Microbial balance index — A view on the intestinal microbiota

Livestock Science 109 (2007) 174 – 178 www.elsevier.com/locate/livsci

Microbial balance index — A view on the intestinal microbiota ☆ Jussi Vaahtovuo a,⁎,1 , Mika Korkeamäki a,1 , Eveliina Munukka a , Pirkko Hämeenoja b , Juhani Vuorenmaa b a

b

CyFlo Ltd, Itäinen Pitkäkatu 4 B, 20520 Turku, Finland Suomen Rehu Ltd, Upseerinkatu 1, PL 401, 02601 Espoo, Finland

Abstract The aim of the Finnish Research Programme is to characterise the intestinal microbiota of the production animals and learn to modulate animals' intrinsic microbiota in order to support productivity. For a simplified and better description of the complex microbiota, Microbial Balance Index (MBI) counted from the proportions of several bacterial groups present in intestinal samples was developed. In piglet and pig feeding trials MBI was observed to associate with animal growth (r = 0.68, P ≤ 0.01). In addition, the effect of hydrolysed brewery yeast on intestinal balance and daily weight gain was studied. The findings indicate that the intestinal microbiota is an essential factor affecting animal productivity and well being. We suggest that monitoring of intestinal microbiota should be better taken into account when developing domestic animal production. © 2007 Elsevier B.V. All rights reserved. Keywords: Gastrointestinal tract; Intestinal microbiota; Cytometry; Brewery yeast

1. Introduction Gastrointestinal microbiota is a uniquely diverse ecosystem achieving one of the highest cell densities recorded for any ecosystem (Bäckhed et al., 2005). Despite the vast microbial burden and the close contact between the microbes and the host's cells, normal intestinal microbiota is considered to be beneficial. Intestinal microbes interact actively with the mucosa associated immune cells pertaining to healthy immunologic maturation (Umesaki and Setoyama, 2000). Non-pathogenic ☆ This paper is part of the special issue entitled “Digestive Physiology in Pigs” guest edited by José Adalberto Fernández, Mette Skou Hedemann, Bent Borg Jensen, Henry Jørgensen, Knud Erik Bach Knudsen and Helle Nygaard Lærke. ⁎ Corresponding author. Tel.: +358 2 4788 520; fax: +358 2 4788 521. E-mail address: [email protected] (J. Vaahtovuo). 1 J. Vaahtovuo and M. Korkeamäki contributed equally to this work.

1871-1413/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.livsci.2007.01.137

normal microbiota also protects the gut from the colonization of harmful microbes and symbiosis between the host and microbiota supports good animal health and productivity (Hooper and Gordon, 2001). Antibiotic growth promoters (AGPs) used in domestic animal production have effectively inhibited specific gastrointestinal infections, but also disturbed the natural balance between the host and gut microbes (Dibner and Richards, 2005). The maintenance of animal health, with the host — microbial balance being a starting point, has been overlooked, but the recent ban in the use of AGPs has created increasing needs to support and control normal microbiota. The first step in modern microbiota-emphasizing approach is the characterisation of the normal microbiota. Intestinal microbiota with its unknown microbial species and innumerable variables is difficult to study, and due to the inadequacy of traditional analysis methods such as

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analyse bacterial compositions of intestinal samples (Vaahtovuo et al., 2005). The aim of the programme is to characterise intestinal microbiota of production animals and to find out how different feed materials and additives affect the microbiota and digestibility. The unique knowledge and database acquired is used to reveal associations between the overall composition of the microbiota and intestinal health and productivity. As a demonstration of the possibilities of this microbiotaemphasised philosophy, we introduce the concept of Microbial Balance Index (MBI). 2. Materials and methods Fig. 1. An example of an FCM analysis of faecal sample. In the dot plot, the fluorescence of the probe hybridizing target bacteria is presented in the x direction and the fluorescence of DNA-stain in the y direction. The hybridized target bacteria are shown in the region 1 and the unhybridized bacteria in the region 4. The DNA-stain negative and probe negative particles are seen in the region 3 and the DNA-stain negative probe positive particles (i.e. false-positives) in the region 2. The bacteria are separated from the non-DNA-stained material, and the hybridized target bacteria are discriminated from other bacteria in the sample.

bacterial cultivation, the bacterial composition of the normal intestinal microbiota is still largely unknown. During the last two decades the methods based on the detection of nucleic acids of microbes have enabled more detailed analysis of microbiota, but there are increasing needs to describe microbiota in a more comprehensive manner and concisely (Zoetendal et al., 2004). In the Finnish Research Programme, a rapid and bacterial group specific flow cytometry (FCM) method has been used to

To characterise the composition of normal faecal microbiota, samples from 10-week-old piglets (n = 224) and 16 to 20-week-old pigs (n = 256) were collected. The samples were collected from each animal individually and not pooled. The animals were housed in normal farming conditions and they participated in feeding trials including feeds of several different compositions. The animals were divided to feeding groups (17 groups for piglets and 16 for pigs) containing 12–18 animals. The average daily weight gains (DWG) were measured for each feeding group. Further, to study the effect of hydrolysed brewery yeast Progut™ (Suomen Rehu, Espoo, Finland) on faecal microbiota and animal growth, faecal samples from 10-week-old piglets (n = 60) were collected. The piglets were divided to five feeding groups containing 12 animals. The piglets of two groups had got control weaning feed from the age of 5 weeks and the piglets of three groups had received similar feed

Table 1 Bacterial contents and MBI values (mean ± SEM) of piglet and pig faecal samples Bacteria

Animal Piglet

Pig

Total bacteriaa

1.5 × 1011 ± 4.9 × 109 (n = 141) 3.6 × 1010 ± 1.5 × 109 (n = 95) 5.0 × 109 ± 2.5 × 108 (n = 96) 7.7 × 108 ± 5.4 × 107 (n = 95) 5.2 × 109 ± 2.3 × 108 (n = 95) 5.2 × 109 ± 2.5 × 108 (n = 95) 0.29 ± 0.01 (n = 95)

1.4 × 1011 ± 3.6 × 109 (n = 238) 2.8 × 1010 ± 1.0 × 109 (n = 238) 3.1 × 109 ± 1.3 × 108 (n = 237) 7.6 × 108 ± 3.7 × 107 (n = 238) 4.1 × 109 ± 1.7 × 108 (n = 238) 7.0 × 109 ± 3.0 × 108 (n = 174) 0.26 ± 0.01 (n = 239)

Bacteriodes–Porphyromonas–Prevotella-groupa genus Bifidobacteriuma Enteric groupa Faecalibacterium prausnitzii-groupa Clostridium leptum-groupa MBI

Symbols: ⁎⁎P ≤ 0.01; ⁎P ≤ 0.05; NS, P N 0.05; abacteria per gram of faeces (dry matter). The statistical differences between the piglet and pig samples are given as P-values.

P-value

NS ⁎⁎ ⁎⁎ NS ⁎⁎ ⁎⁎ ⁎

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with hydrolysed brewery yeast. The average DWG were measured for each feeding group. After the sampling, the faecal bacterial cells were separated from the sample and analysed with a method based on FCM, 16S rRNA hybridization and DNAstaining (Vaahtovuo et al., 2005). The faecal sample was suspended in phosphate-buffered saline (PBS) and the bacteria were separated with centrifugations. The bacterial cells were fixed with paraformaldehyde, washed several times with PBS and re-suspended in 50% ethanol-PBS. The fixed bacteria were stored at − 20 °C until hybridized with oligonucleotide probes targeted to different bacterial genera and groups (Doré et al., 1998;

Langendijk et al., 1995; Lay et al., 2005; Sghir et al., 2000; Suau et al., 2001). After the hybridization, the bacteria were stained with SYTOX® DNA-stain (Molecular Probes, Eugen, Oregon) and analysed with BD FACSCalibur™ flow cytometer (Becton Dickinson, San Jose, California). In addition, the total bacterial counts (i.e. the counts of DNA-stained bacteria) were counted. MBI values describing the microbiota in a comprehensive manner were counted by a formula (patent pending): MBI ¼ ðA þ BÞ=ðC þ DÞ; where A is the count of bifidobacteria, B is the count of Faecalibacterium prausnitzii-group bacteria, C is the

Fig. 2. Correlation between MBI and DWG. 224 piglets and 256 pigs participating in the trials were divided to 17 and 16 feeding groups, correspondingly. Mean MBI (counted from individual samples' MBI values) and mean DWG from each feeding group (12–18 animals per group) were determined and correlation between MBI and DWG counted. Both in piglet and pig trials the correlation coefficients between MBI and DWG were statistically significant (r = 0.68, r2 = 0.46, P ≤ 0.01 in piglets; r = 0.68, r2 = 0.46, P ≤ 0.01 in pigs). Symbols: □, measured values for each animal group participating in trials; –, regression line.

J. Vaahtovuo et al. / Livestock Science 109 (2007) 174–178 Table 2 The effect of hydrolysed brewery yeast on MBI and DWG (mean ± SEM) in piglets Feeding

MBI DWG (g)

Hydrolysed brewery yeast

Control

0.36 ± 0.03 511 ± 25

0.31 ± 0.03 448 ± 22

Piglets having feed added with hydrolysed brewery yeast tended to have higher MBI (P = 0.20) and DWG (P = 0.07).

count of Bacteroides–Porphyromonas–Prevotellagroup bacteria and D is the count of enteric group bacteria. The bacterial counts and MBI values were counted individually for each sample. Data were analysed with Student's t test for two independent sets of samples with unequal variance. Correlations between MBI and DWG were assessed using Pearson's correlation coefficient and regression analysis. In all analyses P ≤ 0.05 was considered to denote a significant difference. 3. Results An example of an FCM analysis is presented in Fig. 1. In the dot plot, the fluorescence of the probe hybridizing target bacteria is presented in the x direction and the fluorescence of DNA-stain in the y direction. The bacteria are separated from the non-DNA-stained material, and the hybridized target bacteria are discriminated from other bacteria in the sample. The bacterial composition of faecal samples is presented in Table 1. The total bacterial counts were on the same level both in piglet and in pig samples: 1.5 × 1011 bacteria and 1.4 × 1011 bacteria per gram of faeces (dry matter), respectively. Of the bacterial groups studied, Bacteroides–Porphyromonas–Prevotella-group bacteria were the most common, piglet samples containing 3.6 × 1010 bacteria and pig samples 2.8 × 1010 bacteria per gram of faeces. In piglet samples, bacteria of Bacteroides–Porphyromonas–Prevotella-group represented 24% and in pig samples 20% of the total bacterial counts. The bacteria of Clostridium leptumgroup were the second most common, piglet samples containing 5.2 × 109 bacteria and pig samples 7.0 × 109 bacteria per gram of faeces. Both piglet and pig samples contained abundantly F. prausnitzii-group bacteria and bifidobacteria, while enteric group bacteria were the fewest in number of the bacteria studied. Fig. 2 presents the associations between MBI and DWG. Both in piglets and pigs the correlation coefficients between MBI and DWG were statistically significant (r = 0.68, r2 = 0.46, P ≤ 0.01 in piglets; r = 0.68, r2 = 0.46,

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P ≤ 0.01 in pigs). The effect of hydrolysed brewery yeast on MBI and DWG of piglets is shown in Table 2. Addition of hydrolysed brewery yeast to piglet feed enhanced DWG and increased MBI values clearly, although the changes were not statistically significant (P = 0.07 for DWG, P = 0.20 for MBI). 4. Discussion The FCM methodology used in the Finnish Research Programme has enabled the acquisition of this comprehensive research data. FCM analyses are rapid and reliable and have high numerical resolution. This unique approach is based on the detection of whole bacterial cells and is not dependent on the cultivation of the bacteria or the extraction and amplification of the nucleic acids, which could distort the analysis. The results acquired strengthen the concept of normal intestinal microbiota that develops gradually during animal growth and consists of certain bacterial species and genera in proportions typical of host animal (Conway, 1997). Although there were apparent similarities in the bacterial compositions of piglet and pig samples, characterisation revealed also significant differences between the animal groups. The bacteria of Bacteroides–Porphyromonas– Prevotella-group were the most common both in piglets and pigs, but the changes in bacterial proportions and counts indicated a clear difference between their microbiota. The counts of Bacteroides–Porphyromonas– Prevotella-group bacteria, bifidobacteria and F. prausnitzii-group bacteria diminished significantly with age, while the counts of enteric group bacteria did not change and the counts of C. leptum-group bacteria increased. The total bacterial counts remained approximately the same. The samples analysed were collected from animals living in normal farming conditions and having several different kinds of feeds, and the results can be considered to represent the composition of the normal microbiota of pigs and piglets on a general level. Intestinal microbiota is an exceptionally intricate ecosystem and description of its composition has been difficult. The MBI was developed to describe the microbiota succinctly and comprehensively. MBI is counted from the proportions of four major bacterial groups present in the intestinal microbiota. It is important to understand that even such bacterial species, whose proportions are not directly measured, will influence MBI. Microbiota is an adaptive entirety with intrinsic balance, and a change in the proportion of some microbial group inevitably affects the proportions of other microbes. MBI enables a concise and understandable overview of the complex microbiota and is particularly

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suitable for monitoring the changes in microbiota. The results concerning the association between MBI and growth are of particular interest and indicate that the composition of intestinal microbiota has fundamental effects on animals' well-being and productivity. In these feeding trials MBI could be estimated to account moderately (r2 = 0.46) for the variation measured in DWG. Hydrolysed brewery yeast Progut™ was observed to increase MBI and enhance growth in piglets. The finding is an example of possibilities to enhance animal productivity by modulating intestinal microbiota with dietary measures. New functional feed materials and additives have often been reported to have specific bacterial effects, but the importance of their effects on the whole intestinal microbiota should be paid more attention to since microbiota is a central factor affecting host's physiologic and immunologic state. Analysis methodology and the MBI concept introduced will help the evaluation of the in vivo microbial effects of the AGPreplacing products and advance the development of new feeds and feeding programs based on the control and modulation of intestinal microbiota. References Bäckhed, F., Ley, R.E., Sonnenburg, J.L., Peterson, D.A., Gordon, J.I., 2005. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920. Conway, P.L., 1997. Development of intestinal microbiota. In: Mackie, R.I., White, B.A., Isaacson, R.E. (Eds.), Gastrointestinal Microbiology, vol. 2. Chapman and Hall Microbiology Series, New York, pp. 3–38.

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