Avian leukosis virus subgroup J infection influencing composition of gut microbiota within chicken

Background: Avian leukosis virus (ALV) is one of the major causes of disease in poultry. Probiotics play a critical role in animal health maintenance. Studies have indicated that viral infection can alter the composition of chicken gut flora. We hypothesized that the ALV-J infection could alter Probiotics composition in chicken fecal bacterial microbiome. To test is, w e performed high-throughput 16S rRNA gene sequencing and evaluated gut flora proﬁles from the feces of ALV-J infected and healthy chickens. Results: Relative abundance at the phylum and species levels was calculated. The phylum Proteobacteria was expressed in higher abundance in ALV-J infected chickens than in healthy chickens. Additionally, the abundance of the opportunistic pathogen, Propionibacterium acnes , significantly increased in ALV-J infected chickens. Interestingly, ALV-J infection tended to be significantly decreased by the probiotics Lactobacillus helveticus and Lactobacillus reuteri. Conclusions: The study indicated ALV-J infection significantly altered the gut microbiota distribution in chickens. It also showed that ALV-J infection significantly influenced composition of the probiotics including Lactobacillus helveticus and Lactobacillus reuteri in chicken gut, which implied that to relieve avian leucosis subgroup J, microbiota-targeted therapies such as probiotic supplements are required.


Background
Avian leukosis virus (ALV) is one of the major causes of disease in poultry and commonly produces tumors and immunosuppression in infected chickens. The subgroup J ALV (ALV-J) shows greater pathogenicity and transmission ability than the other subgroups [1]. ALV-J is primarily associated with myeloid leukosis (ML) in broiler breeders. ALV-J infection of broilers was first detected in China in 1999. During the past decade, the host range of 3 ALV-J has gradually expanded to commercial layers, the Chinese local breeds [2][3][4], suggesting ALV-J infection has been a major problem in China.
Host health is highly on maintaining stasis within the gut microflora [5][6][7]. The gastrointestinal tracts (GITs) of chickens harbor various bacteria [8,9]. Therefore, the microbial communities inhabiting the gastrointestinal tract (GIT) of chickens affect the animals' health [10]. However, this delicate balance of gut microbiome can be disrupted by many situations, including chronic viral infections [11,12]. An increasing number of studies have indicated that viral infection can alter the composition of chicken gut flora.
For example, Marek's disease virus changes the core gut microbiome of the chicken during different phases of viral replication [13]. IBDV virus infection significantly influences microbiota composition [14]. Influenza A virus subtype H9N2 infection disrupts the composition of intestinal microbiota of chickens [15].
A previous study showed that ALV-J infected chickens with 21-day-old were characterized by a larger number of notable pathogens from Proteobacteria, and other condition pathogens [16]. However, little is known about effect of ALV-J infection on probiotics within the chicken microflora. Probiotics is a term defined by a United Nations and World Health Organization Expert Panel as "live microganisms which when administered in adequate amounts confer a health benefit on the host". Probiotics ferment undigested carbohydrate residues to produce high levels of short chain fatty acids (SCFAs), which results in acidic environment that is not conducive for the growth of pH-sensitive pathogenic bacteria. Lactobacillus and Bifidobacterium spp. of human intestinal origin produce antimicrobial substances against enteropathogenic microorganisms involved in diarrhea [17]. Strains of Lactobacillus acidophilus interfere with a wide range of pathogens [18][19][20]. So, gut Probiotics play a critical role in animal health maintenance. We hypothesized that the ALV-J infection could alter Probiotics composition in chicken fecal 4 bacterial microbiome. To test it, an extensive microbial diversity survey was conducted in the present study by evaluating the differences in the gut flora of chickens infected with ALV-J compared to healthy chickens using high-throughput 16S rRNA gene sequencing with the Illumina MiSeq platform. Our results indicated that ALV-J infection significantly influenced composition of the probiotics including Lactobacillus helveticus and Lactobacillus reuteri in chicken gut microbiome.

Phyla composition exhibited significant microbial differences between theALV-J infected chickens and the control
Each sample was rarefied to 17,595 sequences; with a threshold of 97% sequence identity, 16,740 unique OTUs were identified in the samples. Total sequences were assigned to 38 phyla (3 archaeal phyla and 35 bacterial phyla). Bacterial phyla isolated from the samples included Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. Distribution of the four phyla, in group A (viral control), showed that the gut microflora was primarily dominated by Firmicutes phyla, the other phyla appeared in smaller quantities including Actinobacteria, Bacteroidetes, and Proteobacteria. Meanwhile, in group B (ALV-J infected chickens), gut microbiota was dominated by both Firmicutes and Proteobacteria, with other phyla noted in smaller quantities including Bacteroidetes,Actinobacteria, and a few other unknown phyla (Fig 1). These results matched a recent study related to microbial diversity in chickens which also found that Firmicutes, Actinobacteria, Proteobacteria, and Interestingly, two of the phyla including Firmicutes and Proteobacteria were found to be proportionally significantly different between the A and B groups (P < 0.05). Among the two phyla, Proteobacteria concentration was much higher in group B than in group A (Fig   1). These results indicated that ALV-J infection had a significant impact on the proportion 5 of Firmicutes and Proteobacteria at the phylum level.

ALV-J infected chickens and the control
Principal coordinate analysis was conducted based on weighted UniFrac distances to assess the microbial distribution between the two groups. Results of weighted UniFrac analysis depicted a notable distribution difference for PC2; However, no difference in distribution for PC1 was observed. The gut microbial community of group A was substantially separated from that of group B ( Fig. 2A) were present in group A (Fig. 2B). The defined taxa are potential biomarkers for group A and group B. For example, Proteobacteria can serve as biomarkers for ALV-J infection in chickens at the phylum, order, and class levels, while a few taxa were markers for the healthy chickens, the most prominent were members of the family Lactobacillaceae. The heatmap displayed a similar pattern in Fig. 2C. These results suggested that the composition of chicken gut microflora was significantly altered due to ALV-J infection.

Difference for composition of probiotics in chicken gut microbial flora found in he
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ALV-J infected chickens and the control
We further identified dominant species found in the gut flora between the two groups.
Results showed significant differences (P<0.05) between eight species including Propionibacteriumacnes, Lactobacilluscoleohominis, Lactobacillushelveticus, Lactobacillusreuteri, and rarely identified species such as Mycoplana spp .,Comamonas spp., Delftia spp ., and Helicobacter spp . ( Figure 3). In the group B(ALV-J infected chickens) three species exhibited a significant reduction in abundance including Lactobacilluscoleohominis, Lactobacillushelveticus, and Lactobacillus reuteri compared with the group A (the control). Two of these species, Lactobacillushelveticus, and Lactobacillus reuteri are probiotics. These results suggested that at the species level ALV-J infection significantly altered the composition of probiotics in chicken gut microbes.

Effect of ALV-J infection on composition of probiotics in the chicken gut microflora
Our results indicated that ALV-J infection significantly influenced composition of probiotics in the chicken gut microflora. This also is the first study to investigate the The abundance of two probiotics Lactobacillus helveticus and Lactobacillus reuteri were significantly decreased in the chicken gut microbiota following ALV-J infection; this drop could be utilized to assist with the diagnosis of this illness post mortem. Moreover, further studies are required in order to understand the mechanism via which ALV-J infection significantly decreased the abundance of these two probiotics. Our study implied that to relieve avian leucosis, ALV-J multiplication must be prevented and microbiota-targeted therapies such as probiotic supplements are required.

Conclusion
ALV-J infection significantly altered the gut microbiota distribution in chickens. The abundance of two probiotics Lactobacillus helveticus and Lactobacillus reuteri were significantly decreased in the chicken gut microbiota following ALV-J infection, which to relieve avian leucosis, ALV-J multiplication must be prevented and microbiota-targeted therapies such as probiotic supplements are required.

Animal and Fecal samples collection
Female Huiyang beared chickens around 25-week-old were used in the study. The chickens belong to a local broiler in Huizhou city, China. They were collected from the national Huiyang Bearded chicken breeding ground at Guangdong Jinzhong Agriculture and Animal Husbandry Technology Co., Ltd. (Huizhou, China). Birds were housed in a commercial caging system (each cage being 40 × 40 × 30 cm in height, width, and depth, respectively). Chickens were randomly assigned to the cages, with three chickens in each unit. Water was supplied via two 'on-demand' nipples per cage. Followed by a method [34], chickens were divided into group of viral control (A group) or naturally ALV-J infected (B group) with 12 individuals in each group, respectively. All chickens were euthanized by cervical dislocation. Their gut contents were instantly collected from the ceca within 5 min of euthanasia, and immediately stored at −80°C.

DNA extraction, PCR, and 16S rRNA gene sequencing
A genomic DNA extraction kit, TIANamp Stool DNA Kit, was utilized to extract DNA from the gut contents (TIANGEN, Beijing, China). Twelve DNA samples from each group were randomly divided into 3 pools to produce 3 DNA samples per pool. DNA concentration and purity were determined using the Nanodrop 2000 Spectrophotometer (Wilmington, DE, USA). Extracted DNA was diluted to 10 ng/µL for PCR amplification. The universal primers 515F and 909R from a previous study were used to amplify the V4-V5 hypervariable region of the microbial 16S rRNA gene [35]. Procedures of PCR amplifications and purification were followed by our previous study [36]. All amplicons were sequenced using an Illumina MiSeq system at Guangdong Meilikang Bio-Science, Ltd. (Shaoqing, China).

Bioinformatics analysis
The raw reads were merged using the FLASH-software [37]. QIIME Pipeline-Version 1.9.0 was used to process the merged sequence data. The UCHIME algorithm was used to filter the clean data [38]. Effective sequences were grouped into operational taxonomic units (OTUs) at a user-defined level of sequence similarity (such as e.g., 97% to approximate species-level phylotypes). The alpha diversity indices and weighted UniFrac distance metrics were determined through the QIIME pipeline. Taxonomy was assigned by the  Husbandry Technology Co., Ltd. The owner has given its consent to use the animals in the study ( consent statement as supplement file).

Consent for publication
Not applicable.

Availability of data and materials
The 16S rRNA gene sequencing raw data of the dataset were deposited at the BIG Sequence Read Archive with BioSample accessions CRA002114.

Competing interest
The authors declare that they have no competing interests.   Dominant species of gut microbial flora found in groups A and B Dominant species found in the gut flora between the two groups. Eight species showed significant differences (P<0.05) between the two groups. Colors represented different group, red for group B, blue for group A. *indicates significant differences between the two indicated groups (P < 0.05).

Supplementary Files
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