The control of intestinal inflammation: A major objective in the research of probiotic strains as alternatives to antibiotic growth promoters in poultry

The reduction of antimicrobial resistance is a major challenge for the scientific community. In a few decades, infections by resistant bacteria are forecasted to be the main cause of death in the world. The withdrawal of antibiotics as growth promoters and their preventive use in animal production is essential to avoid these resistances, but this may impair productivity and health due to the increase in gut inflammation. This reduction in productivity aggravates the problem of increasing meat demand in developing countries and limits the availability of raw materials. Probiotics are promising products to address this challenge due to their beneficial effects on microbiota composition, mucosal barrier integrity, and immune system to control inflammation. Although many modes of action have been demonstrated, the scientific community is not able to describe the specific effects that a probiotic should induce on the host to maximize both productivity and animal health. First, it may be necessary to define what are the innate immune pathways acting in the gut that optimize productivity and health and to then investigate which probiotic strain is able to induce the specific effect needed. This review describes several gaps in the knowledge of host-microbiota-pathogen interaction and the related mechanisms involved in the inflammatory response not demonstrated yet in poultry.info:eu-repo/semantics/publishedVersio

Relative bioavailability of DL and L-methionine in broilers

Studies on the relative bioavailability (RBV) of DL-Methionine (DL-Met) to L-Methionine (L-Met) have produced variable results. An experiment was conducted to determine the RBV of DL to L-Met. A total of 2268 1-day old male chicken were housed in 54 floor pens (42 bird/pen). There were 9 treatments (6 repetitions) including the basal diet (BD). The BD was deficient in Met content with 0.27, 0.26 and 0.25 in the starter, grower and finisher periods respectively. Four levels of experimental diets for each DL-Met and L-Met were created by supplementing 0.05%, 0.10%, 0.15% and 0.20% of DLor L-Met to the BD. The feeding program consisted of starter (0-14 d, 21% CP and 2900 kcal ME/kg), grower (15 - 28 d, 20% CP and 3000 kcal ME/kg) and finisher period (29 - 37 d, 18.5% CP and 3050 kcal ME/kg). Chickens and feed were weighed at the end of each age period. Regression coefficients of a common plateau asymptotic regression were used to calculate RBV. Birds responded to gradual increase in Met levels, BW, FCR and ADG were significantly (P < 0.05) higher in treatment groups as compared to control. Through the study period (37 d), the RBVs of DL-Met for BW and FCR were 89 and 77 respectively.info:eu-repo/semantics/publishedVersio

Relationship between chemical composition and standardized ileal digestible amino acid contents of corn grain in broiler chickens

This experiment was conducted to evaluate the chemical composition and standardized ileal amino acid digestibility of corn grain and to use these data to develop prediction equations for estimating total amino acids (TAAs) and standardized ileal digestible amino acids (SIDAAs) for broiler chickens. Four types of corn grains were obtained from different origins (Brazil, Ukraine, Russia, and Iran). Eighty-day-old Ross 308 male broiler chicks were fed a standard diet until day 18, and experimental diets were fed from 19 to 24 D of age. Five dietary treatments consisted of 4 semi-purified diets containing corn from each origin as the only source of amino acid (AA) and a N-free diet for determination of basal endogenous AA losses. Assay diets contained 939 g of test corn/kg. The concentration of crude protein and gross energy ranged from 7.58 to 8.39% (coefficient of variation [CV] = 4.72%) and 4,121 to 4,621 kcal/kg (CV = 5.09%), respectively. There was significant variation among the 4 corn grains in standardized ileal digestibility (SID) for CP, Phe, Leu, Asp, Glu, Ser, Gly, Ala, and Tyr (P ≤ 0.05). The results of linear regression showed that linear prediction equations based on protein content can be used to predict the TAA and SIDAA contents (e.g., TLys = 0.041 × CP, adj R2 = 95.9, standard error of prediction [SEP] = 0.05; SIDLys = 0.0356 × CP, adj R2 = 96, SEP = 0.051). Inclusion of other proximate components of test samples into the regression equation increased the R2 value and decreased the SEP value (e.g., TLys = 0.329 × crude fiber [CF] ‒ 0.209 × Ash, adj R2 = 99.9, SEP = 0.005; SIDLys = ‒1.1591 + 0.836 × CF ‒ 0.055 × Ash, adj R2 = 99.9, SEP = 0.001). The concentration of TAA and SIDAA was highly correlated (adj R2 > 89%) for most AA and showed that the amount of SIDAA could be predicted from its total concentration with a high degree of accuracy (e.g., SIDLys = 0.0023 + 0.861 × TLys, adj R2 = 99.9, SEP = 0.0001). In conclusion, this in vitro assays and equations accurately predicted TAA and SIDAA corn grain samples for broiler chickens and can serve as a reference analysis to develop calibration equations for rapid feed quality evaluation methods such as near-infrared reflectance spectroscopy.info:eu-repo/semantics/publishedVersio

Prediction of the total and standardized ileal digestible amino acid contents from the chemical composition of soybean meals of different origin in broilers

The objective of this experiment was to determine total amino acid (TAA) content, standardized ileal digestibility (SID) of crude protein, and standardized ileal amino acid digestibility in 9 sources of soybean meal (SBM) of different origin and to subsequently establish equations for predicting the TAA content and concentration of standardized ileal digestible amino acids (SIDAA) based on their protein content and other proximate components. Concentration of SIDAA of the samples was also predicted using TAA values. A total of 160 1-day-old male broiler chicks were randomly assigned to 10 dietary treatments consisted of 9 semipurified diets containing one SBM (200 g of crude protein/kg) as the only source of dietary amino acid (AA) and one N-free diet to determine endogenous ileal AA flow. The birds were fed with a standard diet from 0 to 18 D of age, and experimental diets were fed from 19 to 24 D of age. The fitness of the models of the study was tested using the adjusted coefficient of determination (R2) value, P-value regression and coefficients, and standard error of prediction (SEP). The coefficient of SID for Lys and Cys among SBM varied from 86.7 to 96.3 and 74.1 to 89.3, respectively, with significant difference (P < 0.05). In equations based on protein content, the adjusted R2 value ranged from 40.7 (Ile) to 99.6 (Met) and 37.2 (Met + Cys) to 99.6 (Met) for TAA content and concentration of SIDAA, respectively. Inclusion of other proximate components of test samples (e.g., crude fiber, neutral detergent fiber, acid detergent fiber, ash, gross energy, and so on) into the regression equation increased the adjusted R2 value and decreased the SEP. The results of linear regression revealed that it is possible to satisfactorily estimate the TAA content and concentration of SIDAA of SBM through its protein content and other proximate components, but the prediction equations based on other proximate components were more accurate in terms of reflecting the measured results; however, additional time and costs were associated with this approach. It is also possible to estimate the concentration of SIDAA through TAA values with reasonable accuracy and lower SEP.info:eu-repo/semantics/publishedVersio

Effects of deoxynivalenol contaminated diets on productive, morphological and physiological indicators in broiler chickens

The present study with 1-day-old male broilers (Ross 308) was conducted to evaluate the effects of deoxynivalenol (DON) at different levels (5 and 15 mg/kg feed) on growth performance, relative weight of organs, morphology of the small intestine, serum biochemistry, and welfare parameters of broiler chickens. Forty-five broiler chicks were randomly divided into three different experimental groups with five replicates each: (1) control group received a non-contaminated diet, (2) contaminated diet with 5 mg DON/kg of feed, and (3) contaminated diet with 15 mg DON/kg of feed for 42 days. Results showed that feed artificially contaminated with DON at guidance level (5 mg/kg diet) did not affect growth performance parameters. However, 15 mg/kg reduced body weight gain and altered feed efficiency. DON at two assayed levels significantly increased the absolute and relative weight of thymus and the relative weight of gizzard and decreased the absolute and the relative weight of the colon. Compared to controls, both doses affected small intestine morphometry parameters. In terms of biochemical indicators, DON at 5 mg/kg reduced the creatine kinase level and at 15 mg/kg DON reduced the cholesterol level. Furthermore, DON at 15 mg/kg induced more fear in broilers compared to broilers fed the guidance level. It was concluded that even the guidance level of DON did not affect the chickens' performance. However, its toxic effect occurred in some organs and biochemical parameters.This research was funded by Phileo by Lesaffre Company

Effects of deoxynivalenol-contaminated diets on metabolic and immunological parameters in broiler chickens

The current study was conducted to examine the effects of deoxynivalenol (DON) at different levels (5 and 15 mg/kg feed) on the metabolism, immune response and welfare parameters of male broiler chickens (Ross 308) at 42 days old. Forty-five 1 day-old broiler chickens were randomly distributed into three different dietary treatments: (1) control, (2) DON-contaminated diet with 5 mg DON/kg of feed (guidance level), and (3) DON-contaminated diet with 15 mg DON/kg of feed. Five replicated cages with three birds each were used for each treatment in a randomized complete block design. The results showed that DON was detected in excreta of birds fed contaminated diets compared with controls. The metabolite DON-3 sulphate (DON-3S) was detected in plasma and excreta in both treated groups, as well as in the liver (but only at 15 mg/kg feed). The increase in the level of DON decreased the hemoglobin concentration (p < 0.001), whereas the erythrocyte counts were only decreased at 15 mg DON/kg feed. No effect of DON on the responses to common vaccines was observed. In plasma, interleukin 8 levels in both contaminated groups were significantly higher than in the control group. The expression of interleukin 6, interleukin 1β and interferon-γ increased in jejunum tissues of broilers fed 5 mg/kg of DON compared with controls. The stress index (heterophil to lymphocyte ratio) was not affected by DON-contaminated diets compared with controls. The plasma corticosterone level was significantly lower in both DON groups compared with controls. In conclusion, DON-3S could be used as a specific biomarker of DON in different biological matrices, while the immune response in broiler chickens is stimulated by the presence of DON at the guidance level, but no adverse effect was observed on physiological stress parameters.This research was funded by the Phileo by Lesaffre Company

Biomarkers of deoxynivalenol toxicity in chickens with special emphasis on metabolic and welfare parameters

Deoxynivalenol (DON), a trichothecene mycotoxin produced by Fusarium species, is the most widespread mycotoxin in poultry feed worldwide. Long term‐exposure from low to moderate DON concentrations can produce alteration in growth performance and impairment of the health status of birds. To evaluate the efficacy of mycotoxin‐detoxifying agent alleviating the toxic effects of DON, the most relevant biomarkers of toxicity of DON in chickens should be firstly determined. The specific biomarker of exposure of DON in chickens is DON‐3 sulphate found in different biological matrices (plasma and excreta). Regarding the nonspecific biomarkers called also biomarkers of effect, the most relevant ones are the impairment of the productive parameters, the intestinal morphology (reduction of villus height) and the enlargement of the gizzard. Moreover, the biomarkers of effect related to physiology (decrease of blood proteins, triglycerides, hemoglobin, erythrocytes, and lymphocytes and the increase of alanine transaminase (ALT)), immunity (response to common vaccines and release of some proinflammatory cytokines) and welfare status of the birds (such as the increase of Thiobarbituric acid reactive substances (TBARS) and the stress index), has been reported. This review highlights the available information regarding both types of biomarkers of DON toxicity in chickens.This research was funded by PHILEO BY LESAFFRE

Influence of dietary n-3 long-chain fatty acids on microbial diversity and composition of sows’ feces, colostrum, milk, and suckling piglets’ feces

Introduction: Very little is known about the impact of n-3 long-chain fatty acids (n-3 LCFAs) on the microbiota of sows and their piglets. The aim of this study was to evaluate the effect of n-3 LCFA in sow diets on the microbiota composition of sows’ feces, colostrum, and milk as well as that of piglets’feces. Methods: Twenty-two sows were randomly assigned to either a control or an n-3 LCFA diet from service to weaning. Sows’ and piglets’ performance was monitored. The gestating and lactating sows’microbiomes in feces, colostrum, and milk were characterized by 16s ribosomal RNA gene sequencing. The fecal microbiome from the two lowest (>800 g) and the two highest birth weight piglets per litter was also characterized, and the LPS levels in plasma were analyzed at weaning. Results and Discussion: n-3 LCFA increased microbiota alpha diversity in suckling piglets’ and gestating sows’ feces. However, no effects were observed in colostrum, milk, or lactating sows’ feces. Dietary n-3 LCFA modified the microbiota composition of gestating sows’ feces, milk, and suckling piglets’feces, without affecting lactating sows’ feces or colostrum. In gestating sows’ feces and milk, the decrease in genus Succinivibrio and the increase of Proteobacteria phylum, due to the increased genera Brenneria and Escherichia, respectively, stand out. In the feces of suckling piglets, the higher abundance of the beneficial genus Akkermansia and Bacteroides, and different species of Lactobacillus are highlighted. In addition, positive correlations for families and genera were found between lactating sows’ feces and milk, milk and suckling piglets’ feces, and lactating sows’ feces and suckling piglets’feces. To conclude, dietary n-3 LCFA had a positive impact on the microbiome of suckling piglet’s feces by increasing microbial diversity and some beneficial bacteria populations, had a few minor modifications on the microbiome of milk and gestating sows’ feces and did not change the microbiome in lactating sows’ feces or colostrum. Therefore, this study shows the effect of dietary n-3 LCFA on the microbiota of sows, colostrum, milk, and suckling piglets during the lactation period providing crucial information on the microbiota status at the early stages of life, which have an impact on the post-weaning.info:eu-repo/semantics/publishedVersio

Novel strategies to improve chicken performance and welfare by unveiling host-microbiota interactions through hologenomics

Fast optimisation of farming practices is essential to meet environmental sustainability challenges. Hologenomics, the joint study of the genomic features of animals and the microbial communities associated with them, opens new avenues to obtain in-depth knowledge on how host-microbiota interactions affect animal performance and welfare, and in doing so, improve the quality and sustainability of animal production. Here, we introduce the animal trials conducted with broiler chickens in the H2020 project HoloFood, and our strategy to implement hologenomic analyses in light of the initial results, which despite yielding negligible effects of tested feed additives, provide relevant information to understand how host genomic features, microbiota development dynamics and host-microbiota interactions shape animal welfare and performance. We report the most relevant results, propose hypotheses to explain the observed patterns, and outline how these questions will be addressed through the generation and analysis of animal-microbiota multi-omic data during the HoloFood project