Effects of oligosaccharides on performance, egg quality, nutrient digestibility, antioxidant status, and immunity of laying hens: a meta-analysis

Abstract

A meta-analysis was conducted to determine the effects of different types of oligosaccharides (OS) on the egg quality, intestinal profile, nutrient digestibility, and immunity of laying hens. A dataset was constructed from articles published between 2006 and 2023 via a literature search using several keywords related to oligosaccharides and laying hens’ performance. After careful evaluation, the final dataset was developed from 25 in vivo studies comprising 165 comparisons. The meta-regression showed that levels of OS supplementation curvilinearly increased (p < 0.05) hen day egg production (HDEP), and crude protein digestibility (CPD). However, OS supplementation did not affect (p > 0.05) feed intake (FI), feed conversion ratio (FCR), egg mass, egg weight, eggshell thickness, shell strength, and Haugh unit. OS supplementation showed a positively improved antioxidant activity, as indicated by the curvilinear effect on superoxide dismutase (SOD) and malondialdehyde (MDA) concentration. In the categorical meta-analysis, mannan oligosaccharide (MOS), xylooligosaccharides (XOS), and chitosan oligosaccharide (COS) significantly increased (p < 0.01) HDEP and CPD. MOS was the only type of OS that decreased (p < 0.05) FCR while FOS showed to increase (p < 0.01) Haugh unit. To sum up, oligosaccharides could generally increase HDEP but MOS is superior to improving HDEP and FCR while FOS is better than other OS to increase eggshell thickness.

HIGHLIGHTS

• Oligosaccharides increase egg production and protein digestibility in laying hens.

• Mannan oligosaccharide improves feed conversion ratio in laying hens.

• Elevated trends of IgG and IgA after supplementation with oligosaccharides.

• Fructo-oligosaccharides improve eggshell thickness and suppress Malondialdehyde (MDA) in laying hens.

Keywords:

• Egg production
• antioxidant
• laying hens
• prebiotics

Introduction

In response to the continuous demand for eggs, higher efficiency is required in the production aspects of laying hens, one is by utilising feed additives that can improve egg production and health over the laying periods (Jahanian and Ashnagar 2015; Sjofjan et al. 2021). One effort of attaining this objective is by improving intestinal microflora and the immune system using functional feed additives (Irawan et al. 2022; Adli et al. 2023). Oligosaccharides (OS) are known to have important roles in those parameters (Salami et al. 2022). Depending on their configural structure and their sources, OS may present as mannan oligosaccharides (MOS), fructooligosaccharides (FOS), raffinose oligosaccharides (RFOS), xylooligosaccharides (XOS), and chitooligosaccharides (COS) (Janardhana et al. 2009; Chacher et al. 2017; Tiwari et al. 2020).

Given the promising effect of MOS, researchers have been interested in further exploring the potential of other types of OS at improving the laying performance. Documented studies have shown that various OS could enhance intestinal morphology and flora while increasing feed efficiency and egg production and quality of laying hens (Zhou, Zhang, et al. 2021). The improvement of the production traits was attributed to their intestinal modulatory effects such as reducing propionic acid and ammonia production and suppressing gram-negative bacteria such as E. coli and Salmonella. Specifically, OS acts as a high-affinity ligand that can bind to pathogenic bacteria (Spring et al. 2000; Parks et al. 2001; Ferket et al. 2005; Soumeh et al. 2019; Zhou et al. 2021; Gu et al. 2022), which may facilitate better nutrient absorption in maintaining the integrity of the intestinal lining to increase feed efficiency, egg production, quality, gut health and immune response of laying hens (Iji et al. 2001; Shashidhara and Devegowda 2003). However, it is not clearly known the comparability effects among the OS types and sources on their modulatory effects.

A previous meta-analysis exclusively reported the use of commercial MOS products and demonstrated that MOS improved hen day egg production (HDEP) feed conversion ratio (FCR), without negatively affecting feed intake (Salami et al. 2022). The study, however, did not examine other types of OS such as COS, XOS, FOS, and RFOS. A more comprehensive meta-analysis is thus required to better understand the divergence effects of various OS as discrepancies have been identified in several published works. Therefore, this study aimed to investigate the effect of different types of OS supplementations in the diets of laying hens on their production performance, egg quality, antioxidant status, and digestibility using a meta-analysis method by integrating related studies.

Materials and methods

Eligibility criteria

Peer-reviewed articles were strictly evaluated and chosen following Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) protocols. A selected article was assessed for inclusion based on the population, intervention, comparators, outcomes, and study design (PICOS) framework. The population was laying hens, the intervention was dietary OS, the comparator was a basal or control diet with no OS supplementation, and the outcomes were hen day egg production (HDEP), feed intake, feed conversion ratio (FCR), and egg quality parameters data, the study design was a randomised control trial. Secondary outcomes were considered including dry matter digestibility (DMD), organic matter digestibility (OMD), crude protein digestibility (CPD), and immunity parameters (IgA, IgG, and IgM).

The articles chosen needed to fulfil the following inclusion requirements: (1) articles published in peer-reviewed journals in the English language; (2) research directly investigated the use of OS on laying hens as the experimental animal; (3) reported level of addition (%) and the type or source of OS in the method; (4) the experiments were conducted in controlled-trial environments; (5) The parameters such as production performance, egg quality, blood serum, intestinal profile data, and nutrient digestibility were included in the dataset and analysis; (6) mentioned in the article information such as the year published, the country where the experiment was conducted, the experimental period, and the strain of laying hens used. The exclusion criteria were: (1) studies did not perform in vivo; (2) did not report production performance data; (3) non-original research articles such as letters to the editor, editorials, research pieces, conference abstracts, notes, papers presented at congresses, books, and thesis.

Search strategy

Peer-reviewed published articles were searched on the following websites: ScienceDirect; Scopus, Web of Science, PubMed; and other platforms such as Taylor and Francis, The CSIRO publishing, Google Scholar, and ResearchGate. The authors retrieved data from related articles after the initial examination based on titles. We then looked through the reference lists of the selected papers to see if there were any relevant articles. Abstracts were screened to meet the inclusion criteria and were stored in Mendeley. The period set for appropriate published articles was from 2006 to 2023, and the following keywords were used: “oligosaccharide”, “mannan oligosaccharides”, “fructooligosaccharides”, “raffinose-oligosaccharides”, “xylooligosaccharides”, “chitooligosaccharides”, “performance”, and “laying hens”.

Data selection and extraction

Full-text articles were imported into a Mendeley reference manager and four authors were responsible for screening the titles and abstract lists to evaluate the published articles. The final dataset consisted of 25 in vivo articles with 165 treatment units. In the beginning, 548 scientific articles reported the use of prebiotic sources in laying hens. One hundred forty-four articles were excluded due to non-relevant parameters. Furthermore, one hundred twenty-sixes were excluded because referred to non-relevant sources of prebiotics. Thirty-four In-vitro studies were excluded since it was irrelevant to the criteria. After this process, 25 eligible studies were retained for meta-analysis: Çabuk et al. (2006); Li et al. (2007); Yan et al. (2010); Bozkurt, Küçükyilmaz et al. (2012); Bozkurt, Tokuşoğlu et al. (2012); Drażbo et al. (2014); Yalçin et al. (2014); Zdunczyk et al. (2014); Zdunczyk et al. (2019); Jahanian and Ashnagar (2015); Krawczyk et al. (2015); Bozkurt et al. (2016); Ghasemian and Jahanian (2016); Koiyama (2018); Ding et al. (2018); Feng and Xia (2019); Jiao et al. (2018); Xu et al. (2020); Zhou, Wu et al. (2021); Zhou, Zhang et al. (2021); Gu et al. (2022); Tao et al. (2022); Obianwuna et al. (2022); Wen et al. (2022); Morgan et al. (2022). The details for the study selection process are provided in Figure 1 and the summary of the final dataset and descriptive statistics are presented in Table 1, respectively.

Figure 1. Diagram flow of article selection in the meta-analysis using SYRCLE method.

Table 1. Studies included in the meta-analyses of the effect of different sources of prebiotics on the performance, egg quality, nutrient digestibility, intestinal profile, and immunity of laying hens.

No.	References	Prebiotic (g/kg)	Form	Type	Age (week)	Length rearing (week)	Strain of laying hens
1.	Çabuk (2006)	0–0.1	Powder	MOS	54	20	Nick Brown
2.	Li et al. (2007)	0.2–0.6	Powder	FOS	25-42	31	Lohmann
3.	Yan et al. (2010)	0–0.2	Powder	COS	27-31	4	Hy-line
4.	Bozkurt, Küçükyilmaz et al. (2012)	0–0.1	Powder	MOS	36	16	Lohmann
5.	Bozkurt, Küçükyilmaz et al. (2012)	0–0.1	Powder	MOS	52	16	Lohmann
6.	Drażbo et al. (2014)	0–1.59	Powder	RFOS	18	20	Lohmann
7.	Yalçın et al. (2014)	0–0.4	Raw	MOS	39	26	Hy-line
8.	Zdunczyk et al. (2014)	0–2.08	Raw	RFOS	18	20	Lohmann
9.	Zdunczyk et al. (2019)	1.36–2.54	Raw	RFOS	33	15	Lohmann
10.	Jahanian and Ashnagar (2015)	0–0.15	Powder	MOS	55-61	6-12	Hy-line
11.	Krawczyk et al. (2015)	1.36–2.54	Powder	RFOS	32	16	Lohmann
12.	Bozkurt et al. (2016)	0–0.1	Powder	MOS	82	16	White leghorn
13.	Ghasemian and Jahanian (2016)	0–0.2	Powder	MOS	68	11	Hy-line
14.	Koiyama et al. (2018)	0–0.9	Powder	MOS	21	46	Hy-line
15.	Ding et al. (2018)	0–0.05	Powder	XOS	28	8	Lohmann
16.	Feng and Xia (2019)	0–0.6	Powder	MOS and FOS	18	26	ISA Brown
17.	Jiao et al. (2018)	0–0.3	Powder	COS	46	8	Hy-line
18.	Xu et al. (2020)	0–0.125	Powder	COS	52	10	Fengda
19.	Zhou et al. (2021)	0–0.04	Powder	XOS	50	12	Hy-line
20.	Zhou et al. (2021)	0–0.4	Powder	XOS	39	12	Hy-line
21.	Gu et al. (2022)	0–0.05	Powder	COS	80	8	Hy-line
22.	Tao et al. (2022)	0–0.04	Powder	COS	28	14	Lohmann
23.	Obianwuna et al. (2022)	0–0.6	Powder	FOS	30	4	Hy-line
24.	Wen et al. (2022)	0–0.6	Powder	XOS	50	12	Hy-line
25.	Morgan et al. (2022)	0–0.2	Powder	XOS	39	9	ISA brown

COS: chitosan oligosaccharide; FOS: fructo-oligosaccharides; MOS: mannan-oligosaccharide; RFOS: Raffinose family oligosaccharides; XOS: xylo-oligosaccharides.

Data analysis

Data analysis and coding were performed in PROC MIXED and NLMIXED procedures of the SAS 9.4 software. The model used was as follows: (1) $$Y_{\mathit{ijk}}=\mu +S_i+{\tau }_j+{S\tau }_{ij}+{\beta }_1{X}_{ij}+b_i{X}_{ij}+{\beta }_2{X^2}_{ij}+b_i{X^2}_{ij}+e_{\mathit{ijk}}$$(1)

Where: $Y_{\mathit{ijk}}$ = dependent variable, $\mu$ = overall mean value, $S_i$ = random effect of the ith study, assumed to be $\sim N_{\mathit{iid}} (0, {\sigma }_S^2),$ ${\tau }_j$ = fixed effect of the jth of $\tau$ factor, ${S\tau }_{ij}$ = random interaction between the ith and jth level of $\tau$ factor, also assumed to be $\sim N_{\mathit{iid}} (0, {\sigma }_{S\tau }^2),$ ${\beta }_1$ = overall value of the linear regression coefficient of Y to X (a fixed effect), ${\beta }_2$ = overall coefficient value of the quadratic regression of Y to X (a fixed effect), $X_{ij}$ and ${X^2}_{ij}$= continuous values of the predictor variable (in linear and quadratic form, respectively), $b_i$ = random effect of the study on the regression coefficient of Y to X, assumed to be $\sim N_{\mathit{iid}} (0, {\sigma }_b^2),$ and $e_{\mathit{ijk}}$ = residual value from unpredictable error. ${S\tau }_{ij}$ and $S_i$ are taken to be independent variables that are chosen at random. The strains, type of OS, and laying phase were considered important covariates and the effects of their interaction with the inclusion levels were assessed following a forward selection procedure in the model analysis. The root means square error (RMSE) and determination coefficient (R²) were used as criteria to select the best model.

Additionally, a categorical meta-analysis was performed to compare the different effects of OS on the parameters of interest. In the model, the types of OS were encoded and stated as fixed effects and the different experiments within studies were coded as random effects by using the following statistical model: (2) $$Y_{ij}=\mathrm{\mu }+{s\tau }_{ij}+{\beta }_a+{({\beta }_a\times {\beta }_b)}_{ij}+s{\beta }_{ij}+e_{ij}\mathrm{ }$$(2) where $Y_{ij}$ = the estimated means of Y, µ = overall mean, $S_i$ = random effect of the different experiment, ${\beta }_j$ = fixed effect of treatment group, ${\beta }_a\times {\beta }_b$ = interaction effect between treatment group and covariate, ${s\tau }_{ij}$ = random interaction between i experiment and the j treatment group, and $e_{ij}$ = residual error ∼ N (0, σ²). Tukey-Kramer’s test was used to separate the least square means within the categorical variables. Significance was declared at p-value ≤ 0.05 and a tendency if the p-value was between 0.05 and 0.10 (Sholikin et al. 2023).

Results

The results of linear mixed models examining the relationships between inclusion levels and variable outcomes are presented in Table 2. The increasing level of OS supplementation up to 2.54% exhibited a significant quadratic relationship (p = 0.028; R² = 0.605) on HDEP but the magnitude effects were depended on the laying phase as shown by the significant interaction effects (p < 0.05) between inclusion levels × phase. No interaction effect was found on inclusion levels × type of OS. OS supplementation in laying hens had no effect (p > 0.05) on feed intake, FCR, egg mass, egg weight, eggshell thickness, shell strength, and Haugh unit. Levels of OS inclusion strongly improved dry matter digestibility (DMD) (p = 0.036; R² = 0.983) and crude protein digestibility (p = 0.044; R² = 0.992) in curvilinear patterns regardless of the type of OS. There were significant interaction effects (p = 0.042) between level × strain on the CPD.

Table 2. Regression linear model of the effect of different sources of prebiotics on the performance, egg quality, nutrient digestibility, and immunity of laying hens.

Response parameter	Model	N	Parameter estimates				Model statistics				p-value
			Intercept	SE	Slope	SE	AIC	RMSE	R^2	L/Q	L × Strain	L × Type	L × Phase
Performance and egg quality
HDEP, %	L	165	84.31	2.01	5.12	1.74	876	0.215	0.151	0.042	0.059	0.191	0.045
	Q				−1.20	0.54	870	0.313	0.605	0.028
Feed intake, g/d	L	157	110.6	2.93	1.11	1.13	964	3.431	0.009	0.332	0.314	0.526	0.072
FCR	L	129	2.15	0.07	−0.04	0.03	−91	0.108	0.038	0.288	0.114	0.427	0.071
Egg mass, g/d	L	90	59.41	2.93	0.85	1.89	539	3.652	0.011	0.653	0.799	0.934	<0.001
Egg weight, g	L	99	64.86	1.63	0.25	0.59	394	1.119	0.002	0.678	0.974	0.781	<0.001
Eggshell strength, N	L	83	3.98	0.14	−0.06	0.09	22.3	0.123	0.008	0.511	0.588	0.522	0.339
Eggshell thickness, µm	L	83	38.67	0.95	1.02	1.35	462	3.352	0.014	0.452	0.227	0.011	0.198
Haugh unit	L	83	82.47	1.04	2.06	1.31	420	3.011	0.443	0.123	0.009	0.219	0.231
Digestibility
DMD, %	L	20	63.22	2.11	7.88	3.46	91.4	1.226	0.582	0.949	0.125	0.109	0.254
					−2.14	0.92	84.8	1.189	0.983	0.036
OMD, %	L	10	71.8	1.59	4.90	13.04	41.1	2.863	0.086	0.718	0.718	0.718	0.909
CPD, %	L	24	49.54	6.69	16.89	7.62	116	2.794	0.446	0.793	0.014	0.006	0.006
	Q				−4.42	1.98	111	2.642	0.992	0.044
Serum antioxidant and immune status
MDA, nmol/mL	L	10	9.05	0.73	−24.33	3.02	45.4	2.417	0.024	0.426	0.111	0.070	0.111
	Q				23.94	3.16	24.3		0.953	0.002
SOD, U/mL	L	10	72.14	33.06	18.39	10.24	81.5	12.799	0.171	0.132	0.015	0.028	0.015
	Q				−121.8	31.98	64.6		0.962	0.019
IgG, ng/L	L	11	53.31	14.81	12.99	6.387	63.8	2.738	0.419	0.082	0.002	0.002	0.007
IgM, µg/mL	L	11	2.28	0.40	2.81	0.705	18.5	0.308	0.772	0.005	0.084	0.084	0.027
IgA, ng/L	L	11	40.34	5.34	22.66	7.99	62.8	3.554	0.368	0.025	0.318	0.318	0.282

N: sample size; SE: standard errors; FCR: feed conversion ratio; DMD: dry matter digestibility; HDEP: hen day egg production; OMD: organic matter digestibility; CPD: crude protein digestibility; IgA: immunoglobulin A; IgG: immunoglobulin G; IgM: immunoglobulin M; MDA: Malondialdehyde; SOD: Superoxide dismutase.

AIC: Akaike information criterion; RMSE: root mean-squared errors; R²: coefficient of determinant; L: linear model; L × Strain: p-value of interaction effect between OS levels and strain of laying hens; L × Type: P-value of interaction effect between OS levels and OS types; L × Phase: p-value of interaction effect between OS levels and laying phase.

Analysis of categorical data suggested that MOS, COS, and XOS significantly increased (p < 0.01) HDEP with the greatest increase shown by MOS compared to CON (87.27 vs 83.71%; Table 3). MOS was the only type of OS showing an improvement effect (p < 0.05) on FCR. For egg quality parameters, FOS was the only OS to increase (p < 0.05) eggshell thickness. No effect of all types of OS was detected on feed intake, egg mass, egg weight, egg strength, and Haugh unit. All OS showed to increase (p < 0.05) CPD except RFOS which was comparable to CON.

Table 3. Interaction of the effect of different sources of prebiotics on the performance, egg quality, nutrient digestibility, and immunity of laying hens.

Response variable	N	CON vs TRT						SEM	p Value	Interaction effects
		CON (n = 49)	MOS (n = 35)	FOS (n = 20)	COS (n = 43)	RFOS (n = 10)	XOS (n = 20)			TRT × Strain	TRT × Phase
Performance and egg quality
HDEP, %	165	83.71^b	87.27^a	84.83^b	84.93^ab	84.45^b	84.93^ab	2.435	0.002	0.003	<0.001
Feed intake, g/d	157	111.0	111.5	111.7	111.7	109.0	110.9	3.816	0.752	0.300	0.111
FCR	129	2.22^a	2.11^b	2.18^a	2.15^a	2.16^a	2.14^a	0.090	0.029	0.318	<0.001
Egg mass, g/d	90	58.91	60.49	59.05	59.88	57.71	59.64	5.658	0.888	0.973	0.988
Egg weight, g	99	61.74	61.65	61.91	62.39	61.74	62.83	1.944	0.589	0.785	0.014
Eggshell strength, N	83	3.95	3.97	4.09	3.98	3.69	4.06	0.214	0.365	0.199	0.366
Eggshell thickness, µm	83	38.46^b	38.65^b	44.86^a	37.56^b	37.45^b	40.55^ab	2.224	0.004	0.068	0.020
Haugh unit	83	82.07	82.94	86.44	83.08	82.87	83.21	2.454	0.141	0.021	0.035
DM, %	20	63.77	67.73	–	64.73	63.89	64.73	2.819	0.209	0.110	0.110
OM, %	10	68.8	72.91	–	–	–	–	1.832	0.173	0.032	0.173
CP, %	24	51.31^c	55.78^b	56.22^ab	62.13^a	51.61^c	62.12^a	4.637	<0.001	<0.001	<0.001
Serum antioxidant and immune status
MDA, nmol/mL	10	9.02^a	8.79^a	3.35^b	6.79^ab	–	–	1.179	0.039	0.139	0.139
SOD, U/mL	10	69.28	78.04	102.63	77.53	–	–	30.715	0.162	0.396	0.396
IgG, ng/L	11	43.75^b	–	49.78^a	53.87^a	–	–	20.853	0.017	0.057	0.027
IgM, µg/mL	11	2.22^b	–	4.01^a	3.01^a	–	–	0.385	0.032	0.065	0.047
IgA, ng/L	11	30.56	–	40.26	36.79	–	–	14.558	0.232	<0.001	0.332

N: number of data; DMD: dry matter digestibility; FCR: feed conversion ratio; HDEP: hen day egg production; OM: organic matter; CP: crude protein; IgA: immunoglobulin A; IgG: immunoglobulin G; IgM: immunoglobulin M; MDA: Malondialdehyde; OM: Organic Matter; SOD: Superoxide dismutase.

CON: control diet; COS: chitosan oligosaccharide; FOS: fructo-oligosaccharides; MOS: mannan-oligosaccharide; RFOS: Raffinose family oligosaccharides; XOS: xylo-oligosaccharides.

TRT × strain = p-value of interaction effect between TRT (type of OS) and strain of laying hens; TRT × phase = p-value of interaction effect between TRT (type of OS) and laying phase.

Malondialdehyde (MDA) and total superoxide dismutase (SOD) as biomarkers of antioxidant activity were affected by increasing OS inclusion levels in a curvilinear pattern (p < 0.05). For SOD, interaction effects (p < 0.01) were observed between levels of inclusion and strain, type of OS, and laying phase. Among the different types of OS, FOS showed a significant reduction effect (p < 0.05) on MDA while MOS and COS showed no effect compared to CON (p > 0.05). SOD was not significantly influenced by the OS treatments (p > 0.05) due to the large variation of inter-studies data. Immunology parameters in plasma showed that IgM was the only immune parameter to linearly increase (p = 0.005) in response to increasing OS supplementary levels while a tendency for linear increase (p < 0.10) was observed on IgG and IgA. However, there is no significantly influenced by the MOS and COS treatments (p > 0.05) on on IgG, IgM and IgA. The regression effects, however, depended on the strain, type of OS, and laying periods (p < 0.01) for IgG and on the laying period (p = 0.027) for IgM. When compared to CON, categorical data showed that IgG and IgM were higher (p < 0.05) for laying hens supplemented with COS and FOS.

Discussion

Our meta-analysis revealed an overall positive response to OS dosing effects on the HDEP of laying hens. Additional discrimination based on the types of OS suggested that MOS was the most superior to improve HDEP and it is the most frequently used OS representing 9/25 studies in this meta-analysis. Other OS including FOS, COS, and XOS but not RFOS also improved the HDEP. The difference between OS could be attributed to the specific chemical structure of each OS which might imply their biological roles when digested by laying hens. The superiority of MOS to improve HDEP found in our meta-analysis can partly be explained by its multiple functions in the gut of laying hens especially attributed to its antimicrobial properties and gut modulatory actions compared to other OS. MOS is known as an alternative antibiotic growth promoter from nature and can control antibacterial activity in the digestive tract. Residing microflora modulation, pathogen load reduction, and proliferation of beneficial bacteria stimulation were identified as the beneficial effects of MOS on intestinal morphology (Agazzi et al. 2020). In addition, it was reported by several studies that MOS shifted the intestinal microbiome signatures to favour fibre digestion (Corrigan et al. 2011; Cho et al. 2020; Singh et al. 2022). Compared to XOS, COS, FOS, and RFOS which are derived from non-microbe materials, MOS is a prebiotic derived from the cell wall of yeast (Saccharomyces cerevisiae). The specific structure of MOS has the advantage to be stable in extreme conditions and other specific mode of actions related to GIT positive modulation as outlined by several researchers (Spring et al. 2000; Ferket et al. 2002; Baurhoo et al. 2007; Mountzouris et al. 2007). In addition, multiple digestive enzymes including maltase, aminopeptidase, leucine, and alkaline phosphatase were reported to increase by supplementation with MOS which increased in the presence of MOS (Iji et al. 2001). These mechanisms promote better gut integrity (Bozkurt et al. 2012; Chacher et al. 2017), thus enabling more efficient nutrient absorption that subsequently improves egg production. Numerous empirical studies have consistently backed up this claim (Jahanian and Ashnagar 2015; Rajani et al. 2016; Julendra et al. 2020; Salami et al. 2022).

In addition to MOS, XOS was also acknowledged for its favourable effects on gut microflora. The XOS has been reported to enrich bacterial diversity in the caecal microbiota and specifically increase the abundance of Firmicutes and decrease the relative abundance of Bacteroidetes, leading to an increase in non-digestible nutrient fractions and resulting in higher SCFA concentrations (Zdunczyk et al. 2019; Zhou et al. 2021). More specifically, butyrate-producing bacteria have been reported to increase, which is beneficial since butyrate is known to facilitate the improvement of epithelial cells (Kumar et al. 2015). Similar functional effects regarding the ability of COS, XOS, and FOS to positively modulate microbial composition have been demonstrated by other researchers (Jung et al. 2008; Chang et al. 2022; Wang et al. 2022). Another important feature of these OS is the ability to increase the proliferation of bifid bacteria and Lactobacillus; these have a superior ability to degrade oligomer compared to other types of bacteria and could further promote gut health and integrity (Tiwari et al. 2020). This is additionally supported by studies demonstrating a linear increase in α-glucosidase, α-galactosidase, β-galactosidase, α-arabinopyranosidase, and β-xylosidase enzyme activities in response to dietary OS (Zdunczyk et al. 2014; 2019) as inherent effects of microbial shift.

Furthermore, the effects of OS on egg quality were inconsistent in the literature; most studies reported a lack of effect (Bozkurt et al. 2016; Zhou et al. 2021; Gu et al. 2022), which aligns with the results of our meta-analysis. Several studies reported a minor improvement in egg mass in laying hens fed OS, such as Ghasemian and Jahanian (2016) and Obianwuna et al. (2022); however, the effects depended on the supplementation levels (0.3–1.0%). In these studies, the inclusion of more than 1% OS showed no effect on egg quality parameters. Interestingly, according to our discrete analysis, the eggshell thickness was markedly improved by FOS supplementation. The reported increase in eggshell thickness can be associated with an increase in mineral absorption in the digestive tract. Regarding this, fermentation of FOS in the GIT was suggested to enhance minerals ionisation especially Ca²⁺ and Mg²⁺ levels via stimulation of enterocytes proliferation that decreased the lower part of GIT (Świątkiewicz et al. 2010; Li et al. 2017). The enhanced effects of FOS on intestinal histomorphology and overall gut integrity (Obianwuna et al. 2022) might also facilitate higher mineral absorption, which would contribute to increased eggshell formation.

In this meta-analysis, MOS was the only OS showing to reduce FCR. Positive modulatory effects on gut microbiota as explained above may be partially responsible for the improvement in FCR (Ferket et al. 2002). The modulatory effects could increase crypt depth that renders intestinal tissue turnover to be slow, meaning that the crypt does not need to create new tissue; this aligns with the findings reported by Awad et al. (2011). Improvement of crypt depth is also linear with the study by Chacher et al. (2017). The data on nutrient digestibility indicate that OS inclusion levels strongly (R² > 0.80) increased DMD and CPD. The contrasting effects were more obvious on CPD, as evident from the different increases between the types of OS in the control group. Previous experiments have reported that the increase in N utilisation by supplemental OS was higher than dry matter and organic matter (OM) (Ghasemian and Jahanian 2016; Ding et al. 2018). However, the mechanism was unclear and inconsistent between studies. While a majority of experiments have reported an improvement in intestinal morphology as an absorption capacity indicator, this did not translate into better nutrient digestibility as reported in many studies using broiler chickens (Soumeh et al. 2019) and laying hens (Zdunczyk et al. 2019). Indeed, updated literature has suggested that dietary OS results in an increase in short-chain fatty acids (SCFAs) in the intestinal tract and can be used as a source of energy and reduce the competition to utilise glucose between microflora-host interactions (Ghasemian and Jahanian 2016; White et al. 2021; Zhou et al. 2021). Another plausible factor can be the modulatory effect of OS on microbial communities. For instance, the lower family of Bacteroides and higher Firmicutes, Lactobacillus, and Desulfovibrio in birds fed OS is a clear indication of positive effects on intestinal microbes. Specifically, enrichment of >10 bacterial genera abundance that belongs to Firmicutes phylum as reported by Zhou, Wu et al. (2021), Zhou, Zhang et al. (2021) was confirmed to be highly correlated with the increase of N utilisation and intestinal morphology measurements.

Denoted as the end product of lipid peroxidation, MDA is an important biomarker of oxidative stress and SOD is an important enzyme in eliminating the reactive oxygen species (Yin et al. 2014). This meta-analysis demonstrated that OS could elevate antioxidant activity by increasing SOD concentration and simultaneously decreasing MDA concentration. It has been consistently reported across studies that the majority of OS could reduce reactive oxygen metabolites (ROS), which is attributable to an increase in glutathione (GSH) precursors such as methionine (Elnesr et al. 2019; Obianwuna et al. 2022). Despite a general knowledge that OS can enhance antioxidant enzymes (Chacher et al. 2017), there has been a lack of significant effects of various OS on SOD due to large variations and lack of replicates in effects among the available studies. Obianwuna et al. (2022) suggested that the discrepancies in SOD effects were due to physiological status, age, and strain. However, our findings suggested that there was also a lack of significant effect between the types of OS and strain and laying phase. Thus, other physiological factors may explain the inconsistency and may be considered for investigation in future studies.

Additionally, OS has been reported to be able to increase the secretion of mucin, protein barrier factors, and sulphated goblet cells (Borges Dock-Nascimento et al. 2007; Bergstrom et al. 2008), which accumulatively provide greater host protection and major pathogens degradation (Rajani et al. 2016; Tiwari et al. 2020). This biological role of OS was reflected in the linear increase of IgA and IgM in our meta-analysis results, especially IgA as the most abundant immunoglobulin substance in mucosal immunity. In this meta-analysis, COS showed the greatest increase in IgG while FOS and COS had a similar elevating effect on IgM. A previous study also demonstrated that OS had a different ability to influence the secretion of functional immunity molecules and reported that COS had the greatest stimulatory effects on IgM (Chang et al. 2022). This indicates that COS could be more effective to ameliorate acute infection. FOS has also been reported to stimulate IgG and IgM (Janardhana et al. 2009; Obianwuna et al. 2022). It was suggested that the stimulating effect on immunoglobulin concentrations was partly due to an enhancement of the mucosal integrity effect from OS (Obianwuna et al. 2022). The increase in CPD in this study could plausibly be an important factor in the synthesis of immunoglobulins due to the increase in amino acids’ bioavailability.

Conclusion

This meta-analysis demonstrated strong positive relationships between OS supplementary levels with the increase of HDEP and digestibility of dry matter and protein in curvilinear patterns and linearly increase IgG and IgA. Categorical meta-analysis revealed that MOS was identified to have the most superior effects to increase HDEP and reduce FCR in laying hens while FOS was the only group of oligosaccharides that was able to increase eggshell thickness. Thus, it is recommended to add MOS to improve HDEP or FOS to enhance eggshell thickness in the diets of laying hens.

Ethical approval

Ethical Approval for the study was not needed, since there is no laboratory or animal subject in this research. This research is based on the literature review.

Disclosure statement

No potential conflict of interest relevant to this article is reported.

Data availability statement

The data presented in this study are available on request from the corresponding author upon reasonable request.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The authors are grateful to PPKID Batch II Universitas Brawijaya.