Multi-omics analysis reveals flavor differences between Queshan and Yunong black pigs

Abstract

Background

Flavor is an important factor influencing consumers' evaluation of pork. However, the molecular regulatory mechanism of flavor differences among different pig breeds remains unclear. In this study, using flavoromics, transcriptomics and lipidomics techniques, the key genes and substances in the longissimus dorsi muscle of Queshan Black Pig (QS) and Yunong Black Pig (YN) were identified and analyzed.

Results

Between the two breeds, 37 differential volatile organic compounds (VOCs), 2,559 differentially expressed genes (DEGs) and 460 differential lipids (DELs) were identified. Flavoromics identified phenol, pyridine and 1-hexanol as potential flavor biomarkers. Transcriptomics indicated that DEGs were mainly enriched in pathways such as fatty acid degradation and AMPK signaling pathway. Moreover, 10 lipids, including PC (26:3) and PE (34:6e), were identified as potential biomarkers. Multi-omics analysis further identified 14 VOCs, 15 DEGs and 10 DELs as being associated with pork flavor. These may regulate lipid production and lipolysis by participating in fatty acid (FA) biosynthesis, FA oxidation and glycerophospholipid metabolism. Finally, this study found that ACAA2 promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells.

Conclusions

These results provide important insights into the flavor differences between QS and YN pork and the underlying molecular regulatory mechanisms. They also offer theoretical references for improving the quality of pork.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-025-12178-5.

Introduction

Pork is one of the most widely consumed meat products globally, and its quality directly affects consumers' preferences and market value. However, meat quality is a complex multidimensional trait that mainly includes organoleptic attributes such as flavor, tenderness, juiciness and color, and is comprehensively affected by a combination of several factors, including genetics, nutrition, living conditions and slaughter treatment [1]. Flavor, which encompasses aroma and taste, is a crucial element in evaluating pork quality and profoundly influences consumers' sensory experience [2]. VOCs mainly include aldehydes, esters, ketones, hydrocarbons, furans, and alcohols, etc. These substances are generated by flavor precursor substances through lipid oxidation, Strecker reaction, Maillard reaction, and thiamine degradation, thereby contributing to the formation of flavor aroma. Flavor precursor substances can be divided into two major categories: water-soluble and lipid-soluble. Among them, the former chiefly comprise amino acids (AAs), reducing sugars, peptides, and thiamine, etc., while lipid-soluble precursor substances mainly include lipids. It has been reported that amino acids and peptides can enhance the flavor of meat, and most amino acids have one or more of the taste qualities such as sweetness, saltiness, bitterness, sourness, or umami [3]. They can generate sulfur-, nitrogen-, and oxygen-containing aromatic compounds through the Maillard reaction, which constitute the main aroma of cooked meat [4]. Cysteine and methionine are also considered the biggest contributors to the development of meat flavor [2]. Lipids, as important lipid-soluble flavor precursor substances, the free fatty acids (FAs) produced by their decomposition can be further converted into specific flavor compounds [5]. Current research generally believes that phospholipids are the key lipids determining the flavor of meat products, and phosphatidylcholine (PC) is the most abundant phospholipid molecule in muscle, being the main cause of flavor changes [6]. In addition, phosphatidylethanolamine (PE) is also crucial for the formation of good flavor during processing [5]. Intramuscular fat (IMF) as an important component of flavor precursors, is mainly composed of lipids and glycerides, with lipids being the main component, accounting for 60% to 70% [7]. Studies have shown that meat flavor comes from the interaction of volatile compounds, and high IMF content can increase the content of volatile compounds [8]. Moreover, gender, age, feeding management, genetics, and slaughtering and processing methods all affect the formation of flavor substances.

In recent years, the rapid advancement of omics technologies, including flavoromics, transcriptomics and lipidomics have provided new perspectives for in-depth exploration of the formation mechanism of pork flavor [9]. Among them, two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF–MS), as a highly sensitive and high-resolution analytical method, can more comprehensively identify VOCs in pork, thereby revealing the chemical basis of flavor differences [10, 11]. For example, Wang et al. [12] employed UHPLC-MS/MS coupled with GC × GC-TOF MS to investigate metabolites, lipids, and volatile flavor compounds of Ning Xiang pigs, Berkshire pigs, and their crossbred (Berkshire × Ning Xiang) pigs. Pork flavor is regulated by multiple genes. The application of RNA-seq can explore the genetic basis of flavor differences in pork more deeply. At the same time, combined with liquid chromatography-mass spectrometry (LC–MS) technology to accurately analyze the composition and changes of lipid compounds in pork, clarify the key role of lipid oxidation in the formation of flavor, and thereby construct a systematic molecular regulatory network of pork flavor [13]. At present, a few studies have indicated that some odor-active compounds can serve as potential flavor markers for characterizing and differentiating various pork varieties. For instance, Lammers et al. discovered that the unique flavors of different pork varieties are related to the content of flavor compounds [14]. Wang et al. [9]explored the flavor characteristics of Jinhua pigs, Lvjiahei pigs, and Duroc × (Landrace × Yorkshire) pigs through flavoromics, targeted lipidomics and transcriptomics, and constructed a 'genes-lipids-VOCs' regulatory network (n = 4). However, the related research on the flavor composition and formation mechanism of local pigs and bred breeds in China has not yet been clarified.

High-quality breeds are an important foundation for the healthy development of the pig industry and a key to enhancing the core competitiveness of the pig industry. The majority of Chinese native breeds have distinct genetic characteristics of excellent meat quality [15]. Among them, QS is well known for its high content of IMF, stable genetic traits, rich flavor and excellent meat quality, and is considered a valuable genetic resource in China's livestock gene banks [16]. Additionally, YN was developed through crossbreeding Duroc pigs with excellent local breeds such as Nanyang Black pig, Laiwu Black pig, and Erhualian pig. It has the outstanding characteristics of high fertility rate and strong feed tolerance. [17, 18], Therefore, it is necessary to systematically compare and understand the differences in meat quality between the QS variety and the YN variety, in order to clarify the molecular mechanism of pork flavor formation, provide a theoretical basis for the comprehensive utilization of local germplasm resources and the selection and breeding of the excellent traits of new pig breeds, and thereby better meet the market demand for high-quality pork.

This study comprehensively employed flavoromics, transcriptomics and lipidomics methods to systematically compare and analyze the differences in flavor characteristics, gene expression and lipid metabolites between local pig breeds (QS) and bred pig breeds (YN). Through multi-omics combined analysis, a molecular regulatory network of pork flavor was initially constructed, and the potential functional association of the ACAA2 gene in the flavor formation-lipid metabolism pathway was revealed for the first time. This research provides new insights on the regulatory mechanism of pork flavor formation and lays the foundation for the breeding and molecular mechanism research of high-quality pork.

Materials and methods

Animals and samples collection

In this study, 10 castrated male pigs each were selected from QS (provided by the Qushan Black Pig Farm in Henan Province) and YN (provided by Henan Yifa Animal Husbandry Co., Ltd.), and they were reared under similar management and feeding conditions, the diet formulations are detailed in table S1. These pigs were allowed to feed and drink water without restrictions. All the test pigs were raised and managed under similar conditions. When their body weight reached 101 ± 5.35 kg, they were blinded by electric shock and then slaughtered. The longissimus dorsi (LD) of pigs was collected from the front end of the third thoracic vertebra in the penultimate section for meat quality determination and sample preservation. Three samples were collected from each pig, with the entire collection process completed within 45 min. Then, four pigs were randomly selected from the two breeds respectively for sequencing analysis. The remaining samples were stored at − 80 °C for subsequent experiments.

Meat quality, FAs and AAs samples analysis

Samples were collected in accordance with the " NY/T 821–2019 Technical Specification for Determination of Pig Muscle Mass." And the meat quality indexes such as water content, crude protein content, IMF, meat color _24 h, marbling score, pH at 24 h post-slaughter (pH_24h) and drip loss (DL) were determined. Biological tests were conducted thrice for each index, and the average value was utilized for subsequent analysis. FAs were determined according gas chromatography (DB37/T 3817–2019) and Free Amino Acidswere determined by Liquid Chromatography (LC) according to Elite-AKK amino acid analysis manual.

Flavoromic analysis

Flavoromics study of the LD was performed to examine the VOCs in QS and YN. Analyses were conducted using a LECO Pegasus® 4D instrument (LECO Corporation, St. Joseph, MI, USA). High-purity helium (> 99.999%) served as the carrier gas, at a steady flow rate of 1.0 mL/min. The detection of flavor compounds was carried out using the LECO Pegasus BT 4D system. The NIST2020 database and the Chroma TOF (1.2.0.6) search software were utilized to annotate the flavor compounds on the original data off the machine. Additionally, PubChem (2022) and Classyfire (2022) were used to annotate and analyze the types of flavor substances, as well as the number and relative content of various flavor substances [19].

Transcriptomic analysis and validation

RNA extraction was conducted using TRIzol reagent (15,596,018, Thermo Fisher Scientific, Waltham, MA, USA) and its integrity was evaluated using a gel imaging system (Bio-Rad, Hercules, CA, USA), and its purity was measured using a Nanodrop NC2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Utilizing an Illumina NovaSeq 6000 (Novogene Bioinformatics Technology Co., Ltd., Beijing, China), the samples underwent paired-end high-throughput sequencing. The reference genome was mapped to the filtered sequencing reads using the upgraded HISAT2 (2.1.0) software, which is an improved version of TopHat2. The DEGs were detected using the DESeq algorithm, with conditions of P-value < 0.05 and Fold Change (FC) > 1.2 or FC < 0.83.

Reverse transcription was performed using the Evo M-MLV RT Kit (AG11705, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Next, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted on the CFX96™ Real-Time System (Thermo Fisher Scientific, Waltham, MA, USA) using SYBR Green Premix Pro Taq HS qPCR Kit (AG11701, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Each reaction was conducted in triplicate, with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) serving as the normalization controls. The relative levels of gene expression were determined using the 2^−ΔΔCt method.

Untargeted lipidomic analysis

Untargeted lipidomics analysis was performed on LD of QS and YN to examine lipid composition. After lipids were extracted, an ACQUITY UPLC® BEH C18 (2.1 mm × 100 mm, 1.7 m, Waters Corporation, Milford, MA, USA) column kept at 50℃ was utilized for the chromatographic separation. The temperature inside the capillaries was 325℃. The normalized collision energy was 30 eV, and dynamic exclusion was employed to remove extraneous data from the MS/MS spectra.

Comprehensive analysis of flavoromics, transcriptomics and lipidomics

To deeply explore the influence of VOCs, DEGs and DELs on the flavor of pork, this study conducted Pearson correlation analysis on the flavoromics, transcriptomics and lipidomics data through the website of OmicShare tools (https://www.omicshare.com/). In pairwise comparisons and joint analysis among the omics, the strong correlations among VOCs, DEGs nd DELs were identified by the standard of P < 0.05 and |r|> 0.8, thereby screening out the key VOCs, genes and lipids that affect the flavor of pork. In addition, the interaction relationships among them were visualized by constructing network diagrams.

Isolation, culture and transfection of porcine intramuscular preadipocytes

Porcine intramuscular preadipocytes were isolated according to previously described methods [20], which were cultured using complete medium containing 89% DMEM (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China), 10% FBS (Gibco, Carlsbad, CA, USA), and 1% penicillin–streptomycin solution (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China) at 37℃ with 5% CO₂. The cells were transfected after the cell density reached 70–80% after being inoculated into a 6-well cell culture plate. They were then cultured at 37℃ with 5% CO₂, with medium change interval of 2 d.

Plasmid construction

The coding region of porcine ACAA2 was amplified by PCR and subcloned into pcDNA3.1-EGFP as the vector to construct an overexpression plasmid (p-ACAA2). Subsequently, on the 6th day of cell differentiation, according to the manufacturer's instructions, p-ACAA2 was transfected into the cells using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA), and the cells were collected on the 8th day for subsequent verification.

Oil Red O Staining

The cells in the 6-well plate were stained according to the Oil Red O kit procedure (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China) at the day 8 of cell differentiation. The lipid droplets were visualized under inverted fluorescence microscope (Leica Microsystems, Wetzlar, Germany). Subsequently, 100% isopropanol was used for extraction for 10 min, and the absorbance at 450 nm was measured using an enzyme reader.

Statistical analysis

For both statistical analysis and data visualization, the OmicShare tools (https://www.omicshare.com/tools) and BioDeep Platform (https://www.biodeep.cn) were utilized. The DELs and differential VOCs were identified based on criteria of P < 0.05, VIP > 1. Data in this study were expressed as mean ± standard deviation (SD). Statistical analyses were conducted utilizing SPSS 26.0, employing independent sample T-test. When P < 0.05, statistical significance was determined. Significance levels were indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001.

Results

Comparison and analysis of muscle quality between QS and YN

To study the muscle quality of the two breeds, the meat quality related indexes were measured. The results indicated that the water content of QS was significantly lower than that of YN (P < 0.05). At the same time, the pH_24h and meat color_24h in QS were higher, and the DL was lower. IMF content and marbling score were significantly higher than YN (P < 0.01, Table 1).

Table 1.

Comparison of muscle quality between QS and YN

Items	QS	YN
Moisture (%)	72.4 ± 1.41*	73.53 ± 0.37
Protein (%)	22.10 ± 1.62*	20.44 ± 0.94
IMF (%)	4.52 ± 0.98**	3.33 ± 0.21
pH24h	5.83 ± 0.14	5.71 ± 0.18
DL (%)	1.24 ± 0.21	1.36 ± 0.41
Meat color24h	3.25 ± 0.50	3.19 ± 0.43
Marbling score	4.50 ± 1.03***	2.50 ± 0.35

Data are expressed as mean ± SD

FAs and AAs composition and content in QS and YN

In order to study the changes of FAs and AAs between QS and YN, a total of 15 FAs and 16 AAs were detected by GC and LC (Table S2 and 3). Overall, the content of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were significantly higher than those in YN (P < 0.05), and the contents of essential AAs, umami AAs and 5 AAs (isoleucine, lysine, histidine etc.) in YN were significantly higher than those in QS (P < 0.05), while there was no significant difference in bitter AAs and other AAs between QS and YN (P > 0.05, Fig. 1A and B). The contents of linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher compared to YN (P < 0.05). However, no significant difference was identified for palmitoleic acid (P > 0.05, Fig. 1C).

Fig.1.

FAs and AAs composition and contents in QS and YN. A FAs contents in LD muscles of QS and YN; B AAs contents in LD muscles of QS and YN; C Different classifications of AAs and their relative contents

Differential VOCs identification and functional analysis

In this study, the VOCs were detected by GC × GC TOF–MS, and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) results showed that there was dispersion between the principal components of QS and YN (Fig. 2A). And, 1,320 VOCs were identified in QS and 1,173 in YN. Among the 37 significant VOC compounds, 16 increased and 21 decreased in QS compared to YN (Fig. 2B).

Fig.2.

Differential VOCs identification and KEGG enrichment analysis. A OPLS-DA analysis of the two groups of samples; B The number of the VOCs were significantly different between QS and YN; C Significantly differential VOCs were explored through KEGG pathway enrichment analysis; D Correlation analysis of FAs and differential VOCs

The kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis was performed on differential VOCs, mainly including protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism etc. The differential VOCs involved in enriching metabolic pathways mainly include phenol, propanal, ethylbenzene and 1-Hexanol (Fig. 2C, Table S4). The relative odor activity value (ROAV) of VOCs were shown in the table S5. The results revealed a total of 137 VOCs with ROAV, and 8 VOCs with ROAV ≥ 1 were found in QS and YN. Among them, 2,3-butanedione has the highest ROAV in QS, and 2-Nonenal, (E)—has the highest ROAV in YN. However, only 2-Octenal, (E) -is a differential VOCs and can be considered as the key volatile compound. Besides, the correlation analysis of FAs and differential VOCs was performed, and the results showed that 15 FAs were identified that may lead to the difference in flavor between the two pig breeds through the regulation of differential VOC formation (P < 0.05, |r|> 0.8, Fig. 2D).

DEGs identification and functional enrichment analysis

Transcriptomic analysis was performed on longissimus muscle samples from QS and YN to investigate the differences in gene expression between the two breeds. Distinct differences in the principal components between the two breeds were indicated by the partial least squares-discriminant analysis (PLS-DA) results. Specifically, PC1 explained 30.1% of the variance, while PC2 accounted for 19.8% of the variance (Fig. 3A). In addition, compared with YN, there were 1,446 up-regulated and 1,113 down-regulated DEGs in QS (Fig. 3B).

Fig. 3.

DEGs identification and functional enrichment analysis. A PLS-DA analysis of the two pig breeds; B Volcano plot of all measured genes; C—D GO analysis for up-regulated and down-regulated DEGs; E—F KEGG enrichment analysis for up-regulated and down-regulated DEGs; G PPI analysis of the DEGs; H The interaction network of pathway and DEGs

Gene ontology (GO) analysis indicated that DEGs were significantly enriched in regulation of macromolecular metabolic process, regulation of primary metabolic process, cellular macromolecular metabolic process, and small molecule metabolic process (P < 0.05, Fig. 3C and D). According to the results of the KEGG enrichment study, DEGs were mostly engaged in IL-17 signaling pathway, fatty acid degradation, fatty acid elongation and AMPK signaling pathway (P < 0.05, Fig. 3E and F, Table S6 and 7). To further explore the critical factors that play a critical role, protein and protein interactions (PPI) were used. The analysis of DEGs interactions suggested a strong correlation and significant connection between hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta (HADHB), ACAA2 and peroxisome proliferator activated receptor gamma (PPARG) etc., and these DEGs were involved in AMPK signaling pathway, IL-17 signaling pathway and fatty acid metabolism etc. (Fig. 3G). Besides, some genes in the pathways were involved in multiple pathways, such as carnitine palmitoyltransferase 1B (CPT1B), hydroxyacyl-CoA dehydrogenase (HADH), hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha (HADHA), HADHB and ACAA2 (Fig. 3H).

Validation of transcriptomic data by qRT-PCR

Furthermore, to ensure the reliability of transcriptomic sequencing, six DEGs were selected for qRT-PCR validation. The results showed that the expression trends of qRT-PCR and RNA-seq were consistent, further confirming the reliability of the sequencing results (Fig. 4).

Fig.4.

Validation of transcriptomic data by qRT-PCR. A The expression levels of DEGs from RNA-Seq data of QS and YN. B The relative mRNA expression levels of DEGs were detected by qRT-qPCR and expressed as means ± SD. * means P < 0.05, ** means P < 0.01

Analysis of DELs related to pork flavor

LC–MS detected 2,210 lipids and 2,209 lipids in QS and YN, which were divided into 51 categories. These lipids included 501 triglycerides (TG), 378 phosphatidylcholine (PC) and 212 phosphatidylethanolamine (PE), as well as 116 and 117 diglyceride (DG) in QS and YN (Table S8). According to the OPLS-DA, there were marked differences between the QS and YN groups, making it easy to distinguish between them (Fig. 5A). Compared with YN, QS had 208 lipids up-regulated, mostly TG and PC (36 and 51 respectively), while 252 lipids were down-regulated, including 50 PE, 39 PC and 48 TG (Fig. 5B and C).

Fig.5.

Analysis of DELs related to pork flavor. A OPLS-DA analysis of the two groups of samples; B The number of DELs in QS and YN; C Cluster analysis of DELs in QS and YN; D Relative lipid content (% total lipids) in QS and YN; E Cluster analysis of top ten DELs (VIP)

TG, DG and PC are the three main components of lipids in pork, which are directly related to the meat flavor. Among the DELs detected in this study, there were 90 PC, 84 TG, 61 PE and 31 DG (Table S9). In this study, the relative contents of PC, Sphingomyelin (SM), monohexose ceramide (Hex1Cer), and monogalactosyl glyceride (MGDG) in QS were significantly higher than those in YN, while the contents of TG, PE, and Bis-methylphosphatidic acid (BisMePA) were significantly lower than those in YN (P < 0.05, Fig. 5D). Pearson correlation analysis was performed on the DELs, found that there were 289 DELs showing a significant positive correlation and 234 DELs showing a significant negative correlation (Table S10). This may mean that the accumulation of DELs promotes the further accumulation of lipids. Besides, the top 10 lipids of VIP were mostly phospholipids and sphingolipids, and the expression level was high in QS (Fig. 5E).

Correlation analysis among the DEGs, DELs and differential VOCs

In an effort to further explore the regulation mechanism of pork flavor, the correlation analysis of DEGs and DELs, DELs and differential VOCs, DEGs and differential VOCs were performed. The joint analysis results revealed significant positive or negative correlations among 16 DEGs and 10 DELs (Fig. 6A), 10 DELs and 16 differential VOCs (Fig. 6B), 20 DEGs and 18 differential VOCs (Fig. 6C). Furthermore, the multi-omics joint analysis results showed that there was a correlation among 15 DEGs, 10 DELs and 14 differential VOCs (Fig. 6D), which might affect the pork flavor.

Fig.6.

Correlation analysis of DEGs. DELs and differential VOCs. A Correlation analysis of DEGs and DELs; B Correlation analysis of DELs and differential VOCs; C Correlation analysis of DEGs and differential VOCs; D The results of multi-omics joint analysis

Key pathways and interactions regulating pork flavor

To further explore the interaction between the above genes and lipids, the associated metabolic pathways were studied. The results showed that FAs could enter the cell through CD36, and the fatty acyl-CoA produced by FAs could interact with glycerol-3-phosphate (G3P), participate in glycerolipid metabolism and glycerophospholipid metabolism, and generate TG. TG can be decomposed to produce FAs, and enter mitochondrion through CPT1B, and ultimately participate in FA oxidation. Besides, CPT1B, CPT2, ACADS, ACAA2, HADH/HADHA in the DEGs work together to regulate the glycerophospholipid metabolism process, affecting the supply of downstream lipid synthesis substrates (such as Acetyl-CoA, Malonyl-CoA), and thereby indirectly regulating the synthesis and homeostasis of TG, phospholipids (such as PC, PE, PI, PS, PG), and SM. The adrenoceptor alpha 1 A (ADRA1A) can inhibit the expression of SREBP1c through AMPK, and then promote the expression of FAS, thereby regulating FA biosynthesis (Fig. 7).

Fig.7.

The mutual regulation network of key genes and lipids

Effects of ACAA2 on differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells

Through the above multi-omics combined analysis, it was found that ACAA2 is a key gene involved in the lipid metabolism pathway. It is involved in fatty acid degradation, fatty acid elongation, and the AMPK signaling pathway, etc. To further explore the role of ACAA2 in lipogenesis, this study transfected the overexpression plasmid of ACAA2 to investigate its regulatory effect on adipocytes. The results showed that after overexpression of ACAA2, its expression levels were significantly up-regulated in porcine intramuscular preadipocytes and 3T3-L1 cells (P < 0.01, Fig. 8A). Additionally, the expression levels of differentiation marker genes, including CCAAT enhancer binding protein alpha (CEBPA), PPARG, fatty acid binding protein 4 (FABP4), and Perilipin 1 (PLIN1) were significantly increased after ACAA2 overexpression in both cell types (P < 0.05, Fig. 8B). Oil Red O staining results demonstrated a significant increase in lipid droplet deposition after overexpression of ACAA2 (P < 0.01, Fig. 8C and D). These results indicated that overexpression of ACAA2 significantly promote the differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells.

Fig.8.

Effects of ACAA2 on differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells. A Detection of ACAA2 overexpression efficiency 8 days after differentiation; B The effect of overexpression of ACAA2 on differentiation marker genes in porcine intramuscular preadipocytes and 3T3-L1 cells; C-D Oil Red O staining on porcine intramuscular preadipocytes and 3T3-L1 cells after 8 days of differentiation

Discussion

Pork plays an important role in the global meat industry due to its unique flavor and high-quality protein supply capacity. Driven by the surge in global pork demand, high-quality pork has become the focus of competition in the modern pig industry. Among them, flavor is a prerequisite for determining the quality of meat. [21]. China has abundant local breeding resources and these local pig breeds tend to excellent characteristics, such as the QS black pig, are known for their fine meat texture, superior flavor and high IMF. Our team bred a new breed, YN black pig, through crossbreeding to meet the growth rate and meat quality [16]. In this study, the two breeds were analyzed with multi-omics analyses to reveal the complex molecular mechanisms that regulate the differences in pork flavor between the different pig breeds.

The degradation of lipids is a major factor in the formation of meat flavor, lipid hydrolysis produces flavor precursors such as free FAs, which are subsequently oxidized to yield VOCs [22]. As an important chemical substance that constitutes fat, FAs can not only provide the necessary nutrients for the human body, but also act as flavor precursors to affect the overall flavor of the muscle [23]. The content and composition of FAs in meat are affected by the breed type [24]. This study found QS has more palmitoleic acid than YN. Kimata et al. studied the correlation between muscle FAs composition and pork edible quality, and found that SFAs and MUFAs were positively correlated with pork tenderness, juiciness and flavor. In particular, palmitoleic acid content was highly positively correlated with meat flavor [25]. Linoleic acid, linolenic acid and arachidonic acid are essential FAs within PUFAs, and linoleic acid is one of the essential FAs that cannot be synthesized in humans and animals. Several studies have confirmed that conjugated linoleic acid can enhance the transformation of mesenchymal cells into preadipocytes, increase IMF content and improve meat quality [26]. cis-4,7,10,13,16,19-Docosahexaenoic acid can assist brain thinning [27]. This study found the contents of PUFAs and linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher. And PUFAs cannot be produced in humans and must be obtained through dietary consumption and are therefore considered essential for the body. In general, the content of PUFAs in QS was higher than that in YN.

Besides, AAs are key compounds for growth, immunity and regulation of metabolic pathways [24]. It is reported that AAs can enhance the meat flavor, including sour, sweet, bitter, salty, and umami [3, 4]. Serine largely determines the meat flavor [28], and threonine can improve the meat quality [29]. In the production of mutton, arginine may be utilized to enhance meat quality and protein deposition [30]. In this study, the contents of total amino acids, sweet amino acids, serine, threonine and arginine in QS were significantly higher than those in YN.

Flavor, as the dominant factor, significantly influences both meat quality and consumer purchasing decisions. However, only a few of the major VOCs in food have ROAV that indeed contributes to the overall aroma. Therefore, it is important to figure out which VOCs play an important role in food flavor. Proteins can affect IMF deposition. OTX2 protein is a transcription factor containing a homologous domain and may be involved in the regulation of adipose tissue function [31, 32]. Propionate can be converted into lipids by lipogenesis and induce the expression of lipogenic genes. It can also stimulate lipid accumulation in 3T3-L1 adipocytes [33, 34]. Thus, genes may regulate the production of phenol, propanal, ethylbenzene and 1-Hexanol by affecting pathways like protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism.

Therefore, in order to further explore the genetic basis leading to the difference of pork flavor in different breeds, this study also carried out transcriptome analysis. The AMPK signaling pathway is a critical pathway for lipid metabolism. This pathway's activation enhances fatty acid oxidation and simultaneously inhibits lipid production in adipocytes [35]. IL-17 can regulate adipogenesis and adipocyte metabolism [36]. Fat deposition is governed by the synthesis of FAs as well as the uptake of exogenous FAs [37]. CPT1B is a rate-limiting enzyme that inhibits the β-oxidation of long-chain fatty acids within the mitochondria of muscle cells. In bovine fetal fibroblasts, elevated expression of CPT1B notably increases triglyceride levels [38]. The last step of the fatty acid β-oxidation cycle is catalyzed by HADHB, which facilitates the reaction of β-ketoacyl-CoA with a molecule of free coenzyme A, cleaving the carboxyl-terminal two-carbon fragment from the original fatty acid to form acetyl-CoA [39]. ACAA2 encoded protein catalyzed the last step of mitochondrial fatty acid β-oxidation spiral, ensuring a continuous supply of acetyl-CoA in the mitochondrial matrix. When cellular energy is abundant and lipid synthesis signals are active (such as elevated insulin levels), these acetyl-CoA can be used to synthesize citrate. After shuttling to the cytoplasm, citrate is cleaved back into acetyl-CoA by ACLY and serves as a substrate for fatty acid synthase (FASN), thereby promoting fat generation and lipid droplet accumulation. [40, 41]. Adipocytes differentiation is tightly regulated by various transcription factors including PPARG and CCAAT/Enhancer Binding Protein – α (C/EBP-α) [42]. PPARG regulates the expression of numerous key adipocyte genes, these genes are engaing in coordinating fatty acid uptake, metabolism, and storage [43]. Genes are located in the upstream of regulating metabolic processes, so their expression patterns can lead to differences in VOCs. These genes are closely linked to adipocyte differentiation, fatty acids synthesis, and lipid metabolism, etc. Consequently, they may be the key factors for the difference in pork flavor between the two breeds.

Lipids are vital in the formation of unique meat flavor through lipid degradation and fatty acid oxidation [2]. Current research generally believes that phospholipids are the key lipids determining meat flavor, and the volatile compounds generated from their thermal decomposition and oxidation reactions are important sources of the unique flavor of meat products [7]. PCs is the most abundant phospholipid molecule in muscle and is the main cause of flavor variation [6, 44]. The different lipids have distinct physiological effects on the human body. For instance, sphingolipids (SPs) have the ability to inhibit some cancers [5]. In this study, QS was found to have a significantly higher level of PC than YN. Besides, SM, Hex1Cer, MGDG, TG, PE and BisMePA were significantly different in QS and YN, so this study speculated that the FAs that affect the different flavors of the two pork were mainly produced by these lipids.

The formation factors of pork flavor are complex and diverse. A single omics approach is no longer sufficient to explain the complex characteristics and interrelationships of flavor formation. Therefore, in order to explore the molecular regulatory mechanisms that cause the flavor differences between these two types of pork, this study conducted a combined analysis of flavoromics, transcriptomics and lipidomics. By integrating multiple omics, a comprehensive interpretation of the flavor was achieved. Association analysis between flavoromics and lipidomics, SM (t40:5) was found to be significantly positively correlated with pyridine. Surprisingly, ACAA2 exhibited a significant negative correlation with both SM (t40:5) and pyridine. And there was also a significant negative correlation between ACAA2 and pyridine. Acetyl-CoA acyltransferase 1 (ACAA1), acyl-CoA dehydrogenase short chain (ACADS) and CPT1B etc. have a directly positive or negative relationship with other DELs and differential VOCs. Therefore, PC (26:3), PC (18:1e_6:0) and PC (29:3) etc. may be the upstream metabolites of pyridine, phenol and 1-Hexanol etc., which can affect the formation of pork-specific flavor. Thus, they may cooperate to regulate meat flavor. It is inferred that these genes and lipids may regulate the FA biosynthesis, FA oxidation, glycerolipid metabolism and glycerophospholipid metabolism, by investigating the metabolic pathways associated with them, thereby regulating lipid production and decomposition. And, these genes were significantly positively correlated with TG and DG contents. Furthermore, they also showed a positive correlation with particular VOCs. Thus, it is speculated that the overexpression of these critical genes may promote the synthesis of TG, thereby facilitating the degradation of TG into glycerol and FAs. And this may accelerate the oxidation of FAs into VOCs.

The IMF is essential to the development of pork flavor. Research has shown that the unsaturated fatty acids in IMF, especially the PUFA, are prone to thermal degradation and oxidation reactions, generating volatile compounds such as aldehydes and ketones. These substances are the key factors that give pork its unique aroma. Moreover, the lipid oxidation products can also react with other molecules, further influencing the flavor characteristics [45]. The deposition of IMF is closely related to lipid metabolism. In-depth study of the lipid metabolism process is helpful in revealing the molecular mechanism of flavor formation. Through joint analysis and literature mining, we found that ACAA2 is important candidate genes that may affect meat quality differences. ACAA2 is a critical gene involved in the lipid metabolism pathway, positively linked with the content of IMF, and is regarded as an important regulatory factor determining the accumulation of IMF [46]. Studies have shown that ACAA2 can promote the differentiation of preadipocytes. For example, miR-193a-5p inhibits the differentiation of 3T3-L1 preadipocytes by targeting the expression of ACAA2 gene [47]. This study further verified that ACAA2 can promote lipid deposition in porcine intramuscular preadipocytes and 3T3-L1 cells. The findings suggest that ACAA2 may indirectly affect the generation of flavor substances by regulating lipid accumulation. It is an important regulatory factor connecting lipid metabolism and flavor formation, offering a potential target for further improving pork quality. Future studies will construct an ACAA2 knockdown cell model in vitro to further explore its regulatory function.

Conclusion

In general, this study compared the differences in pork flavor between the two pig breeds based on the methods of flavoromics, transcriptomics and lipidomics. The results indicated that the contents of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were higher than those in YN. In addition, 14 VOCs (pyridine, 1- hexanol, phenol, etc.), 15 DEGs (ACAA2, HADHB, CPT1B, etc.) and10 DELs (PC (18:1e_6:0), PC (26:3), PE (34:6e), etc.) may play important roles in pork flavor. In addition, the analysis revealed that these genes may be involved in FA biosynthesis, FA oxidation, and glycerophospholipid metabolism by regulating lipid production and lipid breakdown. Finally, this study found that ACAA2 promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells. These findings provide a theoretical basis for exploring the molecular regulatory mechanisms of multi-omics in influencing the flavor of pork.

Abbreviations

VOCs

Volatile organic compounds

DEGs

Differential expressed genes

DELs

Differential lipids

FAs

Fatty acids

IMF

Intramuscular fat

SFAs

Saturated fatty acids

MUFAs

Monounsaturated fatty acids

PUFAs

Polyunsaturated fatty acids

ACAA2

Acetyl-CoA acyltransferase 2

LD

Longissimus dorsi

AAs

Amino acids

pH24h

PH at 24 h post-slaughter

DL

Drip loss

FC

Fold Change

qRT-PCR

Quantitative real-time polymerase chain reaction

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

SD

Standard deviation

KEGG

Kyoto Encyclopedia of Genes and Genomes

ROAV

Relative odor activity value

GO

Gene Ontology

PPI

Protein-protein interactions

PPARG

Peroxisome proliferator activated receptor gamma

CPT1B

Carnitine palmitoyltransferase 1B

HADH

Hydroxyacyl-CoA dehydrogenase

HADHA

Hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha

TG

Triglyceride

PC

Phosphatidylcholine

PE

Phosphatidylethanolamine

DG

Diglyceride

SM

Sphingomyelin

BisMePA

Bis-methylphosphatidic acid

Hex1Cer

Monohexosyl ceramide

MGDG

Monogalactosyl glyceride

G3P

Glycerol-3-phosphate

ADRA1A

Adrenoceptor alpha 1A

CEBPA

CCAAT enhancer binding protein alpha

FABP4

Fatty acid binding protein 4

PLIN1

Perilipin 1

C/EBP-α

CCAAT/Enhancer Binding Protein – α

ACAA1

Acetyl-CoA acyltransferase 1

ACADS

Acyl-CoA dehydrogenase short chain

Authors’ contributions

WBJ: Visualization, Validation, Formal analysis, Writing – original draft, Methodology. WYL: Visualization, Validation, Writing – original draft, Formal analysis. WC: Validation, Formal analysis. CLB Validation. WTF: Investigation. LXJ: Resources. YT: Software. BJ: Formal analysis.YLW: Validation. Wei Wang: Supervision. QRM: Supervision. Feng Yang: Supervision. LXL &HXL: Writing – review & editing, Resources, Data Curation, Supervision, Investigation, Project administration, Funding acquisition.All authors reviewed the manuscript.

Funding

This research was financed and supported by the Pig Industry Technology System Innovation Team Project of Henan Province (HARS-22–12-G4), the 14th Five-Year National Key R&D Program of China (2021YFD1301202), the Agricultural Breeds Research Project of Henan Province (2022020101) and Special Project for the Industrial Development of Key Scientific Research Initiatives in Colleges and Universities of Henan Province (25CY014).

Data availability

The RNA-seq data of this study has been deposited in the National Center for Biotechnology Information (NCBI), with the accession number PRJNA1310286 (https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1310286).

Declarations

Ethics approval and consent to participate

This study was performed in compliance with the protocols for the care and use of experimental animals established by the People’s Republic of China’s Ministry of Science and Technology (Approval Number: DWLL20211193). And this experiment was approved by the Ethics Committee of Henan Agricultural University. In addition, all test methods were conducted in compliance with applicable regulations and adhered to the ARRIVE guidelines governing animal research. All animal experiments involved in this study were conducted with the informed consent of the owners.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.