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Impact of Chlorella vulgaris and probiotic supplementation on performance, immunity and intestinal microbiota of broiler chickens

  • Verena Pereira Dinalli,

    Roles Conceptualization, Data curation, Formal analysis, Writing – original draft

    Affiliation Department of Animal Science, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • Marcio Carvalho Costa,

    Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Writing – review & editing

    Affiliation Department of Biomedical Sciences, University of Montreal, Saint-Hyacinthe, Quebec, Canada

  • Emerson José Venâncio,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Department of Pathological Sciences, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • João Antônio Barbosa Filho,

    Roles Conceptualization, Methodology, Visualization, Writing – review & editing

    Affiliation Department of Animal Science, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • José Antônio Bessegatto,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Laboratory of Animal Virology, Department of Veterinary Preventive Medicine, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • Augusto Tasch Holkem,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Department of Biomedical Sciences, University of Montreal, Saint-Hyacinthe, Quebec, Canada

  • Amauri Alcindo Alfieri,

    Roles Formal analysis, Methodology

    Affiliation Laboratory of Animal Virology, Department of Veterinary Preventive Medicine, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • Caio Abercio da Silva,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Department of Animal Science, State University of Londrina (UEL), Londrina, Paraná, Brazil

  • Alexandre Oba

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – review & editing

    oba@uel.br

    Affiliation Department of Animal Science, State University of Londrina (UEL), Londrina, Paraná, Brazil

Abstract

Chlorella vulgaris has antioxidant, antimicrobial, and anti-inflammatory properties, as well as the probiotic that is important for keeping the intestinal microbiota balanced. The objective was to test the impact of supplementation with microalgae and/or probiotics on broiler chickens’ performance, immunity, and intestinal microbiota. The experimental design was in randomized blocks in a 4x2 factorial scheme, with four levels of inclusion of C. vulgaris (0; 0.25; 0.50 and 1%) associated or not with a commercial probiotic with five replications of 26 chickens per experimental unit. The results showed that probiotics improved feed conversion. Probiotics increased the productivity index only at 0.25% C. vulgaris supplementation. There was a reduction in spleen weight at 42 days of age in chickens fed with probiotics, but the different treatments did not alter serum antibodies. Sampling age had a significant impact on richness addressed by the number of observed genera and diversity addressed by the Shannon index. The most abundant phylum in the chicken intestinal tract was Firmicutes followed by Bacteroidetes and Proteobacteria. Bifidobacterium spp. was found in animals receiving 1% microalgae and probiotics on day 42, suggesting that this genus has benefited from microalgae supplementation. It is concluded that the probiotic and C. vulgaris have the potential to improve performance without causing major changes in the immunity and cecal microbiota.

Introduction

The increasing consumption of animal protein concomitant with the restriction on the use of growth promoter antibiotics has led to the search of alternatives to maintain performance in the food animal industry. A healthy gut is critical to the general health and welfare of broiler chickens. In order to have optimal intestinal health, it is necessary that animals have a balanced microbiota that constantly interacts with the host. The composition of the diet is a major factor influencing the microbiota and health of the gastrointestinal tract [1]. Therefore, the intake of dietary supplements, particularly probiotics and prebiotics, can produce beneficial changes in the morphology of the mucosa and in microbiota composition [2, 3].

Chlorella vulgaris is a unicellular green microalgae, which stands out for its high biomass production [4], being used as an additive in human and animal food [5]. It is used in the form dried powdered biomass and has about 60% protein [6], 1–4% chlorophyll, 9–18% fiber, vitamins and minerals [7], and polyunsaturated fatty acids [8]. In addition, Chlorella vulgaris contributes to the health of chickens by exerting antimicrobial activity [9], presents prebiotic activity [10] and improves the immune response related to inflammatory status. Thus, it can contribute to greater weight gain in broilers, as observed by Roques et al. [11] and El-Bahr et al. [12] providing 0.8% and 0.1% of Chlorella vulgaris, respectively.

Probiotics are live micro-organisms which confer health benefits to the host [13]. Several microbial species such as Lactobacillus spp, Bacillus spp, Bifidobacterium spp, and Enterococcus spp have been used as probiotics in the poultry industry [14]. The functionality of multi-strain/multi-species probiotics can be more consistent and more effective than that of a mono-strain. Broilers treated with a multi-species probiotic have increased levels of lysozyme, IgA, T lymphocyte response, of IgA, IgG, and IgM-producing cells in the intestinal mucosa, indicating the potential of these species in stimulating the immune system [1517].

Supplementation of broiler chickens with microalgae and probiotics has been used in poultry production in an attempt to increase the production of short-chain fatty acids (SCFAs) and to decrease the proliferation of pathogenic microbes by the reduction of the intestinal pH and direct competition for nutrients, thus maintaining the balance necessary to a healthy intestine [18, 19]. In addition, probiotics and microalgae can stimulate different subsets of immune cells to produce cytokines, which in turn play a role in inducing and regulating the immune response [20, 21].

Few studies have evaluated the impact of microalgae and probiotics on the intestinal microbiota of chickens [22, 23]. More data is necessary to allow the establishment of consensus taxa associated with nutritional supplementation and growth performance, since environmental and methodological factors largely vary across studies [24, 25]. In addition, the use of probiotics in production animals remains controversial as studies continue to produce conflicting results [26, 27], mainly because of uncontrolled environmental factors that are likely influencing the efficacy of those supplements, as well as the different microorganisms and doses used as probiotics. This study was designed to test the impact of supplementation with microalgae and/or probiotics on performance, immunity, and the intestinal microbiota of broiler chickens. Based on previous scientific evidences, we hypothesized that supplementation with Chlorella vulgaris and probiotics would independently improve immunity, microbiota composition and bird performance. In addition, the hypotheses that a synergistic interaction between the two supplements would occur based on the concept of symbiotic products that provide a prebiotic substratum for probiotic microorganisms.

Material and methods

Study design

In this study, one thousand forty 1-day-old male chicks (Cobb 500) were allocated into cages of 2.10 m2 (12 animals per m2) at the poultry research center of the University of Londrina. This study was approved by the University of Londrina’s Animal Care and Use Committee (process number: 10985.2019.33).

The experimental design was in randomized blocks in a 4x2 factorial scheme, with four levels of inclusion of C. vulgaris (0; 0.25; 0.50 and 1%) associated or not with a commercial probiotic (0.02% of Probimais® A–Biomart/São Paulo/Brazil) with five replications of 26 chickens per experimental unit. The broiler chickens received 24 hours of light for 14 days, due to the heating system using 250W lamps. After this, the birds received 18 hours of light per day. The average temperature in the experimental period was 26 ± 4 °C. The birds received water and food ad libitum during the 42-day experimental period. The commercial probiotic contained Bacillus subtilis (3.6x109 CFU/g); Bifidobacterium bifidum (2.5x109 CFU/g); Enterococcus faecium (2.6x109 CFU/g) and Lactobacillus acidophilus (1.3x109 CFU/g). For the formulation of the diets, the nutritional composition of the C. vulgaris was considered according to Kang et al. [5] and probiotic was included as inert. The experimental diets are presented in the supplementary material (S1 Table).

Performance

For performance analysis, one thousand forty chickens were assessed at 7, 21, 35 and 42 days of age. Feed intake (FI) was determined by calculating the difference between the weight of the feed offered and the weight of the leftover feed, the difference was divided by the number of birds. Weight gain (WG) was calculated as the final weight minus the initial weight of the birds and feed conversion (FC) was calculated as the total amount of feed consumed divided by the total weight gain. These data were adjusted for the number and weight of birds killed during the experimental period. Viability (V) was calculated with the following formula: (100—mortality in percent). Production efficiency index (PEI) was calculated using the following formula: PEI = (daily weight gain (kg) × viability /feed conversion ratio) × 100, according to the method described previously by Lorençon et al. [28].

Immunological parameters

For immunological analysis, a total of 80 chickens were used (n = 10/treatment), were weighed and slaughtered through electrical stunning at 21 and 43 days of age [29]. The chickens were necropsied for the collection of spleen and bursa of Fabricius, which were weighed and values were expressed as a percentage of the live weight of the bird [30]. Blood samples from two chickens per experimental unit (n = 10/treatment) were collected at 13 days, 21 days, and 42 days of age. The serum was stored at -20 °C until use.

To evaluate the humoral immune response, two chickens from each experimental unit (n = 10/treatment) were inoculated intramuscularly with 5% sheep red blood cells (SRBC) in phosphate-saline buffer (1X PBS) pH 7.2 (200 μL) on the 14th and 35th days of the experiment. Serological analyzes were performed with serum at 21 and 42 days of age.

The analysis of anti-SRBC antibody levels were performed using ELISA as described by Silva et al. [31] with the following modifications. SRBC protein extract was used at 5 μg/mL, the dilution of serum was 1:80 in 1X PBS with 1% non-fat dry milk (1 X PBS/1% milk), and the dilution of HRP antibodies was 1:25000 in 1X PBS/1% milk. To determine the levels of natural anti-KLH antibodies, serum from chickens at 13, 21 and 42 days of age were used, and the ELISA was performed as described above with the following modifications. The microplates were sensitized with KLH (Keyhole limpet hemocyanin at 10 μg/mL) and serum samples were diluted 1:40.

Microbiota analysis

For microbiota investigation, a total of 40 chickens were used (n = 5/treatment) were electrically stunned in a water bath (Model FX 2.0 Fluxo, Chapecó, Brazil) and then bled before slaughter on day 21 and 42. The animals had their cecal content collected in sterile plastic tubes that were immediately refrigerated (for a maximum of 1.5 hours) and frozen at -80°C until DNA extraction.

The V4 region of the bacterial 16S rRNA gene was amplified by PCR using the following primers: 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT) as previously recommended [32]. Sequencing was performed using an Illumina MiSeq platform, using the V2 reagent kit (2 × 250 cycles) at the Genome Quebec Innovation Centre.

Sequence data were processed using the software mothur [33] following the Standard Operating Procedure previously described Kozich et al. [34]. Good quality reads were clustered in operation taxonomic units (OTUs) with 97% similarity and classified according to the Ribosomal Database Project databank. OTUs belonging to the same genus were then clustered into “phylotypes” for alpha and beta diversity analyses. The number of observed genera and the Shannon index were used for characterization of alpha diversity. Beta diversity evaluating similarities in composition among samples was addressed by the Jaccard index and the Yue and Clayton indices to compare, respectively, community composition (that considers only presence or absence of the different bacteria) and structure (that considers the different taxa and their proportions within each sample). Beta diversity was explored visually using principal coordinate analysis (PCoA).

Statistical analysis

For performance and weight of lymphoid organs variables, statistical analysis was performed using analysis of variance for a 4 x 2 factorial model using the software R [35]. When significance was observed (P<0.05), the data was subjected to regression analysis to obtain the model with the best adjustment using the ExpDest.pt package.

The concentrations of IgY, IgM, and IgA were analyzed using the repeated measures procedure in the General Linear Model (GLM), followed by a Tukey post-hoc test of Statistica for Windows (Statsoft 13.0). A P value of 0.05 was used to assess significance among means. The model included microalgae levels, probiotic presence, day, and block as fixed factors, as well as the two-way interactions between microalgae levels and probiotic presence, microalgae levels and day, and the three-way interaction between microalgae levels, day, and probiotic presence, as shown in the following equation: Where μ is the overall mean, αi is the effect of the i-th level of factor A, βj is the effect of the j-th level of factor B, (αβ)ij is the interaction effect of factors A and B, πkm(i) is the effect of the m-th experimental unit within the i-th level of factor A and j-th level of factor B (Error 1), γk is the effect of the k-th level of factor C, (αγ)ik is the interaction effect of factors A and C, (βγ)jk is the interaction effect of factors B and C, (πγ)km(i) is the interaction effect of the experimental unit and factor C, (αβγ)ijk is the interaction effect of factors A, B, and C, and εijkm is the error term which represents the interaction between factor C (repeated factor) and Error 1 (Error 2).

For microbiota analyses the indices of alpha diversity were compared using a 2-way ANOVA considering time of sampling and treatment (C. vulgaris and probiotic) as variables. Beta diversity (community composition and structure) was compared using the analysis of molecular variance (AMOVA) test, considering a P < 0.05 as significant. Finally, the Linear Discriminant Analysis Effect Size (LEfSe) analysis was used to identify bacterial taxa associated with each experimental group, as well as sampling time [36].

Results and discussion

Performance

The treatments did not influence the results obtained for feed intake, weight gain and viability (Table 1). The reasons why viability was low in the experiment is related to the high sanitary challenge and the non-addition of antibiotics in the ration to avoid another variable in the experiment, as this could affect probiotic viability, as well as the utilization of the microalgae in the chicken’s gut. This resulted in a high rate of low development birds, which were removed from the experiment, providing a low viability.

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Table 1. Mean values referring to feed intake (FI), weight gain (WG), feed conversion (FC), viability (V) and productive efficiency index (PEI) of broilers fed with different levels of C. vulgaris associated or not to the probiotic.

https://doi.org/10.1371/journal.pone.0313736.t001

The feed conversion was enhanced by probiotic addition and an interaction between C. vulgaris and probiotic was found for PEI (Table 2), in which the addition of only 0.25% of C. vulgaris with the probiotic provided the best PEI (P < 0.05). Elements present in C. vulgaris such as chlorellin, fibers, polysaccharides, mannan oligosaccharide, rhamnose, galactose, glucose, xylose, arabinose, and mannose can be digested by intestinal microorganisms increasing the proliferation of beneficial bacteria in the gastrointestinal tract, increasing absorption of nutrients [37] in consequence of their higher capacity to extract nutrients from food or of the production of molecules improving intestinal health (e.g. butyrate) by improving tight junctions and production of mucous. In addition, the microalgae are rich in essential polyunsaturated fatty acids, with high levels of α-linolenic acid (omega 3 series fatty acid), which can reduce the formation of eicosanoids, and therefore inflammation [38, 39].

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Table 2. Deployment of the interaction between the levels of inclusion of C. vulgaris associated or not with the probiotic for productive efficiency index (PEI) from one to 42 days of age.

https://doi.org/10.1371/journal.pone.0313736.t002

Although the activation of important immune responses consumes nutrients and energy [40], the immune activation achieved by the addition of probiotics is in general associated with better food conversion, possibly by inhibiting sub-clinical infections with pathogens [41], preserving intestinal integrity [42] and increasing the activity of digestive enzymes such as lipase, protease and amylase [43].

In this study, the use of 0.25% C. vulgaris and probiotic (P < 0.05) showed a better productive efficiency index. Several prebiotic substances present in C. vulgaris could be working as selective substrates for beneficial bacteria [44] because they are resistant to the enzymes of the upper gastrointestinal tract and fermented by the intestinal microbiota in the large intestine [45]. Thus, C. vulgaris might have enhanced the probiotic strains, which exerts beneficial effects on animal performance. The reasons why this effect was observed only at a level of 0.25% of microalgae is uncertain, but it might be related with the excess of non-digestible carbohydrates stimulating other members of the microbiota. Further in vitro or ex vivo studies including mechanistic approaches designed to better understand the symbiotic interaction between the two products, as well as the metabolism of this probiotic strain could provide more insights into our current understanding.

Immunology

The inclusion of C. vulgaris and/or probiotic in the diet of broilers had no impact on the weight of spleen and bursa of Fabricius (Table 3) at 21 days of age as showed earlier [46]. The addition of probiotic provided a lower (18%) relative weight of the spleen (P < 0.05), without changing the relative weight of the bursa of Fabricius at 43 days of age. These results support the capacity of probiotics to enhance intestinal integrity and immunity reducing challenge exposure, avoiding hypertrophy, as the spleen performs the function of capturing antigens, stimulating B lymphocytes and T cells to develop nonspecific and general immunity [47, 48].

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Table 3. Relative weight of spleen and bursa of Fabricius of broilers fed diets containing C.vulgaris and/or probiotic inclusion.

https://doi.org/10.1371/journal.pone.0313736.t003

The results show that the addition of C. vulgaris and/or probiotics to the diet of broiler chickens did not influence the natural anti-KLH antibodies evaluated at 13, 21 and 42 days of age and anti-SRBC at 21 and 41 days of age (Table 4). These results are consistent with a previous study that did not observe an effect of C. vulgaris on the production of specific antibodies against vaccine antigens [46]. On other hand, it is interesting to note that some studies have observed an effect of C. vulgaris on the humoral immune response. These studies show an effect of C. vulgaris on the concentration of mucosal IgA (20) an serum IgM and IgG [46]. These microalgae can modulate the immune system by having high levels of omega-3 fatty acids, vitamin B12 [49], antioxidants [50] and phenolic compounds [51]. In the present study, no differences were observed in serum immunoglobulins in chickens fed C. vulgaris, despite similar levels of inclusion in the diets. This may be due to the composition of C. vulgaris, which was not analyzed to verify the quantify the presence of immunomodulatory components.

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Table 4. Natural antibodies (13, 21 and 42 days of age) and anti-SRBC- (21 and 42 days of age) in serum of chickens fed diets containing C.vulgaris and/or probiotic inclusion.

https://doi.org/10.1371/journal.pone.0313736.t004

The addition of probiotic did not change the serum immunoglobulins, similar to the results obtained by Mountzouris et al. [52]. These results are contrary to those obtained by Hassanpour et al. [53] who report that probiotics stimulate immune function and increase the production of immunoglobulins.

Microbiota analysis

Average and standard deviation of alpha diversity indices found in the cecal microbiota of broiler chickens at two different ages are presented. Sampling age had a significant impact on richness addressed by the number of observed genera on day 21 (68.82 ± 5) and day 42 (2.23 ± 0.30) (P < 0.001) and diversity addressed by the Shannon index on day (53.00 ± 5) and day 42 (2.09 ± 0.34) (P = 0.031). In this study, age independently modulated the cecal microbiota, decreasing richness and diversity over time, which is in agreement with previous studies [25, 54]. Chicken age is one of the most important factors influencing gastrointestinal bacterial composition, cell density and metabolic function [55]. No differences in alpha diversity indices were observed among treatments.

The similarity between bacterial communities present in each sample is represented by the Principal Coordinate Analysis (PCoA) in Figs 1 and 2 and Table 5. Age had a strong impact in composition and structure, whereas treatment with microalgae or probiotics did not significantly affect community composition or structure. Although not statistically significant, a clustering in microbiota composition of chickens receiving probiotics at Day 21 can be visualized in the PCoA plot (Fig 1B). The lack of significance was likely caused by the presence of one outlier as well as the low sample size, but this might support the fact that modulation of the intestinal microbiota is easier at younger ages [56, 57].

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Fig 1. Microbiota similarity represented by PCoA of bacterial composition influenced by age (A), supplementation with probiotic on D21 (B), with probiotic on Day 42 (C), with C. vulgaris on Day 21 (D) and with C. vulgaris on Day 42 (E).

https://doi.org/10.1371/journal.pone.0313736.g001

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Fig 2. Microbiota similarity represented by PCoA of bacterial structure influenced by age (A), supplementation with probiotic on Day 21 (B), with probiotic on Day 42 (C), with C. vulgaris on Day 21 (D) and with C. vulgaris on Day 42 (E).

https://doi.org/10.1371/journal.pone.0313736.g002

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Table 5. P values of AMOVA test (Statistical comparison of beta diversity).

https://doi.org/10.1371/journal.pone.0313736.t005

Treatment with probiotics and microalgae did not cause significant changes in the structure of the cecal community compared to the control group (AMOVA, P > 0.05). In broiler chickens, the administration of microalgae has been associated with prebiotic properties and an increase in the intestinal population of lactic acid bacteria (LAB) [58, 59]. Unlike these earlier studies, treatment with C. vulgaris and probiotics in the present study did not affect those specific populations. The reason for these divergent data remains unclear, but the distinct levels and the nutritional qualities of C. vulgaris flour as well as environmental conditions may be responsible. Our data corroborates with the study carried out by Sugiharto and Lauridsen [20] reporting that supplementation of broilers with microalgae (S. platensis) did not affect the ileal and caecal populations of LAB. Another possible reason for the lack of change in the structure of the cecal community is that probiotics generally do not reduce the total amount or activity of bacteria in the gut, but they can sometimes increase concentrations of bacterial metabolites in broilers chickens [60]. In fact, this is supported by the statistically greater concentration of α-linolenic acid observed in meat of microalgae supplemented animals published somewhere else [61], suggesting either greater production or higher intestinal absorption of those molecules. Further studies using metabolomics approach in the cecal content are required to confirm this.

It has been shown that consequences of early life manipulation of the intestinal microbiota can persist into adulthood, possibly decreasing the incidence of diseases [6264] and administration of Lactobacillus reuteri to broilers during the first week of the life had a positive effect on gut microbiota composition (diversity, abundance, and reduction of pathogens) for up to 6 weeks [65], however in the present work this was not observed.

The relative abundances of different phyla and genus across treatment groups are presented in Figs 3 and 4, respectively. The most abundant phylum in the chicken intestinal tract was Firmicutes followed by Bacteroidetes and Proteobacteria. In addition, members of the Actinobacteria phylum were found in very low abundance in broiler chicken at 21 days of life. At the genus level, Barnesiella and Faecalibacterium were the most abundant, respectively at 21 days and 42 days of age. The results obtained in this study corroborate with others describing the cecal microbiota of chickens [6668]. In the study by Oakley and Kogut [69], it was also observed that after the age of 3 weeks, the bacterial population of chickens changed from Proteobacteria, Bacteroides and Firmicutes to mainly Firmicutes.

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Fig 3. Relative abundances (> 1%) of the main bacterial phyla found in the cecum of broiler chickens treated with microalgae and probiotic and in a control group at two different ages.

https://doi.org/10.1371/journal.pone.0313736.g003

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Fig 4. Relative abundances (>1%) of the main bacterial genera found in the cecum of broiler chickens on Day 21 and Day 42 of life.

https://doi.org/10.1371/journal.pone.0313736.g004

Results of LEfSe analysis are shown in Figs 5 and 6. Several taxa were statistically associated with different ages (D21 and D42 of life). Faecalibacterium spp. and Barnesiella spp were the most strongly represented in samples collected on day 21 and 42, respectively (Fig 5).

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Fig 5. LEfSe analysis representing cecal bacteria that were statistically overrepresented on Day 21 and Day 42 of life in broiler chickens.

https://doi.org/10.1371/journal.pone.0313736.g005

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Fig 6. LEfSe analysis representing cecal bacterial that were statistically increased by supplementation with nutritional supplements on Day 21 (A) and Day 42 (B) of life in broiler chickens.

https://doi.org/10.1371/journal.pone.0313736.g006

Animals that received 1% microalgae and probiotics on day 42 had statistically greater abundances of Bifidobacterium spp. (Fig 6B), suggesting that this genus has benefited from microalgae supplementation likely because of its prebiotic effect. Microalgae species have complex polysaccharides and phytochemicals such as polyphenols, carotenoids, and fatty acids with potential to modulate the microbiota. Polysaccharides from Grateloupia filicina and Eucheuma spinosum have been shown to significantly promote the proliferation of Bifidobacterium [70]. Those findings can be useful in future studies identifying potential prebiotics related to better performance in the search of alternatives to replace the use of growth promoter antibiotics.

Conclusions

The results of this exploratory investigation support the view that supplementation with C. vulgaris and probiotics has the potential to improve performance without causing major changes in the cecal microbiota and serum antibodies of broiler chickens. This could be attributed to the capacity of probiotics to enhance intestinal integrity reducing challenge exposure. The present study supports further investigation to confirm this strategy as an alternative to growth promoter antibiotics.

Supporting information

S1 Table. Percentage and calculated composition of the experimental diets in the different stages of creation.

https://doi.org/10.1371/journal.pone.0313736.s001

(DOCX)

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