Research Article · Volume 11, Issue 6, 3 May 2023 · Open Access
Lactobacillus as Growth Promoter: A Meta-Analysis of Performance, Histology and Microbiota on Broiler Tract Digestive
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Affiliations & Notes ⌄
- 1Animal Science Faculty, Jenderal Soedirman University, Purwokerto 53123, Indonesia
- 2Animal Feed Nutrition and Modelling Research Group, Animal Science Faculty, IPB University, Bogor, 16680, Indoenesia
- 3Bogor Agricultural Development Polytechnic, Bogor, 16119, Indonesia. *Correspondence | Bambang Hartoyo, Animal Science Faculty, Jenderal Soedirman University, Purwokerto 53123, Indonesia
- 4Email: bambang.hartoyo@unsoed.ac.id
Article Info ⌄
- Journal:
- Advances in Animal and Veterinary Sciences
- Published:
- 3 May 2023

Abstract
INTRODUCTION
The European nation aim to develop production that efficiently uses such as feed and renewable energy. Determination of novel solution meet the animal feed requirement balancing of production animals is key to development of animal industry in future trends . Indonesia facing several problems such as availability of the raw materials, and producing healthy meat . One of regulation has been established by government were prohibition of the use of antibiotic growth promoters on broiler chicken production. Prohibition on the use of Antibiotic Growth Promoter (AGP) as feed additives is stipulated in Minister of Agriculture regulation in 2017 concerning the classification of veterinary drugs. The regulation clarifies the mixing of veterinary drugs in feed for therapy based on instructions and under the supervision of a veterinarian.
Prohibition on the use of AGP on broilers can reduce the productivity. However, there is actually a way to keep the broilers performing well by using ingredients derived from nature. Natural ingredients do not cause any side effects on the host and researchers are looking for them to replace antibiotics. Resistance problem has become huge clinical and public health problem nowadays and will face multiresistant disease . Phytochemicals ; , probiotics and their derivate and other metabolites are potential as antibiotics.
Probiotics are good bacteria with many types. Lactobacillus is one of the types of with abundant amount in fermentation products. Every fermentation product mostly produce Lactobacillus and it works optimally with the presence of a material providing an optimal environment. This condition results in an increase in the number/population of probiotics in the gastrointestinal tract. An increase in the Lactobacillus population results in an increase in the digestibility and absorption of nutrients resulting in an increase in performance. Actually, Lactobacillus has various mechanisms to improve performance, but the principal mechanism of Lactobacillus is by working anaerobically so pH of the digestive tract drops, and inhibits the development and growth of pathogenic bacteria.
Even mechanism of Lactobacillus as alternative antibiotics seems promising, but another report shows different results. Systematic review such as meta-analysis helps researchers find out inconsistency from several studies to conclude. Meta-analysis refers to a quantitative and methodical strategy creating a continuous analysis of previous studies . Meta-analysis can also be used to quantitatively verify the type of findings in a study. Therefore, this study aimed to evaluate, using a meta-analysis of previously published articles, the effects of Lactobacillus on the performance and intestine condition of broiler.
MATERIALS AND METHODS
Database development
Database established for this meta-analysis were collected from published articles in multiple search engines for scientific paper such as Google Scholar, Scopus and Science Direct using keywords “lactobacillus” and “broiler”. 48 articles have been collected discussing Lactobacillus as feed additives for broilers but only 38 articles were chosen as potential articles based on its title and abstract. Diagram flow of article selection in the meta-analysis using Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) method was reported in Figure 1. The parameters chosen were (1) productivity of broilers: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR), (2) histologic structure of intestine: villus height, crypt depth and ratio of villus height and crypt depth and (3) gastrointestinal microbiota specifically in caecum and ileum.
After strict evaluation of 38 articles, 17 articles were selected and reported in Table 1 based on their numerical results, confirmed specific species and dosage of the Lactobacillus. All parameters have been concluded based on descriptive method and reported in Table 2. All parameters have equal units as a requirement of meta-analysis such as average daily gain and feed intake were expressed in g/day, FCR was g/g, villus height and crypt depth were µm, microbiota population were log cfu/g, and dosage of Lactobacillus was in cfu/g.
Table 1: Articles included in the meta-analysis.
| No | Article | Lactobacillus | Broiler | ||
| Species | Dosage (cfu/g) | Breed | Age (d) | ||
| 1 | Wu et al. | L. acidophilus | 0 – 1 x 109 | Cobb | 1 – 21 |
| 2 | Wang et al. | L. plantarum | 0 – 2 x 106 | Cobb | 1 – 42 |
| 3 | Peng et al. | L. plantarum | 0 – 2 x 109 | Arbor Acres | 1 – 42 |
| 4 | Li et al. | L. acidophilus | 0 – 4 x 106 | Arbor Acres | 1 – 21 |
| 5 | Jahromi et al. | Mixed Lactobacillus | 0 – 1 x 109 | Cobb | 1 – 35 |
| 6 | Shokyazdan et al | L. salivarius | 0 – 1 x 109 | Cobb | 1 – 42 |
| 7 | Qing et al. | L. johnsonii | 0 – 1 x 106 | Cobb | 1 – 28 |
| 8 | Chen et al. | Mixed Lactobacillus | 0 – 1 x 106 | Arbor Acres | 1 – 35 |
| 9 | Wang et al. | L. plantarum | 0 – 1 x 108 | Arbor Acres | 1 – 42 |
| 10 | Vantsawa et al. | L. acidophillus | 0 – 1 x 109 | Arbor Acre+ | 1 – 42 |
| 11 | Wu et al. | L. acidophillus | 0 – 1 x 1010 | Arbor Acres | 1 – 42 |
| 12 | Yang et al. | L. plantarum | 0 – 1 x 109 | Cobb | 1 – 42 |
| 13 | Cholis et al. | Mixed Lactobacillus | 0 – 1 x 108 | Lohmann | 1 – 42 |
| 14 | Wang et al. | L. johnsonii | 0 – 1 x 106 | Cobb | 1 – 42 |
| 15 | Wang et al. | L. plantarum | 0 – 1 x 108 | Arbor Acres | 1 – 42 |
| 16 | Vineetha et al. | L. plantarum | 0 – 1 x 108 | Caribo Dhanraja | 1 – 35 |
| 17 | Liu et al. | L. plantarum | 0 – 1 x 108 | Cobb | 1 – 21 |
Table 2: Descriptive statistics of the chosen article of meta-analysis.
| Response parameter | Unit | Mean | SD | Min | Max |
| Performance | |||||
| Starter ADG | g/day | 32.97 | 10.52 | 20.81 | 79.19 |
| Starter ADFI | g/day | 47.96 | 11.99 | 33.65 | 80.48 |
| Starter FCR | g/g | 1.500 | 0.162 | 1.280 | 1.860 |
| Finisher ADG | g/day | 64.15 | 20.67 | 27.40 | 89.23 |
| Finisher ADFI | g/day | 129.3 | 35.71 | 58.09 | 171.9 |
| Finisher FCR | g/g | 1.843 | 0.203 | 1.460 | 2.170 |
| Total ADG | g/day | 50.22 | 10.55 | 29.97 | 63.32 |
| Total ADFI | g/day | 92.53 | 16.00 | 63.54 | 111.5 |
| Total FCR | g/g | 1.880 | 0.402 | 1.340 | 3.280 |
| Intestine histology | |||||
| Duodenum villus height | µm | 1017 | 169.1 | 790.5 | 1316 |
| Duodenum crypt depth | µm | 182.8 | 40.23 | 144.6 | 236.0 |
| Duodenum V: H | µm/µm | 5.826 | 1.756 | 4.450 | 9.100 |
| Jejunum villus height | µm | 890.9 | 228.2 | 527.9 | 1247 |
| Jejunum crypt depth | µm | 154.6 | 50.97 | 95.56 | 237.9 |
| Jejunum V: H | µm/µm | 6.035 | 0.953 | 4.650 | 8.130 |
| Ileum villus height | µm | 687.1 | 200.8 | 349.4 | 968.0 |
| Ileum crypt depth | µm | 155.5 | 53.67 | 52.78 | 223.8 |
| Ileum V: H | µm/µm | 4.822 | 1.243 | 3.470 | 4.822 |
| Intestine microbiota | |||||
| Caecum Lactobacillus | Log cfu/g | 8.577 | 0.308 | 7.900 | 9.010 |
| Caecum E. coli | Log cfu/g | 6.587 | 0.450 | 5.920 | 7.280 |
| Ileum caecum | Log cfu/g | 8.251 | 0.514 | 7.350 | 8.980 |
| Ileum E. coli | Log cfu/g | 5.301 | 1.258 | 4.180 | 7.180 |
ADG, average daily gain; ADFI, average daily feed intake; FCR, feed conversion ratio.
Statistical analysis
Database were processed for statistical analysis using mixed model procedure in linear and quadratic model for meta-analysis ; . Statistical analysis was conducted using SAS on demand for academic with PROC MIXED procedure. Lactobacillus addition dosage was used as fixed effect, while the studies were as random effect. The significance value was set as p<0.05.
Lactobacillus dosage was used as continuous predictor in which the response variables were regressed using the mathematical model:

Where, Yij = dependent variable, B0= overall intercept across all studies (fixed effect), B1= linear regression coefficient of Y on X (fixed effect), B2= quadratic regression coefficient of Y on X (fixed effect), Xij = value of the continuous predictor variable (Lactobacillus addition level), si= random effect of study i, bi= random effect of study i on the regression coefficient of Y on X in study i, eij= the unexplained residual error while a low akaike information criteria (AIC) value indicates that the model is better at describing the observed data. The smaller the difference in AIC values between the two models, the smaller the difference in model quality between the two. Meanwhile, intercept is used to assist in understanding how the independent variable affects the dependent variable. The intercept can also provide information about the baseline or initial value of the dependent variable before the independent variable influences it.
Table 3: Lactobacillus addition effect on performance of broiler chicken.
| Response parameter | Model | n | Parameter estimates | Model estimates | ||||
| Intercept | SE intercept | Slope | SE slope | P-value | AIC | |||
| Starter | ||||||||
| ADG | Q | 49 | 32.94 | 2.460 | -0.001 | 0.001 | <0.001 | 338.7 |
| 0.010 | 0.018 | <0.001 | 327.9 | |||||
| ADFI | Q | 52 | 48.08 | 2.620 | -0.001 | 0.001 | <0.001 | 316.5 |
| 0.002 | 0.008 | <0.001 | 304.3 | |||||
| FCR | Q | 52 | 1.512 | 0.034 | 0.001 | 0.001 | <0.001 | -58.90 |
| -0.001 | 0.001 | <0.001 | -76.70 | |||||
| Finisher | ||||||||
| ADG | Q | 49 | 66.11 | 4.281 | -0.002 | 0.002 | <0.001 | 367.8 |
| 0.018 | 0.026 | <0.001 | 358.1 | |||||
| ADFI | Q | 46 | 128.3 | 7.914 | -0.010 | 0.002 | <0.001 | 390.5 |
| 0.012 | 0.034 | <0.001 | 380.4 | |||||
| FCR | Q | 46 | 1.866 | 0.045 | 0.001 | 0.001 | <0.001 | 0.200 |
| -0.001 | 0.001 | <0.001 | -17.00 | |||||
| Total | ||||||||
| ADG | Q | 37 | 49.78 | 2.403 | -0.001 | 0.001 | <0.001 | 247.1 |
| 0.019 | 0.017 | <0.001 | 236.7 | |||||
| ADFI | Q | 40 | 91.28 | 4.117 | 0.001 | 0.001 | <0.001 | 271.5 |
| 0.003 | 0.013 | <0.001 | 260.4 | |||||
| FCR | Q | 40 | 1.881 | 0.087 | 0,001 | 0,001 | <0.001 | 46.70 |
| -0.001 | 0.001 | <0.001 | 31.60 | |||||
SE, standard error; AIC, akaike information criteria; Q, quadratic; ADG, average daily gain; ADFI, average daily feed intake; FCR, feed conversion ratio.
RESULTs AND DISCUSSION
In fact, all parameters had significant influence (p<0.05) due to Lactobacillus addition in positive way. Statistical analysis of this study was reported in Table 3. In this study, broilers gained good FCR score in starter, finisher and total phase. Average FCR of its respective phase were 1.5 ± 0.162, 1.843 ± 0.203 and 1.88 ± 0.402 g/g. Those FCR supported ADG in highest weight, namely 32.97 ± 10.52, 64.15 ± 20.67 and 50.22 ± 10.55 g, respectively. It can’t be separated due to escalation of intestine histology reported in Table 4.
Good condition in productivity of broilers cannot be separated from well-maintained intestinal ecosystem. Based on Table 5, Lactobacillus addition boosted Lactobacillus population and reduced Escherichia coli population. The population of Lactobacillus in intestine especially in caecum and ileum was significantly boosted (p<0.05) due to Lactobacillus addition in feed to 9.010 and 8.980 log cfu/g, respectively. Opposite result showed by Escherichia coli, the addition of Lactobacillus suppressed its population to support the performance of broilers.
The histologic structures of organs in digestive tract were significantly affected (p<0.05) due to Lactobacillus addition both in quadratic and linear model. Duodenum and ileum support the performance improvement in broilers even though jejunum did not. Duodenum and ileum construct good condition in intestine with average unit of 1017 ± 169.1 and 687.1 ± 200.8 µm, respectively and 5.826 ± 1.756 and 4.822 ± 1.243 µm/m for their villus height. Jejunum had a minimum trend due to Lactobacillus specifically in its villus height and ratio of villus and crypt depth due to linear decrease in crypt depth.
The results above have demonstrated the effect of Lactobacillus addition to broilers specifically in their performance based on their histologic structures and gastrointestinal microbiota. These results are in line with ; ; , both in mixed or single Lactobacillus species. The capability to boost performance is inseparable from the power of Lactobacillus to modify or modulate such as regulate the microbial population in the digestive tract thereby influencing the immune response to efficiently absorb nutrients. Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus johnsonii, Lactobacillus salivarius and mixed Lactobacillus were used in this study with each bacterium has its own mechanism to encourage the performance of broilers. Lactobacillus acidophilus has a mechanism by directly fermenting nutrients in the stomach ,
Table 4: Lactobacillus addition effect on intestine histology of broiler chicken.
| Response parameter | Model | n | Parameter estimates | Model estimates | ||||
| Intercept | SE intercept | Slope | SE slope | P value | AIC | |||
| Duodenum | ||||||||
| Villus height | L | 49 | 1001 | 75.18 | 17.85 | 6.571 | <0.001 | 112.5 |
| Crypt depth | Q | 52 | 180.1 | 18.14 | -0.520 | 0.165 | <0.001 | 78.20 |
| -0.270 | 0.473 | <0.001 | 82.50 | |||||
| V:C | L | 52 | 5.750 | 0.553 | 0.042 | 0.042 | 0.002 | 37.30 |
| Jejunum | ||||||||
| Villus height | Q | 49 | 865.4 | 74.47 | 2.621 | 1.297 | <0.001 | 318.8 |
| 3.780 | 4.581 | <0.001 | 324.1 | |||||
| Crypt depth | L | 46 | 147.9 | 15.60 | -0.047 | 1.129 | <0.001 | 253.7 |
| V:C | Q | 46 | 6.090 | 0.284 | 0.018 | 0.018 | <0.001 | 83.40 |
| 0.011 | 0.037 | <0.001 | 77.80 | |||||
| Ileum | ||||||||
| Villus height | Q | 37 | 670.8 | 69.16 | -0.590 | 0.608 | <0.001 | 285.9 |
| -0.165 | 3.104 | <0.001 | 287.6 | |||||
| Crypt depth | Q | 40 | 148.4 | 17.95 | -0.010 | 0.125 | <0.001 | 219.8 |
| -0.041 | 0.494 | <0.001 | 215.4 | |||||
| V:C | Q | 40 | 4.958 | 0.421 | -0.002 | 0.005 | <0.001 | 74.10 |
| -0.001 | 0.019 | <0.001 | 63.80 | |||||
SE, standard error; AIC, akaike information criteria; Q, quadratic; L, linear; V:C, ratio of villus height and crypt depth.
Table 5: Lactobacillus addition effect on microbiota population intestine of broiler chicken.
| Response parameter | Model | n | Parameter estimates | Model estimates | |||||
| Intercept | SE intercept | Slope | SE slope | P-value | AIC | ||||
| Ileum | |||||||||
| Lactobacillus | Q | 11 | 8.156 | 0.308 | -0.001 | 0.001 | <0.001 | 33.4 | |
| 0.004 | 0.001 | <0.001 | 20.2 | ||||||
| E. coli | Q | 11 | 5.679 | 0.574 | 0.001 | 0.001 | <0.001 | 32.8 | |
| -0.003 | 0.001 | 0.001 | 22.9 | ||||||
| Caecum | |||||||||
| Lactobacillus | Q | 11 | 8.440 | 0.161 | -0.001 | 0.001 | <0.001 | 27.2 | |
| 0.003 | 0.002 | <0.001 | 13.8 | ||||||
| E. coli | Q | 11 | 6.787 | 0.158 | 0.001 | 0.001 | <0.001 | 24.5 | |
| -0.007 | 0.002 | <0.001 | 11.2 | ||||||
SE, standard error; AIC, akaike information criteria, Q, quadratic.
Lactobacillus plantarum stimulates protective immune responses , Lactobacillus johnsonii assesses changes in lipid metabolism, gut microbiota, gut development, and digestive abilities . As mentioned above, it can be theoretically meaningful that Lactobacillus can replace antibiotics.
Supplementing diets with probiotics is one of the promising methods for preventing and treating bacterial illnesses. It is necessary for lactobacilli to get past physical and chemical barriers, such as stomach acid and bile in the gut, in order to exert health-promoting probiotic effects. Stimulating and modifying digestive tract increase the performance of broilers. One of the indicators representing the optimization of feed to performance is feed conversion ratio . This study reported that of all phase in broilers with minimum trend in quadratic model, 5 x 107 cfug-1 was the best dosage of Lactobacillus. The Lactobacillus addition to FCR parameter was analogous with Huang et al. (2004) and Mountzouris et al. (2010). This meta-analysis also validated overall performance parameters such as ADG and ADFI in all phase. In quadratic model, negative slope indicates maximum trend of Lactobacillus in representing the feed intake increase of broilers which in line with previous studies ; . The increase in feed intake and palatability (Jia et al., n.d.) is due to natural fermentation products such as acetic acid and biogenic amine .
Higher ADFI and lower FCR with an increase in ADG at maximum point cannot be separated with the histologic structure of broilers and the capability of Lactobacillus to produce digestive enzymes. The growth performance is improved by the secreted amylolytic, cellulolytic, proteolytic, and lipolytic enzymes because they increase the digestibility of starch, protein, and fat components and release the most energy. Furthermore, overall histologic structure of gut showed better condition than control. The high villi of duodenum, jejunum and ileum and supported by low crypt depth are notable parts of digestive tract related to immune health , stress control and nutrient absorption . Villus height of duodenum and ileum showed improvement than control with the better results. The longer the villus, the less damage can be caused by external factors. Each Lactobacillus species has each capability to increase villus height such as Lactobacillus acidophillus by producing enzyme to stimulate small intestine peristalsis , Lactobacillus plantarum by affecting mucosal immunity and the gut barrier , Lactobacillus johnsonii by balancing gut microflora in small intestine thereby healing the damaged mucosa through the renewal of epithelial cells , Lactobacillus salivarius by supporting the gut to reduce the enterocytes damage and renew it .
All mechanisms of Lactobacillus in this study are associated with reducing damage of intestine by producing digestive enzyme (Dudley et al., 2018; ; ; due to renewal cell of intestine such as villus height. Table 2 shows the correlation of good intestinal villi and an increase in broiler performance. The primary elements involved in nutrient absorption in the small intestine are villi. Epithelium surface of intestine area is increased by high villi for better nutrient absorption . Normally, pathogen microflora in intestine invades villi surface ; by altering their permeability resulting in chronic inflammation of intestine epithelium which leads to a decrease in villi size . In addition, a defense mechanism against other undesired bacterial colonization from the cecum, or control ileal flora is the bacterial adhesion to the ileal epithelial wall .
In other way, metabolites of Lactobacillus producing bacteriocin and organic acids help the immune system of broilers to inhibit the growth of pathogen bacteria. Both in ileum and caecum, Lactobacillus reduce the amount of Escherichia coli and making them a natural probiotic. The potential use of lactic acid bacteria (LAB)-produced bacteriocins as a non-toxic and secure bio-preservative to increase food safety has garnered a lot of attention . Bacteriocin is stable in acidic condition and inhibits the growth of Escherichia coli by transporting small ions like K+ and Na+ as essential electrolytes through the bacterial cell membrane, promoting cell membrane activities, and maintaining correct enzyme activity. Increased electrolyte release will signify the disrupted permeability barrier ; . Along with Na+ and K+, adenosine triphosphate (ATP), and nucleic acids are ingredients of membrane constituents to identify certain intracellular components. Leakage markers serve as a measure of the membrane’s resistance to a particular antimicrobial agent in comparison to untreated cells.
Due to the lipophilic character of their undissociated state, organic acids have the ability to permeate cell membranes and alter the amounts of related anion and proton in the cytoplasm. Genetic, age, and sperm factors also related to the cell membranes production in the cytoplasm ; , 2020). As a result, purine bases and crucial enzymes are affected, and bacterial viability is reduced ; . Escherichia coli is one kind of pathogen bacteria categorized as gram negative bacteria with its membrane cell Gómez-García et al. (2019) aims to form organic acids especially formic acid. In addition to the metabolites, the capability of Lactobacillus is one of main factor how Lactobacillus work as antibiotic. Alp and Kuleaşan (2019) reported some factors for Lactobacillus to bind with intestine such as (a) mucus binding protein; (b) lipoteichoic acid (c) extracellular polysaccharides and (d) flagella and pili. Intestinal mucus has main role as the protection of epithelial surfaces against pathogens by maintaining a favorable environment for digestion thereby allowing the movement of nutrients from the lumen to the underlying epithelium. Douillard et al. (2013) reported pili by Lactobacillus increased mucus-binding activity. However, findings about the adhesion mechanism of Lactobacillus have not clearly explained. The binding of epitopes on carbohydrate chains and type of several reason become an obstacle and need to be investigated in the future .
CONCLUSIONS AND RECOMMENDATIONS
The present meta-analysis concludes that overall Lactobacillus addition in broilers can increase performance due to improvement in the digestive tract and decrease in pathogenic bacteria with 5 x 10-7 cfu log-1 Lactobacillus population recommendation. Future research in this area is required, specifically in separated Lactobacillus strain since different bacterial strains could produce different outcomes.
Novelty Statement
The current study, shows the best evaluation and dosage of the addition of various types of lactobacillus in broilers which are seen in performance, histology and digestive tract profile through a meta-analysis approach.
AUTHOR’S CONTRIBUTION
BH, TRP and WW conducted the experiments, analyzed the data, and drafted the article. TRP reviewed the data analysis and revised the draft article. BH and SR supervised the experiment. MB, EAR and FMS designed the experiment, reviewed the data analysis, and revised the article draft.
Ethical approval
Ethical approval is not required for meta-analysis study.
Conflict of interest
The authors have declared no conflict of interest.
Figures

Diagram flow of article selection in the meta-analysis using systematic review centre for laboratory animal experimentation (SYRCLE) method.
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