E). And DM (gentisic acid) was involved in the “tyrosine metabolism (map00350)” pathway (Figure 2E). Among them, DG (11M3/9M5/0:0) participates in the PKC pathway induced by ET-1, and CAMK2A participates in the CAMK pathway induced by ET-1, both of which jointly regulate melamin synthesis. WNT6 and TCF7 jointly participate in the Wnt pathway, while POMC participates in the PKA pathway induced by αMSH, jointly regulating MITF to regulate tyrosine metabolism and ultimately affecting melanin synthesis (Figure 2E). The expression heatmaps of these DM and DEGs were also depicted in Figure 2E. Notably, DG (11M3/9M5/0:0) was most highly expressed in Black group and least highly expressed in green group, while gentisic acid was most highly expressed in Green group and least highly expressed in Black group. Additionally, TCF7 was most highly expressed in Black group and WNT6 was least highly expressed in Black group; CAMK2A was most highly expressed in green group and POMC was least highly expressed in green group (Figure 2E). This means that the difference between peacock green earlobes (green and blue groups) and dark reddish-purple earlobes (black group) was likely mainly regulated by the Wnt pathway of CAMK2A and TCF7 and influenced by the gentisic acid on tyrosine.

DISCLOSURES

There was no conflict of interest during submission of this manuscript for publication.

ACKNOWLEDGMENTS

This research was funded by Zhejiang Province University Student Science and Technology Innovation Activity Plan (New Seedling Talent Plan Subsidy Project, 2024R412B047 ), A Project Supported by Scientific Research Fund of Zhejiang Provincial Education Department (Y202249637 ), Jiangshan Agriculture and Rural Bureau (2023110 ), and Zhejiang A&F University Talent Initiative Project (2023LFR090 ).
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