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Meta-analysis of dietary Bacillus spp. on serum biochemical and antioxidant status and egg quality of laying hens

  • Ifeanyichukwu Princewill Ogbuewu EMAIL logo , Monnye Mabelebele and Christian Anayo Mbajiorgu
Published/Copyright: June 21, 2024

Abstract

The purpose of the current meta-analysis was to determine the efficacy of Bacillus spp. (BS) feed additive in enhancing serum biochemical indices (total protein and cholesterol) and antioxidant enzymes (total antioxidant capacity [TAC], catalase [CAT], superoxide dismutase [SOD], glutathione peroxidase [GSH-Px], and malondialdehyde [MDA]) status and egg quality (Haugh unit [HU], eggshell thickness [EST], and eggshell strength [ESS]) of laying chickens. Seventeen articles were identified via a systematic search performed on PubMed, Google Scholar, and Scopus, and results were combined using a variance component model. The results indicate that dietary BS supplementation resulted in higher HU (P < 0.001), EST (P < 0.001), and ESS (P < 0.001) values with evidence of heterogeneity. Furthermore, dietary BS increased total protein (P = 0.008) and GSH-Px (P < 0.001) and reduced the concentrations of CAT (P = 0.018), SOD (P = 0.039) and MDA (P < 0.001) in the serum of laying hens. In contrast, dietary BS did not affect serum cholesterol and TAC in laying chickens. Restricted subgroup analyses showed that the studied moderators (i.e., treatment duration, supplementation level, BS, hen’s age, and hen’s strains) influenced the outcomes of the meta-analysis. Additionally, meta-regression revealed that the studied moderators accounted for most of the sources of variations among the 17 studies utilised for the meta-analysis. In conclusion, dietary BS can be utilised as a nutritional strategy to improve egg quality, serum total proteins, and the serum antioxidant status of laying hens.

1 Introduction

Eggs are regarded as high-quality food since they have high protein and other nutrients needed by humans [1]. The demand for eggs is increasing in developing countries as people become more aware of their nutritional values [2]. Laying hens in commercial environments are regularly exposed to a variety of stressors, including environmental, nutritional, and physiological factors, all of which can have an adverse impact on laying hen performance [3,4]. Probiotics are one of several approaches that can reduce stress in poultry due to their beneficial effects on gut health [5]. Probiotics are live, non-pathogenic microbes that, when given in sufficient quantities, help to maintain the host’s normal microbiota while also improving digestion and nutrient utilisation [6]. Furthermore, probiotics benefit poultry by balancing the intestinal microbiota, improving intestinal epithelial cell integrity, and increasing mucosal immunity responses [7]. Probiotics also serve as growth promoters and nutritional bioregulators by delivering enzymes and other important substances into the host’s intestine. The gut ecosystem contains several microbes that may have both beneficial and harmful effects on the chicken’s gastrointestinal tract [7]. Thus, there is growing interest in the use of probiotics to change intestinal microbiota populations and increase nutrient uptake. The application of Bacillus spp. (BS) in this context is well documented [8,9].

Bacillus species are rod-shaped, aerobic, and sporulating bacteria that, unlike conventional probiotics like Saccharomyces spp. and Bifidobacterium, can withstand heat during feed processing, have increased shelf life during feed storage, and survive the harsh environment of a chicken’s digestive system [10,11]. Several studies found that BS intervention improved egg production, egg quality, and physiological parameters of laying hens [1,2,11,12], whereas other researchers found no effect [10,13,14,15,16]. These discrepancies might be attributed to drivers, such as environmental stressors, BS, hen’s age, diet composition, hen strains, dosage, mode of administration, and feeding duration, that were found to influence laying hen performance [17].

The application of meta-analysis, a statistical method that aggregates results from multiple published articles addressing the research topic in animal science to resolve studies with contradictory outcomes and to create research areas in animal agriculture, has been reported [18]. However, little is known about the action of dietary BS supplementation on the performance indices of laying hens. The purpose of this investigation, therefore, was to determine the meta-analytic effect of BS supplementation on serum biochemical and antioxidant enzyme levels and egg quality of laying chickens.

2 Materials and methods

2.1 Literature search

Articles relevant to the topic were retrieved via a systematic search carried out in PubMed, Scopus, and Google Scholar in accordance with the standard method [19], as displayed in Figure 1. The search uses a blend of search queries and related keywords, including laying chickens, BS supplementation, serum parameters, and egg quality. The reference section of the retrieved articles was searched for other potential studies. Table 1 shows the search keywords and queries utilised for the analysis using the PICO framework, where PICO stands for Population (laying hens), Intervention (BS supplementation), Comparators (diet without BS supplementation), and Outcomes (egg quality and serum parameters).

Figure 1 
                  Publication selection flow chart.
Figure 1

Publication selection flow chart.

Table 1

Search strategies for PubMed, Scopus, Google Scholar, and Web of Science databases

Database Search terms Number of articles identified
PubMed (“Bacillus” OR “probiotic-bacillus”) AND (“laying hens” OR “layers”) AND (“productive performance” OR “egg production” OR “egg quality” OR “blood characteristics” OR “serum antioxidant enzymes”) 305
Scopus (“Bacillus” OR “probiotic-bacillus”) AND (“laying hens” OR “layers”) AND (“productive performance” OR “egg production” OR “egg quality” OR “blood characteristics” OR “serum antioxidant enzymes”) 298
Google Scholar (“Bacillus” OR “probiotic-bacillus”) AND (“laying hens” OR “layers”) AND (“productive performance” OR “egg production” OR “egg quality” OR “blood characteristics” OR “serum antioxidant enzymes”) 502

2.2 Selection criteria

Inclusion criteria were the following: (i) randomised controlled experiments that assessed dietary BS supplementation on measured outcomes, (ii) published in peer-reviewed journals, and (iii) diets were free of antibiotic growth promoters. Review articles were excluded from the study. Trials not conducted in laying hens were excluded. Studies that did not report on parameters of interest in layers were also excluded. Trials that appeared in more than one database were removed. All retrieved articles, after excluding duplicate articles were evaluated by two authors; a third author was consulted to resolve disagreements. Hand searches of published articles were also evaluated. Seventeen peer-reviewed studies met the inclusion criteria [1,2,8,11,12,13,15,16,20,21,22,23,24,25,26,27,28]. The Cochrane Risk-of-Bias (ROB) Assessment Method [29] was employed to assess the qualities of individual publications included in the meta-analysis, as shown in Table S1.

2.3 Database development and statistical analysis

Data on the surname of the principal author, publication year, study location (Canada, China, Egypt, Italy, Korea, and Poland), and measured outcomes (Haugh unit [HU], eggshell thickness [EST], ESS, serum cholesterol, total protein, total antioxidant capacity [TAC], catalase [CAT], superoxide dismutase [SOD], glutathione peroxidase [GSH-Px], and malondialdehyde [MDA]) were retrieved from 17 eligible articles. Information was also collected on the following moderators: hen age (18–86 weeks), hen strains (Hi-sex, Lohmann, HyLine, Xuefeng black‐bone, Shaver white and Isa Brown), BS (B. amyloliquefaciens, B. velezensis, B. subtilis, and B. licheniformis), supplementation level (0–5.0 g BS/kg feed), and supplementation duration (5–30 weeks). All analyses were carried out using OpenMEE software [30]. The VCM [31] was used, and aggregated results were presented as standardised mean difference (SMD) at a 95% confidence interval (CI). Publication bias and heterogeneity were evaluated using standard methods [32]. Meta-regression analysis was used to determine whether the moderators studied (hen age, hen strains, Bacillus count, BS, supplementation level, and treatment duration) were predictors of egg quality. A priori subgroup analyses were performed based on factors that could potentially affect the magnitude of the BS treatment: (i) hen’s age, (ii) hen’s strains, (iii) BS, (iv) supplementation level, and (v) treatment duration. Subgroup analyses were not done in the stratum with fewer than three studies due to the small sample size [33]. Meta-regression and publication bias were not executed in outcome measures with <10 studies due to a lack of statistical power [34]. Data represented as graphs were extracted using WebPlotDigitizer [35]. Results were significant at a 5% probability value. Forest plots were deemed significant when the 95% CI did not contain zero [33].

3 Results

3.1 Study characteristics

Table 2 shows the details of the 17 peer-reviewed publications that were analysed. The earliest publication was published in 2006, and the most recent was in 2023. These publications were conducted in six countries (i.e. Canada, China, Egypt, Italy, Korea, and Poland) that cut across four continents (Europe, Africa, Asia, and North America). The majority of the experiments utilised B. subtilis (n = 12) and were carried out in China (n = 10).

Table 2

Studies included in the meta-analysis and their features

Authors Location Explanatory moderator variables Study characteristics
Hen strain B. spp. BC1 SL2 TD3 HA4 CP ME Ca P LD5 RT6 DC7 NR8 NHR9
Xu et al. (2006) China Lohmann Subtilis 6.00 × 109 0–1 30 25 16.50 2,639 3.30 0.35 16 1 Corn/SB 6 32
Lei et al. (2013) China HyLine ++ 2.00 × 1010 0–0.9 8 28 18.70 2,749 3.34 0.38 16 1 Corn/SB 6 15
Forte et al. (2015) Italy HyLine Subtilis 0–0.5 16 18 18.01 2,810 3.88 0.62 Corn/SB
Sobczak and Kozłowski (2015) Poland Lohmann Subtilis 24 18 18.00 2,746 3.83 0.36 15 1 Corn/SB 9 16
Abd El-Hack et al. (2016) Egypt Hisex Subtilis 1.50 × 108 0–1 12 22 18.00 2,850 3.64 0.54 17 1 Corn/SB 9 3
Guo et al. (2017) China HyLine Subtilis 1.00 × 1010 24 28 16.52 2,753 3.50 0.40 16 1 Corn/SB 6 12
Liu et al. (2018) China + Subtilis 1.00 × 109 8 25 16.00 2,600 3.55 0.36 16 1 Corn/SB 6 20
Tang et al. (2018) China Isa Brown +++ 6 28 15.65 2,904 3.43 0.68 16 1 Corn/SB 10 6
Chen et al. (2019) China HyLine Subtilis 1.00 × 109 0–5 10 29 16.90 2,701 3.51 0.34 16 1 Corn/SB 6 15
Neijat et al. (2019) Canada Shaver white Subtilis 1.1–2.2 × 108 0–5 29 19 17.00 2750 3.73 0.43 1 Corn/SB 6 14
Upadhaya et al. (2019) Korea HyLine Subtilis/++ 0–0.5 27 18 17.81 2,791 3.83 0.28 Corn/SB 9 6
Shi et al. (2020) Korea HyLine Subtilis 1.00E × 109 0–0.5 5 40 15.02 2,904 3.25 0.61 1 Corn/SB 8 6
Ye et al. (2020) China HyLine Velezensis 0–2 6 49
Zhou et al. (2020) China HyLine +++ 0–0.6 10 28 16.52 2,753 3.50 0.40 16 1 Corn/SB 12 20
Liao et al. (2023) China HyLine Subtilis 2.0–3.06 × 108 6 81 15.00 2,650 4.00 0.12 16 1 Corn/SB 6 10
Tsai et al. (2023) Taiwan Leghorn Subtilis/+++ 1.00 × 109 0–3 8 65 17.81 2,850 4.21 0.68 18 1 Corn/SB 3 10
Wang et al. (2023) China HyLine Coagulans 1.26–9.35 × 105 0–0.2 8 86 16.59 632.9 3.23 0.54 16 1 Corn/SB 6 32

+ – Xuefeng black‐bone; ++ – licheniformis; +++ – amyloliquefacien; Ca – Calcium; P – phosphorus; SB – soybean. 1BC – Bacillus count (cfu/g). 2SL – supplementation level (g/kg). 3TD – treatment duration (week). 4HA – hen’s age (week). 5LD – lighting duration (Hours). 6RT – rearing type [1 – BCS (battery cage system) vs 2 – DLS (deep litter system)]. 7DC – diet composition. 8NR – number of replications. 9NHR – number of hen per replicate.

3.2 Blood chemistry and serum antioxidant enzyme status

Table 3 shows the serum total protein, cholesterol, and antioxidant status of layers fed BS-supplemented diets. The layers in the BS group recorded statistically higher blood total protein and GSH-Px than those in the control group. In contrast, layers on BS supplementation had serum cholesterol and TAC values similar to those of laying hens on control diets. However, BS-enriched rations improved CAT, SOD, and MDA values in laying hens.

Table 3

Serum cholesterol, total protein, and antioxidant enzyme concentrations of laying hens fed Bacillus probiotic-supplemented diets

Variables nc+ SMD (95% CI) Heterogeneity
SMD P-values X 2 (Q) I 2 (%) P-values
Total protein 8 1.06 (0.28, 1.84) 0.008 338.49 98 <0.001
Cholesterol 12 −0.39 (−1.07, 0.30) 0.267 753.139 99 <0.001
CAT 11 −1.32 (−2.42, −0.22) 0.018 1327.79 99 <0.001
GSH-Px 14 1.20 (0.75, 1.65) <0.001 450.29 97 <0.001
SOD 14 −0.52 (−1.01, −0.03) 0.039 596.53 98 <0.001
TAOC 14 0.07 (−0.53, 0.67) 0.819 837.89 98 <0.001
MDA 15 −1.21 (−1.92, −0.51) <0.001 1218.65 99 <0.001

SMD, standardised mean difference; nc+, number of comparisons; REM, random effects model; CI, confidence interval; P, probability; I 2, inconsistency index; TAOC, total antioxidant capacity; CAT, catalase; SOD, superoxide dismutase; GSH-Px, glutathione peroxidase; and MDA, malondialdehyde.

3.3 HU, EST, and eggshell strength (ESS)

Data on HU values of layers given BS-enriched diets are displayed in Figure 2. The layers on the BS additive had better HU than those on the control diet (SMD = 0.18; 95% CI: 0.06, 0.30). Table 4 shows the impacts of the studied modifiers on HU in laying hens. Restricted subgroup analysis shows that HyLine strain aged 18–31 weeks that received BS (B. coagulans, B. licheniformis, and B. amyloliquefaciens) at <1.0 g/kg feed for 1–10 and 21–30 weeks had significantly improved HU. Figures 3 and 4 show the results of BS diets on EST and ESS. The layers on BS-supplemented diets recorded better EST (P < 0.001; Figure 3) and ESS (P < 0.001; Figure 4) than those on the control feed. Table 5 shows that EST was significantly increased in HyLine, XBB, and Leghorn strains aged 18–31 weeks fed B. amyloliquefaciens, B. subtilis, and B. licheniformis at <1.0 and 1.0–5.0 g/kg feed for 1–10 weeks. The results of the influence of the studied moderators on ESS, as illustrated in Table 6, suggested that Lohmann, HyLine, and Xuefeng black‐bone strains aged 18–31 weeks fed ration containing B. subtilis, B. licheniformis, and B. amyloliquefaciens at <1.0 g/kg feed for 1–10 and 21–30 weeks had increased ESS (Table 6).

Figure 2 
                  Effect of dietary Bacillus invention on HU in laying hens.
Figure 2

Effect of dietary Bacillus invention on HU in laying hens.

Table 4

Subgroup analysis of the effect of Bacillus probiotics on the HU of laying hens

Modifiers Subgroup nc+ SMD (95% CI) Heterogeneity
Random effects P-values I 2 P-values
Hen’s age 18–31 30 0.15 (0.04, 0.25) 0.006 69 <0.001
32–72 4 0.44 (−0.04, 0.91) 0.072 88 <0.001
>72 6 0.19 (−0.17, 0.56) 0.303 93 <0.001
Hen strains
Lohmann 3 0.21 (−0.05, 0.46) 0.109 68 0.046
HyLine 25 0.25 (0.09, 0.41) 0.003 87 <0.001
XBB 3 −0.23 (−0.52, 0.07) 0.128 75 0.020
Shiver white 3 0.24 (−0.01, 0.48) 0.056 47 0.153
Leghorn 3 −0.11 (−0.40, 0.19) 0.477 0 0.926
Supplementation level (g/kg)
<1.0 18 0.170 (0.03, 0.31) 0.019 79 <0.001
1.0–5.0 7 0.21 (−0.19, 0.61) 0.308 87 <0.001
Treatment duration (weeks)
1–10 27 0.21 (0.05, 0.38) 0.010 88 <0.001
21–30 11 0.13 (0.01, 0.26) 0.039 47 0.041
BS
B. subtilis 22 0.11 (−0.04, 0.25) 0.139 78 <0.001
B. licheniformis 6 0.365 (0.17, 0.558) <0.001 58 0.036
B. amyloliquefaciens 6 0.32 (0.12, 0.520) 0.002 42 0.134
B. coagulans 4 −0.18 (−0.28, −0.08) <0.001 0 0.713

SMD, standardised mean difference; BS, Bacillus spp.; XBB, xuefeng black bone; nc+, number of comparison; CI, confidence interval; P, probability; I 2, inconsistency index.

Figure 3 
                  Influence of dietary Bacillus invention on EST in laying hens.
Figure 3

Influence of dietary Bacillus invention on EST in laying hens.

Figure 4 
                  Impact of dietary Bacillus invention on ESS in laying hens.
Figure 4

Impact of dietary Bacillus invention on ESS in laying hens.

Table 5

Subgroup analysis of the effect of Bacillus probiotics on the EST of laying hens

Modifiers Subgroup nc+ SMD (95% CI) Heterogeneity
Random effects P-values I 2 P-values
Hen’s age 18–31 21 0.56 (0.38, 0.73) <0.001 84 <0.001
32–72 5 0.22 (−0.08, 0.51) 0.155 52 0.081
>72 6 0.12 (−0.08, 0.32) 0.237 76 0.001
Hen strains
HyLine 18 0.45 (0.24, 0.66) <0.001 89 <0.001
XBB 3 0.58 (0.26, 0.90) <0.001 78 0.010
Shaver white 3 0.01 (−0.17, 0.18) 0.933 0 0.871
Leghorn 3 0.46 (0.17, 0.76) 0.002 0 0.461
Supplementation level (g/kg)
<1.0 16 0.44 (0.21, 0.68) <0.001 90 <0.001
1.0–5.0 5 0.29 (0.07, 0.50) 0.008 9 0.358
Treatment duration (weeks)
1–10 25 0.52 (0.35, 0.70) <0.001 88 <0.001
21–30 6 0.12 (−0.04, 0.24) 0.058 0 0.553
BS
B. subtilis 16 0.28 (0.13, 0.43) <0.001 68 <0.001
B. licheniformis 6 0.70 (0.43, 0.97) <0.001 78 <0.001
B. amyloliquefaciens 6 0.91 (0.64, 1.18) <0.001 64 0.016
B. coagulans 4 −0.01 (−0.18, 0.18) 0.989 68 0.025

SMD, standardised mean difference; BS, Bacillus spp.; XBB, xuefeng black bone; nc+, number of comparison; CI, confidence interval; P, probability; I 2 , inconsistency index.

Table 6

Subgroup analysis of the effect of Bacillus probiotics on the ESS of laying hens

Modifiers Subgroup nc+ SMD (95% CI) Heterogeneity
Random effects P-values I 2 P-values
Hen’s age 18–31 22 0.83 (0.67, 0.99) <0.001 83 <0.001
32–72 7 0.37 (−0.24, 0.98) 0.233 94 <0.001
Hen strains
Lohmann 3 0.67 (0.31, 1.03) <0.001 83 0.002
HyLine 20 0.80 (0.58, 1.02) <0.001 88 <0.001
XBB 3 0.52 (0.08, 0.97) 0.022 89 <0.001
Leghorn 3 −0.10 (−0.45, 0.26) 0.595 30 0.238
Supplementation level (g/kg)
<1.0 13 0.82 (0.57, 1.07) <0.001 86 <0.001
1.0–5.0 6 0.50 (−0.11, 1.12) 0.108 94 <0.001
Treatment duration (weeks)
1–10 23 0.71 (0.49, 0.93) <0.001 90 <0.001
21–30 8 0.65 (0.41, 0.89) <0.001 80 <0.001
BS
B. subtilis 17 0.46 (0.27, 0.65) <0.001 83 <0.001
B. licheniformis 6 0.93 (0.59, 1.27) <0.001 85 <0.001
B. amyloliquefaciens 6 0.94 (0.51, 1.37) <0.001 85 <0.001

SMD, standardised mean difference; BS, Bacillus spp.; XBB, xuefeng black bone; nc+, number of comparison; CI, confidence interval; P, probability; I 2, inconsistency index.

3.4 Meta-regression and bias analyses

Table 7 shows the associations between the studied modifiers and egg quality parameters in layers given a BS-supplemented diet. The results found a significant linear relationship between HU and aspects of study moderators (i.e. BS and Bacillus count). The results indicated that BS and Bacillus count were the cause of the variability in HU of layers on fed BS-supplemented rations. They also showed a significant relationship between measured outcomes (EST and ESS) and the studied moderators except for hen’s strain, supplementation level, and treatment duration. Table 8 displays publication bias results of layers fed with BS-enriched diets. The Rosenberg’s Nfs for the database are 321, 1,380, and 4,970 for the HU value, EST, and ESS, respectively. These values were 3.6, 18.4, and 63.9 fold higher than the thresholds of 90, 75, and 75 required to consider the mean effect size robust in the presence of publication bias.

Table 7

Relationship between modifiers and variables (EM, HU, EST, and ESS) in laying hens

Variables Moderators SMD Q M DF P-values R 2 (%)
HU
Hen’s age 0.15 2.40 2 0.301 2
Hen strains 0.12 6.30 6 0.391 1
Supplementation level 0.23 0.14 1 0.712 0
Treatment duration 0.07 0.66 2 0.718 0
BS 0.11 19.7 4 0.001 38
Bacillus count 0.12 62.1 13 2.2 × 10−8 78
EST
Hen’s age 0.56 6.98 2 0.031 19
Hen strains 0.03 9.81 6 0.133 13
Supplementation level 0.31 0.28 1 0.594 0
Treatment duration 0.03 5.94 2 0.051 13
BS 0.28 33.1 3 3.08 × 10−7 60
Bacillus count 0.03 24.2 11 0.012 45
ESS
Hen’s age 0.83 6.21 2 0.045 12
Hen strains 0.67 9.00 4 0.061 15
Supplementation level 0.52 1.02 1 0.312 0
Treatment duration 0.71 0.09 1 0.762 0
BS 0.45 12.9 3 0.005 29
Bacillus count 0.24 26.6 5 6.89 × 10−5 59

HU, haugh unit; EST, eggshell thickness; BS, Bacillus spp.; ESS, eggshell strength; df, degree of freedom; Q M, coefficient of moderator; P, probability; R 2 , amount of heterogeneity explained by moderators.

Table 8

Analysis of publication bias

Outcomes SMD Observed significance Target significance Nfs number No. of studies (n) Nfs > [5 (n) + 10]
HU 0.1388 <0.0001 0.05 321 16 90
EST 0.3548 <0.0001 0.05 1380 13 75
ESS 0.7440 <0.0001 0.05 4970 13 75

SMD, standardised mean difference; n, number of studies; Nfs, fail-safe number.

4 Discussion

Several mechanisms of action for probiotics in poultry were proposed, including the growth and multiplication of beneficial gut microbes, alteration in the gut ecology that stimulates the release of enzymes that promote nutrient absorption, and improvement in oxidative stability [26]. The intensive system of rearing chickens has left them susceptible to oxidative stress [36]. Oxidative stress occurs when the pace of the body-generated free radicals exceeds the biological system’s capacity to counter their effects [36]. Probiotics have been shown to scavenge free radicals and boost antioxidant capacity [16]. Antioxidant enzymes are the first line of defence against oxidative attack [16]. The concentrations of SOD, CAT, and MDA were significantly reduced by dietary BS supplementation in the study, suggesting that BS increases the antioxidative capacity of layers. The significantly higher serum GSH-Px content in the present study suggests improved cell functions via increased ability of BS to ameliorate the negative consequence of excessive free radicals. This also indicates its ability as a dietary antioxidant for chickens. The observed increase in serum antioxidant enzyme concentrations was consistent with the results of other investigators [7,21,37], who discovered that BS additive improves antioxidative capacity in chickens and livestock. In this study, BS additive showed no evidence for the statistical effect on serum TAC, which is in concordance with the results of Zhou et al. [8] in layers fed with rations having different levels of B. amyloliquefaciens BLCC1-0238.

Blood constituents are utilised in nutritional studies to assess the health status of animals [15,16]. This meta-analysis indicates that layers fed BS-based rations recorded higher serum protein than the control. The significantly increased serum proteins in laying hens fed BS-enriched rations could be related in part to the BS’s capability to improve protein digestion and utilisation. However, further investigations are needed to explore the mechanism of action of BS in the metabolism of ingested feed, particularly protein. This observation agrees with that of Abudabos et al. [38], who found that B. subtilis supplementation in livestock feed increased the concentration of serum proteins in layers. Probiotics have been shown to possess immunomodulatory properties in chickens [9]. The increased serum protein levels in this study might be traced to the action of BS in the immunoglobulin A (IgA) production [16]. This study showed that BS supplementation reduced serum cholesterol content in laying hens [13,38]. However, the results of this analysis differ from those of Forte et al. [13]. Zhou et al. [8] noticed that dietary BS supplementation increased blood values of follicle-stimulating hormones and estradiol, which are produced from cholesterol. The lower values of cholesterol in the blood of layers given BS diets compared to those fed with a diet without BS could be linked to higher needs of cholesterol required for the biosynthesis of egg production-related hormones in the ovary and the liver.

HU, computed as 100 × log (H = albumen height + 7.57) − (1.7 × egg weight0.37), is an essential parameter for determining egg quality [10]. A higher HU score suggests increased egg white viscosity and, thus, superior egg quality. The higher HU score observed in this meta-analysis implies that BS can improve protein utilisation in the ration, resulting in better egg quality, which agrees with the findings of other researchers [8,12,22], who found increased HU scores in laying hens fed BS-enriched diets. The mechanism behind the increased HU score in laying hens fed BS is not known; however, this improved score might be related to BS’ ability to modulate intestinal microbiota composition, leading to an increase in nutrient absorption [8,16].

There was a positive correlation between eggshell quality and egg breakage, with the number of cracked eggs decreasing as the shell quality improved [28]. In this study, layers given BS-supplemented diets exhibited higher EST and ESS than the controls, which corroborates the findings of Guo et al. [22], who found that feeding a BS-enriched diet for 24 weeks increased ESS and EST in 28-week-old laying hens. The three distinct segments of the small intestine (i.e., duodenum, jejunum, and ileum) are the main locations for nutrient absorption in chickens [39]. The improved eggshell quality could be related to the positive effect of BS on the uptake of calcium and phosphorus in the small intestine, as well as in bone mineralisation [40]. Although the effect of BS supplementation on mineral digestibility was not analysed in this meta-analysis due to the small sample size, it is likely that BS facilitated the uptake of calcium in the gastrointestinal tract of laying hens. Overall, these findings suggest that BS supplements improve shell quality in laying hens; however, the mode through which BS enhances egg quality is poorly understood, and further research is required in this area.

5 Analysis of moderators

5.1 Hen age, strains, and supplementation level

Hen age was a strong predictor of both EST and ESS in laying hens, with shell quality decreasing as the layers aged. The improved HU score and shell quality in layers aged 18–31 and 32–72 weeks confirmed the earlier report that BS improved nutrient absorption in poultry [40]. The impact of chicken genetics on egg production and quality in chickens has been documented [41]. The current meta-analysis revealed that hen strain is not a significant predictor of HU and shell quality in layers given BS-supplemented diets. These results show the absence of a linear relationship between hen strains and egg quality. The influence of the supplementation level of BS on aspects of egg quality has been examined [1,16,18]. The probiotic effect on HU and ESS was observed in experiments that fed BS at <1.0 g/kg feed. In contrast, the effect on EST was observed in studies that fed BS both at <1.0 g/kg or 1–5.0 g/kg feed. This observation implies that supplementation levels that improve egg quality parameters in layers are not statistical and may depend on the traits being analysed. The results are in harmony with the results of others [8,16].

5.2 Treatment duration, Bacillus count, and BS

The information on the effect of the duration of BS treatment on the performance indices of laying chickens is limited. The results show that treatment duration was not a significant predictor of HU, EST, and ESS. However, HU and ESS were improved in layers from experiments that administered BS for 1–10 and 21–30 weeks, whereas EST was only improved in layers from experiments that administered BS for 1–10 weeks. The reasons for comparable EST in laying hens administered BS-supplemented rations for 21–30 weeks in this meta-analysis are not clear. However, this meta-analytic study suggests that BS is more likely to improve EST as laying hen advances in lay. This observation, however, needs to be validated. This study also showed that BS and count affected the HU, EST, and ESS in layers. The influence of BS on HU was identified in experiments that used B. amyloliquefaciens and B. licheniformis, whereas the impact on EST and ESS was evident in studies that used B. licheniformis, B. subtilis, and B. amyloliquefaciens. In addition, B. amyloliquefaciens and B. licheniformis appear to be better than B. coagulans in improving HU scores. The results show that differences in BS and count may have contributed to disparities in the effect of BS additives on egg quality parameters of laying hens.

5.3 Source of variability and bias analysis

This investigation used 17 published studies, assisting in concluding that dietary BS supplementation improves performance parameters of laying hens, taking cognizance of heterogeneity and publication bias. However, stratification analyses did not address the problem of significant heterogeneity in this data synthesis study. Meta-regression reveals that BS and count lead to inconsistent findings among studies that examine the influence of BS on HU score, whereas hen age, BS, and count were responsible for variability in EST and ESS. Evidence exists that pooled effect estimations are prone to publication bias since journal editors may be uninterested in publishing studies with insignificant or negative findings [42]. This meta-analysis also indicates that publication bias was not a concern in this analysis since a considerable amount of unpublished negative or non-significant studies would be required to increase the P values of HU, EST, and ESS to >0.05 [43].

6 Conclusions

This investigation revealed that administration of BS to the diet of layers up to 5 g/kg feed improved total serum protein (standardised mean difference [SMD] = 1.06; 95% CI: 0.28, 1.84), GSH-Px (SMD: 1.20, 95%CI: 0.75, 1.65), SOD (SMD = −0.52, 95% CI: −1.01, −0.03), MDA (SMD = −1.21, 95% CI: −1.92, −0.51), HU (SMD = 0.18, 95% CI: 0.06, 0.30), EST (SMD = 0.43; 95% CI: 0.28, 0.58), and ESS (SMD = 0.70; 95% CI: 0.52, 0.87). The results also suggested that BS, hen’s age, and Bacillus count influenced the results of the meta-analysis and accounted for 38–60, 12–19, and 45–78% sources of heterogeneity across the 17 studies utilised for the analysis.



  1. Funding information: Authors state no funding involved.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results and approved the final version of the manuscript. IPO conceptualised this meta-analysis; IPO, MM, and CAM performed literature search, data extraction, data analyses, and visualisation; IPO and MM wrote the draft; and CAM edited the draft.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: All data generated or analysed during this study are included in this published article [and its supplementary information files].

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Received: 2024-02-18
Revised: 2024-04-24
Accepted: 2024-05-09
Published Online: 2024-06-21

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  147. Effect of pruning height and organic fertilization on the morphological and productive characteristics of Moringa oleifera Lam. in the Peruvian dry tropics
  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
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