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. 2024 Feb 7;103(4):103533. doi: 10.1016/j.psj.2024.103533

Genome sequencing of drake semen micobiome with correlation with their compositions, sources and potential mechanisms affecting semen quality

Xinyue Hu 1,1, Jie Li 1,1, Shuai Xin 1, Qingyuan Ouyang 1, Jialu Li 1, Lipeng Zhu 1, Jiwei Hu 1, Hua He 1, Hehe Liu 1, Liang Li 1, Shenqiang Hu 1, Jiwen Wang 1,2
PMCID: PMC10878113  PMID: 38359770

Abstract

Artificial insemination (AI) technology has greatly promoted the development of the chicken industry. Recently, AI technology has also begun to be used in the duck industry, but there are some problems. Numerous researchers have shown that microbes colonizing in semen can degrade semen quality, and AI can increase the harmful microbial load in hen's reproductive tract. Different from the degraded external genitalia of roosters, drakes have well-developed external genitalia, which may cause drake semen to be more susceptible to microbial contamination. However, information on the compositions, sources, and effects of semen microbes on semen quality remains unknown in drakes. In the current study, high-throughput sequencing technology was used to detect microbial communities in drake semen, environmental swabs, cloacal swabs, and the spermaduct after quantifying the semen quality of drakes to investigate the effects of microbes in the environment, cloaca, and spermaduct on semen microbiota and the relationships between semen microbes and semen quality. Taxonomic analysis showed that the microbes in the semen, environment, cloaca, and spermaduct samples were all classified into 4 phyla and 25 genera. Firmicutes and Proteobacteria were the dominant phyla. Phyllobacterium only existed in the environment, while Marinococcus did not exist in the cloaca. Of the 24 genera present in semen: Brachybacterium, Brochothrix, Chryseobacterium, Kocuria, Marinococcus, Micrococcus, Rothia, Salinicoccus, and Staphylococcus originated from the environment; Achromobacter, Aerococcus, Corynebacterium, Desemzia, Enterococcus, Jeotgalicoccus, Pseudomonas, Psychrobacter, and Turicibacter originated from the cloaca; and Agrobacterium, Carnobacterium, Chelativorans, Devosia, Halomonas, and Oceanicaulis originated from the spermaduct. In addition, K-means clustering analysis showed that semen samples could be divided into 2 clusters based on microbial compositions, and compared with cluster 1, the counts of Chelativorans (P < 0.05), Devosia (P < 0.01), Halomonas (P < 0.05), and Oceanicaulis (P < 0.05) were higher in cluster 2, while the sperm viability (P < 0.05), total sperm number (P < 0.01), and semen quality factor (SQF) (P < 0.01) were lower in cluster 2. Furthermore, functional prediction analysis of microbes showed that the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, microbial metabolism in diverse environments, and quorum sensing pathways between cluster 1 and cluster 2 were significantly different (P < 0.05). Overall, environmental/cloacal microbes resulted in semen contamination, and microbes from the Chelativorans, Devosia, Halomonas, and Oceanicaulis genera may have negative effects on semen quality in drakes by affecting the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, and quorum sensing pathways that are associated with carbohydrate metabolism. These data will provide a basis for developing strategies to prevent microbial contamination of drake semen.

Key words: 16SrRNA sequencing, artificial insemination, Cloaca, environment, spermaduct

INTRODUCTION

Since the 21st century, global market demand for poultry meat has increased year by year from 71,293,729.64 tons in 2001 to 139,219,230.84 tons in 2022 (FAO, 2024), which prompted the development of intensive rearing systems and AI technology in the poultry industry (Campbell et al., 2019; Shaheen, et al., 2020). As early as the last half of 20th century, AI technology began using in the chicken industry to improve fertility and achieve breeding goals (Bilcik et al., 2005; Santiago-Moreno and Blesbois, 2022). Habibullah et al. (2015) pointed out that compared to natural mating, AI technology could produce more chicks per hen; and the actual mating capability of each rooster could be increased tenfold through AI technology (Kharayat et al., 2016; Santiago-Moreno et al., 2016). Recently, breeders have also started applying this technology in the duck industry (Ouyang et al., 2021; Tang et al., 2022). However, in production applications, AI in ducks appears to reduce egg quality and increase the likelihood of health issues such as rectocele, peritonitis, salpingitis, and ascites in female ducks.

Microbes, widely distributed in the environment, play crucial roles in various physiological processes including immunomodulation (Kau et al., 2011), defense (Flowers and Grice, 2020), metabolism (Le Chatelier et al., 2013), neurodevelopment (Ma et al., 2019), and the digestion/absorption of nutrients (Yuan et al., 2020). Some emerging researches suggested that microbes even presented in the semen of mammals and could negatively affect semen quality (Cojkic et al., 2021; Zhang et al., 2020), and Haines et al. (2013) found that exposure to microbes could reduce sperm motility in broiler breeders, while the addition of penicillin (200 U/mL) to semen improved semen quality in Indian red jungle fowl (Rakha et al., 2023). However, unlike mammals, which have separate reproductive channel and collect semen using false mount method. Poultry, collecting semen by abdominal massage method, have a common channel (cloaca) connecting the reproductive channel and intestine to the external environment (Łukaszewicz et al., 2015; Lee et al., 2020; Nadaf et al., 2022). These differences make the mammalian methods that respectively use ultraviolet light and alcohol to sterilize the equipment (e.g., false mounts, glass tubes, and straws) required for semen collection and the area around the male external genitalia to prevent microbial contamination of semen are unsuitable for poultry (Althouse et al., 2000; Sannat et al., 2015). In other words, the semen used for AI in poultry is more susceptible to microbial contamination during collection (Althouse et al., 2000; Łukaszewicz et al., 2015; Sannat et al., 2015; Lee et al., 2020; Nadaf et al., 2022). Shaheen et al. (2020) observed significantly higher loads of Escherichia coli, Salmonella Pullorum, and Mycoplasma gallisepticum in hens and their offspring in the AI group compared to those in the natural mating group, which result sufficient support the view. Previous reports indicated that the external genitalia of roosters will degenerate during the embryonic stage, whereas drakes possess developed external genitalia (Hamburger and Hamilton, 1951; Herrera, et al., 2013), allowing outside microbes to enter the reproductive tract along the exposed genitalia after each ejaculation, thus contaminating the semen with microbes. Based on this information, it is speculated that the negative effects of AI in the duck industry may be caused by semen microbes. However, there is a lack of microbial studies on poultry semen.

With the development of high-throughput sequencing technology, methods targeting 16S ribosomal ribonucleic acid (16SrRNA) gene sequencing have been used to conduct studies of microbial communities, which played vital roles in revealing microbial sources and action mechanisms (Westermann and Vogel, 2021; Ma et al., 2023). Therefore, the present study aims to: 1) Investigating the microbiota of the semen, environment, cloaca, and spermaduct in drakes using 16SrRNA sequencing to reveal the diversity and origin of the microbiota in drake semen; 2) Exploring the relationships between semen microbiota and semen quality parameters in drakes. These data will useful for finding potential biomarkers to correlate with semen quality and developing strategies to prevent semen contamination by exogenous microbes in drakes.

MATERIALS AND METHODS

Ethics Statement

All experimental procedures involving animal handling were approved by the Institutional Animal Care and Use Committee (IACUC) of Sichuan Agricultural University (Chengdu Campus, Sichuan, China) under Approval No. DKY20170913.

Management of Experimental Drakes

A total of 20 drakes, incubated in the same batch and reared by the Sichuan Agricultural University Waterfowls Breeding Farm (Ya'an, Sichuan, China), were used as experimental animals. At 140 d of age, the drakes were moved to single cages and kept under natural temperature and light conditions, with lights on from 6 am to 11 pm, as well as unlimited food/water. At 190 d of age, all drakes were trained in the abdominal massage technique by a skilled technician until semen was successfully collected from every drake.

Sample Collection and Semen Quality Analysis

In the present study, the semen (collected by abdominal massage), cloacal swabs (10 sterile cotton swabs were wiped cloaca after soaking in sterile phosphate buffered saline solution), and environmental swabs (3 sterile gauzes were wiped breeding cage after soaking in sterile phosphate buffered saline solution) from the 20 drakes (2 of them were in moult and could not collect semen, so they were discarded) were collected at a 3-d interval from 400 to 408 d of age. Meanwhile, 20 µL of each semen sample was absorbed after measuring volume to assess sperm viability, sperm concentration, total sperm number, and morphological abnormal sperm according to the methods we previously reported (Tang et al., 2022), and the procedures were detailed in below: 1) 10 µL semen was mixed with 200 µL of 1% trypan blue solution (Solarbio, Beijing, China) and incubated for 15 min. Sperm viability was assessed by placing 10 µL of stained semen on a preheated slide (37℃) and a phase contrast microscope (Olympus, Tokyo, Japan) at 400 × was used to observe the color about 200 sperm. Sperm that stained blue were considered dead, while unstained sperm were considered to be viable; 2) 10 µL semen-diluent that was diluted with 3% stroke-physiological saline solution (NaCl) at a ratio of 1:800 was added on a hemocytometer to measure sperm concentration under a phase contrast microscope (Olympus, Tokyo, Japan) at 400 ×; 3) 20 µL semen-diluent that was diluted with 0.9% NaCl at a ratio of 1:20 was smeared onto a slide and air-dried, and then stained with 0.5% gentian violet solution (Sangon, Shanghai, China) for 3 min. The morphology about 300 sperm on the slide was observed under a phase contrast microscope (Olympus, Tokyo, Japan) at 400 ×. Morphological abnormal sperm was determined as the proportion of sperm that was not linear from head to tail out of the 300 sperm. Subsequently, the semen quality factor (SQF) of each drake was calculated by following formula: SQF = semen volume (mL) × sperm viability (%) × sperm concentration (× 106/mL) × morphologically normal sperm (%) (Liu, et al., 2008). Four d after completing the semen, cloacal swabs, and environmental swabs collection, the 18 drakes were sacrificed by carotid artery bloodletting after carbon dioxide anesthesia to collect their spermaduct. All spermaduct was rapidly frozen by liquid nitrogen and stored at -80 ℃ until DNA isolation.

DNA Extraction, Library Preparation, and Sequencing

The E.Z.N.A. Stool DNA Kit (Omega Bio-Tek, Norcross, GA) was used to extract total genomic DNA from the semen, cloacal swabs, environmental swabs, and spermaduct samples according to the manufacturer's instructions. The V3–V4 hypervariable regions of microbial 16S rRNA genes were enriched by PCR after the total genomic DNA was qualified using a NanoDrop 2,000 Microultraviolet Spectrophotometer (Thermo Fisher Scientific, Wilmington, NC) and an Agilent 2100 Bioanalyzer (Agilent Technologies, CA), and systems of PCR reaction were as follows: the PCR components contained 2 µL of DNA template, 5 µL of Q5 reaction buffer (5 ×), 0.25 µL of Q5 High-Fidelity DNA Polymerase (5U/µL), 5 µL of Q5 High-Fidelity GC buffer (5 ×), 2 µl (2.5 mM) of dNTPs, 1 µL (10 µM) of forward primer (338-F: 5′-ACTCCTACGGGAGGCAGCAG-3′), 1 µL (10 µM) of reverse primer (806-R: 5′-GGACTACNNGGGTATCTAAT-3′), and 8.75 µL of ddH2O; the PCR reaction conditions consisted of an initial denaturation (98℃ for 2 min), denaturation (98℃ for 15 s), annealing (55℃ for 30 s), extension (72℃ for 30 s), and a final extension (72℃ for 5 min), a total of 25 cycles. Agencourt AMPure Beads (Beckman Coulter, IN), was used to purify the PCR products. Respectively, the equimolar amplicons were absorbed from 72 purified products as libraries and sent to Kaitai Co., Ltd. (Hangzhou, China) for paired-end sequencing on Illumina Nova-PE150 platform.

Bioinformatics Analysis

The FLASH (version 1.2.11) software was used to assemble paired-end reads of the 72 samples (Magoč and Salzberg, 2011). Then, QIIME2 (version 2021.2) software was used to eliminate the low-quality data that meet following criteria (Gill, et al., 2006; Chen and Jiang, 2014): 1) The length of sequences less than 150 bp; 2) The average Phred scores of sequences less than 20; 3) Sequences contained ambiguous bases; 4) Sequence continuously existed more than 8 same mononucleotide. The remaining high-quality sequences were performed noise reduction and clustered into zero-radius operational taxonomic units (ZOTU) at 97% sequence identity by using Usearch (version 11.0.667) software (Edgar, 2010). In order to minimize difference of sequencing depth across samples, Usearch (version 11.0.667) software was also used to standardize the ZOTUs of each sample at a frequency of 10,000. All ZOTUs were mapped to the Greengenes Database using QIIME2 (version 2021.2) software to obtain the taxonomic classification of phylum, class, order, family, genus, and species (Bolyen, et al., 2019). Vegan (version 2.6.4) package was used to perform principal coordinate analysis (PCoA) and canonical correspondence analysis (CCA) to compare microbial communities across samples (Gower, 1966; Zhou et al., 2023a). The K-means clustering algorithm in stats (version 4.1.2) package and ANOSIM function in vegan (version 2.6.4) package were used to divide semen samples into 2 clusters according to the similarities of microbial compositions (Ikotun and Ezugwu, 2022). Tax4Fun2 (version 1.1.5) package was used to predict the functions of microbes, and the statistical differences of microbial functions between 2 clusters were calculated by using Linear Discriminant Analysis Effect Size (LEfSe) analysis with screening criteria were Linear discriminant analysis (LDA) score > 3 and P < 0.05 (Segata et al., 2011).

Statistical Analysis

Semen quality parameters (including semen volume, sperm viability, sperm concentration, total sperm number, morphological abnormal sperm, and SQF) and microbial abundance of the 2 clusters were subjected to t-test by using SPSS 27.0 software (IBM, Chicago, IL), and P < 0.05 was considered to have statistical significances. GraphPad Prism 8.0 software (GraphPad Software, San Diego, CA) was used to plot the pictures in the form of mean ± standard error.

RESULTS

Microbial Compositions in Semen, Environment, Cloaca, and Spermaduct

In the present study, a total of 1,332 ZOTUs were identified from 72 samples. These ZOTUs were classified into 4 phyla, 7 classes, 11 orders, 20 families, and 25 genera. As shown in Supplementary Table S1, the 4 phyla were Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria; and the 25 genera were Achromobacter, Aerococcus, Agrobacterium, Brachybacterium, Brochothrix, Carnobacterium, Chelativorans, Chryseobacterium, Corynebacterium, Desemzia, Devosia, Enterococcus, Halomonas, Jeotgalicoccus, Kocuria, Marinococcus, Micrococcus, Oceanicaulis, Pseudomonas, Psychrobacter, Rothia, Salinicoccus, Staphylococcus, Phyllobacterium, and Turicibacter. Notably, Phyllobacterium only existed in the environment, while Marinococcus did not exist in the cloaca. Moreover, in the semen, dominant phylum was Proteobacteria which abundance reached 59.406%, and the Psychrobacter was dominant genus with an abundance of 25.233% (Figure 1A, Supplementary Table S1). In the environment, Firmicutes was dominant phylum with an abundance of 53.747%, and dominant genus was Staphylococcus which abundance reached 22.367% (Figure 1B, Supplementary Table S1). In the cloaca, Proteobacteria with an abundance of 73.671% was the dominant phylum, and Psychrobacter with an abundance of 69.715% was the dominant genus (Figure 1C, Supplementary Table S1). In the spermaduct, dominant phylum and genus were Proteobacteria and Psychrobacter, and their abundance reached 66.326% and 26.154% (Figure 1D, Supplementary Table S1), respectively.

Figure 1.

Figure 1

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Microbial compositions at phylum and genus levels. (A) Microbial compositions of semen at phylum and genus levels. (B) Microbial compositions of environment at phylum and genus levels. (C) Microbial compositions of cloaca at phylum and genus levels. (D) Microbial compositions of spermaduct at phylum and genus levels. Different colors in the figures represent different microbes at phylum or genus levels.

Contributions of Microbes in Environment, Cloaca, and Spermaduct to Semen Microbiota

The PCoA analysis showed that the microbial compositions of the semen, environment, spermaduct, and cloaca were similar to some extent, and the microbial compositions of the semen and environment were more similar (Supplementary Figure S1). In order to analyze the contributions of microbes in the environment, cloaca, and spermaduct to the semen microbiota, the counts of various microbes in the environment, cloaca, and spermaduct were considered as environmental variables to perform CCA analysis with the corresponding microbes in semen. As shown in Figure 2, the environment, cloaca, and spermaduct microbes could affect the semen microbiota in drakes, and 9 kinds of semen microbes that including Brachybacterium, Brochothrix, Chryseobacterium, Kocuria, Marinococcus, Micrococcus, Rothia, Salinicoccus, and Staphylococcus mainly originated from the environment; 9 kinds of semen microbes that including Achromobacter, Aerococcus, Corynebacterium, Desemzia, Enterococcus, Jeotgalicoccus, Pseudomonas, Psychrobacter, and Turicibacter mainly originated from the cloaca; 6 kinds of semen microbes that including Agrobacterium, Carnobacterium, Chelativorans, Devosia, Halomonas, and Oceanicaulis mainly originated from the spermaduct.

Figure 2.

Figure 2

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CCA analysis between semen microbes and corresponding microbes in environment/cloaca/spermaduct. Abbreviations: S, semen; E, environment; C, cloaca; SD, spermaduct; CCA, canonical correspondence analysis.“●” represents semen samples; “+” represents microbes at genus level; “→” represents contribution degrees of microbes in environment, cloaca, and spermaduct to semen microbes, and longer the red lines, the contribution degrees were greater.

Similarity Analysis of Microbial Compositions in Semen

The K-means clustering algorithm, based on euclidean distances, found that 18 semen samples could be divided into 2 clusters according to the similarities of ZOTUs distributions after 10 iterations, in which the cluster 1 consists of 14 samples, while cluster 2 consists of 4 samples (Figure 3A). Further ANOSIM analysis showed that the structure of microbial communities between 2 clusters was significantly different (Figure 3B) (R = 0.339, P = 0.021).

Figure 3.

Figure 3

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Similarity analysis of microbes in semen.(A) K-means clustering scatterplot of semen samples. Semen samples were divided into 2 clusters after 10 iterations. (B) Box plot of intergroup and intragroup beta distance of cluster 1 and cluster 2. Abbreviation: S, semen. “Between” represents the differences between cluster 1 and cluster 2; “Cluster 1” and “Cluster 2” respectively represent the differences within clusters; “R = 0.339 > 0.200” means that differences between clusters were greater than the differences within clusters indicating the cluster division was effective.

Semen Microbe Compositions and Semen Quality Parameters Comparison Between Cluster 1 and Cluster 2

In analyzing the microbial compositions of semen, the present study found that the counts of Firmicutes in cluster 1 was significantly higher than that in cluster 2 (P < 0.05), and the counts of Proteobacteria (P < 0.05), Chelativorans (P < 0.05), Devosia (P < 0.01), Halomonas (P < 0.05), and Oceanicaulis (P < 0.05) were significantly lower than those in cluster 2 (Figure 4). In addition, the results of semen quality parameters showed that the semen volume, sperm viability, sperm concentration, total sperm number, morphological abnormal sperm, and SQF in cluster 1 were better than those in cluster 2, and there were statistical differences in sperm viability (P < 0.05), total sperm number (P < 0.01), and SQF (P < 0.01) between cluster 1 and cluster 2 (Table 1).

Figure 4.

Figure 4

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Microbes with statistical differences between cluster 1 and cluster 2 at phylum and genus levels. Data was displayed as “mean ± standard error” in figure. “*” means P < 0.05; “**” means P < 0.01.

Table 1.

Semen quality parameters of drakes in cluster 1 and cluster 2.

Semen variables Cluster 1(n = 14) Cluster 2 (n = 4) P value2
Semen volume (mL) 0.313 ± 0.033 0.263 ± 0.050 0.673
Sperm viability (%) 88.100 ± 1.006 83.727 ± 1.081 0.045*
Sperm concentration (109/mL) 4.997 ± 0.465 3.190 ± 0.466 0.089
Total sperm number (109) 1.620 ± 0.313 0.744 ± 0.031 0.005**
Morphological abnormal sperm (%) 3.708 ± 0.178 4.190 ± 0.227 0.294
SQF1 1407.621 ± 261.921 556.640 ± 29.084 0.002**
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1

SQF: semen quality factor.

2

“*” indicated that the result of t-test was significant (P < 0.05). “**”indicated that the result of t test was extremely significant (P < 0.01). Data was displayed as “mean ± standard error” in table.

Functional Prediction Analysis of Microbes Between Cluster 1 and Cluster 2

As shown in Supplementary Table S2, the functions of semen microbes were predicted in 334 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the dominant pathways (with an abundance higher than 5%) in semen microbes were ABC transporters, biosynthesis of secondary metabolites, microbial metabolism in diverse environments, and metabolic pathways. Furthermore, LEfSe analysis indicated that the activities of phosphotransferase system and starch and sucrose metabolism pathways in semen microbes of cluster 2 were higher than those in cluster 1, while the activities of ABC transporters, microbial metabolism in diverse environments, and quorum sensing pathways in semen microbes of cluster 2 were lower than those in cluster 1 (Figure 5) (LDA score > 3, P < 0.05).

Figure 5.

Figure 5

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LDA score distributions of semen microbes between cluster 1 and cluster 2. Abbreviations: LDA, Linear discriminant analysis.

DISCUSSION

In the present study, microbial classifications showed that 4 phyla including Actinobacteria (0.254 ± 0.068%), Bacteroidetes (0.304 ± 0.206%), Firmicutes (40.036 ± 7.351%), and Proteobacteria (59.406 ± 7.275%) existed in drake semen. These results are consistent with the previous results obtained in boar and stallion semen (Zhang et al., 2020; Quiñones-Pérez et al., 2022). Given the special structure that both the intestine and well-developed external genitalia of drakes are connected to the external environment by the cloaca (Lee et al., 2020), it was hypothesized that microbes in the environment and cloaca might enter the semen during semen collection to affect the microbial compositions of semen. Interestingly, the current study found that only the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria presented in the environment, cloaca, and spermaduct too, and Firmicutes and Proteobacteria were the dominant phyla in all of them. At the same time, the results of further PCoA analysis revealed similar microbial structures in the semen, environment, cloaca, and spermaduct. These results support the hypothesis that drake semen can be contaminated by exogenous microbes during artificial collection.

When the current study attempted to determine the contributions of microbes in the environment, cloaca, and spermaduct to microbiota of drake semen, CCA analysis revealed that 9 (including Brachybacterium, Brochothrix, Chryseobacterium, Kocuria, Marinococcus, Micrococcus, Rothia, Salinicoccus, and Staphylococcus) of the 24 genera identified from the semen mainly originated from the environment; 9 (including Achromobacter, Aerococcus, Corynebacterium, Desemzia, Enterococcus, Jeotgalicoccus, Pseudomonas, Psychrobacter, and Turicibacter) genera mainly originated from the cloaca; and 6 (including Agrobacterium, Carnobacterium, Chelativorans, Devosia, Halomonas, and Oceanicaulis) genera mainly originated from the spermaduct. These results indicate that the environmental and cloacal microbes are the main contributors to pollute drake semen. Previous reports indicated that microbial infections, especially some pathogenic microbes, could reduce the fertility and physiological health of the host (Boonthai et al., 2016; Brennan and Garrett, 2019). Notably, among the 24 genera of microbes presented in drake semen, 8 genera that mainly originated from the environment and cloaca were pathogenic microbes. Achromobacter is a key pathogen causing lung injury (Veschetti et al., 2022; Zhou et al., 2023b); Aerococcus not only associated with urinary tract and bloodstream infections in human (Tai et al., 2021), but also has been reported to be associated with infectious diarrhea in poultry (Khafagy et al., 2023); and Corynebacterium (Enurah et al., 2016), Enterococcus (Dolka et al., 2017), Kocuria (Yang et al., 2021; Ziogou et al., 2023), Pseudomonas (Pattison et al., 2008), Rothia (Zhang et al., 2022), and Staphylococcus infections could affect lots of diseases such as haemorrhagic inflammation of the upper respiratory tract, vertebral abscess, necrotic enteritis, and hepatomegaly (Szafraniec et al., 2022), etc. These results suggest that the negative effects of AI in the duck industry may be due to import the harmful microbes into the reproductive tract of female ducks. Therefore, it is necessary to reduce the risks of exogenous microbes entering drake semen, and further researches should focus on developing effective strategies to control semen contamination by environmental and cloacal microbes.

Some reports have found that semen microbes could affect semen quality in mammals (Zhang et al., 2020; Cojkic et al., 2021; Quiñones-Pérez et al., 2022). In order to reveal whether semen microbes affected semen quality of drakes, all semen samples were divided into 2 clusters according to the similarities of ZOTUs distributions in the present study. Subsequently, results of ANOVA analysis showed that the counts of Chelativorans, Devosia, Halomonas, and Oceanicaulis in cluster 2 were higher than those in cluster 1. Meanwhile, compared with cluster 1, the cluster 2 had lower sperm viability, total sperm number, and SQF. These results suggest that Chelativorans, Devosia, Halomonas, and Oceanicaulis might negatively impact the semen quality of drakes. In addition, functional prediction analysis of microbes showed that there were statistical differences in the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, microbial metabolism in diverse environments, and quorum sensing pathways between cluster 1 and cluster 2. A previous study reported that the phosphotransferase system could catalyze the transport and phosphorylation of carbohydrates in bacteria (Bidart et al., 2023); ABC transporters were the key carriers of carbohydrate transport and metabolism (Chandravanshi et al., 2019); and quorum sensing was a cell density-dependent gene regulation system that played an important role in carbohydrate metabolism (Zeng et al., 2021). All results of the present study suggest that Chelativorans, Devosia, Halomonas, and Oceanicaulis might affect the semen quality of drakes by regulating carbohydrate metabolism.

CONCLUSIONS

In conclusion, the present study found that a large number of microbes including pathogens such as Achromobacter, Aerococcus, Corynebacterium, Enterococcus, Kocuria, Pseudomonas, Rothia, and Staphylococcus existed in the semen of drakes, and these microbes mainly originated from the environment and cloaca. Furthermore, the microbes of Chelativorans, Devosia, Halomonas, and Oceanicaulis might affect the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, and quorum sensing pathways to regulate carbohydrate metabolism, thereby reducing the semen quality of drakes. This study not only revealed the compositions and main sources of semen microbes in drakes, but also identified 4 potential microbes (including Chelativorans, Devosia, Halomonas, and Oceanicaulis) affecting semen quality in drakes. However, the measures to prevent microbial contamination in drake semen still need to be further explored.

ACKNOWLEDGMENTS

This research was supported by China Agriculture Research System of MOF and MARA (CARS-42-4), Key Technology Support Program of Sichuan Province (2021YFYZ0014), and Establishment and Demonstration Extension of Breeding Ability Selection System of Nonghua Drakes (22ZDYFZF0005) for the financial support.

DISCLOSURES

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.103533.

Appendix. Supplementary materials

mmc1.docx (208.9KB, docx)
mmc2.docx (35.2KB, docx)
mmc3.docx (50.8KB, docx)

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