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Changes in the intestinal microbiota of broiler chicken induced by dietary supplementation of the diatomite-bentonite mixture

BMC Veterinary Research volume 21, Article number: 13 (2025) Cite this article

Abstract

Background

Diatomite is a source of biologically available silicon but in feed industry its insecticide and anti-caking properties have been also widely recognized. The aim of the study was to evaluate the effect of dietary diatomite-bentonite mixture (DBM) supplementation on the quantitative and qualitative composition of the bacterial microbiome of the broiler chicken gut. The trial was carried out on 960 Ross 308 broiler chickens divided into 2 experimental groups throughout the entire rearing period lasting 6 weeks. The birds were fed complete granulated diets without (group C) or with DBM (group E) in an amount of 1% from the 11 day of life. Two nutritionally balanced diets were used, tailored to the age of the broilers: a grower diet (from day 11 to 34) and a finisher diet (from day 35 to 42 of life).

Results

Diatomite used in a mixture with bentonite significantly altered the microbiome. Restricting the description to species that comprise a minimum of 1% of all analyzed sequences, 36 species in group E (with diatomite) and 30 species in group C (without diatomite) were selected. Several bacteria species were identified in intestinal contents of chickens for the first time. Thirteen species occurred only in group E: Agathobaculum butyriciproducens, Anaerobutyricum hallii, Anaerobutyricum soehngenii, Blautia producta ATCC 27,340 = DSM 2950, Gordonibacter pamelaeae 7-10-1-b, Helicobacter pullorum NCTC 12,824, Lactobacillus crispatus, L. helveticus DSM 20,075 = CGMCC 1.1877, Mucispirillum schaedleri, Phascolarctobacterium faecium, Phocaeicola coprocola DSM 17,136, P. massiliensis, and Ruthenibacterium lactatiformans.

Conclusions

The findings highlight the intricate and potentially consequential relationship between diet, specifically diatomite-bentonite mixture supplementation, and gut microbiota composition.

Peer Review reports

Background

The gut microbiota of poultry has been the subject of intensive research over the past 20 years [4, 7, 12, 14, 21, 37, 46, 55, 60, 65, 68, 92, 114]. The continuous development of the broiler chicken industry and its growing importance in ensuring the production of healthy food have stimulated the use of new techniques in this area. Thanks to high-throughput sequencing technologies, aimed at identifying new species and determining their metabolic capacity and function in the host organism, understanding the mechanism of protective activity, and describing the horizontal transmission to hosts of other taxonomic classes became available like never before. In this context, it is noteworthy that sequences originally determined in the gut contents of chickens are often found in samples taken from the intestinal system of humans, other animals, plants, soils, and water reservoirs (Global distribution of the 16 S sequence, https://bacdive.dsmz.de). Therefore, it is not possible to separate knowledge related to animals from that related to human health when exploring this topic, especially since raw materials from animals ultimately serve as food for humans. Furthermore, the taxonomic classification of these microorganisms is continually evolving. For example, the phyla previously known as Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes have experienced recent changes in their nomenclature, with Proteobacteria now sometimes referred to as Pseudomonadota, Firmicutes as Bacillota, Actinobacteria as Actinomycetota, and Bacteroidetes as Bacteroidota. Older publications may still use the previous names.

The composition and diversity of the gut microbiota is influenced by many factors, including host genetics [41, 81], long-term diet [14, 19, 39, 58, 81], medication [77, 91], age of the host [65] and several external factors such as ecological conditions of the host environment and laboratory culture of samples [1, 7, 46, 80]. The impact of common parasitic diseases (mainly coccidiosis caused by Eimeria sp.) is also worth mentioning [57].

Among many environmental factors, nutrition has the greatest influence on the composition of microorganisms that inhabit the digestive tract of chickens and the quality of their products. In this regard, the use of different feed additives, including minerals such as clays [63] or diatomaceous earth [10] became more and more common. The role of these substances is not only to provide minerals, but also to bind microbiological or toxicological agents from contaminated feed, which can affect the health, productivity and safety of livestock animals. Diatomaceous earth (diatomite DT) is a naturally occurring sedimentary rock which consists of fossilized diatoms [10] and is made up of almost amorphous silicon dioxide (80–90%), with minor contains of alumina (2–4%) and iron oxide (0,5–2%). Diatomite contains a wide range of naturally occurring minerals such as calcium, magnesium, iron, phosphate, sodium, titanium, potassium and organic amorphous silica [106], has the properties of a mycotoxin absorbing agent [43], can inactivate some bacteria like Staphylococcus aureus and Escherichia coli [17] and prevent the development of ascites in broiler chickens [42]. In feed industry its insecticide and anti-caking proprieties have been widely recognized. Diatomite is also a source of biologically available silicon and has many other positive physiological properties. However, chemical pollution of this material, especially with heavy metals, may limit its nutritional suitability. The earlier work has shown that the mobility and toxicity of heavy metals from DT may be reduced through the use of bentonite especially if a mixture of diatomite and bentonite in a ratio of 75:25% (wt/wt) [36]. Considering the potential of using such a mixture in practical poultry feeding, we decided to evaluate its impact on changes in gut microbiome, which may, in turn, alter the health and performance of broiler chickens.

Most of the microbiome in chickens caecum is represented by Gram-positive (77%) and Gram-negative rods (14%) as well as Gram-positive cocci (9%) [20]. The predominant bacterial phyla are Proteobacteria (2–9%), Firmicutes (50–70%), Actinobacteria (1–3.5%) and Bacteroidetes (approximately 12–40% of the general microbiome) [4, 20]. There are approximately 31 genera described from the Firmicutes family, of which 5% are Eubacterium, Ruminococcus and Clostridium. Other genera identified by sequencing include Riemeralla, Paraprevotella, Tanneralla, Prevotella, Phascolarctobacterium, Megamonas, Faecalibacterium, Subdoligranulum and Gemmiger. The predominant genera of Proteobacteria include Neissenia, Desulfohalobium, Shigella, Escherichia, Helicobacter and Campylobacter as is the genus Phocaeicola in Bacteroidetes [14, 60, 68, 107]. Although some studies report that at 3 weeks of age, the bacterial population of the chick changes from Proteobacteria, Bacteroides and Firmicutes to only Firmicutes [68], others indicate that anatomically distant sites differ in the qualitative composition of the microbiota for example Acinetobacter and Acidobacteria predominate in the jejunum as Bacteroides and Clostridium in the cecum [4]. At least 80% of the total bacterial species present in chicken or human caecum cannot yet be cultured in the laboratory (naturally occurring in quantity 1010–1011 cells per gramme) and can only be identified by high-throughput sequencing techniques [2, 4, 60, 91, 107]. Due to a crucial role of microbiota in digestion and protection processes, the aim of the study was to assess the effect of dietary diatomite-bentonite mixture (DBM) supplementation on the quantitative and qualitative composition of chicken gut bacterial microbiome. The aim of the study was to assess the effect of dietary diatomite-bentonite mixture (DBM) supplementation on the quantitative and qualitative composition of chicken gut bacterial microbiome.

Methods

Animal care and welfare

Animals were treated in a manner according to the principles stated in Directive 2010/63/EU, regarding the protection of animals used for experimental and other scientific purposes, enforced in Poland under Acts 266/2015 and 638/2020 [98]. The practises for animals were equivalent to practices undertaken for the purposes of recognised animal husbandry and not likely to cause pain, suffering, distress, or lasting harm equivalent to, or higher than, that caused by the introduction of a needle in accordance with good veterinary practise. For this reason, an ethics approval by an institutional review board was not necessary according to Directive 2010/63/EU Art 2.5.e-f (OJ L 276, 0.10.2010, p. 33–79) the Act 2015/266/RP Art.1.2. (O.J. 2015 pos. 266). The study reported in the manuscript follows the recommendations of the ARRIVE guidelines [72] and was registered under the number BZ/4240/22/WHBZ. The heating and lighting programmes were in accordance with Ross 308 broiler stock management [6].

Experimental design

The trial was carried out at the Experimental Poultry Farm in Potok, belonging to Ekoplon S.A. Poland. The experiment was conducted on 960 chickens divided into 2 experimental groups throughout the entire rearing period lasting 42 days. Prior to the experiment, the building and equipment were thoroughly cleaned and disinfected in accordance with the principles of veterinary biosecurity. Before the chicks were delivered, the hall was lined with bedding (peat with wood chips) and heated to an air temperature of 34 °C and a floor temperature of 28 °C. The one-day-old broiler Ross 308 chicks (Aviagen EPI ltd, Poland) were randomly divided into two groups of equal weight: control (C) and experimental (E), separated by gender. In each group there were 6 pens (3 for male and 3 for female), with 80 chicks per pen. Sexing the animals and maintaining separate male and female groups was necessary for the production study. For the purposes of this work, only male individuals were used to eliminate factors related to the presence of female hormones. The chicks were fed with the same starter type diet without the addition of experimental diatomite-bentonite mixture (DBM) for 10 days. This procedure aimed to reduce the number of stress-inducing factors during the early stage of rearing while providing highly digestible feed, recommended for the not fully developed digestive tract of chicks. From day 11 of life, the birds were fed complete diets without (C group) or with a 1% addition (10 kg per 1 t of mixture on a fresh matter basis) of DBM (E group) according to the age of the broilers: grower (d 11–34) and finisher (d 35 to 42). Complete nutritionally balanced diets were prepared according to CVB (2018). The DBM consisted of 75% diatomite and 25% bentonite, prepared as described by Gondek et al. [36]. The animals were housed in the same chicken house on both sides of the feeding corridor. Feed and water were given ad libitum throughout the entire growing period.

Parasitological analyses

Coproscopical examinations were performed to exclude the impact of Eimeria spp. infection on the experiment’s results. Fecal samples were collected three times from each pen: after the first, third, and final weeks of the rearing period. The samples were then analyzed using the quantitative McMaster method with centrifugation [73].

Slaughtering and collection of digesta

Immediately after slaughter (5–10 min), the gastrointestinal tract of the males was rapidly removed, and the cecum segment was excised. The cecum content (1 to 1.5 g per bird) was collected into two sterilized tubes (1.5 mL). In total, 36 samples (18 samples per group) were flash-frozen in liquid nitrogen and then stored at −80 °C for sequencing. In each sample, analyses were performed in triplicate, resulting in 54 replicates sequenced within each group. The final body weight at slaughter of the male birds selected for digesta collection was 3067 ± 262 g and 3222 ± 225 g, respectively for the C and E groups.

Sequencing, data calculation, and statistical analysis

Prior to sequencing, the samples were thawed at a controlled temperature. DNA was then isolated using a silica column-based kit (QIAamp PowerFecal Pro DNA Kit, QIAGEN), according to the manufacturer’s instructions. Following DNA isolation, polymerase chain reaction (PCR) was performed to amplify the 16 S rRNA gene regions of the bacterial DNA. This amplification was carried out using specific primers provided in the 16 S Barcoding Kit (Oxford Nanopore), following the kit’s protocol. After PCR amplification, the samples were prepared for sequencing according to the Oxford Nanopore library preparation protocol. Two 16 S Forward primers (NanoF-1 and NanoF-2) with the sequence AGAGTTTGATCMTGGCTCAG and one 16 S Reverse primer (NanoR) with the sequence CGGTTACCTTGTTACGACTT were used. Amplification was performed using the following cycling conditions (Table 1). Nanopore sequencing was then carried out using the MinIon device (Oxford Nanopore). Upon completion of the sequencing, the raw data was processed using the MiniKnow software (Oxford Nanopore) to assess the quality of the reads and perform base calling. Further analysis, including taxonomic classification of the sequences, was performed using the Epi2Me platform (Fastq 16s workflow).

Table 1 PCR amplification cycling conditions
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The bacterial microbiome dataset, which includes information about different species and their counts, was grouped into diatomit and nondiatomit diet groups (e.g., treatment groups, E and C respectively). The species count data were standardized using the Z score normalization method (StandardScaler) to ensure that each species contributed equally to the analysis. Principal Component Analysis (PCA) was applied to the standardized data to reduce dimensionality and identify the principal components that captured the majority of the variance in the data. A redundancy analysis (RDA) was performed by fitting a linear regression model using the “group” variable as the predictor and the principal components as the response variables. Ordinary least squares (OLS) regression was used to estimate the relationship between the groups and the principal components. Multivariate Analysis of Variance (MANOVA) was applied to test the differences in the first two principal components between the groups, using the formula “PC1 + PC2 ~ group.” Additionally, One-Way ANOVA tests were performed separately for the first two principal components to compare the means between the groups.

Visualisation techniques were employed, including the generation of a scatter plot to visualise the distribution of the first two principal components for each group, and a stacked bar plot to display the percentage of the top 10 species for each group. Additionally, a phylogenetic tree was constructed to elucidate the evolutionary relationships among the identified bacterial species in the gut microbiome of both groups. This tree was generated using aligned 16 S rRNA gene sequences and was visualized to highlight the taxonomic classification up to the species level for groups C and E. In the statistical tests and interpretation phase, the RDA results provided information on the relationship between the groups and the composition of the species, as represented by the principal components. The MANOVA test determined whether there were statistically significant differences in the principal components between the groups. The ANOVA tests for PC1 and PC2 assessed differences in the means of these components between the groups, with statistical significance determined using P > 0.05.

To identify significant differences in the abundance of bacterial taxa between the diatomit and nondiatomit diet groups, a series of univariate statistical analyses were conducted at the phylum, genus, and species levels. For each taxonomic level, Fisher’s Exact Test was employed to determine whether there were statistically significant differences in the abundance of each taxon between the two diet groups. To mitigate increased risk of Type I errors (false positives) due to multiply comparisons, p-values obtained from Fisher’s Exact Tests were adjusted using the False Discovery Rate (FDR) method, specifically the Benjamini-Hochberg procedure.

The analysis was conducted using the Python programming language, leveraging several widely used libraries for data manipulation, statistical modeling, and visualization. This included Pandas for data manipulation and analysis, Scikit-learn for normalization and PCA, Statsmodels for conducting RDA, MANOVA, and ANOVA tests, and Matplotlib for generating scatter plots and bar plots. For the univariate taxonomic level comparisons, the scipy.stats library was utilized to perform Fisher’s Exact Tests, while statsmodels.stats.multitest was employed to apply the Benjamini-Hochberg FDR correction to the resulting p-values.

Results

Parasite analyses did not reveal any infection caused by coccidia (Eimeria sp.) or helminths, during the whole rearing period. In turn, the samples obtained from cecal chicken feces from both research groups, with (E) or without the addition of DBM (C), differed in the presence of several species characteristic of each other. Sequences assigned isolates to well-known and relatively new species. Library coverage ranged from 85 to 99.8% for both groups. Limiting the description to species with ≥ 1% share among all analysed sequences, 36 species in group E and 30 species in group C were selected (Fig. 1). The specific phyla and genus composition of identified sequences is presented in Tables 2, 3, and 4.

Fig. 1
figure 1

Average contribution with standard deviation of species specific to all identified sequences in group E with DBM addition and in group C without DBM addition

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Table 2 Taxonomic composition of identified sequences
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Table 3 The percentage distribution of the cecal microbial community the genus level
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Table 4 The percentage distribution of the cecal microbial community at the phylum level
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Thirteen species occurred only in Group E (Agathobaculum butyriciproducens, Anaerobutyricum hallii, (A) soehngenii, Blautia producta ATCC 27340 = DSM 2950, Gordonibacter pamelaeae 7–10-1-b, Helicobacter pullorum NCTC 12824, Lactobacillus crispatus, L. helveticus DSM 20075 = CGMCC 1.1877, Mucispirillum schaedleri, Phascolarctobacterium faecium, Phocaeicola coprocola DSM 17136, P. massiliensis, Ruthenibacterium lactatiformans), and 7 in Group C (Anaerostipes butyraticus, Blautia pseudococcoides, Intestinimonas timonensis, Megamonas funiformis YIT 11815, M. hypermegale, Neglectibacter timonensis, Phocaeicola plebeius DSM 17135). The remaining 23 species were confirmed in both groups (Acutalibacter muris, Blautia coccoides, (B) glucerasea, Butyricicoccus pullicaecorum, Faecalibacterium butyricigenerans, F. duncaniae, F. gallinarum, F. hattorii, F. longum, F. prausnitzii, Fournierella massiliensis, Fusicatenibacter saccharivorans, Gemmiger formicilis, G. gallinarum, Gorbachella massiliensis, Lactobacillus gallinarum, Ligilactobacillus salivarius, Limosilactobacillus urinaemulieris, Mediterraneibacter glycyrrhizinilyticus, Megamonas rupellensis, Oscillibacter massiliensis, Phocaeicola dorei, Subdoligranulum variabile).

In Figs. 2 and 3, the taxonomy trees for Group C and Group E are respectively presented, extending down to the species level. These trees provide a comprehensive visual representation of the bacterial communities in each group, highlighting the diversity and relative abundance of bacterial taxa. The hierarchically organized percentage compositions illustrate differences in dominant and less abundant taxa, allowing for a direct comparison of the microbial communities between the two groups and showcasing how variations in species composition impact the overall structure of the microbiome.

Fig. 2
figure 2

Graphical representation of the bacterial communities in Group E with DBM addition, illustrating the taxonomic breakdown and respective percentage composition for each branch

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Fig. 3
figure 3

Graphical representation of the bacterial communities in Group C without DBM addition, illustrating the taxonomic breakdown and respective percentage composition for each branch

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Principal Component Analysis (PCA) was conducted to understand how the samples differentiate from each other based on the presence of various microbial species. The two main components (PC1 and PC2) explained a significant proportion of the variability in the data (Fig. 4). The plot illustrates the pronounced separation between the two dietary treatments, particularly along the PC1 axis, highlighting the influence of diatomite on the gut microbiome. Group C (red) represents the diet without DBM, and group E (blue) represents the diet with DBM. Individual data points are depicted for each group and the corresponding ellipses represent the spread of the data within each group. PC1 explains 56.47% of the total variance and significantly differentiates the two groups (ANOVA, F-value: 7.33, P-value: 0.017), indicating a distinct effect of DBM on microbial composition. PC2 accounts for 19.85% of the variance but does not differentiate significantly between the groups (ANOVA, F-value: 0.35, P-value: 0.565). The highest positive correlations with PC1 were observed for the following 10 species: Akkermansia muciniphila, Bacteroides thetaiotaomicron, B. vulgatus, Bifidobacterium longum, Escherichia coli, Eubacterium rectale, Faecalibacterium prausnitzii, Lactobacillus rhamnosus, Roseburia intestinalis and Ruminococcus bromii. These findings suggest that the presence of DBM has a significant impact on the composition of microbiome in the samples. PC2 did not show a significant difference between groups.

Fig. 4
figure 4

Principal Component Analysis (PCA) of Microbial Composition Between Diets with and without Diatomite. Group C (without diatomite) and Group E (with diatomite)

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A graph of side-by-side horizontal bar charts was created to display the percentage of the top 10 species for each group (with and without DBM; Fig. 5). Each bar represents a single sample, and the colours within the bar denote distinct species. The percentage contribution of the species was calculated based on the normalized read count for each species relative to the sum of the read counts. Differences in the structure of the microbiome allow the identification of species that may have a particular impact on the differentiation of groups of chickens with and without the addition of DBM. Until now, in poultry, mainly Blautia coccoides, Faecalibacterium prausnitzii, Helicobacter pullorum, Lactobacillus gallinarum and Ligilactobacillus salivarius, identified in this work, have been described in the literature due to their high frequency or pro-health or disease-promoting properties. Most of the species identified and presented in this work are described in poultry for the first time.

Fig. 5
figure 5

Percentage contribution of the Top 10 Microbial Species in each sample. Group C (without diatomite) and Group E (with diatomite)

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Discussion

Identified species are not insignificant for the health of poultry or humans. The human microbiota is correlated with the microbiota of raw materials, also of animal origin. Poultry health is closely related to the quantitative and qualitative composition of the gut microbiota [70, 91]. Functions of the bacteria include host metabolic and immune response and thereby influence the development and treatment of infections and chronic diseases, as well as absorption of nutrients [2, 4, 114]. Young chickens are very sensitive to enteropathogen infections because their intestinal microbiota is not fully established [18]. The health of gastrointestinal tract (GIT) impacts therefore animal productivity [4]. Short-chain fatty acids (SCFAs), produced by fermentation of dietary fibre by several abundant genera of the intestinal microbiota, have been reported to induce beneficial effects on energy metabolism [21, 74, 76, 90, 11378 ]. Butyrate is the main energy source for colonocytes, and it has protective properties against colorectal cancer and inflammatory bowel diseases inter alia by inhibiting NF‑κβ activation and interferon-γ expression [11, 12, 47, 59, 76, 93, 104, 114]. A potential protective role of gut bacteria was found through the reduction of inflammatory cytokines [13, 67, 68, 90, 101 ]. Subdoligranulum variabile and Faecalibacterium genus are e.g. currently recognized as one of the most important gut bacteria for human and animals health [31, 53, 65, 78, 104] (Table 5). Several authors have demonstrated the antimicrobial activity of human and avian strains against bacterial pathogens, including Campylobacter spp., Clostridium perfringens, Pasteurella multocida, Riemerella anatipestifer, Salmonella enterica and Staphylococcus aureus [5, 31, 57, 74, 104]. The competitive exclusion of unfavorable strains depends on the production of lactic acid, hydrogen peroxide and bacteriocins, as well as the ability of the gut strains to permanently colonize the intestine [76]. Lund et al. [56] indicated that the poultry farm environment therefore plays a key role in the recruitment and development of the gut microbiota on the example of Gemmiger gallinarum, Gorbachella massiliensis, Faecalibacterium hattorii, F. prausnitzii and Subdoligranulum variabile. Faecalibacterium gallinarum and Subdoligranulum variabile were found as the most abundant sequences in this work, with an average share of 4.4 to 12.3% among all sequences. They are described in the literature as strictly anaerobic, mesophilic, non-spore-forming, non-motile, rod-shaped, Gram-positive (S. variabile, G. gallinarum) or Gram-negative (G. massiliensis, F. gallinarum, F. hattori), host-associated and found in the digestive system (cecum, ileum) of birds and mammals, including human. They are associated with health-promoting activity [23]. Their major end-product in M2G medium is n-butyrate. Furthermore, bacteria are mostly cathalase-negative, except for G. gallinarum, and can produce formic (S. variabile, F. hattori) as well as lactic acid (G. gallinarum, F. hattori) [26, 37, 40, 82, 114]. Diatomite has already been a material for research on the health condition of chicken flocks. This mineral was applied during composting of chicken faeces and its inhibitory effect on Firmicutes and Proteobacteria communities was confirmed [75].

Table 5 Characteristics of the morphology, habitat and beneficial/adverse effects on the host organism of selected intestinal bacteria, determined based on 16s sequence
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The increasing research reveals several beneficial effects and therapeutic properties of butyrate-producing bacteria for both humans and animals. A summary of the basal metabolism, probiotic qualities and habitat of selected strains determined in this study is summarised in Table 4. The studies of Pattar et al. [71] indicate that the addition of diatomaceous earth to feed contaminated with aflatoxin B1 and ochratoxin A decreased the toxic effects of mycotoxins. Therefore, there was an improvement in body weight gain, feed conversion ratio, and feed intake, and a reduction in mortality. The addition of this mineral to the broilers diets also had a positive effect on the higher participation of breast muscles and lower fat content of broiler carcasses. Furthermore, the broilers thigh bones were characterized by a higher strength as compared to the control group [42, 108]. In turn, in the research of Isabirye at al. [44] it has been shown the efficacy of diatomite in the treatment of chicken against Ascaridia galli and ectoparasites. Birds infected with A. galli treated with diatomite supplement showed reduce intestinal parasitic load and better controlling mites in chicken.

Conclusions

Diatomite used in a mixture with bentonite (DBM) significantly alters the microbiome, which may have implications in the context of the studied environment and the health-promoting properties of food. Our analysis identified bacterial species not previously found in the intestinal contents of chickens, expanding our knowledge of the complex interactions in this microbial community. We observed that the dietary intervention not only affected the abundance and diversity of bacterial species but also led to the emergence of potentially beneficial or harmful taxa. These findings highlight the intricate and potentially consequential relationship between diet, specifically diatomite supplementation, and gut microbiota composition. The presented results constitute a part of a larger analysis, demonstrating that the use of diatomite-bentonite mixture to the broiler chicken diet in an amount of 1% resulted in a favourable increase in body weight gain, with a tendency to higher overall final body weight of the birds (Micek et al. unpublished).

Data availability

Sequence data that support the findings of this study have been deposited in the National Library of Medicine NCBI with the promary accession code PRJNA1104621.

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Acknowledgements

Not applicable.

Funding

This research was included in the grant entitled: Implementation of the concept of new products based on activated diatomite, intended for use in poultry production. Grant number: BZ/4240/WHiBZ/2022.

Author information

Authors and Affiliations

  1. Department of Infectious Diseases and Public Health, University of Agriculture in Krakow, Al. Mickiewicza 21, Krakow, 31-120, Poland

    E. Węsierska

  2. Department of Nutrition, Animal Biotechnology, and Fisheries, University of Agriculture in Krakow, Al. Mickiewicza 24/28, Krakow, 30-059, Poland

    P. Micek

  3. SPARK-TECH, Sp. z o.o., Rynek Główny 28, Krakow, 31-010, Poland

    M. G. Adamski, G. Kunstman & S. Mosiołek

  4. Department of Agricultural and Environmental Chemistry, University of Agriculture in Krakow, Al. Mickiewicza 21, Krakow, 31-120, Poland

    K. Gondek

  5. Department of Zoology and Animal Welfare, University of Agriculture in Krakow, Al. Mickiewicza 24/28, Krakow, 30-059, Poland

    M. Lis, M. Trela, J. Kowal & A. Wyrobisz-Papiewska

  6. Department of Genetics, Animal Breeding and Ethology, University of Agriculture in Krakow, Al. Mickiewicza 24/28, Krakow, 30-059, Poland

    D. Wojtysiak

  7. Doctoral School of Exact and Natural Sciences, Jagiellonian University, Lojasiewicza 11, Krakow, 30-348, Poland

    S. Mosiołek

  8. Jagiellonian Centre for Experimental Therapeutics, Jagiellonian University, Bobrzynskiego 14, Krakow, 30-348, Poland

    S. Mosiołek

  9. Specialized Mining Company “Górtech” Sp. z o.o, ul. Wielicka 50, Krakow, 30-552, Poland

    K. Smoroń

Authors
  1. E. Węsierska
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  2. P. Micek
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  3. M. G. Adamski
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  4. K. Gondek
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  5. M. Lis
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  6. M. Trela
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  7. D. Wojtysiak
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  8. J. Kowal
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  9. A. Wyrobisz-Papiewska
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  10. G. Kunstman
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  11. S. Mosiołek
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  12. K. Smoroń
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Contributions

E.W. and M.A. wrote the main manuscript text, S.M. and K.S. prepared Figs. 1, 2, 3, 4 and 5. Other authors: P.M., K.G., M.L., M.T., D.W., J.K., A.W-P., G.K. participated in the study (laboratory analyses). All authors reviewed the manuscript.

Corresponding author

Correspondence to E. Węsierska.

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Ethics approval and consent to participate

The study was conducted according to the guidelines of the Declaration of Helsinki. All the animals were treated according to the principles stated in Directive 2010/63/EU, regarding the protection of animals used for experimental and other scientific purposes, enforced in Poland by Legislative Decree 266/2015. According to EU/PL law, approval from an animal ethics committee was not required, and the birds were not subjected to any invasive procedures. All broiler chicken rearing procedures were conducted as laid out in the Ross 308 broiler management following Directive [21]/43/EC.

Competing interests

The authors declare no competing interests.

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Węsierska, E., Micek, P., Adamski, M.G. et al. Changes in the intestinal microbiota of broiler chicken induced by dietary supplementation of the diatomite-bentonite mixture. BMC Vet Res 21, 13 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12917-024-04439-4

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12917-024-04439-4

Keywords

BMC Veterinary Research

ISSN: 1746-6148

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