Next Article in Journal
High Prevalence and Genetic Variability of Hepatozoon canis in Grey Wolf (Canis lupus L. 1758) Population in Serbia
Previous Article in Journal
Roles of Ghrelin and Leptin in Body Mass Regulation under Food Restriction Based on the AMPK Pathway in the Red-Backed Vole, Eothenomys miletus, from Kunming and Dali Regions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Animals
Volume 12
Issue 23
10.3390/ani12233334
animals-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Dietary Quinoa Seeds on Cecal Microorganisms and Muscle Fatty Acids of Female Luhua Chickens

by
Tao Wu
1,
Xiaofan Jiang
1,
Farong Yang
2,
Yuming Wei
2,
Shengguo Zhao
1 and
Ting Jiao
3,*
1
College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
2
Animal Husbandry Pasture and Green Agriculture Institute of Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
3
College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Animals 2022, 12(23), 3334; https://doi.org/10.3390/ani12233334
Submission received: 3 October 2022 / Revised: 20 November 2022 / Accepted: 25 November 2022 / Published: 28 November 2022
(This article belongs to the Section Animal Nutrition)
Browse Figures
Versions Notes

Abstract

:

Simple Summary

Providing high-quality feed for animals to improve the quality of animal products and, therefore, meet the needs of the public is a focus of animal husbandry. As a high-altitude crop, quinoa has high and abundant nutritional value. In recent years, with the planting area increasing year by year in our country, feed development and utilization of quinoa seeds and by-products have increased. At present, few studies gave examined the optimal addition of quinoa seeds in livestock and poultry diets and, in particular, the effects of the dietary addition of quinoa seeds on the intestinal microorganisms and muscle fatty acids of Luhua chickens. Therefore, in this study, different proportions of quinoa seeds (raw grain) were added in the diets of Luhua chickens to analyze their effects on intestinal microbiota and muscle fatty acids. The results showed that the content of muscle docosahexaenoic acids (C22:6n3, DHA), unsaturated fatty acids (UFAs) and n-3 polyunsaturated fatty acids (n-3 PUFAs) was significantly increased by adding a certain proportion of quinoa seeds to the diet. The content of saturated fatty acids (SAFs) and the ratio of n-6/n-3 significantly decreased. The increase can effectively improve the cecal microbiota structure, regulate the intestinal environment and promote the body health of Luhua chickens. These data provide a theoretical basis for the scientific application of quinoa seeds in female Luhua chickens’ feeding and fodder development.

Abstract

To study the effects of adding quinoa seed (raw grain) to the diet of the Luhua chicken on the cecal microorganism abundance and fatty acid composition of muscle, 120 49-day-old healthy female dewormed Luhua chickens (body weight 1476.21 ± 101.39 g) were randomly divided into 4 groups, with 3 replicates in each group and 10 chickens in each repetition. The control group (CK group) was fed a basal diet and the experimental groups were fed with 4% (Q4), 8% (Q8), and 12% (Q12) quinoa seed (raw grain) added to the basal diet for 75 days. After 121 days of age, the animals were slaughtered and the 16S rRNA characteristics of cecal flora, as well as composition and content of fatty acids in muscle, were determined and analyzed. The content of unsaturated fatty acids (UFAs), docosahexaenoic acid (C22:6n3; DHA) and n-3 polyunsaturated fatty acids (n-3 PUFAs) in the breast and leg muscles significantly increased in the experimental groups supplemented with quinoa seeds (p < 0.05). However, the content of saturated fatty acids (SAFs) and ratio of n-6/n-3 in breast muscle and leg muscle significantly decreased (p < 0.05). In addition, adding a certain percentage of quinoa seeds in the diet can also affect the community composition and content of microorganisms in the ceca of Luhua chickens. At the phylum level, the Proteobacteria, Actinobacteria, Synergistetes and Melainabacteria in experimental groups (Q4, Q8 and Q12) were significantly lower than those in the CK group (p < 0.05). At the genus level, Desulfovibrio, Synergistes, Olsenella, Parabacteroides, Mailhella, Sutterella and Ruminiclostridiu in group Q4 were significantly lower than those in group CK (p < 0.05) while Faecalibacterium in Q8 group, and Lawsonia and Faecalibacterium in Q12 group were significantly higher than those in the CK group (p < 0.05). Enrichment analysis of the microbial function showed that compared with the CK group, Metabolism and Enzyme Families were significantly enriched in the Q4 group (p < 0.05). Cellular Processes and Signaling were significantly enriched in the Q8 group (p < 0.05). The association analysis of fatty acids with microorganisms showed that the abundance of Faecalibacterium, Lawsonia and Meagmonas was significantly correlated with partial SFAs and UFAs (p < 0.05). In conclusion, adding quinoa seeds to diets significantly increased the content of muscle DHA, UFAs and n-3 PUFAs. The content of SAFs and the n-6/n-3 ratio were significantly reduced. Taken together, quinoa can effectively improve the cecal microbiota structure, inhibit the number of harmful bacteria and increase the number of beneficial bacteria, regulating the intestinal environment and promoting the body health of female Luhua chickens.

1. Introduction

Chenopodium quinoa is an annual dicotyledonous herb of the genus Chenopodiaceae, which originated in the Andes Mountains of South America and has been cultivated for more than 5000 years. Compared with other crops, quinoa has strong adaptability and can grow in high altitude, dry and cold areas [1]. Because quinoa seeds are rich in protein, minerals, vitamins, amino acids and other nutrients [2,3,4], including essential amino acids, the National Aeronautics and Space Administration (NASA) regards quinoa seeds as the ideal “space food” [5,6]. Saponins in quinoa have antibacterial, antioxidant, immunomodulatory, anti-tumor and other pharmacological regulatory effects [7]; and its straw, seed and bran all have great feeding potential [8,9]. Quinoa seeds can provide minerals, protein and vitamins for livestock, and improve the proportion of amino acids in feed. Byproducts, such as quinoa straw, bran and chaff, show comparable feeding value to other superior forage materials in feeding livestock [8,9]. The nutritional value of the quinoa whole plant and its straw is comparable to that of corn, alfalfa and sweet sorghum, with high digestibility [8]. The lignin content of quinoa straw is lower than that of corn straw, but is suitable for the production of roughage for ruminants such as cattle and sheep [8]. Currently, quinoa research is focused onbreeding, cultivation and primary processing. There are few studies on the utilization of quinoa seeds and their byproducts.
Currently, intestinal microorganisms are receiving increasing attention due to their vital role in intestinal development and metabolic homeostasis [10]. Studies have found that mammalian gut microbiota is closely related and potentially important to food digestion, vitamin and amino acid synthesis [11], organ development [12,13], host physiological regulation [14], immune system regulation, and growth and neural development [15,16]. Some studies have found that adding a certain amount of washed and cooked quinoa seeds in the diet has no significant effect on the performance of chickens [17]. As the most important intestinal segment in the distal part of the chicken gut, the ceca of chicken is a complex ecosystem with the highest concentration of microorganisms and highly diversified microbiota in adult chickens, which has an important impact on the growth and development of chickens [18,19,20]. The digestion and absorption of nutrients in cecum are closely related to its microorganisms [21]. Ceca resection could significantly reduce the digestibility and metabolism of nutrients in poultry [22]. The analysis of ceca microbiota was a key field in poultry nutrition research, which was helpful to understand its diversity and interaction with the host [23]. Microorganisms in the ceca could transform fiber components into digestible components through fermentation, thus promoting animal growth. Thus, it is necessary to study the intestinal microbial diversity of the Luhua chicken. Intramuscular fat deposition was mainly affected by animal age, sex, breed, and nutrition level. In recent years, more and more studies have confirmed that intestinal flora could also regulate intramuscular fat deposition in animals [24,25]. One study found that intestinal microbes could regulate fat metabolism and affect the level of fat deposition in blood and tissues [26,27,28,29]. Intramuscular fat deposition in animals is also regulated by intestinal flora [24,25,30,31]. Relevant studies have shown that the flora in duodenum and the ceca of broilers have a great influence on fat deposition, and the abundance of Methanobacterium and Mucispirillum Schaedleri in ceca have a significant positive and negative correlation with abdominal fat deposition, respectively [32]. The fat deposition of broilers can be affected by regulating intestinal flora. Intestinal microorganisms play an important role in the process of fat digestion, absorption and deposition in animals, and further affect intramuscular fat deposition.
With the improvement in living standards, people have higher and higher expectations of meat quality. High quality, healthy and safe chicken meat is favored by consumers. Studies have shown that a high concentration of n-3 PUFAs, increased concentration ratio of unsaturated fatty acids (PUFA/SFA) and n-3/n-6 are beneficial to human health [33]. Since the intake of n-3 PUFAs in the human body is low [34], scientists have shown great interest in producing chickens rich in n-3 PUFAs for human consumption [35]. Marino R et al. [36] found in their study that due to the close connection between stress and the immune system, supplementing flaxseed and quinoa seeds can reduce the impact of stress on animals and significantly improve muscle tenderness.
So far, no studies have evaluated the effects of dietary quinoa seeds on intestinal microbiota and muscle fatty acids of Luhua chickens. Therefore, this study used 16S rRNA microbiome and gas chromatography to evaluate the effects of different formulations made with quinoa seeds as feed materials on gut microbes and muscle fatty acids of Luhua chickens. Correlation analysis between gut microbes and fatty acids may provide a theoretical basis for exploring the mechanism of quinoa seeds on cecal microbiota and fatty acid deposition of broilers and its application in Luhua chicken production.

2. Materials and Methods

2.1. Moral Statement

All procedures for the use of laboratory animals were approved by the Laboratory Animal Management Committee of Gansu Agricultural University under license number GSAU-2019-0018, and the animals were tested in accordance with the guidelines of the committee. Experiments involving animals shall be conducted in accordance with the Regulations on the Administration of Laboratory Animals (Ministry of Science and Technology of China. Revised June 2004). Samples were collected in accordance with the Guidelines of the Ethics Committee for the Care and Use of Laboratory Animals of Gansu Agricultural University.

2.2. Experimental Design

In this experiment, a single factor completely random design was adopted. A total of 120 dewormed healthy female Luhua chickens (weight 1476.21 ± 101.39 g) aged 49 days were selected and randomly divided into 4 groups, with 3 replicates in each group and 10 chickens in each repetition. Hens in the control group (CK group) were fed a basal diet, and hens in the experimental groups were fed the basal diet supplemented with 4% (Q4), 8% (Q8) and 12% (Q12) quinoa seeds (original diet). The experimental period lasted for 75 days, including the pre-experimental period of 3 days and the formal experimental period of 72 days.

2.3. Experimental Diet and Feeding Management

2.3.1. Composition and Nutritional Level of Experimental Diets

The diets of the experimental chickens were formulated according to the nutritional requirements of broilers in “Chicken Feeding Standards (NY/T33-2004)” and, combined with the Luhua chicken breeding manual, the nutritional levels of the experimental chickens all met the nutritional requirements of Luhua chickens. The composition and nutritional levels of the experimental basal diets are shown in Table 1.

2.3.2. Test Animals

Forty-nine-day-old healthy dewormed Luhua chickens were purchased from Longsheng Family Farm, Beizhai Town, Weiyuan County. Quinoa seeds were provided by the Tianzhu Quinoa Alpine Test Station of the Gansu Academy of Agricultural Sciences. The basal diet was produced by Gansu Aonong Feed Science Technology Co., Ltd (Wuwei, China), according to the experimental formula.

2.3.3. Experimental Animal Feeding and Management

The feeding experiment was carried out in the training base of the Animal Science and Technology College of Gansu Agricultural University. Ten days before the experiment, the coop was thoroughly cleaned and washed, utensils such as the sink and trough were cleaned, and walls were also disinfected with lime water. After cleaning and drying, the doors and windows of the henhouse and ventilation fan were sealed and the whole henhouse was fumigated with potassium permanganate for 24 h before the doors and windows were opened for ventilation for 1 week. The coop was kept dry, clean and well-ventilated. The chickens were examined, immunized, disinfected, numbered and weighed. The chicken crates from the farm we use were sterilized before being transferred into the henhouse (powder, water spray) to help maintain disinfection. During the breeding period, the coop (with chickens) was disinfected once every 2 weeks with sanitizer or 0.1% new germicide. Waste was regularly cleaned from the henhouse as much as possible and steps were taken to avoid inducing various chicken diseases. During the experiment, the chickens were fed twice at a fixed time (7:00 and 15:00 p.m.) every day and free to sufficiently eat and drink. Sufficient feed was added to each trough to ensure feed was in the trough at all times while the chickens were feeding. The diet was provided as mash during the whole experimental period from 12 July 2019 to 26 September 2019. During the rearing process of the broilers, the environmental indicators of the hen house were strictly controlled and recorded. The control range of the main indicators were as follows: temperature 22–28 °C, humidity 60–65%, light time controlled at about 16 h (light on from 6:00 a.m. to dawn, light on at 18:00 p.m. and light off at 22:00 p.m.); and the coop was divided into three layers: upper, middle and lower.

2.4. Collection and Processing of Test Samples

2.4.1. Collection and Processing of Muscle Tissue Samples

On the 75th day of the experiment, two Luhua chickens were randomly selected from the different replicates of each group. After weighing, the chickens were sacrificed by cervical dislocation and bled, feathers were removed; and after draining water, the slaughter performance index was determined. Breast muscle and leg muscle samples with skin and fascia removed were collected and vacuum packed and placed in the refrigerator at −80 ℃ for testing.

2.4.2. Collection of Cecal Microbial Samples

At the age of 121 days, two Luhua chickens were randomly selected from each group of the different replicates and slaughtered. Sterilized surgical scissors were used to separate the ceca from other different intestinal segments, and the cecal contents were collected into 5 mL cryopreserved tubes, quickly put into a liquid nitrogen tank, and stored in the −80 ℃ cryogenic refrigerator measuring intestinal microbial diversity.

2.5. Determination of Indexes and Methods

2.5.1. Determination of Fatty Acid Content in Muscle

The meat samples in the vacuum packaging bag were thawed at room temperature for 12 h, and the muscle surface was peeled off and removed with a knife. The samples were placed in a mortar and ground with liquid nitrogen, and then 1.0 g of the ground samples were weighed in a 10 mL stopper tube. Then, 0.7 mL of KOH solution at a concentration of 10 mol·L−1 and 5.3 mL of anhydrous methanol (analytical methanol (for chromatography)) were added, respectively, and the test tube was shaken for 5 s every 20 min in a water bath at 55 °C for 1.5 h. At the end of the water bath, the tube was removed and cooled to below room temperature under tap water. Then, 0.58 mL of 12 mol∙L−1 H2SO4 solution was added, and the constant temperature water bath was continued at 55 °C for 1.5 h for free fatty acid methylation, while the tube was shaken every 20 min for 5 s. At the end of the water bath, the test tube was cooled with tap water to below room temperature, 3 mL n-hexane was added, the tube shaken well, then transferred to the centrifuge tube, centrifuged at 3000 r·min−1 for 5 min. The supernatant was filtered into the sample bottle using the organic phase filtration membrane, heated at 45 °C, and applied to a concentrate 2 mL sample to less than 1.5 mL. Samples were stored at −20 °C for gas chromatography (GC) detection.
Three parallel samples were tested for each sample and the average value of the three samples was taken as the test result of the sample. Fatty acids were identified according to the relative retention times of fatty acid methyl ester standards. The peak area normalization method was used to quantify the fatty acid. The ratio of PUFA/SFA to n-6/n-3 was calculated according to the composition and specific content of the measured fatty acids.

Chromatographic Condition

The contents of fatty acids in muscle were determined by gas chromatography (GC-2010 plus; Shimadzu Company, Kyoto, Japan). The chromatographic column was an SPTM-2560 capillary column (100 m × 0.25 mm × 0.2 m), and the injection volume was 1.0 μL. Chromatographic conditions: the temperature of the injector detector was 250 °C, nitrogen flow rate 1.11 mL·min−1, and split ratio 100:1. Programmed heating mode: the initial temperature was kept at 100 °C for 5 min, and then the temperature was increased to 240 °C at 4 °C∙min−1 for 30 min, with a total time of 70 min.

2.5.2. Genomic DNA Extraction, PCR Amplification and 16S rRNA High-Throughput Sequencing

Genomic DNA Extraction

Cecal content was collected from 6 chickens in each group for gut microbiome analysis. Genomic DNA was extracted by the CTAB method, and its concentration and purity were detected by a Nanodrop 2000 ultrafine spectrophotometer. After that, agarose gel electrophoresis was used for detection. An appropriate amount of DNA was placed into a centrifuge tube, and the sample was diluted to 1 ng·μL−1 with sterile water. DNA samples were stored at −80 ℃ in an ultra-low temperature refrigerator for later use.

PCR Amplification

Using diluted genomic DNA as a template, the characteristics of cecal microbiota were obtained by amplification of the V4 region of the 16S rRNA gene, according to the selection of the sequencing region. Subsequently, the 16S V4 region was selected and specific primers with barcode (515F and 806R) were used to identify the bacterial diversity. The specific primers were: 515F (5′-GTGCCAGCMGCCGCGGTAA-3′), 806R (5′-GGACTACHVGGGTWTCTAAT-3′). PCR was performed using New England Biolabs’ Phusion High-Fidelity PCR Master Mix with a GC Buffer, and high-performance High-Fidelity enzymes to ensure amplification efficiency and accuracy.
Reaction procedure: pre-denaturation at 95 °C for 5 min, 25 cycles (denaturation at 95 °C for 30 s. Annealing at 55 °C for 30 s. 72 °C extension 40 s). Extend at 72 °C for 7 min.

Mixing and Purification of PCR Products

The PCR products were detected by electrophoresis using 2% agarose gel, and the same amount of samples was mixed according to the concentration of PCR products, and the PCR products were detected by electrophoresis using 2% agarose gel after full mixing, for the target strip. The adhesive recovery kit provided by Qiagen Company was used to recover the product.

Library Construction and Computer Sequencing

The TruSeq® DNA PCR-Free Sample Preparation Kit was used for library construction. The constructed libraries were quantified by Qubit and Q-PCR. After the qualified libraries were tested, NovaSeq6000 (Illumina, San Diego, CA, USA) was used to finish the sequencing.

2.5.3. Bioinformatics Analysis

The data obtained from sequencing on the Illumina NovaSeq platform were spliced with various sample reads using FLASH (V1.2.7) [37] to obtain Raw Tags; then, after strict filtering [38], the Tags data (Clean Tags) were obtained. The Tags were then compared with the species annotation database to remove the chimera sequences and obtain Effective Tags [39]. The Effective Tags were clustered by operational taxonomic units (OTUs) with 97% similarity using Usearch software (Uparse v7.0.1001). OTUs were annotated based on the Silva (bacterial) taxonomy database. Based on the results of the OTUs analysis, the samples were analyzed at each taxonomic level, and the community composition of each sample was obtained at the taxonomic level of kingdom, phylum, class, order, family, genus and species. R software (Version 2.15.3) was used for alpha diversity analysis and beta diversity index difference analysis between groups to obtain the Alpha diversity index with the Ace, Chao1, Shannon and Simpson indices and sample dilution curve. PICRUST was used for the functional prediction of microbial communities in the samples [40,41,42].

2.5.4. Statistical Analysis

All statistical analyses were performed with SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). The differences in fatty acid composition between breast and leg muscles were analyzed, and the results were expressed as mean ± standard deviation. p < 0.05 was statistically significant, p < 0.01 was extremely statistically significant. The Spearman correlation test was used to analyze the correlation between the composition and content of fatty acids in muscle of the breast and leg and cecal microbes at the genus level (relative abundance > 0.5%).

3. Results

3.1. Effect of Quinoa on Fatty Acid Composition and Content in Breast Muscle of Female Luhua Chicken

Twenty-three fatty acids were detected in the breast muscles of each group, including eight SFAs, 7 species of MUFAs and 8 species of PUFAs (Table 2). The content of C16:0, C16:1, C18:0, C18:1n9c, C18:2n6c, C20:4n6 and C24:1 was higher than 1% in each group. The content of C18:1n9c was the highest among the groups, about 30% among the groups; followed by C16:0, about 25% among the groups; and C18:2n6c was the third highest among the groups; its content was about 12% in all groups. Compared with the CK group, C14:0, C16:0, C17:0, C18:0, C18:2n6c, C18:3n3, SFAs, MUFAs, n-6/n-3 and n-6 PUFAs in the experimental groups (Q4, Q8 and Q12 groups) were significantly lower (p < 0.05). C16:1, C17:1, C18:1n9c, C18:1n9t, C20:1, C20:2, C20:3n6, C22:6n3 (DHA), C24:1, UFAs and n-3 PUFAs in the experimental groups were significantly higher than those in the CK group (p < 0.05). The content of C4:0 and C8:0 in the CK group was significantly higher than those in the Q8 and Q12 groups (p < 0.05), content of C14:0 in the Q12 group was significantly lower than those in the CK, Q4 and Q8 groups (p < 0.05), and content of C20:3n6 in the Q4 group was significantly higher than those in the CK, Q8 and Q12 groups (p < 0.05). However, there were no significant differences in C15:0, C18:3n6, C20:4n6 (AA), C22:0, PUFAs or PUFA/SFA between the experimental groups and CK group (p > 0.05).

3.2. Effect of Quinoa on Fatty Acid Composition and Content in Leg Muscle of Female Luhua Chicken

Twenty-six fatty acids were detected in the muscles of each experiment group, including 9 kinds of SFAs and 17 kinds of UFAs; among the UFAs, there were 8 MUFAs and 9 PUFAs (Table 3). The content of C16:0, C16:1, C18:0, C18:3n3 and C20:4n6 (AA) was higher than 1%, and C18:1n9c was the highest, with the content of about 33% among all groups. The content of C16:0 in each group was about 26%. The third highest content was C18:2n6c, which was about 14% among the groups. There are significant differences in some fatty acids of leg muscle in diets supplemented with a certain amount of quinoa, among which, C14:1, C15:1, C16:1, C17:1, C18:1n9c, C18:1n9t, C18:3n3, C18:3n6, C20:1, C20:5n3 (EPA), C22:6n3 (DHA), C24:1, UFAs, MUFAs, n-3 PUFAs and the ratio of PUFA/SFA, Q4, Q8, Q12 were significantly higher than those in the CK group (p < 0.05). The content of C14:0, C16:0, C17:0, C18:0, C18:2n6t, C21:0, SFAs and n-6/n-3 ratio in the experimental groups (Q4, Q8, Q12) was significantly lower than those in the CK group (p < 0.05). The content of C18:2n6c and EPA in the Q4 group was significantly higher than those in the CK, Q8 and Q12 groups (p < 0.05). The content of PUFAs in the Q8 group was significantly higher than that in the CK group (p < 0.05). However, there were no significant differences in C12:0, C13:0, C15:0 or n-6 PUFAs between the experimental groups and CK group (p > 0.05).

3.3. Cecal Microbial Diversity

The PCR-free library was constructed based on the Illumina Nova sequencing platform, and paired-end sequencing was performed. By splicing Reads, an average of 90,178 tags were obtained per sample, and an average of 85,917 tags were obtained by quality control. The effective data amount of quality control was 65,201, and the effective rate of quality control was 72.34% (Table 4). Using Uparse software, Effective Tags were clustered at a 97% similarity level, and the number of OTUs samples was obtained. A total of 1209 OTUs were obtained; there were 850, 923, 991 and 902 OTUs in CK, Q4, Q8 and Q12 groups, and 78, 33, 56 and 20 unique OTUs in CK, Q4, Q8 and Q12 groups, respectively. The total number of OTUs shared by the 4 groups was 678 (Figure 1A). Then, the OTUs sequence and Silva132 database were annotated. A total of 484 OTUs (40.03%) were annotated to the genus level. The dilution curve described the species diversity and species richness of the samples, and tended to flatten at 40,000 reads, indicating that the sequence coverage was saturated. This indicates that the species evenness in the samples tends to stabilize under the experimental conditions, and that the current sequencing depth of each sample is sufficient to reflect the microbial diversity contained in the community sample (Figure 1B). As shown in Table 5, the Alpha Diversity Index showed that Shannon was significantly higher in the CK group than in each Test group, and the Simpson index of the CK group was significantly higher than the Q4 group, indicating that cecal microbial species abundance was significantly higher in the CK group than in each test group. The plot of species accumulation (Figure 1C) shows that the number of species and common species in the environment has reached saturation with the increasing sample size but does not increase with the increasing sample size. As shown by the PCA figure (Figure 1D), there were significant differences in the cecal microbial species between the CK group and trial group with different proportions of quinoa added, as well as some differences between the different proportions of quinoa added.

3.4. Cecal Microbial Composition

By comparing with the Silva132 database (Table 6), the species were annotated, and the statistical results of different taxonomic levels were as follows: There were a total of 1209 OTUs, among which the number of OTUs that could be annotated to the database was 1179 (97.52%), proportion of OTUs annotated to the boundary level was 97.52%, proportion of OTUs annotated to the phylum level was 95.70%, proportion of OTUs annotated to the class level was 93.05%, and proportion of OTUs annotated to the target level was 89.00%. The proportion at the family level was 80.23%, genus level 40.03%, and species level 12.49%.
At the phylum level (Figure 2A), Firmicutes, Bacteroidetes and Proteobacteria were the dominant phyla, with relative abundance greater than 3%. The relative abundance of Firmicutes and Bacteroidetes was the highest in all experimental groups, accounting for more than 89% of the total abundance. At the genus level (Figure 2B), the relative abundance of 30 genera was more than 0.1%. Bacteroides, Lactobacillus and unidentified_Lachnospiraceae were the dominant genera in all groups.

3.5. Species Diversity Analysis

At the phylum level (Figure 3), compared with the experimental groups (Q4, Q8, Q12), the Proteobacteria, Actinobacteria, Synergistetes and Melainabacteria CK groups were significantly higher than those in the experimental groups (p < 0.05). In Q4 compared with Q12, Actinobacteria in the Q12 group were significantly higher than in the Q4 group (p < 0.05), but Spirochaetes in the Q12 group were significantly higher than in the Q4 group (p < 0.05). Compared with the Q12 group, Firmicutes in the Q12 group were significantly higher than in the Q8 group (p = 0.047).
At the genus level (Figure 4), compared with the CK group, Desulfovibrio, Synergistes, Olsenella, Parabacteroides, Mailhella, Sutterella and Ruminiclostridium in the CK group were significantly higher than in the group Q4 (p < 0.05); and Odoribacter bacteria in the Q4 group were significantly higher than in the CK group (p = 0.008). Compared with the CK group, Faecalibacterium in the Q8 group was significantly higher than in the CK group (p = 0.032). While Olsenella, unidentified_Clostridiales, Ruminiclostridium, unidentified_Christensenellaceae and Anaerostipes in group CK were significantly higher than in the Q8 group (p < 0.05). Compared with the CK group, Lawsonia and Faecalibacterium in the Q12 groups were significantly higher than in the CK group (p < 0.05). While Olsenella, unidentified_Clostridiales, Subdoligranulum, Ruminiclostridium and Anaerostipes in the CK group were significantly higher than in the Q12 group (p < 0.05). Compared with group Q8, Faecalibacterium, Phascolarctobacterium, Desulfovibrio, Parasutterella and Sutterella in group Q8 were significantly higher than in group Q4 (p < 0.05). While Odoribacter in the Q8 group was significantly lower than in the Q4 group (p = 0.022). Compared with the Q12 group, Faecalibacterium and Negativibacillus in the Q12 group were significantly higher than in the Q4 group (p < 0.05), while Sphaerochaeta and Odoribacter in the Q4 group were significantly higher than in the Q12 group (p < 0.05). Compared with group Q12, Enorma and Eisenbergiella in group Q8 were significantly lower than in group Q12 (p < 0.05).

3.6. Prediction of Cecal Microbial Function

PICRUST was used to predict the abundance of functional genes with significant differences in the L2 level of the KEGG pathway (n = 6/group), and thusly analyze the functional differences between the two groups. The analysis results are shown in Figure 5. Compared with the CK group, the Metabolism and Enzyme Families pathways were significantly enriched in the Q4 group (p < 0.05), and Cellular Processes and Signaling pathways were significantly enriched in the Q8 group (p < 0.05), while the Cancers, Metabolism of Other Amino Acids and Infectious Diseases pathways were significantly enriched in the CK group (p < 0.05). Compared with group Q12, the Replication and Repair pathway was significantly enriched in group Q4 (p < 0.05) and Metabolism of Cofactors and Vitamins was significantly enriched in the Q8 group (p < 0.05), while the Transcription pathway was significantly enriched in the Q12 group (p < 0.05).

3.7. Correlation Analysis

There was a significant correlation between cecal microbiota and muscle fatty acid deposition (Figure 6), and among the fatty acids in the pectoralis muscle (Figure 6A), the abundance of Desulfovibrio was positively correlated with C18:0, C22:0, SFAs, n-6 PUFAs and n-6/n-3 (p < 0.05), and negatively correlated with C18:3n3, UFAs and MUFAs (p < 0.05). The abundance of Phascolarctobacterium was positively correlated with the abundance of C14:0 (p < 0.05). The abundance of Faecalibacterium was negatively correlated with the content of C4:0 and C8:0 (p < 0.05), and positively correlated with the content of C18:1n9t (p < 0.05). The abundance of Lawsonia was positively correlated with the content of C17:0, C18:1n9t, C20:5n3, C20:6n3 (p < 0.05), and negatively correlated with the content of n-6/n-3 (p < 0.05), while that of Meagmonas showed the opposite relationship. The abundance of Bacteroides was negatively correlated with C14:1 (p < 0.05), but Romboutsia showed a positive correlation.
In the fatty acids of leg muscles (Figure 6B), the abundance of Desulfovibrio was positively correlated with the content of C15:0, SFAs, n-6 PUFAs (p < 0.05), and negatively correlated with that of C20:2, UFAs (p < 0.05). The abundance of Phascolarctobacterium was significantly positively correlated with the content of C18:3n6, C20:5n3 and n-6 PUFAs (p < 0.05), but negatively correlated with that of C20:2 (p < 0.05). The abundance of Faecalibacterium was negatively correlated with C13:0, C17:0, C20:2 and n-6/n-3 (p < 0.05), and C18:1n9t, C18:3n3, C18:3n6, C20:3n6, C20:4n6, C20:5n3 and C22:6n3 were significantly positively correlated (p < 0.05). The abundance of Lawsonia was positively correlated with C14:1, C17:1, C18:3n3, C18:3n6, C20:5n3 and C24:1, but negatively correlated with C18:0. The abundance of Meagmonas was negatively correlated with C12:0, C16:1, C18:1n9c, C18:1n9t, C18:3n3, C18:3n6, C20:1 and MUFAs (p < 0.05), but positively correlated with C17:0, C18:0 and n-6/n-3(p < 0.05).

4. Discussion

4.1. Effect of Quinoa on Fatty Acids of Female Luhua Chicken Muscle

Studies have shown that SFAs, UFAs, PUFA/SFA, n-6/n-3 and other health indicators are important to human health, and can improve the cerebrovascular disease of the heart, and provide anti-cancer, weight loss, and immune regulation [43]. In this study, the content of SFAs in experimental groups was significantly lower than that in the CK group, while the content of UFAs showed the opposite relationship. Because of muscle fatty acid involvement in the Maillard reaction, the content of flavor compounds increases to a certain extent, thus increasing the meat flavor [44]. The richer the composition and content of UFAs in muscles, the higher and more balanced the nutritional value of the muscles. For humans, chicken is one of the major sources of UFAs, especially n-3 PUFAs, whose fatty acid composition is regulated by changing the level of fat intake and absorption [45,46]. In this study, the content of n-3 PUFAs in all experimental groups was significantly higher than in the CK group, because quinoa seeds are rich in protein, amino acids, UFAs, vitamins and mineral elements [47], among which the content of UFAs is twice that of corn kernels, and most of the UFAs are n-3 and n-6 series [48]. Therefore, adding a certain amount of quinoa in the diet can effectively improve the composition of PUFAs in the diet to a certain extent, increase the content of n-3 PUFAs in the diet, and thus improve the content of n-3 PUFAs in the muscle.
In this study, the content of C18:1n9c in pectoralis and leg muscles was the highest, followed by C16:0 and C18:2n6c. The content of C16:0 in experimental groups was significantly lower than in the CK group. C18:1n9c, C18:2n6c, C18:3n3 and DHA were significantly higher than in the CK group. This is mainly because the main SFAs found in quinoa are C16:0, and the UFAs are C18:1n9c, C18:2n6c and C18:3n3 [48,49,50]. Adding a certain proportion of quinoa in the diet changes the composition and content of fatty acids in the diet, which has a certain effect on meat quality. Meanwhile, studies have found that C18:2n6c can be metabolized to C20:4n6, and C18:3n3 can be metabolized to EPA and DHA, which play an important role in the prevention and treatment of prostaglandins, thrombosis, atherosclerosis, immunity, and anti-inflammatory and membrane function [7,51]. The results showed that the addition of quinoa to the diet promoted the deposition of PUFAs in muscle tissue, presumably because the tannin in quinoa inhibited the activity of hydrogenated microorganisms and thus prevented some of the PUFAs from being hydrogenated, and thus more PUFAs are deposited in the meat. Additionally, α-tocopherols (such as vitamin E) found in quinoa act as natural oxidants at the cell membrane level to protect fatty acids from free radical damage [48]. Among them, the World Health Organization (WHO) recommends an n-6/n-3 ratio in the range of (5–10):1 [52,53]. While the recommended range of the n-6/n-3 ratio in the Reference Intake of Dietary Nutrients for Chinese Residents is (4–6) [44]. In this study, the content of SFAs and the n-6/n-3 ratio in the chest muscle and leg muscle of experimental groups was significantly lower than in the CK group, while the UFAs were significantly higher than in the CK group. The ratio of n-6/n-3 in each experimental group was within the suitable range recommended by WHO. It showed that adding a different proportion of quinoa in the diet could improve the composition and content of fatty acids in the muscle of Luhua chickens. Studies have shown that fatty acid composition of feed is an important determinant of fatty acid composition in broiler muscle [54]. Dietary protein level or n-3 PUFAs content can affect the content and flavor of UFAs in the muscle [55,56]. Therefore, increasing dietary raw materials rich in PUFAs can change muscle fatty acid synthase (FAS) and the lipid profile [57,58] by decreasing the content of SFAs and increasing the content of UFAs in muscle [59]. This is consistent with the results of this experiment, which verifies the regulation and influence of quinoa on muscle fat. The PUFA/SFA ratio is also an important index to measure the nutritional value of muscle, and the appropriate ratio recommended by the WHO should be greater than 0.4 [52,53,54]. In this study, the ratio was about 0.54 in the pectoral muscle tissue and 0.6 in the leg muscle between the groups, both greater than 0.4, which was in line with the range recommended by the WHO.

4.2. Effect of Quinoa on Cecal Microbiota of Female Luhua Chickens

The poultry gut is a complex ecosystem. As the largest digestive organ for nutrient absorption and utilization, it contains a complex and highly diverse microbial community. In this study, it was found that the Simpson index of microbial diversity had some differences among groups, and the Shannon index of the CK group was significantly higher than that of other experimental groups, indicating that adding a certain proportion of quinoa in the diet had a certain effect on the cecal microbial species diversity of Luhua chickens. Studies have shown that gut microbiota is closely related to maternal nutrient level [60]. Different proportions of quinoa were added to the diet, resulting in certain differences in cecal microbial species composition.
In this study, Firmicutes, Bacteroidetes and Proteobacteria were the dominant phyla at the phylum level, with their relative abundance greater than 3%. The relative abundance of Firmicutes and Bacteroidetes was the highest in all experimental groups. Firmicutes and Bacteroidetes play important roles in energy metabolism in animals [61], and Firmicutes can produce various digestive enzymes to promote the digestion and absorption of nutrients [62]. Bacteroidetes showed strong degradation of protein and carbohydrates [63,64,65]. The greater the ratio of Firmicutes: bacteroidetes in the gut, the greater the absorption capacity of the body for energy-related substances. The smaller the ratio, the more prone the animal to become obese [63,66]. Bacteroidetes and Firmicutes constitute most of the microbial communities at the level of intestinal microbiota in broilers. The results of this study are consistent with that. The relative abundance of Firmicutes and Bacteroidetes is the highest in all experimental groups, accounting for more than 89% of the total abundance. At the genus level, the relative abundance of 30 bacterial genera detected in this study was greater than 0.1%, and Bacteroides, Lactobacillus and unidentified_Lachnospiraceae were all the dominant genera in each experimental group. Bacteroidetes have been found to improve the intestinal environment of animals, degrade plant polysaccharides, regulate electrolyte balance and improve intestinal metabolic function [67,68,69,70]. Bacteroides in the Q8 group were significantly higher than in the other groups, indicating that 8% quinoa added in the basal diet was conducive to the fermentation of Bacteroides in ceca; production of acetate, propionate and other short-chain fatty acids; and maintenance of intestinal health homeostasis. Firmicutes represent the largest population of gut microbes in mice and humans [71], and many species of this phylum are capable of producing endospores that are resistant to drying and other harsh conditions [72]. Firmicutes have been shown to be involved in energy absorption and may be associated with the development of diabetes and obesity in humans [66,73,74]. Our results are consistent with these previous studies, suggesting that a significant increase in firmicutes may contribute to an improved intestinal environment and healthy growth in broilers. Using PICRUST software to predict KEGG function, it was found that Cancers, Infectious Diseases and other harmful metabolic pathways were mainly enriched in the CK group. The results indicated that quinoa of different proportions in the diet could improve the structure of cecal microflora, inhibit the number of harmful microflorae, increase the number of beneficial microflora, significantly regulate the intestinal environment and promote the health of broilers. While Metabolism and Enzyme Families were significantly enriched in the Q4 group, Cellular Processes and Signaling were significantly enriched in the Q8 group, and Transcription was significantly enriched in the Q12 group. This may be because quinoa has medicinal properties such as anti-cancer, weight loss, and prevention of cardiovascular and cerebrovascular diseases [48]. After the body ingests quinoa, it affects the composition and structure of intestinal microbes through digestion and absorption, thus exerting its efficacy and having an impact on the body. Additionally, we speculate that quinoa seeds contain rich and comprehensive nutritional value, and are rich in protein, amino acids, UFAs, vitamins and mineral elements [47]. Moreover, it is rich in n-3 PUFAs, which can effectively increase the content of n-3 PUFAs in the diet, thereby changing the content of PUFAs and the number and structure of intestinal microbiota in broilers to some extent. But its specific regulatory mechanism needs to be further explored.

4.3. Correlation Analysis

Intramuscular fat deposition in animals is regulated by intestinal flora [24,25,30,31]. The results of this study are consistent with those of Lactobacillus, which can increase the content of various UFAs and the ratio of PUFA/SFA [75]. The main reason is that Lactobacillus has improved the fatty acid profile of broilers attacked by Clostridium perfringens [75]. The abundance of Bacteroides was positively correlated with the immune system, glycan biosynthesis and metabolism, and the signaling pathways related to cofactor and vitamin metabolism. The genus Bacteroides exhibits a high degree of host specificity, reflecting individual differences in the digestive system of host animals [76].
Studies have found that supplementation with probiotics can improve fatty acid composition in chickens [77], either by modulating gut microbiota or influencing fat deposition in broilers. In this study, there was a significant correlation between cecal microorganisms and muscle fatty acid deposition. The abundance of Faecalibacterium was negatively correlated with the content of C4:0 and C8:0, and positively correlated with C18:1n9t in pectoralis muscle. In leg muscle tissue, the abundance of Faecalibacterium was negatively correlated with C13:0, C17:0, C20:2 and n-6/n-3. And the content of C18:1n9t, C18:3n3, C18:3n6, C20:3n6, C20:4n6, C20:5n3, C22:6n3 were significantly positively correlated. Meanwhile, there was also a significant correlation between the abundance of Lawsonia and Meagmonas and the content of partially saturated and UFAs. This is mainly because Bacteroides and Lactobacillus are the main bacteria of fatty acid hydrogenation, and Faecalibacterium co-occurs with several members of Bacteroidetes, and Bacteroidetes may be the main bacteria of linolenic acid (C18:3n3) hydrogenation [78]. Because of bacteroides, lactobacillus contribute to the changes in abundance in the ceca and lead to changes in other bacterial genus abundance in the ceca, which indicates that there is a synergistic effect among the various microbial genera in the caecum, thus affecting muscle fatty acid deposition, leading to the change in fatty acid content in the muscle, but its exact regulatory mechanism is not clear and needs to be further explored. In this study, the content of n-3 PUFAs in the muscle tissue of each test group was significantly higher than that of the CK group, and the content of linolenic acid (C18:3n3) in the breast muscle of each test group was significantly lower than that of the CK group. Therefore, it can be concluded that this observation may be related to the decrease of the abundance of Bacteroidetes, resulting in the decrease in the hydrogenation of linolenic acid (C18:3n3), and thus the increase in the total content of n-3 PUFAs. The results are consistent with those of previous studies. Additionally, Yu [79], Yang [80], and Frutos [81] et al. found in their studies on finishing pigs and ruminants that there was a correlation between microbial abundance and muscle fatty acid content, and the results of this experiment were similar to their results. This is mainly because microbial activity is affected by dietary protein level, carbohydrates, starch type and active metabolites such as flavonoids, tannins and saponins, thereby regulating the effect of intestinal lipid metabolism on muscle PUFAs [79,80,81].

5. Conclusions

Adding quinoa seeds to diets significantly increased the content of muscle DHA, UFAs and n-3 PUFAs. The content of SAFs and the n-6/n-3 ratio were significantly reduced to provide ideal fatty acid composition and content. Thus, quinoa seeds can improve the structure of cecal microbiota, inhibit the number of harmful microbiota, increase the number of beneficial microbiota, significantly regulate the intestinal environment and promote the health of female Luhua chickens. We identified a degree of correlation between cecal microorganisms and muscle fatty acid deposition.

Author Contributions

Conceptualization, methodology, software, formal analysis, writing—original draft, T.W.; methodology, software, X.J. and Y.W.; methodology, formal analysis, F.Y.; conceptualization, writing—review & editing, supervision, project administration, funding acquisition, S.Z. and T.J. All authors have read and agreed to the published version of the manuscript.

Funding

The study was supported by the Research and Demonstration and Promotion of Quinoa (Straw) Feedstock (Central Guidance of Local Science and Technology Development) Fund (701-03120081) and Southern Xinjiang Key Industry Innovation and Development Support Project (2022DB017). The funding bodies had no role in the design of the study, collection, analysis, or interpretation of data, or writing of the manuscript.

Institutional Review Board Statement

All procedures for using experimental animals have been approved by the Experimental Animal Management Committee of Gansu Agricultural University with license number GSAU-2019-0018.

Informed Consent Statement

Not applicable.

Data Availability Statement

The sequencing data were deposited into the Sequence Read Archive (SRA) of NCBI (PRJNA905337).

Acknowledgments

Thanks to all participants for their advice and support of this study.

Conflicts of Interest

All authors declare no conflict of interest.

References

  1. Kang, J.K. Cultivation technology of organic quinoa in Qinghai plateau. Qinghai Agro-Technol. Ext. 2018, 4, 24–25. [Google Scholar]
  2. Villa, D.; Russo, L.; Kerbab, K.; Landi, M.; Rastrelli, L. Chemical and nutritional characterization of Chenopodium pallidicaule (caihua) and Chenopodium quinoa (quinoa) seeds. Emir. J. Food Agric. 2014, 26, 609–615. [Google Scholar] [CrossRef] [Green Version]
  3. Nickel, J.; Spanier, L.P.; Botelho, F.T.; Gularte, M.A.; Helbig, E. Effect of different types of processing on the total phenolic compound content, antioxidant capacity, and saponin content of Chenopodium quinoa Willd grains. Food Chem. 2016, 209, 139–143. [Google Scholar] [CrossRef] [PubMed]
  4. Nowak, V.; Du, J.; Charrondière, U.R. Assessment of the nutritional composition of quinoa (Chenopodium quinoa Willd). Food Chem. 2016, 193, 47–54. [Google Scholar] [CrossRef] [PubMed]
  5. Schilick, G.; Bubenheim, D.L. Quinoa: An Emerging New Crop with Potential for CELSS; National Aeronautics and Space Administration, Ames Research Center: Mountain View, CA, USA, 1993. [Google Scholar]
  6. Quinoa FAO. An Ancient Crop to Contribute to World Food Security; Food and Agriculture Organization: Roma, Italy, 2011. [Google Scholar]
  7. James, L. Chapter 1 Quinoa (Chenopodium quinoa Willd): Composition, Chemistry, Nutritional, and Functional Properties. Adv. Food Nutr. Res. 2009, 58, 1–31. [Google Scholar]
  8. Asher, A.; Galili, S.; Whitney, T.; Rubinovich, L. The potential of quinoa (Chenopodium quinoa) cultivation in Israel as a dual-purpose crop for grain production and livestock feed. Sci. Hortic. 2020, 272, 109534. [Google Scholar] [CrossRef]
  9. Kala, P.; Moudr, J. Composition and nutritinal value of quinoa (Chenopodium quinoa)—A review. Czech J. Food Sci. 2018, 18, 115–119. [Google Scholar] [CrossRef] [Green Version]
  10. Tremaroli, V.; Backhed, F. Functional interactions between the gut microbiota and host metabolism. Nature 2012, 489, 242–249. [Google Scholar] [CrossRef]
  11. Spanogiannopoulos, P.; Bess, E.N.; Carmody, R.N.; Turnbaugh, P.J. The microbial pharmacists within us: A metagenomic view of xenobiotic metabolism. Nat. Rev. Microbiol. 2016, 14, 273–287. [Google Scholar] [CrossRef]
  12. Stephens, W.Z.; Burns, A.R.; Stagaman, K.; Wong, S.; Rawls, J.F.; Guillemin, K.; Bohannan, B.J. The composition of the zebrafish intestinal microbial community varies across development. ISME J. 2016, 10, 644–654. [Google Scholar] [CrossRef] [Green Version]
  13. Felix, S.; Fredrik, B. The gut microbiota--masters of host development and physiology. Nat. Reviews. Microbiol. 2013, 11, 227–238. [Google Scholar]
  14. Waite, D.W.; Taylor, M.W. Characterizing the avian gut microbiota: Membership, driving influences, and potential function. Front. Microbiol. 2014, 5, 223–230. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Hsiao, E.Y.; Mcbride, S.W.; Hsien, S.; Sharon, G.; Hyde, E.R.; Mccue, T.; Codelli, J.A.; Chow, J.; Reisman, S.E.; Petrosino, J.F. Microbiota Modulate Behavioral and Physiological Abnormalities Associated with Neurodevelopmental Disorders. Cell 2013, 155, 1451–1463. [Google Scholar] [CrossRef] [PubMed]
  16. Clemente, J.; Ursell, L.; Parfrey, L.; Knight, R. The impact of the gut microbiota on human health: An integrative view. Cell 2012, 148, 1258–1270. [Google Scholar] [CrossRef] [Green Version]
  17. Jacobsen, E.E.; Skadhauge, B.; Jacobsen, S.E. Effect of dietary inclusion of quinoa on broiler growth performance. Anim. Feed. Sci. Technol. 1997, 65, 5–14. [Google Scholar] [CrossRef]
  18. Johansson, K.R.; Sarles, W.B.; Shapiro, S.K. The Intestinal Microflora of Hens as Influenced by Various Carbohydrates in a Biotin-deficient Ration. J. Bacteriol. 1948, 56, 619–634. [Google Scholar] [CrossRef] [Green Version]
  19. Degolier, T.; Mahoney, S.; Duke, G. Relationships of Avian Cecal Lengths to Food Habits, Taxonomic Position, and Intestinal Lengths. Condor 1999, 101, 622–634. [Google Scholar] [CrossRef]
  20. Dragana, S.; Stuart, E.D.; Robert, J.H.; Mark, S.G.; Tamsyn, M.G.; Chen, H.; Volker, R.H.; Robert, J.M. Intestinal microbiota associated with differential feed conversion efficiency in chickens. Appl. Microbiol. Biotechnol. 2012, 96, 1361–1369. [Google Scholar]
  21. Clench, M.H.; Mathias, J.R. The avian cecum: A review. Wilson Bull. 1995, 107, 93–121. [Google Scholar]
  22. Chaplin, S.B. Effect of cecectomy on water and nutrient absorption of birds. J. Exp. Zool. 1989, 3, 81–86. [Google Scholar] [CrossRef]
  23. Li, M.; Zhou, H.; Pan, X.; Xu, T.; Zhang, Z.; Zi, X.; Jiang, Y. Cassava foliage affects the microbial diversity of Chinese indigenous geese caecum using 16S rRNA sequencing. Sci. Rep. 2017, 7, 45697. [Google Scholar] [CrossRef] [PubMed]
  24. Fang, S.; Xiong, X.; Su, Y.; Huang, L.; Chen, C. 16S rRNA gene-based association study identified microbial taxa associated with pork intramuscular fat content in feces and cecum lumen. BMC Microbiol. 2017, 17, 162. [Google Scholar] [CrossRef]
  25. Zhao, X.; Ding, X.; Yang, Z.; Shen, Y.; Zhang, S.; Shi, S. Effects of Clostridium butyricum on thigh muscle lipid metabolism of broilers. Chin. J. Anim. Nutr. 2017, 29, 2884–2892. [Google Scholar]
  26. Schoeler, M.; Caesar, R. Dietary lipids, gut microbiota and lipid metabolism. Rev. Endocr. Metab. Disord. 2019, 20, 461–472. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Lin, Z.D.; Han, F.L.; Lu, J.T.; Guo, J.L.; Qi, C.L.; Wang, C.L.; Xiao, S.S.; Bu, X.Y.; Wang, X.D.; Qin, J.G.; et al. Influence of dietary phospholipid on growth performance, body composition, antioxidant capacity and lipid metabolism of Chinese mitten crab, Eriocheir sinensis. Aquaculture 2020, 516, 734653. [Google Scholar] [CrossRef]
  28. Martinez-Guryn, K.; Hubert, N.; Frazier, K.; Urlass, S.; Chang, E.B. Small Intestine Microbiota Regulate Host Digestive and Absorptive Adaptive Responses to Dietary Lipids. Cell Host Microbe 2018, 23, 458–469. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Kindt, A.; Liebisch, G.; Clavel, T.; Haller, D.; Hörmannsperger, G.; Yoon, H.; Kolmeder, D.; Sigruener, A.; Krautbauer, S.; Seeliger, C.; et al. The gut microbiota promotes hepatic fatty acid desaturation and elongation in mice. Nat. Commun. 2018, 9, 3760. [Google Scholar] [CrossRef] [Green Version]
  30. Sudikas, G.; Kulpys, J.; Jerešiunas, A.; Juškiene, V.; Norviliene, J. The influence of probiotics on carcass, meat and fat quality in pigs. Vet. Zootech. 2010, 52, 79–86. [Google Scholar]
  31. Liu, Y.H.; Li, Y.Y.; Feng, X.C.; Wang, Z.; Xia, Z.F. Dietary supplementation with Clostridium butyricum modulates serum lipid metabolism, meat quality, and the amino acid and fatty acid composition of Peking ducks. Poult. Sci. 2018, 97, 3218–3229. [Google Scholar] [CrossRef]
  32. Wen, C.L.; Yan, W.; Sun, C.J.; Ji, C.L.; Zhou, Q.Q.; Zhang, D.X.; Zheng, J.X.; Yang, N. The gut microbiota is largely independent of host genetics in regulating fat deposition in chickens. ISME J. 2019, 13, 1422–1436. [Google Scholar] [CrossRef]
  33. Monk, J.M.; Mcmurray, D.N.; Chapkin, R.S. Clinical Effects of n-3 PUFA Supplementation in Human Health and Inflammatory Diseases. In Omega-3 Oils; AOCS Press: Urbana, IL, USA, 2011; pp. 31–60. [Google Scholar]
  34. Burdge, G.C.; Calder, P.C. Conversion of α-linolenic acid to longer-chain polyunsaturated fatty acids in human adults. Reprod. Nutr. Dev. 2005, 45, 581–587. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Konieczka, P.; Czauderna, M.; Smulikowska, S. The enrichment of chicken meat with omega-3 fatty acids by dietary fish oil or its mixture with rapeseed or flaxseed—Effect of feeding duration:Dietary fish oil, flaxseed, and rapeseed and n-3 enriched broiler meat. Anim. Feed. Sci. Technol. 2017, 223, 42–52. [Google Scholar] [CrossRef]
  36. Marino, R.; Caroprese, M.; Annicchiarico, G.; Ciampi, F.; Ciliberti, M.G.; Malva, A.D.; Santillo, A.; Sevi, A.; Albenzio, M. Effect of Diet Supplementation with Quinoa Seed and/or Linseed on Immune Response, Productivity and Meat Quality in Merinos Derived Lambs. Animals 2018, 8, 204. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Mago, T.; Salzberg, S.L. FLASH: Fast Length Adjustment of Short Reads to Improve Genome Assemblies. Bioinformatics 2011, 27, 2957–2963. [Google Scholar] [CrossRef] [Green Version]
  38. Bokulich, N.A.; Subramanian, S.; Faith, J.J.; Gevers, D.; Gordon, J.I.; Knight, R.; Mills, D.A.; Caporaso, J.G. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 2013, 10, 57–59. [Google Scholar] [CrossRef] [PubMed]
  39. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ Inc. 2016, 4, e2584. [Google Scholar] [CrossRef] [Green Version]
  40. Haas, B.J.; Gevers, D.; Earl, A.M.; Feldgarden, M.; Ward, D.V.; Giannoukos, G.; Ciulla, D.; Tabbaa, D.; Highlander, S.K.; Sodergren, E. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res. 2011, 21, 494–504. [Google Scholar] [CrossRef]
  41. Edgar, R.C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 2013, 10, 996–998. [Google Scholar] [CrossRef] [PubMed]
  42. Wang, Q.; George, M.G.; James, M.T.; James, R.C. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 2007, 73, 5261–5267. [Google Scholar] [CrossRef] [Green Version]
  43. Wang, P.; Zhang, Y.; Jiang, M. Research progress of polyunsaturated fatty acids. China Oils Fats 2008, 33, 42–46. [Google Scholar]
  44. Chen, D.; Wang, X.; Guo, Q.; Deng, H.; Luo, J.; Yi, K.; Sun, A.; Chen, K.; Shen, Q. Muscle Fatty Acids, Meat Flavor Compounds and Sensory Characteristics of Xiangxi Yellow Cattle in Comparison to Aberdeen Angus. Animals 2022, 12, 1161. [Google Scholar] [CrossRef] [PubMed]
  45. Hulan, H.W.; Ackman, R.G.; Ratnayake, W.; Proudfoot, F.G. Omega-3 Fatty Acid Levels and General Performance of Commercial Broilers Fed Practical Levels of Redfish Meal. Poult. Sci. 1989, 68, 153–162. [Google Scholar] [CrossRef] [PubMed]
  46. Poorghasemi, M.; Seidavi, A.; Qotbi, A.A.A.; Laudadio, V.; Tufarelli, V. Influence of dietary fat source on growth performance responses and carcass traits of broiler chicks. Asian-Australas. J. Anim. Sci. 2013, 26, 705–710. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Yang, F.-R.; Huang, J.; Wei, Y.-M.; Li, M.-Q.; He, X.-G.; Zheng, J. Biological characteristics and application of quinoa. Pratacultural Sci. 2017, 34, 607–613. [Google Scholar]
  48. Filho, A.M.M.; Pirozi, M.R.; Borges, J.T.D.S.; Sant’Ana, H.M.P.; Chaves, J.B.P.; Coimbra, J.S.D.R. Quinoa: Nutritional, functional, and antinutritional aspects. Crit. Rev. Food Sci. Nutr. 2017, 57, 1618–1630. [Google Scholar] [CrossRef]
  49. Altuna, J.L.; Silva, M.; Álvarez, M.; Quinteros, M.F.; Morales, D.; Carrillo, W. Ecuadorian quinoa (Chenopodium quinoa Willd) fatty acids profile. Asian J. Pharm. Clin. Res. 2018, 11, 109. [Google Scholar]
  50. Peiretti, P.G.; Gai, F.; Tassone, S. Fatty acid profile and nutritive value of quinoa (Chenopodium quinoa Willd.) seeds and plants at different growth stages. Anim. Feed. Sci. Technol. 2013, 183, 56–61. [Google Scholar] [CrossRef] [Green Version]
  51. Alvarez-Jubete, L.; Wijngaard, H.; Arendt, E.K.; Gallagher, E. Polyphenol composition and in vitro antioxidant activity of amaranth, quinoa buckwheat and wheat as affected by sprouting and baking. Food Chem. 2010, 119, 770–778. [Google Scholar] [CrossRef]
  52. Simopoulos, A.P. Evolutionary aspects of diet, the omega-6/omega-3 ratio and genetic variation: Nutritional implications for chronic diseases. Biomed. Pharmacother. 2006, 60, 502–507. [Google Scholar] [CrossRef]
  53. Zotte, A.D.; Szendroe, Z. The role of rabbit meat as functional food. Meat Sci. 2011, 88, 319–331. [Google Scholar] [CrossRef]
  54. Cortinas, L.; Barroeta, A.; Villaverde, C.; Galobart, J.; Guardiola, F.; Baucells, M.D. Influence of the dietary polyunsaturation level on chicken meat quality: Lipid oxidation. Poult. Sci. 2005, 84, 48–55. [Google Scholar] [CrossRef]
  55. Xu, J.; Feng, L.; Jiang, W.D.; Wu, P.; Liu, Y.; Jiang, J.; Kuang, S.Y.; Tang, L.; Zhou, X.Q. Different dietary protein levels affect flesh quality, fatty acids and alter gene expression of Nrf2-mediated antioxidant enzymes in the muscle of grass carp (Ctenophar-yngodon idella). Aquaculture 2018, 493, 272–282. [Google Scholar] [CrossRef]
  56. Xue, T.; Wang, Y.Z.; Pan, Q.H.; Wang, Q.; Yuan, J.F.; Che, T.S. Establishment of a cell line from the kidney of black carp and its susceptibility to spring viremia of carp virus. J. Fish Dis. 2018, 41, 365–374. [Google Scholar] [CrossRef]
  57. Scaife, J.R.; Moyo, J.; Galbraith, H.; Michie, W.; Campbell, V. Effect of different dietary supplemental fats and oils on the tissue fatty acid composition and growth of female broilers. Br. Poult. Sci. 2007, 35, 107–118. [Google Scholar] [CrossRef] [PubMed]
  58. Abm, R.B.; Mun, H.S.; Yang, C.J. Breast and Thigh Meat Chemical Composition and Fatty Acid Profile in BroilersFed Diet with Dietary Fat Sources. J. Food Process. Technol. 2017, 8, 672. [Google Scholar]
  59. Saleh, A.A.; Alharthi, A.S.; Alhotan, R.A.; Atta, M.S.; Abdel-Moneim, A.M.E. Soybean Oil Replacement by Poultry Fat in Broiler Diets: Performance, Nutrient Digestibility, Plasma Lipid Profile and Muscle Fatty Acids Content. Animals 2021, 11, 2609. [Google Scholar] [CrossRef] [PubMed]
  60. Valdes, A.M.; Walter, J.; Segal, E.; Spector, T.D. Re: Role of the gut microbiota in nutrition and health. BMJ 2018, 361, 17–22. [Google Scholar]
  61. Ahir, V.B.; Koringa, P.G.; Bhatt, V.D.; Ramani, U.V.; Tripathi, A.K.; Singh, K.M.; Dhagat, U.M.; Patel, J.S.; Patel, M.M.; Katudia, K.H.; et al. Metagenomic analysis of poultry gut microbes. Indian J. Poult. Sci. 2010, 45, 111–114. [Google Scholar]
  62. Kaakoush, N.O. Insights into the role of erysipelotrichaceae in the human host. Front. Cell. Infect. Microbiol. 2015, 5, 84. [Google Scholar] [CrossRef] [Green Version]
  63. Fernando, S.C.; Purvis, H.T.; Najar, F.Z.; Sukharnikov, L.O.; Krehbiel, C.R.; Nagaraja, T.G.; Roe, B.A.; Desilva, U. Rumen microbial population dynamics during adaptation to a high-grain diet. Appl. Environ. Microbiol. 2010, 76, 7482–7490. [Google Scholar] [CrossRef] [Green Version]
  64. Jami, E.; White, B.A.; Mizrahi, I. Potential role of the bovine rumen microbiome in modulating milk composition and feed efficiency. PLoS ONE 2017, 9, e85423. [Google Scholar] [CrossRef] [PubMed]
  65. Meital, N.O.; Hadar, N.; Omry, K. Microbial Changes during Pregnancy, Birth, and Infancy. Front. Microbiol. 2016, 7, 1031–1033. [Google Scholar]
  66. Ruth, E.L.; Turnbaugh, P.J.; Samuel, K.; Jeffrey, I.G. Microbial ecology: Human gut microbes associated with obesity. Nature 2006, 444, 1022–1023. [Google Scholar]
  67. Marcobal, A.; Barboza, M.; Froehlich, J.W.; Block, D.E.; German, J.B.; Lebrilla, C.B.; Mills, D.A. Consumption of human milk oligosaccharides by gut-related microbes. J. Agric. Food Chem. 2010, 58, 5334–5340. [Google Scholar] [CrossRef] [Green Version]
  68. Wexler, A.G.; Goodman, A.L. An insider’s perspective: Bacteroides as a window into the microbiome. Nat. Microbiol. 2017, 2, 17026. [Google Scholar] [CrossRef]
  69. Venegas, D.P.; Fuente, M.; Landskron, G.; González, M.J.; Hermoso, M.A. Corrigendum:Short chain fatty acids(SCFAs)-mediated gut epithelial and immune regulation and Its relevance for inflammatory bowel diseases. Front. Immunol. 2019, 10, 277. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Vallès, Y.; Artacho, A.; Pascual-García, A.; Ferrús, M.L.; Gosalbes, M.J.; Abellán, J.J.; Francino, M.P. Microbial succession in the gut: Directional trends of taxonomic and functional change in a birth cohort of Spanish infants. PLoS Genet. 2014, 10, e1004406. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Ley, R.E.; Peterson, D.A.; Gordon, J.I. Ecological and Evolutionary Forces Shaping Microbial Diversity in the Human Intestine. Cell 2006, 124, 837–848. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Filippidou, S.; Wunderlin, T.; Junier, T.; Junier, T.; Jeanneret, N.; Dorador, C.; Molina, V.; Johnson, D.; Junier, P. A combination of extreme environmental conditions favor the prevalence of Endospore-forming Firmicutes. Front. Microbiol. 2016, 7, 1707. [Google Scholar] [CrossRef] [Green Version]
  73. Ley, R.E.; Bckhed, F.; Turnbaugh, P.; Lozupone, C.A.; Knight, R.D.; Gordon, J.I. Obesity alters gut microbial ecology. Natl. Acad. Sci. 2005, 102, 11070–11075. [Google Scholar] [CrossRef] [Green Version]
  74. Komaroff, A.L. The Microbiome and Risk for Obesity and Diabetes. JAMA J. Am. Med. Assoc. 2017, 317, 355–356. [Google Scholar] [CrossRef]
  75. Wang, H.; Ni, X.; Lei, L.; Dong, Z.; Jing, L.; Qing, X.; Li, G.; Pan, K.; Bo, J. Controlling of growth performance, lipid deposits and fatty acid composition of chicken meat through a probiotic, Lactobacillus johnsonii during subclinical Clostridium perfringens infection. Lipids Health Dis. 2017, 16, 1–10. [Google Scholar] [CrossRef] [Green Version]
  76. Madigan, M.T.; Martinko, J.M.; Parker, J. Brock Biology of Microorganisms, 11th ed.; Prentice Hall: Upper Saddle River, NJ, USA, 2005. [Google Scholar]
  77. Hossain, M.E.; Kim, G.M.; Lee, S.K.; Yang, C.J. Growth Performance, Meat Yield, Oxidative Stability, and Fatty Acid Composition of Meat from Broilers Fed Diets Supplemented with a Medicinal Plant and Probiotics. Asian-Australas. J. Anim. Sci. 2012, 25, 1159–1168. [Google Scholar] [CrossRef] [PubMed]
  78. Wang, B.H.; Wang, Y.; Rui, D.U.; Luo, Y.L.; Liu, C.; Yao, D.; Jin, Y. Research of Fatty Acid Deposition Mechanism in Adipose Tissue of Sunit Sheep. Sci. Technol. Food Ind. 2019, 40, 11–16. [Google Scholar]
  79. Yu, M.; Li, Z.; Rong, T.; Wang, G.; Liu, Z.; Chen, W.L.J.; Li, J.; Ma, X. Different dietary starch sources alter the carcass traits, meat quality, and the profile of muscle amino acid and fatty acid in finishing pigs. J. Anim. Sci. Biotechnol. 2020, 11, 78. [Google Scholar] [CrossRef] [PubMed]
  80. Yang, F. Effects of Paper Mulberry Silage on the Growth Performance, Rumen Microbiota and Muscle Fatty Acid Composition in Hu Lambs. Fermentation 2021, 7, 286. [Google Scholar]
  81. Frutos, P.; Hervás, G.; Natalello, A.; Luciano, G.; Fondevila, M.; Priolo, A.; Toral, P.G. Ability of tannins to modulate ruminal lipid metabolism and milk and meat fatty acid profiles. Anim. Feed. Sci. Technol. 2020, 269, 114623. [Google Scholar] [CrossRef]
Animals 12 03334 g001 550
Figure 1. Analysis of cecal microbial diversity. Notes: (A) Operational taxonomic units−Venn (OTU−Venn) analysis; (B) Saturation curve of species number (dilution curve); (C) Species accumulation box pattern; (D) PCA analysis.
Figure 1. Analysis of cecal microbial diversity. Notes: (A) Operational taxonomic units−Venn (OTU−Venn) analysis; (B) Saturation curve of species number (dilution curve); (C) Species accumulation box pattern; (D) PCA analysis.
Animals 12 03334 g001
Animals 12 03334 g002 550
Figure 2. Distribution of microbial abundance. Notes: (A) Microbe abundance distribution at phylum level; (B) Abundance distribution of genus-level microorganisms.
Figure 2. Distribution of microbial abundance. Notes: (A) Microbe abundance distribution at phylum level; (B) Abundance distribution of genus-level microorganisms.
Animals 12 03334 g002
Animals 12 03334 g003 550
Figure 3. Analysis of species difference between phylum level T-test groups.
Figure 3. Analysis of species difference between phylum level T-test groups.
Animals 12 03334 g003
Animals 12 03334 g004 550
Figure 4. Analysis of species differences between genus level T-test groups.
Figure 4. Analysis of species differences between genus level T-test groups.
Animals 12 03334 g004
Animals 12 03334 g005 550
Figure 5. Function prediction analysis.
Figure 5. Function prediction analysis.
Animals 12 03334 g005
Animals 12 03334 g006 550
Figure 6. Spearman correlation analysis of caecal microorganisms and muscle fatty acids at genus level. Note: (A) Correlation analysis between pectoral muscle fatty acids and cecal microorganisms; (B) Correlation analysis between fatty acids of leg muscle and cecal microorganisms. * indicates p < 0.05; ** indicates p < 0.01.
Figure 6. Spearman correlation analysis of caecal microorganisms and muscle fatty acids at genus level. Note: (A) Correlation analysis between pectoral muscle fatty acids and cecal microorganisms; (B) Correlation analysis between fatty acids of leg muscle and cecal microorganisms. * indicates p < 0.05; ** indicates p < 0.01.
Animals 12 03334 g006
Table
Table 1. Composition and nutrient level of experimental diets (dry matter basis).
Table 1. Composition and nutrient level of experimental diets (dry matter basis).
ItemsDiets (%)
CKQ4Q8Q12
Corn64.0064.0064.0064.00
Wheat middling12.008.004.000.00
Quinoa seeds0.004.008.0012.00
Soybean meal20.0020.0020.0020.00
Limestone1.201.201.201.20
CaHPO41.201.201.201.20
NaCl0.300.300.300.30
1% Premix1.001.001.001.00
Zeolite powder0.300.300.300.30
Total100100100100
Nutrient levels
Metabolic energy, ME (MJ/Kg)12.2412.3212.4012.48
Dry matter, DM84.2084.4384.6684.88
Crude protein, CP16.1216.1816.2516.31
Crude fiber, CF2.472.602.742.88
Ether extract, EE2.862.983.103.22
Calcium, Ca0.870.880.880.88
Total phosphorus, TP0.590.590.580.57
Available phosphorus, AP0.200.200.200.20
Lysine, Lys0.810.830.840.86
Methionine, Met0.260.300.330.36
Methionine + Cystine, Met + Cys0.560.590.610.64
Threonine, Thr0.620.620.620.62
Tryptophan, Trp0.190.190.180.18
Note: Premix (provided per kilogram of feed content): vitamin A, 158,000 IU; vitamin D, 44,000 IU; vitamin E, 500 IU; vitamin K, 39 mg; vitamin B1, 45 mg; vitamin B2, 125 mg; vitamin B8, 19 mg; vitamin B12, 0.24 mg; niacinamide, 790 mg; pantothenic acid, 300 mg; folic acid, 9 mg; H2O ≤ 8%; D-biotin, 2.9 mg; Zn, 730 mg; Fe, 1400 mg; Mn, 980 mg; Cu, 240 mg; I, 14 mg; Se, 4.8 mg; Ca, 10%; NaCl, 5~13%; total phosphorus (TP), 3.5%; choline chloride, 7000 mg. Nutrient level is calculated value.
Table
Table 2. Effect of quinoa on composition and content of fatty acids in breast muscle of female Luhua chicken %.
Table 2. Effect of quinoa on composition and content of fatty acids in breast muscle of female Luhua chicken %.
ItemsGroup
CKQ4Q8Q12
Butyric acid (C4:0)0.44 ± 0.14 a0.40 ± 0.06 a0.18 ± 0.06 c0.29 ± 0.08 b
Octanoic acid (C8:0)0.35 ± 0.07 a0.20 ± 0.02 ab0.16 ± 0.03 b0.18 ± 0.004 b
Myristic acid (C14:0)0.69 ± 0.05 a0.50 ± 0.03 d0.64 ± 0.09 b0.56 ± 0.05 c
Myristoleic acid (C14:1)0.21 ± 0.03 c0.27 ± 0.02 b0.21 ± 0.03 c0.30 ± 0.04 a
Pentadecanoic acid (C15:0)3.04 ± 0.632.87 ± 0.372.83 ± 0.622.56 ± 0.65
Palmitic acid (C16:0)26.96 ± 1.54 a24.84 ± 0.30 b24.88 ± 3.03 b25.43 ± 0.79 b
Palmitoleic acid (C16:1)4.64 ± 0.90 b5.82 ± 0.44 a5.46 ± 0.92 a5.35 ± 0.92 a
Heptadecanoic acid (C17:0)0.69 ± 0.17 a0.36 ± 0.09 b0.42 ± 0.10 b0.40 ± 0.05 b
Heptadecenoic acid (C17:1)0.56 ± 0.13 c0.83 ± 0.18 a0.69 ± 0.06 b0.67 ± 0.17 b
Stearic acid (C18:0)10.90 ± 1.11 a8.44 ± 0.30 b8.40 ± 1.21 b8.21 ± 0.63 b
Oleic acid (C18:1n9c)29.07 ± 5.50 b31.95 ± 2.16 a31.70 ± 4.22 a31.89 ± 2.32 a
Elaidic acid (C18:1n9t)0.29 ± 0.04 c0.51 ± 0.04 b0.49 ± 0.07 b1.04 ± 0.11 a
Linoleic acid (C18:2n6c)13.55 ± 1.25 a12.62 ± 1.50 b12.23 ± 1.39 b11.99 ± 1.01 b
Linolenic acid (C18:3n3)0.55 ± 0.13 b0.70 ± 0.04 a0.69 ± 0.08 a0.71 ± 0.06 a
γ-linoleic acid (C18:3n6)0.16 ± 0.050.17 ± 0.010.16 ± 0.030.14 ± 0.001
Eicosenoic acid (C20:1)0.26 ± 0.03 c0.49 ± 0.02 a0.42 ± 0.04 b0.41 ± 0.03 b
Eicosadienoic acid (C20:2)0.21 ± 0.04 c0.75 ± 0.02 a0.45 ± 0.04 b0.46 ± 0.05 b
Eicostrienoic acid (C20:3n6)0.56 ± 0.17 b0.74 ± 0.05 a0.56 ± 0.13 b0.64 ± 0.07 b
Arachidonic acid (AA,C20:4n6)4.73 ± 1.404.24 ± 1.044.76 ± 1.535.22 ± 1.35
Eicosapentaenoic acid (EPA,C20:5n3)0.86 ± 0.17 c1.08 ± 0.09 b1.07 ± 0.12 b1.27 ± 0.06 a
Behenic acid (C22:0)0.34 ± 0.120.30 ± 0.050.36 ± 0.070.35 ± 0.10
Docosahexaenoic acid (DHA, C22:6n3)0.37 ± 0.11 c0.68 ± 0.08 b0.67 ± 0.14 b0.81 ± 0.08 a
Nervonic acid (C24:1)1.12 ± 0.26 b1.76 ± 0.16 a1.55 ± 0.41 a1.74 ± 0.35 a
Saturated fatty acid (SFA)42.18 ± 4.33 a37.84 ± 0.62 b38.55 ± 1.62 b37.79 ± 1.22 b
Unsaturated fatty acid (UFA)57.82 ± 4.33 b61.90 ± 0.88 a62.50 ± 4.65 a62.10 ± 1.29 a
Monounsaturated fatty acid (MUFA)37.93 ± 3.60 a41.36 ± 2.01 b42.47 ± 6.69 b41.21 ± 2.72 b
Polyunsaturated fatty acid (PUFA)20.22 ± 2.5120.54 ± 1.6520.03 ± 2.4820.88 ± 2.09
n-3 Polyunsaturated fatty acids (n-3 PUFAs)1.83 ± 0.23 c2.46 ± 0.19 b2.45 ± 0.24 b2.79 ± 0.12 a
n-6 Polyunsaturated fatty acids (n-6 PUFAs)20.29 ± 2.63 a17.58 ± 1.87 b17.44 ± 1.93 b17.79 ± 1.90 b
n-6PUFA/n-3PUFA9.88 ± 1.59 a7.18 ± 0.91 b6.81 ± 1.37 b6.39 ± 0.65 c
PUFA/SFA0.53 ± 0.120.54 ± 0.040.54 ± 0.060.55 ± 0.05
Note: a,b,c,d Values with different superscripts in the same row are significantly different (p < 0.05).
Table
Table 3. Effect of quinoa on fatty acid composition and content in leg muscle of female Luhua chicken %.
Table 3. Effect of quinoa on fatty acid composition and content in leg muscle of female Luhua chicken %.
ItemsGroup
CKQ4Q8Q12
Lauric acid (C12:0) 0.04 ± 0.0080.04 ± 0030.04 ± 0.002
Tridecylic acid (C13:0) 0.51 ± 0.110.37 ± 0.020.46 ± 0.08
Myristic acid (C14:0)1.25 ± 0.09 a0.63 ± 0.06 b0.63 ± 0.11 b0.65 ± 0.07 b
Myristoleic acid (C14:1)0.24 ± 0.02 b0.42 ± 0.03 a0.44 ± 0.03 a0.42 ± 0.02 a
Pentadecanoic acid (C15:0)0.10 ± 0.0050.09 ± 0.0080.10 ± 0.010.90 ± 0.01
Pentadecenic acid (C15:1)0.20 ± 0.06 b0.35 ± 0.07 a0.35 ± 0.05 a0.36 ± 0.04 a
Palmitic acid (C16:0)27.41 ± 1.53 a25.76 ± 0.59 b26.06 ± 1.29 b26.03 ± 1.41 b
Palmitoleic acid (C16:1)5.50 ± 0.82 b7.63 ± 0.78 a7.63 ± 1.02 a7.45 ± 0.93 a
Heptadecanoic acid (C17:0)0.14 ± 0.01 a0.13 ± 0.02 b0.12 ± 0.02 b0.12 ± 0.02 b
Heptadecenoic acid (C17:1)0.13 ± 0.04 b0.28 ± 0.03 a0.28 ± 0.02 a0.26 ± 0.02 a
Stearic acid (C18:0)11.22 ± 1.55 a7.05 ± 1.55 b7.19 ± 1.02 b7.21 ± 0.61 b
Oleic acid (C18:1 n9c)29.89 ± 2.59 b34.14 ± 3.37 a33.12 ± 2.80 a34.19 ± 2.28 a
Elaidic acid (C18:1n9t)0.31 ± 0.03 c0.43 ± 0.04 b0.42 ± 0.03 b0.88 ± 0.05 a
Linoleic acid (C18:2n6c)14.37 ± 1.51 b15.44 ± 1.95 a14.93 ± 1.13 b14.31 ± 1.64 b
Linolelaidic acid (C18:2n6t)0.13 ± 0.01 a0.09 ± 0.02 b0.09 ± 0.02 b0.09 ± 0.02 b
Linolenic acid (C18:3n3)1.08 ± 0.04 d1.21 ± 0.09 c1.38 ± 0.07 a1.29 ± 0.06 b
γ-linoleic acid (C18:3n6)0.10 ± 0.03 d0.12 ± 0.02 c0.19 ± 0.04 a0.16 ± 0.03 b
Eicosenoic acid (C20:1)0.25 ± 0.04 b0.42 ± 0.04 a0.41 ± 0.05 a0.40 ± 0.03 a
Eicosadienoic acid (C20:2)0.19 ± 0.05 b0.31 ± 0.06 a0.16 ± 0.03 bc0.12 ± 0.06 c
Eicostrienoic acid (C20:3n6)0.35 ± 0.11 a0.25 ± 0.08 b0.36 ± 0.10 a0.30 ± 0.05 ab
Arachidonic acid (AA,C20:4n6)2.79 ± 0.72 a2.52 ± 0.62 ab2.18 ± 0.46 b2.48 ± 0.56 ab
Eicosapentaenoic acid (EPA,C20:5n3)0.70 ± 0.12 c0.81 ± 0.09 b0.92 ± 0.07 a0.84 ± 0.07 b
Heneicosan oic acid (C21:0)0.29 ± 0.05 a0.04 ± 0.002 b0.04 ± 0.002 b0.09 ± 0.05 b
Behenic acid (C22:0)0.24 ± 0.07 a0.15 ± 0.08 b0.15 ± 0.05 b0.20 ± 0.08 ab
Docosahexaenoic acid (DHA,C22:6n3)0.75 ± 0.10 c0.80 ± 0.04 b0.84 ± 0.03 a0.84 ± 0.06 a
Nervonic acid (C24:1)0.48 ± 0.16 b0.70 ± 0.14 a0.60 ± 0.12 a0.68 ± 0.11 a
Saturated fatty acid (SFA)42.85 ± 3.85 a34.27 ± 1.65 b34.76 ± 1.43 b34.73 ± 1.38 b
Unsaturated fatty acid (UFA)57.02 ± 4.11 b65.72 ± 1.66 a65.22 ± 1.44 a65.32 ± 1.42 a
Monounsaturated fatty acids (MUFA)36.65 ± 3.08 b44.34 ± 3.77 a43.24 ± 2.93 a44.56 ± 2.57 a
Polyunsaturated fatty acids (PUFA)19.85 ± 2.26 b21.38 ± 2.79 ab21.98 ± 2.38 a20.76 ± 2.76 ab
n-3 polyunsaturated fatty acids (n-3 PUFA)2.42 ± 0.37 d2.82 ± 0.17 c3.14 ± 0.13 a2.98 ± 0.14 b
n-6 polyunsaturated fatty acids (n-6 PUFA)17.43 ± 1.8318.36 ± 2.7318.69 ± 2.3517.68 ± 2.69
n-6PUFA/n-3PUFA8.10 ± 1.60 a6.52 ± 0.94 b5.96 ± 0.75 b5.94 ± 0.88 b
PUFA/SFA0.46 ± 0.07 b0.62 ± 0.08 a0.63 ± 0.07 a0.60 ± 0.09 a
Note: a,b,c,d Values with different superscripts in the same row are significantly different (p < 0.05).
Table
Table 4. Statistics of sample sequencing data processing results.
Table 4. Statistics of sample sequencing data processing results.
ItemsSample Group
CKQ4Q8Q12
Raw PE91,76788,87291,77188,116
Raw Tags85,36584,81588,06084,872
Clean Tags83,63683,12586,50783,432
Effective Tags63,24766,09667,84365,090
Base26,377,04727,643,82228,334,53027,092,227
AvgLen417418.33417.5416
Q2098.4498.3698.4598.515
Q3094.9594.7294.93595.11
GC (%)53.252.9053.2253.08
Effective (%)68.7774.3873.9873.95
Table
Table 5. Alpha diversity indices.
Table 5. Alpha diversity indices.
ItemsGroup
CKQ4Q8Q12
observed_species640.67 ± 24.53635.00 ± 76.96636.50 ± 54.56593.17 ± 47.69
Shannon6.54 ± 0.30 a5.98 ± 0.07 b6.17 ± 0.18 b6.10 ± 0.24 b
Simpson0.97 ± 0.01 a0.95 ± 0.01 b0.96 ± 0.01 ab0.96 ± 0.01 ab
chao1668.93 ± 18.73682.35 ± 89.63674.81 ± 56.79631.91 ± 52.24
ACE675.88 ± 20.52681.89 ± 88.39686.06 ± 55.86636.88 ± 48.49
PD_whole_tree43.46 ± 5.2443.88 ± 9.3639.70 ± 2.4938.58 ± 3.01
Note: a,b Values with different superscripts in the same row are significantly different (p < 0.05).
Table
Table 6. Annotated overview of cecal microbial species.
Table 6. Annotated overview of cecal microbial species.
OTU catalogue1209Annotated on Class level93.05%
Annotated on Database1179 (97.52%)Annotated on Class level89.00%
Annotated on Unclassified30 (2.48%)Annotated on Family level80.23%
Annotated on Kingdom level97.52%Annotated on Genus level40.03%
Annotated on Phylum level95.70%Annotated on Species level12.49%
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wu, T.; Jiang, X.; Yang, F.; Wei, Y.; Zhao, S.; Jiao, T. Effects of Dietary Quinoa Seeds on Cecal Microorganisms and Muscle Fatty Acids of Female Luhua Chickens. Animals 2022, 12, 3334. https://doi.org/10.3390/ani12233334

AMA Style

Wu T, Jiang X, Yang F, Wei Y, Zhao S, Jiao T. Effects of Dietary Quinoa Seeds on Cecal Microorganisms and Muscle Fatty Acids of Female Luhua Chickens. Animals. 2022; 12(23):3334. https://doi.org/10.3390/ani12233334

Chicago/Turabian Style

Wu, Tao, Xiaofan Jiang, Farong Yang, Yuming Wei, Shengguo Zhao, and Ting Jiao. 2022. "Effects of Dietary Quinoa Seeds on Cecal Microorganisms and Muscle Fatty Acids of Female Luhua Chickens" Animals 12, no. 23: 3334. https://doi.org/10.3390/ani12233334

APA Style

Wu, T., Jiang, X., Yang, F., Wei, Y., Zhao, S., & Jiao, T. (2022). Effects of Dietary Quinoa Seeds on Cecal Microorganisms and Muscle Fatty Acids of Female Luhua Chickens. Animals, 12(23), 3334. https://doi.org/10.3390/ani12233334

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop