Performance of distinct microbial based solutions in a Campylobacter infection challenge model in poultry

Background Antibiotic growth promoters (AGPs) are commonly used within poultry production to improve feed conversion, bird growth, and reduce morbidity and mortality from clinical and subclinical diseases. Due to the association between AGP usage and rising antimicrobial resistance, the industry has explored new strategies including the use of probiotics and other microbial-based interventions to promote the development of a healthy microbiome in birds and mitigate against infections associated with food safety and food security. While previous studies have largely focused on the ability of probiotics to protect against Clostridium perfringens and Salmonella enterica, much less is known concerning their impact on Campylobacter jejuni, a near commensal of the chicken gut microbiome that nevertheless is a major cause of food poisoning in humans. Results Here we compare the efficacy of four microbial interventions (two single strain probiotics, the bacterium—Pediococcus acidilactici, and the yeast—Saccharomyces cerevisiae boulardii; and two complex, competitive exclusion, consortia—Aviguard and CEL) to bacitracin, a commonly used AGP, to modulate chicken gut microbiota and subsequently impact C. jejuni infection in poultry. Cecal samples were harvested at 30- and 39-days post hatch to assess Campylobacter burden and examine their impact on the gut microbiota. While the different treatments did not significantly decrease C. jejuni burden relative to the untreated controls, both complex consortia resulted in significant decreases relative to treatment with bacitracin. Analysis of 16S rDNA profiles revealed a distinct microbial signature associated with each microbial intervention. For example, treatment with Aviguard and CEL increased the relative abundance of Bacteroidaceae and Rikenellaceae respectively. Furthermore, Aviguard promoted a less complex microbial community compared to other treatments. Conclusions Depending upon the individual needs of the producer, our results illustrate the potential of each microbial interventions to serve flock-specific requirements.

No-Antibiotic-Pectin-Based Treatment Differently Modified Cloaca Bacteriobiome of Male and Female Broiler Chickens

As the information about the effect of pectin prebiotics on chicken gut microbiota is scarce, by using high throughput metagenomic sequencing with Illumina Miseq we examined the cloaca bacteriobiome of male and female chickens receiving antibiotic- or pectin-containing drinking water. The bacteriobiome was dominated by two phyla (Firmicutes and Proteobacteria) and three classes (Clostridia, Bacilli and Gammaproteobacteria), with the difference displayed by the relative abundance of 42 OTUs. At the level of the major dominant OTUs, prebiotic supplementation drastically increased Enterococcus abundance (from 0 to 11% and 23% in males and females, respectively). The better feed use efficiency and growth performance of the pectin-receiving chickens implied their better health and corroborated putative beneficial role of the altered bacteriobiome, although its ecophysiological and/or pathogenic importance could not be readily inferred. Notably, the gut microbiota response to antibiotics showed more sex-related differential OTUs as compared to the pectin prebiotic (19 vs. 4), suggesting different mechanisms of the studied supplementations in shaping the gut bacteriobiome in different sexes. Therefore, we recommend targeting sex as a separate factor in interventional studies to account for sex-specific peculiarities in the microbiome response and taking into account the male/female ratio of industrial flocks prior to choosing a production technology. The studied prebiotic (pectin) can be used in developing new pre/symbiotic preparations and supplementation regimes as alternatives to antibiotics for stimulating broiler chicken production.

Genome-Resolved Metagenomics of the Chicken Gut Microbiome

Increasing evidence shows that the chicken gastrointestinal microbiota has a major effect on the modulation of metabolic functions and is correlated with economic parameters, such as feed efficiency and health. Some of these effects derive from the capacity of the chicken to digest carbohydrates and produce energy-rich metabolites such as short-chain fatty acids (SCFA) and from host-microbe interactions. In this study, we utilized information from metagenomic assembled genomes (MAGs) from chicken gastrointestinal tract (GIT) samples, with detailed annotation of carbohydrate-active enzymes (CAZymes) and genes involved in SCFA production, to better understand metabolic potential at different ages. Metagenomic sequencing of 751 chicken GIT samples was performed to reconstruct 155 MAGs, representing species which belong to six phyla, primarily Firmicutes followed by Proteobacteria. MAG diversity significantly (p < 0.001) increased with age, with early domination of Lachnospiraceae, followed by other families including Oscillospiraceae. Age-dependent shifts were observed in the abundance of genes involved in CAZyme and SCFA production, exemplified by a significant increase in glycosyltransferases (GTs) and propionic acid production pathways (p < 0.05), and a lower abundance of glycoside hydrolases (GHs) (p < 0.01). Co-occurrence analysis revealed a large cluster highly interconnected by enzymes from GT2_2 and GH3 families, underscoring their importance in the community. Furthermore, several species were identified as interaction hubs, elucidating associations of key microbes and enzymes that more likely drive temporal changes in the chicken gut microbiota, and providing further insights into the structure of the complex microbial community. This study extends prior efforts on the characterization of the chicken GIT microbiome at the taxonomic and functional levels and lays an important foundation toward better understanding the broiler chicken gut microbiome helping in the identification of modulation opportunities to increase animal health and performance.

Eggshell and Feed Microbiota Do Not Represent Major Sources of Gut Anaerobes for Chickens in Commercial Production

In this study, we addressed the origin of chicken gut microbiota in commercial production by a comparison of eggshell and feed microbiota with caecal microbiota of 7-day-old chickens, using microbiota analysis by 16S rRNA sequencing. In addition, we tested at which timepoint during prenatal or neonatal development it is possible to successfully administer probiotics. We found that eggshell microbiota was a combination of environmental and adult hen gut microbiota but was completely different from caecal microbiota of 7-day-old chicks. Similarly, we observed that the composition of feed microbiota was different from caecal microbiota. Neither eggshell nor feed acted as an important source of gut microbiota for the chickens in commercial production. Following the experimental administration of potential probiotics, we found that chickens can be colonised only when already hatched and active. Spraying of eggs with gut anaerobes during egg incubation or hatching itself did not result in effective chicken colonisation. Such conclusions should be considered when selecting and administering probiotics to chickens in hatcheries. Eggshells, feed or drinking water do not act as major sources of gut microbiota. Newly hatched chickens must be colonised from additional sources, such as air dust with spores of Clostridiales. The natural colonisation starts only when chickens are already hatched, as spraying of eggs or even chickens at the very beginning of the hatching process did not result in efficient colonisation.

A reference gene catalogue of chicken gut antibiotic resistomes

Background: The chicken gut microbiota, as a reservoir of antibiotic resistance genes (ARGs), poses a high risk to humans and animals worldwide. Yet a comprehensive exploration of the chicken gut antibiotic resistomes remains incomplete. Results: In this study, we established the largest chicken gut resistance gene catalogue to date through metagenomic analysis of 629 chicken gut samples. We found significantly higher abundance of ARGs in the Chinese chicken gut than that in the Europe. tetX, mcr, and blaNDM, the genes resistant to antibiotics of last resort for human and animal health, were frequently detected in the Chinese chicken gut. The abundance of ARGs was linearly correlated with that of mobile genetic elements (MGEs). The host-tracking analysis identified Escherichia, Enterococcus, Staphylococcus, Klebsiella, and Lactobacillus as the major ARG hosts. Especially, Lactobacillus, an intestinal probiotic, carried multiple drug resistance genes, and was proportional to ISLhe63, highlighting its potential risk in agricultural production processes. Conclusions: We first established a reference gene catalogue of chicken gut antibiotic resistomes. Our study help to improve the knowledge and understanding of chicken antibiotic resistomes for knowledge-based sustainable chicken meat production.

The distribution of antibiotic resistance genes in chicken gut microbiota commensals

Antibiotic resistance in bacterial pathogens or several indicator bacteria is commonly studied but the extent of antibiotic resistance in bacterial commensals colonising the intestinal tract is essentially unknown. In this study, we aimed to investigate the presence of horizontally acquired antibiotic resistance genes among chicken gut microbiota members in 259 isolates with known whole genomic sequences. Altogether 124 isolates contained at least one gene coding for antibiotic resistance. Genes coding for the resistance to tetracyclines (detected in 101 isolates), macrolide-lincosamide-streptogramin B antibiotics (28 isolates) and aminoglycosides (25 isolates) were the most common. The most frequent tetracycline resistance genes were tet(W), tet(32), tet(O) and tet(Q). Lachnospiraceae and Ruminococcaceae frequently encoded tet(W). Lachnospiraceae commonly coded also for tet(32) and tet(O). The tet(44) gene was associated with Erysipelotrichaceae and tet(Q) was detected in the genomes of Bacteroidaceae and Porphyromonadaceae. Without any bias we have shown that antibiotic resistance is quite common in gut commensals. However, a comparison of codon usage showed that the above-mentioned families represent the most common current reservoirs but probably not the original host of the detected resistances.

Geography as non-genetic modulation factor of chicken cecal microbiota

The gastrointestinal tract of chickens harbors a highly diverse microbiota contributing not only to nutrition, but also to the physiological development of the gastrointestinal tract. Microbiota composition depends on many factors such as the portion of the intestine as well as the diet, age, genotype, or geographical origin of birds. The aim of the present study was to demonstrate the influence of the geographical location over the cecal microbiota from broilers. We used metabarcoding sequencing datasets of the 16S rRNA gene publicly available to compare the composition of the Argentine microbiota against the microbiota of broilers from another seven countries (Germany, Australia, Croatia, Slovenia, United States of America, Hungary, and Malaysia). Geographical location played a dominant role in shaping chicken gut microbiota (Adonis R2 = 0.6325, P = 0.001; Mantel statistic r = 0.1524, P = 4e-04) over any other evaluated factor. The geographical origin particularly affected the relative abundance of the families Bacteroidaceae, Lactobacillaceae, Lachnospiraceae, Ruminococcaceae, and Clostridiaceae. Because of the evident divergence of microbiota among countries we coined the term “local microbiota” as convergent feature that conflates non-genetic factors, in the perspective of human-environmental geography. Local microbiota should be taken into consideration as a native overall threshold value for further appraisals when testing the production performance and performing correlation analysis of gut microbiota modulation against different kind of diet and/or management approaches. In this regard, we described the Argentine poultry cecal microbiota by means of samples both from experimental trials and commercial farms. Likewise, we were able to identify a core microbiota composed of 65 operational taxonomic units assigned to seven phyla and 38 families, with the four most abundant taxa belonging to Bacteroides genus, Rikenellaceae family, Clostridiales order, and Ruminococcaceae family.

Avian leukosis virus subgroup J infection influences the gut microbiota composition in chicken

Background: Avian leukosis virus (ALV) is a major cause of disease in poultry. Probiotics play a critical role in maintaining animal health. Studies have indicated that viral infection can alter the composition of the chicken gut microbiota. We hypothesized that ALV-J infection alters the probiotics composition in the chicken fecal bacterial microbiome. We performed high-throughput 16S rRNA gene sequencing and evaluated the gut microbiota profiles using feces from ALV-J-infected and healthy chickens.Results: The relative abundance at the phylum and species levels was calculated. The phylum Proteobacteria was more abundant in ALV-J-infected chickens than in healthy chickens. Additionally, the abundance of the opportunistic pathogen Propionibacterium acnes was significantly increased in ALV-J-infected chickens. Interestingly, ALV-J infection tended to be significantly decreased by the probiotics Lactobacillus helveticus and Lactobacillus reuteriConclusions: The study indicates that ALV-J infection significantly altered the gut microbiota distribution in chickens. Additionally, ALV-J infection significantly influenced the abundance of L. helveticus and L. reuteri in the chicken gut.

Gut Microbiota-Polyphenol Interactions in Chicken: A Review

The gastrointestinal tract of the chicken harbors very complex and diverse microbial communities including both beneficial and harmful bacteria. However, a dynamic balance is generally maintained in such a way that beneficial bacteria predominate over harmful ones. Environmental factors can negatively affect this balance, resulting in harmful effects on the gut, declining health, and productivity. This means modulating changes in the chicken gut microbiota is an effective strategy to improve gut health and productivity. One strategy is using modified diets to favor the growth of beneficial bacteria and a key candidate are polyphenols, which have strong antioxidant potential and established health benefits. The gut microbiota-polyphenol interactions are of vital importance in their effects on the gut microbiota modulation because it affects not only the composition of gut bacteria but also improves bioavailability of polyphenols through generation of more bioactive metabolites enhancing their health effects on morphology and composition of the gut microbiota. The object of this review is to improve the understanding of polyphenol interactions with the gut microbiota and highlights their potential role in modulation of the gut microbiota of chicken.

Composition and Function of Chicken Gut Microbiota

Studies analyzing the composition of gut microbiota are quite common at present, mainly due to the rapid development of DNA sequencing technologies within the last decade. This is valid also for chickens and their gut microbiota. However, chickens represent a specific model for host–microbiota interactions since contact between parents and offspring has been completely interrupted in domesticated chickens. Nearly all studies describe microbiota of chicks from hatcheries and these chickens are considered as references and controls. In reality, such chickens represent an extreme experimental group since control chicks should be, by nature, hatched in nests in contact with the parent hen. Not properly realising this fact and utilising only 16S rRNA sequencing results means that many conclusions are of questionable biological relevance. The specifics of chicken-related gut microbiota are therefore stressed in this review together with current knowledge of the biological role of selected microbiota members. These microbiota members are then evaluated for their intended use as a form of next-generation probiotics.