Food safety and economic gains are the priority consideration for food animal production industry. The antibiotic growth promoters (AGP) have been used in animal feed for decades to promote animal health and production. However, extensive use of antibiotics in animal agriculture led to increased concerns over antibiotic contamination in food and environment, and the emergence of antibiotic-resistant microorganisms. With the reduction and eventual withdrawal of AGP from animal feed due to increasing government regulations over antibiotics use, developing alternatives to antibiotics to promote host immunity and sustainable animal growth is becoming critical. Furthermore, incidence of some enteric infectious diseases increase since the withdrawal of AGP (Yegani and Korver, 2008). Coccidiosis and necrotic enteritis (NE) have emerged as the top two poultry enteric infectious diseases responsible for about $3 billion and $6 billion economic losses worldwide, respectively (Li et al., 2019; Wade and Keyburn, 2015). NE normally occurs at 2–3 weeks post hatch and is characterized by the sudden escalation of mortality, depression, increased feed conversion or reduced growth rate (Hofacre et al., 2018). Coccidiosis is a major parasitic disease resulting in decreased feed intake, low weight gain and mortality (Shirley et al., 2004). Highly pathogenic species of Eimeria, E. acervulina, E. tenella and E. maxima, are most economically important Eimeria species, and are most frequently found within the intestinal tract of intensively reared chickens (Chapman, 2014). Pre-exposure to E. maxima is the highest risk factor for NE mortality (Hofacre et al., 2018). Coccidia-induced mucogenesis fosters the onset of NE by promoting CP growth (Collier et al., 2008). On the other hand, active use of live and attenuated coccidia vaccines may induce mild intestinal lesion in some birds (Williams, 2005), which could potentially promote incidence of NE.
To date, chemoprevention, hygienic measures, vaccination, and anti-coccidial feed additives have been widely used to contain coccidiosis (Kaboudi et al., 2016). However, with the increasing demand for antibiotic-free animal production, alternative control strategies are needed. Accumulating evidence has revealed that many novel antibiotic alternatives including pro- and pre-biotics improve gut health of broiler chickens via the exclusion of pathogens, the modulation of physiology of the digestive system and immune system, and boosting of nutrient exchange to limit Eimeria-induced pathogenicity (Chen et al., 2016; Clavijo and Florez, 2018; Hessenberger et al., 2016; Ritzi et al., 2016).
Infections of Eimeria spp. disrupt intestinal homeostasis and dramatically alter the taxonomic composition of the poultry intestinal microbiota (Stanley et al., 2014). Coccidiosis and early bacterial infection with Salmonella Typhimurium have shown to promote NE severity (Moore, 2016; Prescott et al., 2016). Further studies to identify the relevance of Eimeria infection to other bacterial diseases are needed to better understand the epidemiology and new disease control strategies.
Intestinal microbiota influences the development of the immune system and affects the nutrient acquirement in the gut mucosa of animals in addition to affecting behavior, emotion, gas production, obesity, diabetes, and other metabolic disorders (Belizario et al., 2018; Niccolai et al., 2019). As the major predisposing factor of NE, coccidiosis can facilitate the colonization and proliferation of CP due to intestinal epithelial layer damage (Miska and Fetterer, 2016; Su et al., 2015). The Eimeria maxima (EM) / CP dual infection model has been used to evaluate several potential antibiotic alternatives in our lab, including vaccination and phytonutrients (Lee et al., 2013; Lee et al., 2018; Lillehoj et al., 2017; Oh et al., 2018). Compositions of cecal bacterial communities may influence the growth potential of broiler chickens in normal healthy condition (Lee et al., 2017), although it is not very clear what and how microbes influence the growth of animals after single and co-infections of Eimeria species and C. perfringens. In this study, the goal was to define the variations and functions in the cecal microbiota in NE condition and its potential correlation with growth parameter of commercial broiler chickens following NE-. An enhanced understanding of the effects of coccidiosis and NE on enteric microflora variations in experimental disease model would facilitate the development of antibiotic-independent alternative control measures against coccidiosis and NE.
2. Materials and methods
One-day-old Ross 708 broiler chicks were obtained from the Longenecker's Hatchery (Elizabethtown, PA), housed in Petersime starter brooder units and provided with feed and water ad libitum. All birds were maintained in a temperature-controlled environment following a standard protocol (Oh et al., 2018). All experiments were approved by the Institutional Animal Care and Use Committee at Beltsville Agricultural Research Center (Animal Use Protocol# 17–027).
2.2. Experimental necrotic enteritis disease model
A total of 48 chickens were fed an antibiotic-free starter diet containing 16% dry matter protein (USDA-Feed Mill) from days 1 to 18 of age and a standard grower diet containing 24% dry matter protein from days 19 to 21, as described (Oh et al., 2018). Briefly, birds were randomly assigned to four groups with 12 birds each. For the E. maxima (EM) challenge group, chickens were infected by oral gavage on day 14 with 5.0 × 103 oocysts/bird of EM Beltsville strain 41A. For C. perfringens (CP) challenge group, chickens were infected by oral gavage with CP netB+ strain Del1 of 1.0 × 109 CFUs /bird at day 18. C. perfringens Del1 strain was grown anaerobically overnight at 37 C in brain heart infusion medium (BHI, BD Bacto™, Sparks, MD). For EM/CP dual infection (EP) group, chickens were infected with the same doses of EM at day 14 and CP at day 18, respectively. For the sham control (NV) group, chickens received an equal volume of PBS by oral gavage at day 14 followed by BHI medium at day 18 as a sham control. At day 20, the birds were sacrificed, and the contents in the ceca were collected by scrapping and immediately put into RNALater solution based on the manufacturer's instruction (Sigma, St Louis, MO). The birds were weighed at day 14 (pre-EM infection), day 18 (pre-CP infection) and day 20 (day 2 post CP infection). The gut lesion scores were determined using the intestine sections flanking the diverticulum using 4-point scoring system (Li et al., 2017).
2.3. 16S rRNA gene sequencing
Total DNA from the cecal contents was extracted with a QIAamp PowerFecal DNA Kit (Qiagen Inc., Qiagen, Valenica, CA). The hypervariable V3 −V4 regions (E. coli position 341 to 805) of the 16S rRNA genes were directly amplified from 10 ng of total DNA using PAGE-purified Illumina platform-compatible adaptor oligos that contained features such as sequencing primers, sample-specific barcodes, and 16S PCR primers (forward primer, 341/357F: NNNNCCTACGGGNGGCWGCAG; reverse primer, 805/785R: GACTACHVGGGTATCTAATCC) as described elsewhere (Li et al., 2016). After purification and quantification, amplicons from individual samples were pooled in equal mass (molar) ratios, and the library pool was sequenced using Illumina MiSeq Reagent Kit v3 for 2 × 300 cycles on an Illumina MiSeq sequencer as previously described ((Liu et al., 2019)).
2.4. Bioinformatics and data analysis
The data were preprocessed using MiSeq Control Software (v31) as described (Li et al., 2016). The Quantitative Insights Into Microbial Ecology (QIIME) pipeline was used to analyze preprocessed 16S rRNA gene sequences with default parameters (Caporaso et al., 2010). The mean sequences per sample are 290,483 ± 98,505 (mean ± SD). The data were rarefied to 100,000 quality reads after preprocessing and removal of chimeric sequences. The DNA-Seq raw data are available in the NCBI SRA repository under the Accession Number SAMN13825558. Alpha (α)-diversity at an operational taxonomic unit (OTU) level was estimated using QIIME and Primer (v.7; https://www.primer-e.com). Beta diversity was also estimated using PCA in R. Significant features or taxa between groups of interest were identified based on the Linear Discriminant Analysis (LDA) Effect Size (LEfSe) algorithm (Segata et al., 2011).
Modules are groups of highly interconnected system components (nodes of a network) that may form a biological pathway (Langfelder and Horvath, 2007). Global microbial co-occurrence network patterns were analyzed using Molecular Ecological Network Analyses (MENA) as described elsewhere (Wang et al., 2019). A partial Mantel test was performed to estimate the correlation between node connectivity of the OTUs of cecal microbiota and body weight gain% (Zhou et al., 2012).
The percentage of relative body weight gain (RBWG%) and lesion scores were analyzed using the GLM procedure of SAS v9.4 for Windows (Cary, NC). Mean treatment-group values were compared using Duncan's multiple range test; differences were considered statistically significant at p ≤ .05. All the data were expressed as mean ± standard errors of mean for each treatment (N = 12).
3.1. E. maxima alone or EM/CP dual infection significantly reduced the growth rate
Compared with the sham control group (NV), E. maxima alone (EM) and EM/CP dual infection (EP) groups showed significantly reduced growth rates as demonstrated by RBWG% at day 2 post CP infection (p < .05) (Fig. 1). RBWG% in the EM/CP dual infection group was not significantly different from that in EM group (p > .05). There was no significant difference in RBWG% between NV and CP groups.
3.2. Evaluation of necrotic enteritis lesions
A single dose of CP infection did not induce NE lesions as demonstrated by the lesion scores in CP alone group, when compared with sham control group. However, EP group showed significantly higher gut lesion scores than EM group (Fig. 2; p < .05).
3.3. Neither E. maxima nor CP infection affected cecal microbial diversity
No significant difference in alpha-diversity indices among the four experimental groups was detected in the ceca microbiota at day 2 post CP infection. For example, Shannon index was not different among the four groups tested (Fig. 3; p > .05). The Principal Component Analysis (PCA) and Analysis of Similarities (ANOSIM) results showed that neither EM nor CP infection, alone or in combination, altered microbial communities as beta-diversity among 4 groups remained indistinguishable at the genus or OTU levels (Fig. 4a, b). The cecal microbial communities of the sham control group showed the most abundant phylum as Firmicutes which accounted for more than 92% of all sequences, followed by Bacteroidetes (4.4%), and Proteobacteria (1.1%) (Fig. 5). Abundance of the phylum Proteobacteria increased after either EM or EP infections.
3.4. E. maxima or CP infection altered the cecal microbial composition
The differences in the relative abundance at various taxon levels between sham (NV) control and infected groups (EM, CP, or EP) were compared using the LEfSe. Significant difference in genera between infected (EM or EP) and sham (NV) controls is shown in Fig. 6 (Wilcoxon non-parametric t-test at p < .05 and absolute LDA scores > 2.0). A total of 8 taxa displayed a significant shift in relative abundance between chickens in the sham control (NV) and EM group using a stringent cut off value (LDA ≥ 2.0). For example, the relative abundances in an unclassified genus of the family Enterobacteriaceae and Eubacteriaceae were significantly higher in the EM group than those in the sham control (Fig. 6A). On the other hand, the abundances of Bacteroides and SMB53 as well as an unclassified genus in the family of Coriobacteriaceae were significantly reduced by the EM infection, compared to those in sham NV controls (Fig. 6A). Similarly, the abundance of Anaerofustis was also significantly increased following CP infection (Fig. 6B). The abundances of the genus Clostridium, as well as two unclassified genera in the family Enterobacteriaceae and the order RF32, were significantly elevated in the EP group (Fig. 6C), compared to those in the sham control. At the OTU level, Bacteroideceae bacteroides was decreased in relative abundance in EM, CP or EP groups, while Anaerofustis was increased in EM or CP group (data not shown). Lactobactillus mucosae and Lactobactillus salivarius were increased in ceca post-CP infection.
3.5. Functional categories inferred from the 16S data
Given that microbial phylogeny and biological function are strongly linked, gene families can be predicted using 16S rRNA gene sequences (Li et al., 2016). Two KEGG enzymes showed significantly different abundance in the sham control (NV) group and EM-infected group by LEfSe analysis. ABC-2 type transport system ATP-binding protein (K01990) and maltose 6′-phosphate phosphatase (K06896) had a significantly higher abundance in the sham control group. The hexosaminidase (K12373), an enzyme involved in Keratan sulfate degradation was significantly reduced by CP infection. Furthermore, the dual infection EP group showed reduced abundance of beta-glucosidase (K05349), RNA polymerase sigma-70 factor (K12373), ECF subfamily (K03088), and alpha-galactosidase (K07407), besides ABC-2 type transport system ATP-binding protein (K01990) and maltose 6′-phosphate phosphatase (K06896), when compared with the sham control group.
3.6. Eigengene analysis of correlation between module and body weight trait
Eigengenes are defined as the characteristic expressions of modules, while the weighted links represent the relationships between modules (Langfelder and Horvath, 2007). Eigengene networks may be used to provide a natural framework for studying relationships among network modules and traits. In this study, correlation analysis between RBWG% and module-based eigengenes in cecal microbiota from all 4 groups was conducted (Table 1). In sham control (NV), EM and EP groups, six modules were significantly correlated with RBWG%. In the NV control group, Module 12# with 11 members negatively correlated with RBWG% (r = − 0.70, p = .01). Modules 3# containing 43 members seemed to be positively correlated with RBWG% (r = 0.57, p = .05) and Module 11# consisting of 8 members appeared to show negative correlation with RBWG% (r = − 0.57, p = .05). In the EM group, Module 14# showed a strong correlation with RBWG% (r = 0.61, p = .04, 8 members). Among 8 members in Module 14#, 7 were assigned to the Order Clostridiales under which 3 belonged to Lachnospiraceae and 1 Ruminococaceae. In the EP dual infection group, two modules, 8# and 9#, were strongly correlated with RBWG% (r = 0.66, p = .02, 9 members for Module 8#; r = 0.57, p = .04, with 9 members for Module 9#). Among the total 18 members in Module 8# and 9#, all were assigned to the Order Clostridiales under which 6 belonged to Lachnospiraceae and another 6 to Ruminococaceae. In the CP group, no significant correlation was found.
Fig. 6. The significantly discriminative taxa of genera microbial compositions in chicken ceca microbiota from birds among the sham control (NV, n = 12), Eimeria maxima (EM, n = 12) infected, Clostridium perfringens (CP, n = 12) infected, and EM/CP coinfections (EP, n = 12) groups. The chickens were infected orally with EM at day 14 followed by CP infection at day 18, and sacrificed at day 20. Total DNA from the cecal contents was subjected to 16S rRNA gene sequencing. X-axis represents Linear Discriminant Analysis (LDA) scores of the relative abundance. Y-axis: individual taxa. A. EM vs NV; B. CP vs NV; C. EP vs NV. Results are based on a Wilcoxon non-parametric t-test corrected for multiple hypothesis testing (LDA score log10 > 2.0).
The relationships between network topology and RBWG% were also assessed by calculating the OTU significance (GS), r2 (the square of Pearson correlation coefficient) of OTU abundance profiles with RBWG% and node connectivity as described elsewhere (Wang et al., 2018). In sham control (NV) group, the node connectivity of the OTUs assigned to the family Peptostreptococcaceae was significantly correlated with the RBWG% value (r = 0.55, p = .033) (Table 2). In EM group, the node connectivities of the OTUs assigned to Firmicutes (phylum), Clostridia (Class), and Clostridiales (Order) showed significant but marginal correlations with RBWG% (r = 0.13, 0.14, 0.14, respectively; p < .01). In the CP group, the node connectivities of the OTUs in the Lactobacillales (order) and Lactobacillaceae (family) were well correlated with RBWG% (r = 0.33–0.4; p < .05). No significant correlation was detected between the node connectivity of the OTUs and RBWG% in the EP dual infection group in the study.
NE is a complex and multi-factorial disease which is influenced by many factors including predisposing factors, dietary component, and CP strain virulence (Prescott et al., 2016). Coccidiosis is a major risk factor, since Eimeria parasites disrupt epithelium integrity, and induce increased intestinal mucus secretions to promote CP localization and provide protein-rich nutrient favorable to C. perfringens replication (Collier et al., 2008; Prescott et al., 2016). Mainly two different models have been used for NE induction: Eimeria spp and CP co-infection model (Lee et al., 2013; Prescott et al., 2016; Wu et al., 2014), and CP alone model (Cooper and Songer, 2010; Lacey et al., 2018; Parreira et al., 2017; Sarson et al., 2009). Understanding the gut microbial ecosystem and its interaction with the host is important for development of logical alternatives to antibiotics to promote animal growth and reduce enteric infectious diseases, i.e. through the specific pathogen targeting (vaccines or narrow-spectrum antimicrobial agents) or direct microbiota manipulation (administration of probiotics or prebiotics, fecal transplantation with beneficial microbiota or synthetic microbial communities) (Relman and Lipsitch, 2018).
In this study, a dual infection model with EM and CP was used to induce NE with significant body weight loss and gut lesions at day 2 post CP infection, though there was no significantly statistical difference in RBWG% between EM and EM/CP groups. That phenomenon could be accounted for by the fact that young chickens are more sensitive to coccidiosis challenge than older birds with higher RBWG% reduction after coccidiosis (unpublished data). Additionally, EM/CP challenge did not affect cecal microbial diversity in this study. Our results confirm the results of Bortoluzzi et al. (2019) who used multiple dosing of Eimeria spp. (coccidial vaccine spraying at day 0 and oral gavage of EM at day 14 following by CP challenge in drinking water at days 18 and 20 (Bortoluzzi et al., 2019). Our results were, however, different from another study where strong alpha- and beta-diversity indices were achieved in EM/CP model (Wu et al., 2014). This discrepancy may come from different EM pathogens, CP dosages and different NE model. Besides E. maxima, they also used E. acervuline and E. brunetti at day 9 (Wu et al., 2014). Pre-disposing with these mixed tissue-specific Eimeria spp. could result in a stronger infection than EM alone in ceca. In addition, the high-protein fishmeal diet was found to have a strong effect on the cecal microbiota either with or without administration of Eimeria spp (Wu et al., 2014). A prior study demonstrated that Eimeria tenella challenge notably altered the abundance of the bacteria taxa with the correlation of lesion severity, and led to cecal microbiota dysbiosis (Macdonald et al., 2017). The results obtained by Wu et al. (2014) was confirmed by Stanley et al. (2014), further demonstrating the atypical nature of our findings that we reported here.
In this study, we used the RBWG% to reflect the growth rate change. Correlations exist between RBWG% and node connectivity of the OTUs assigned to certain taxa in the cecal microbial community of sham control (NV) group, E. maxima (EM) or C. perfringens (CP) infected chickens based on the Gene Significance values with a partial Mantel test. In the sham control chickens, a positive correlation was found between RBWG% and the relative abundance of Peptostreptococcaceae (r = 0.55, p = .033). All members of the Peptostreptococcaceae family are anaerobes with fermentative type of metabolism. Very few published studies are available to define such correlation. Indirectly, Peptostreptococcaceae is found to negatively correlate with life span in mice, and life span was inversely correlated with food intake, body weight and fat content in mice (Zhang et al., 2013; Zhou et al., 2012). In the EM group, a marginally positive correlation between RBWG% and the relative abundance of family Clostridiaceae (r = 0.29, p = .054) was seen. Clostridiaceae is a highly diverse family consisting of genera important in nutrient digestibility and carbohydrate / protein metabolism, and pathogenesis as well (Bermingham et al., 2017; RajilicStojanovic and de Vos, 2014). Clostridiaceae is found to exist in significantly greater proportions in diet-induced obese mice when compared to lean mice (Clarke et al., 2013).
In the CP group, a positive correlation between RBWG% and the relative abundance of family Lactobacillaceae (r = 0.40, p = .024) was seen. Numerous studies have shown that Lactobacillus inhibits the growth of pathogenic bacteria by means of production of organic acids and bacteriocins, thus enhancing animal growth as probiotics (Aleksandrzak-Piekarczyk et al., 2019; Angelakis, 2017; Caly et al., 2015; Million et al., 2012; Senok et al., 2005). In this study, two genera of Lactobacillus were increased significantly in relative abundance (L. mucosae and L. salivarius). L. mucosae from mammalian gastrointestinal tract has anti-inflammatory and antioxidant properties, and adhere to mucosal surfaces. Some L. mucosae isolates also display good antimicrobial and competitive exclusion activities against pathogenic bacteria, indicating they could be a good probiotic candidate (Ayyanna et al., 2018; Fakhry et al., 2009; Watanabe et al., 2010). Some isolates of Lactobacillus salivarius have both bacteriocin and probiotic activities and could also be good candidates as probiotics (Cho et al., 2011; Corr et al., 2007; Lo Verso et al., 2018; Messaoudi et al., 2013). These two Lactobacillus bacterial strains may increase resistance to CP infection by inhibiting enteric pathogens through the competitive exclusion and the microbiota composition alteration. It is likely that increase in Lactobacillus population in the ceca which may be a result of an influx from the upper intestine, could contribute to the enhancement of local gut microbial ecology to facilitate the recovery from CP infection (GharibNaseri et al., 2019; Latorre et al., 2018; Stanley et al., 2012).
Following EM, CP, or EP dual infections, OTUs belonging to the genus Bacteroides decreased significantly compared with the sham control group. Bacteroides provide nutrients for the host by metabolizing carbohydrates in normal birds and maintain a complex and generally beneficial relationship with the host in the gut, but they can induce significant pathology outside of the gut environment (Wexler, 2007).
As a result of the disruption of intestinal microbiota homeostasis, components of healthy microbiota residing in highly competitive surroundings may shift in response to invasions of pathogenic EM and or CP. In this study, the relative changes of gene families associated with biological functions were inferred, which may provide relevant insight into competitive dynamics of intestinal communities. ATP-binding protein (K01990) is involved in the energy utilization process of ATP binding and hydrolysis to provide energy needed for the translocation of substrates across membranes (Fath and Kolter, 1993), while maltose 6′-phosphate phosphatase (K06896) catalyzes the dephosphorylation of intracellular maltose 6′-phosphate to form maltose (Mokhtari et al., 2013). In EM-challenged group, these two gene families were dramatically decreased in abundance, suggesting the inhibitive impacts of EM infection on maltose uptake, energy metabolism and substance translocation. Meanwhile, the reduction in abundance of hexosaminidase (K12373) engaged in keratan sulfate degradation was observed in CP-infected group. As part of normal homeostasis of glycoproteins (Caterson and Melrose, 2018), CP infection may interfere with the degradation of glycoproteins in healthy microbiota. Compared to the sham control group in this study, the EP dual infection group had reduced abundances in a number of the enzymes including the abovementioned ATP-binding protein (K01990) and maltose 6′-phosphate phosphatase (K06896): beta-glucosidase (K05349), RNA polymerase sigma-70 factor, extracytoplasmic function (ECF) subfamily (K03088), and alpha-galactosidase (K07407). Beta-glucosidase (K05349) is an enzyme that catalyzes the hydrolysis of β-glucosides, diglucosides and oligosaccharides to release glucose and an aglycone involved a plethora of biological processes including cyanoamino acid, starch and sucrose metabolism, and phenylpropanoid biosynthesis (Qian and Sun, 2009; Zhang et al., 2019). Alpha-galactosidase is an enzyme to hydrolyze the terminal alpha-galactosyl moieties from glycolipids and glycoproteins and specifically catalyze the removal of the terminal α-galactose from oligosaccharides (Scriver, 2001). RNA polymerase sigma-70 factor regulates DNA-templated transcription (Paget, 2015), while ECF subfamily are small regulatory proteins with largely unknown roles and mechanisms of regulation (Helmann, 2002). Thus, EP infection may impede the maintenance of steady-state metabolic levels and normal initiation of transcription machinery of certain populations in cecal microbiota. Taken Together, all these data may reveal the microbiota dysbiosis associated with EM/CP/EP infections and pre-estimate excessive competitions between these microbiota species (Bauer et al., 2018). Understanding of these mechanisms could help manage the chickens with exposure risks to EM/CP infections by dietary manipulations.
E. maxima and C. perfringens coinfections successfully induced NE with gut lesions and significant reductions in RBWG%. The NE challenge model did not affect cecal microbial diversity, but influenced the cecal microbial composition, and abundance of KEGG enzymes in microbiota. Additionally, significant correlations between the cecal microbiota modules and RBWG% have been determined in the sham control, EM and CP groups. Our results thus provide insights into physiological consequences of EM/CP infections on chicken gut microbiota, and increase our understanding of microbiota-host interaction that will facilitate the development of practical antibiotic-independent disease control strategies to improve gut health, immune system and growth.
This article was originally published in Research in Veterinary Science, Volume 132, October 2020, Pages 142-149. https://doi.org/10.1016/j.rvsc.2020.05.013. This is an Open Access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).