https://orcid.org/0000-0003-1225-561X
Abstract
Acetate is a short-chain fatty acid (SCFA) that plays an important role in maintaining intestinal barrier integrity. Campylobacter jejuni (C. jejuni) infection is hypothesised to decrease the presence of acetate-producing bacteria and, consequently, the overall acetate concentration in the ileum, leading to an impaired intestinal barrier. This study aimed to characterise the effect of the C. jejuni challenge on the ileal microbiota and SCFAs concentration in broilers. Sixty broiler chicks were randomly assigned to control and challenge treatments, each with six replications and five birds per replicate. At 21 days of age, birds were inoculated with PBS (control), or 1 × 108 CFU/bird C. jejuni in the challenge group. Body weight, feed intake and feed conversion ratio were measured weekly. Ileal mucus and contents were collected on days 28 and 35 for microbiome and SCFA analysis. C. jejuni challenge didn’t affect body weight, feed intake and feed conversion ratio at days 28 and 35 compared to the control group. C. jejuni didn’t affect alpha diversity compared to the control group. C. jejuni didn’t alter microbial function nor the relative abundances of the phyla, families, genera and species compared to the control group; however, C. jejuni decreased the ileal concentration of acetate on days 28 (p = .09) and 35 (p = .002) compared to the control group. In conclusion, the C. jejuni challenge didn’t alter microbial composition or function and except for the shifts in acetate concentration, it had minimal impact on birds’ intestinal environment, highlighting the near-commensal nature of C. jejuni in broilers.
Introduction
Little is known about the colonisation mechanism of Campylobacter jejuni in broilers, which is concerning given that C. jejuni is the leading foodborne pathogen worldwide, with poultry being the main reservoir of the bacteria (Al Hakeem et al. Citation2022). Broilers are typically infected by C. jejuni through the fecal-oral route at two to three weeks of age and remain colonised until market age (Munoz et al. Citation2023). During slaughter, the rupture of the gastrointestinal tract can contaminate the carcase (Berrang et al. Citation2004). Handling and consuming uncooked poultry products are the leading cause of human campylobacteriosis (Al Hakeem et al. Citation2022).
The chicken gut microbiota, harbouring millions of microorganisms, is now recognised as a significant factor affecting broilers’ health and production performance (Fathima et al. Citation2022). Recent developments in high-throughput sequencing technologies and the wider use of metagenomic approaches have increased our understanding of complex microbial interactions in the gut (Weisburg et al. Citation1991). The 16S rRNA gene is a ubiquitous gene present in all bacterial cells, which serves as a phylogenetic marker that can reveal the taxonomic classification of the gut microbiota (Shang et al. Citation2018). Several studies have been done to understand the ability of C. jejuni to modify the chicken gut, particularly the caecal microbiota (Kaakoush et al. Citation2014; Sofka et al. Citation2015; Thibodeau et al. Citation2015; Awad et al. Citation2016; Han et al. Citation2017; Connerton et al. Citation2018). These studies have revealed that C. jejuni can alter the alpha diversity and decrease the relative abundance of Lactobacillus (Connerton et al. Citation2018) while increasing the relative abundance of Clostridium (Thibodeau et al. Citation2015) in the caeca of infected broilers. These results suggest that C. jejuni can alter the caecal microbial composition and predispose broilers to potential pathogenic bacteria such as Clostridium.
However, there is currently limited research on the effect of C. jejuni on the ileal microbiota, even though C. jejuni is known to colonise the lower tract of poultry species, including the caeca, colon and ileum (Cason et al. Citation2023). C. jejuni can also alter the tight junction proteins in the ileum, facilitating its translocation towards the spleen and liver (von Buchholz et al. Citation2022). Understanding C. jejuni’s interaction with the ileal microbiota is critical to developing effective C. jejuni control strategies in poultry.
There are differences in the ileal microbiota of different breeds. For instance, a study by Richards-Rios and collaborators explored the difference in microbial composition and microbial changes from day 3 until day 42 of age in Cobb 500, Ross 308 and Hubbard JA87 broilers and found that Ross 308’s microbiota matures faster than the other breeds (Richards-Rios et al. Citation2020). However, in the context of C. jejuni infection in the ileal microbiota, there was no effect of breed on the ability to colonise the gut. There are selected lines of birds, however, that show resistance against enteric pathogens, which typically have relatively large production of beta-defensin (Li et al. Citation2010).
The gut microbiota is responsible for the colonisation resistance against pathogens (Lawley and Walker Citation2013), which is mediated through competitive exclusion, bacteriocin production and short-chain fatty acid (SCFA) production (Khan et al. Citation2021). The gut microbiota produces SCFAs through the fermentation of complex non-digestible carbohydrates and these SCFAs release H + into the chicken gut, decreasing the pH and increasing the colonisation resistance against pathogens (Silva et al. Citation2020). SCFAs have been used to control foodborne pathogens, like Salmonella and C. jejuni, but with variable results (Van Deun et al. Citation2008; Mortada et al. Citation2020). Therefore, understanding the impact of C. jejuni on the production of SCFAs can provide valuable insights into C. jejuni’s pathogenesis and host-microbiota interaction in poultry. In this context, the present study aimed to investigate the effect of the C. jejuni challenge on broiler growth performance, as well as its impact on ileal microbiota, microbial function and SCFA profiles. Understanding these interactions can help with the development of more effective strategies to control C. jejuni in poultry.
Materials and methods
Birds, animals and experimental design
A total of 60 one-day-old Cobb 500 broiler chicks were obtained from a commercial hatchery and were raised for 35 days in BSL-2 rooms at the Poultry Research Centre at The University of Georgia. The birds were randomly allocated to two treatments: 1) Control and 2) Challenged, with six pens per treatment and five birds per pen. Birds were orally challenged 1x 108 CFU/mL of C. jejuni at 21 days of age. Birds had ad libtuim access to feed and water and were fed the same diet (Table ) throughout the trial period. Body weight and feed intake were recorded on days 21, 28 and 35 days of age. Average feed intake, body weight gain and feed conversion ratio were also analysed. The feed conversion ratio was corrected for bird removal and mortality.
Table 1. Basal diet composition fed from day 0–35 of age.
C. jejuni challenge
C. jejuni ATCC 33650 strain was cultured on a campy-CEFEX agar and incubated for 48 h at 42 C in microaerobic conditions (85% N2, 10% CO2 and 5% O2) (Potturi-Venkata et al. Citation2007; Lin et al. Citation2023). After 48 h, the bacterial cells were collected using an inoculum loop and resuspended in 1× PBS (NaCl, Sigma Chemical Co., St. Louis, Mo) to form a suspension. The suspension optical density was 0.2 at 540 nm with a spec-20. The 0.2 OD is equivalent to 1 × 108 (Cosby Citation2017). This was also confirmed by serial dilution and plating on Campy-cefex agar.
Sample collection and DNA extraction
On days 28 and 35, one bird per pen was euthanized using CO2.(Gerritzen et al. Citation2004) Ileum samples were collected and opened longitudinally. Feed particles were removed gently by forceps, the mucus was swabbed and collected in a 5 mL sterile cryogenic tube, and the sample was immediately frozen in liquid nitrogen. The samples were transported to the laboratory and stored at −80 C until further analysis. DNA extraction from the ileal mucosa was performed following a hybrid protocol (Rothrock et al. Citation2014). This protocol utilises enzymatic and mechanical methods to optimise DNA extraction. Briefly, 0.35 g of the sample was transferred into a 2 mL Lysing Matrix E tube (MP Biomedicals LLC, Irvine, CA, USA). The mechanical disruption of bacterial cells was done using a QIAGEN vortex adapter for the Vortex-Genie 2 vortex (QIAGEN, Venlo, The Netherlands) for 10 mins at maximum speed. QIAamp Fast DNA Stool Mini Kit (QIAGEN, Venlo, The Netherlands) was used for the enzymatic extraction. Following the completion of the extraction, the concentration and the purity of the DNA were checked by a spectrophotometer (Synergy H4 Hybrid Multi-Mode Microplate Reader along with the Take3 Micro-Volume Plate (BioTek Instruments Inc., Winooski, VT, USA). Samples with concentrations lower than 10 ng/µl were disqualified and the DNA extraction process was repeated.
DNA sequencing
After DNA extraction, the samples were shipped overnight on dry ice to Loop Genomics (San Diego, CA). All the nine variable regions of the 16S rRNA gene were sequenced (V-regions V1 to V9), as described earlier (Abellan-Schneyder et al. Citation2021). Briefly, the whole 16s rRNA gene was synthetically reconstructed from a series of standard Illumina PE150 reads, which were assembled to reconstruct the whole 16S rRNA gene, as established previously (Callahan et al. Citation2021).
Bioinformatics analysis
The sequences were converted to FASTQ files and were imported into QIIME 2 (Bolyen et al. Citation2019). QIME DADA2 plugin (Callahan et al. Citation2016) was used to control the sequencing quality and filter out chimaeras. An amplicon sequence variant (ASV) frequency table and a summary of each ASV length were generated. A phylogenetic tree was generated using QIME 2 phylogeny plugin (Price et al. Citation2010). Taxonomic classification was created using QIME 2 feature-classifier plugin, which uses the Naïve Bayes classifier trained on SILVA 138 SSU database (Quast et al. Citation2013); the reads were classified by taxon using the fitted classifier (Pedregosa et al. Citation2011). The ASV table was rarefied to a common standard sampling depth of 3447 for analyses of alpha and beta diversity. The following alpha diversity indices were computed: Number of observed features (ASV), Shannon diversity index, Faith’s phylogenetic diversity index and Pielou’s evenness index; and for beta diversity, weighted Unifrac distances. The relative bacterial abundance was also quantified at a phylum, family, genus and species level. Finally, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) was used to make inferences about the metabolic functions of the microbial community (Douglas et al. Citation2020), and metagenome metabolic functions were assessed using the MetaCyc pathway database.
Short-chain fatty acid analysis
Analysis of SCFA was performed according to the method previously described (Lourenco et al. Citation2020). Briefly, samples of the ileal digesta were collected on days 28 and 35 of age during the study and stored in 50-mL tubes. The samples were kept on ice during the transfer to the laboratory and then stored at −80 C until further analysis. On the day of analysis, the samples were thawed, and 1 g of the ileal digesta was diluted in 3 mL of distilled water and placed into 15 mL conical tubes. The conical tubes were then homogenised by vortexing for 30 s. After that, 1 mL from each sample was transferred into new centrifuge tubes. The tubes were centrifuged at 10,000 × g for 10 min. For each sample, 1 mL of supernatant was transferred to a new centrifuge tube and combined with 200 µL of a metaphosphoric acid solution (25% w/v). Each sample was vortexed for 30 s to ensure proper mixture and stored at −20 °C overnight. The following morning, samples were thawed and centrifuged at 10,000 × g for 10 min. The supernatant was then placed into polypropylene tubes with ethyl acetate in a 2:1 ratio of ethyl acetate to the supernatant. The samples were vortexed for 10 s and allowed to settle for 5 min to optimise separation. Next, 600 µL of the top layer was transferred into screw-thread vials to analyse the SCFA concentrations. A Shimadzu GC-2010 Plus gas chromatograph (Shimadzu Corporation, Kyoto, Japan) with a flame ionisation detector and a capillary column (Zebron ZB-FFAP; 30 m × 0.32 mm × 0.25 µm; Phenomenex Inx., Torrance, CA, USA) was used for SCFA analysis. This equipment utilised helium as the carrier gas. The sample injection volume was 1.0 µL. The column temperature started at 110 °C and gradually increased to 200 °C. The injector and detector temperatures were set to 250 °C and 350 °C, respectively. The samples’ peak heights were compared to standards to determine the concentrations of SCFAs in the samples.
Statistical analysis
A one-way ANOVA was carried out to analyse the effect of C. jejuni on the performance production and SCFA concentrations, with the pen being considered the experimental unit. As for the individual microbial taxa and alpha diversity indices, they were analysed using the Kruskal-Wallis H test. Differences in beta diversity were assessed by permutational multivariate analysis of variance (MANOVA - Adonis). Results obtained from all the statistical tests were corrected using Bonferroni’s method to account for the false discovery rate produced following multiple comparisons. The FDR-adjusted p values were statistically significant when p < .05 and considered a trend between .05 and .1.
Results
Effect of C. jejuni challenge on performance production
There were no significant differences in body weight, feed intake and feed conversion ratio between the control and challenge groups on days 21, 28 and 35 (Table ).
Table 2. Effect of C. jejuni challenge on production parameters.
Effect of C. jejuni challenge on alpha-diversity indexes
C. jejuni challenge on day 21 had no significant effect (p > .05) on the different alpha diversity indexes: (Figure ) Shannon diversity (Figure ) Faith’s phylogenetic diversity (Figure ) Pielou’s Evenness Index (Figure ) Number of observed features) measured on days 28 and 35 compared to the control group.
Figure 1. Effect of C. jejuni challenge on alpha-diversity indexes. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 and 35 of age, the alpha-diversity indexes: (a) Shannon diversity (b) faith’s phylogenetic diversity (c) Pielou’s Evenness Index and (d) number of observed features were measured.
Effect of C. jejuni challenge on the beta diversity based on weighted Unifrac index
C. jejuni didn’t alter the weighted Unifrac index compared to the control group on days 28 (Figure ) and 35 (Figure ). Adonis test showed p = .50 for treatment, p = .11 for the day and p = .33 for treatment-by-day interaction.
Figure 2. Effect of C. jejuni on the beta diversity based on weighted Unifrac index. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the beta diversity based on weighted Unifrac index were measured.
Effect of C. jejuni challenge on the ileal microbiota at the phyla level on days 28 and 35
After all the quality and filtering steps were done, the resulting sequences across our samples fall in a range of 3447 to 16,712. These sequences were rarified to 3447 per sample. A total of 6 phyla were identified in the ileum. Firmicutes (%), Bacteroidetes (%) and Proteobacteria (%) were the most dominant phyla on day 28. On day 35, Firmicutes (%) completely dominated the phyla in the ileum. C. jejuni didn’t alter the ileal microbiota at the phyla level on days 28 (Figure ) and 35 (Figure ). Age had no significant impact on the phyla present in the two groups.
Figure 3. Effect of C. jejuni challenge on the ileal microbiota at the phyla level on days 28 and 35. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the relative abundance of microbiome composition at phylum level were computed.
Effect of C. jejuni challenge on the ileal microbiota at the family level on days 28 and 35
A total of 20 families were identified in the ileum. On days 28 and 35, Clostridiaceae, Lactobacillaceae and Peptostreptococcaceae were the dominant families. C. jejuni didn’t alter the ileal microbiota at the family level on days 28 (Figure ) and 35 (Figure ). However, there was an age effect on the development of the gut microbiota, as Lachnospiraceae (p < .03), Ruminococcaceae (p < .03) and Bacteroidaceae (p < .08) decreased on day 35.
Figure 4. Effect of C. jejuni challenge on the ileal microbiota at the family level on days 28 and 35. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the relative abundance of microbiome composition at family level were computed.
Effect of C. jejuni on the ileal microbiota at the genus level on days 28 and 35
A total of 22 genera were identified in the ileum. On days 28 and 35, Candidatus Arthromitus, Lactobacillus and Romboutsia were the most dominant genera. C. jejuni didn’t alter the ileal microbiota at the genus level on days 28 (Figure ) and 35 (Figure ). However, there was an age effect on the development of the gut microbiota, as Faecalibacterium (p < .04) decreased from % on day 28 to % on day 35.
Figure 5. Effect of C. jejuni on the ileal microbiota at the genus level on days 28 and 35. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the relative abundance of microbiome composition at genus level were computed.
Effect of C. jejuni challenge on ileal acetate concentration
C. jejuni decreased the acetate concentration compared to the control group on days 28 (p = .09) (Figure ) and 35 (p = .002) (Figure ).
Figure 6. Effect of C. jejuni challenge on ileal acetate concentration. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the acetate concentration was measured. Bars (+SEM) with ‘a’ and ‘b’ superscripts differ significantly (p < .05).
Effect of C. jejuni on microbial functional analysis
C. jejuni didn’t alter (p > .05) the microbial pathways at days 28 (Figure ) and 35 (Figure ) compared to the control group.
Figure 7. Effect of C. jejuni on microbial functional analysis. Day-old broilers were randomly allocated into two treatments: Control or challenge (n = 6). Birds in challenge groups received 1 × 108 CFU/bird of C. jejuni or mock challenge (PBS) via oral gavage. On days 28 (a) and 35 (b) of age, the microbial functional analysis were computed. Bars (+SEM) with no common superscript differ significantly.
Discussion
The intestinal microbiota is vital in mediating colonisation resistance against pathogens (Lawley and Walker Citation2013). However, enteric pathogens are equipped with virulence factors to overcome colonisation resistance and cause an infection (Indikova et al. Citation2015). In chicken, C. jejuni is considered a near-commensal bacteria typically detected in broilers at two to three weeks post-hatch and persists until market age (Al Hakeem et al. Citation2022). C. jejuni primarily colonises the caeca, and several reports have characterised the changes in caecal microbiota following C. jejuni challenge (Kaakoush et al. Citation2014; Awad et al. Citation2016; Al Hakeem et al. Citation2023). While C. jejuni also colonises the ileum and disrupts the tight junctions leading to an increase in E. coli’s translocation towards the internal organs (Awad et al. Citation2016), the impact of C. jejuni on the ileal microbiota remains poorly investigated. Therefore, this study aimed to examine the effect of C. jejuni on growth performance, composition of ileal microbiota and SCFA profile in broilers.
In our study, C. jejuni was inoculated on day 21 of age. Before the challenge, the birds had comparable body weight, feed intake and feed conversion ratio. Following the C. jejuni challenge, there was no significant impact on body weight, feed intake or feed conversion ratio on days 28 and 35 of age. Similar results were found in previous studies that also showed that C. jejuni did not affect performance production in broilers challenged on day 1 (Han et al. Citation2016), day 14 (Mortada et al. Citation2021) and 21 of age (Munoz et al. Citation2023). However, some studies have reported that C. jejuni decreased body weight gains by disrupting intestinal integrity and nutrient absorption in the gut (Dhillon et al. Citation2006; Gharib et al. Citation2012; Awad et al. Citation2014). Notably, differences in production performance were observed at 42 (Awad et al. Citation2014) and 49 (Gharib et al. Citation2012) days of age, which were beyond the time points covered by our study. Such a negative impact on body weight might also be strain-specific (NCTC 12744), as it had been reported that different cocktail strains didn’t reduce body weight in challenge broilers at day 42 (Munoz et al. Citation2023). Therefore, the results observed in our study could be attributed to the near-commensal nature of C. jejuni in poultry, as broiler’s colonisation with C. jejuni doesn’t typically lead to clinical manifestation of the disease or lower performance parameters.
Several indices were computed to measure the effect of C. jejuni on alpha diversity. Thibodeau et al. also found that C. jejuni did not significantly alter alpha diversity (Thibodeau et al. Citation2015). However, in the jejunum and caeca, the C. jejuni challenge was able to alter different alpha diversity indices (Awad et al. Citation2016). Despite this, C. jejuni did not change the number of observed features, Shannon diversity index, Faith’s phylogenetic diversity index or Pielou’s evenness index compared to the control group. These results suggest that C. jejuni can colonise the chicken gut in high numbers without causing a significant shift in gut microbial composition. Additionally, the lack of significance in alpha diversity in our study agreed with the beta diversity index, as C. jejuni did not alter the weighted Unifrac distances. Our control and challenge groups did not cluster into two separate groups, indicating similarities in microbial composition. It is worth noting that differences in C. jejuni’s effects on alpha and beta diversity parameters may be attributed to several factors, including the different organs (jejunum and caeca vs. ileum) studied, the challenge model used, the isolate of C. jejuni and the chicken breeds used in other studies.
The ileum microbial composition was dominated mainly by three phyla, Firmicutes (87% −94%), Bacteroidota (4%–7%) and Proteobacteria (0.6%–3%) on days 28 and 35. There were no significant gut microbiota changes between days 28 and 35 at this taxonomic level. Likewise, C. jejuni didn’t alter the microbial composition at the phyla level compared to the control group on days 28 and 35. Awad et al. reported an increase in Firmicutes at the expense of Proteobacteria following C. jejuni infection (Awad et al. Citation2016). Firmicutes are major producers of short-chain fatty acids resulting from the digestion of complex carbohydrates. In our study, Firmicutes was the dominant phyla in ileum on days 28 (87%–94%) and 35 (98%–99%), which already creates an energy-rich niche for C. jejuni to proliferate. Interestingly at the family level, the relative abundance of Lachnospiraceae, Ruminococcaceae, Clostridia_UCG-014 and Bacteroidaceae decreased over time. This indicates an ongoing reorganisation of the gut microbiome over time, and similar results are reported in different studies (Jurburg et al. Citation2019; Yang et al. Citation2022). C. jejuni did not alter the microbial composition at the family, genus or species levels in our study, although different studies have reported changes at these levels following C. jejuni infection.
The hindgut bacteria ferment dietary fibre to produce metabolites known as short-chain fatty acids (SCFAs), which primarily consist of acetate, propionate and butyrate (Liu L et al. Citation2021). Several reports indicated the role of SCFAs in maintaining intestinal health in poultry (Liao et al. Citation2020; Liu L et al. Citation2021; Liu P et al. Citation2021; Fan et al. Citation2023). Our study tested the presence of acetate, propionate, butyrate, isobutyrate, valerate and isovalerate, but only acetate was detected. Compared to the control group, C. jejuni decreased ileal acetate concentration at 28 (p = .09) and 35 (p = .002) days of age. Acetate is mainly formed through two major pathways: the acetyl-CoA and the Wood-Ljungdahl pathway (Youssef et al. Citation2019). However, our microbial functional analysis didn’t indicate a difference in these pathways between the control and the infected groups. Acetate plays a role in inducing the expression of neuropeptides, namely proopiomelanocortin (PMOC) and agouti-related peptide (AgRP), regulating appetite in broilers and leading to reduced feed intake (Frost et al. Citation2014). Despite the decreased acetate concentration in challenged birds, no difference in feed intake was observed on days 28 and 35 between the control and challenge groups.
Unlike many other bacteria, C. jejuni exhibits a unique property as it lacks the ability to utilise common carbohydrates as carbon sources (Parkhill et al. Citation2000). This limitation is primarily due to the absence of several key enzymes and transporters in the glycolytic pathway, which are necessary for the metabolism of glucose and galactose (Stahl et al. Citation2012). The genome analysis, known metabolic pathways and experimental evidence highlight the ability of C. jejuni to utilise only acetate and lactate as the main carbon source (Wright et al. Citation2009; Thomas et al. Citation2011). In our experiment, we hypothesised that the presence of C. jejuni would consume acetate, leading to a decrease in its concentration, which is what was observed on days 28 (p = .09) and 35 (p = .002) compared to the control group.
In our study, we found that C. jejuni did not alter the alpha and beta diversity of the gut microbiota and subsequently did not alter the microbial composition and function. This was further reflected in no effect on production performance. C. jejuni has been described as near-commensal in broilers, and several studies have highlighted the tolerogenic response against C. jejuni. The ability of C. jejuni to colonise the chicken gut is a significant advantage that ensures its successful enteric lifestyle. C. jejuni colonises and multiplies in the avian mucus without affecting the commensal microbiota. This suitable approach helps C. jejuni evade inducing an immune response against it. Our results support the near-commensal relationship between C. jejuni and the gut microbiota in broilers.
It should be noted that the lack of significance observed in our study could be attributed to the limited time frame of our experiment, which only extended up to 35 days of age. This timeframe may not sufficiently capture the long-term impact of C. jejuni on birds’ performance or gut microbiota. Additionally, the use of a single strain of C. jejuni (ATCC 33650 strain) might be the reason behind the observed results and had we used different strains, it could have yielded different outcomes. Moreover, the timing of exposure to C. jejuni might also be another reason behind the lack of changes in the gut microbiota compared to the control group. Different results may have been obtained if we had challenged the birds earlier, at approximately day 14 of age.
Conclusion
In conclusion, the study aimed to investigate the effect of C. jejuni on performance, ileal microbiota and short-chain fatty acid profiles in broilers. The results suggest that C. jejuni did not significantly impact bird performance, diversity indices or microbial composition at the phyla, family, genus or species levels. However, C. jejuni decreased ileal acetate concentration on days 28 and 35, potentially impacting intestinal health. The study highlights the near-commensal nature of C. jejuni in poultry. Further research is needed to investigate the impact of C. jejuni on the gut microbiota in broilers at different ages and strains of the pathogen.
Ethics statement
All animal protocols used in this trial were approved by the University of Georgia’s Institutional Animal Care and Use Committee (AUP: A2021 06-012-Y1-A2). The broilers were monitored twice daily and euthanized using a humane endpoint if necessary. Birds were humanely euthanized during sample collection and at the end of the experiment (day 35). All researchers involved in the care, handling and sampling of the broilers were trained by the University of Georgia on animal care and handling (UGA IACUC 101 course).
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data presented in this study are available upon request from the corresponding author.
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