Abstract
The immune system of newborns is underdeveloped, leaving them susceptible to infections like rotavirus (RV). Despite vaccines, RV remains a leading cause of child mortality, especially in developing countries. Maternal immunity is transferred during pregnancy and breastfeeding to the offspring providing protection against RV infection. This study aims to explore how the maternal diet can enhance the newborn's ability to fight early infections. Pregnant rats received orally Bifidobacterium breve M‐16 V and short chain galacto‐oligosaccharides (scGOS)/long chain fructo‐oligosaccharides (lcFOS). At day 5 of life pups are infected with RV and at day 8, samples are collected for the infection analysis. Pups whose mothers received the synbiotic have lower RV infection severity. The levels of immunoglobulins (Ig) IgG2c and IgA are raised in pups' plasma and digested milk, respectively. Synbiotic supplementation improves intestinal maturation and increases gene expression of immune‐related genes. In conclusion, the administration of this synbiotic to gestating and lactating mothers ameliorates the incidence and severity of the pup's diarrhea caused by the RV infection by improving their immunity.
Keywords: Bifidobacterium breve M‐16V, infancy, long chain fructo‐oligosaccharides (lcFOS), rotavirus, short chain galacto‐oligosaccharides (scGOS)
The graphical abstract illustrates the impact of maternal synbiotic supplementation with Bifidobacterium breve M‐16V and a mixture of short‐chain galacto‐oligosaccharides (scGOS) and long‐chain fructooligosaccharides (lcFOS) during gestation and lactation on the offspring's response to rotavirus (RV) infection in early life. Following maternal supplementation, the offspring of the supplemented dams exhibited reduced severity and incidence of infection. Additionally, the immunoglobulin profile, intestinal functionality, and microbiota composition of the offspring were modulated as a result of the maternal supplementation

1. Introduction
Maternal immunological status significantly impacts infants' early development, particularly during gestation and lactation, which shape neonatal maturation.[ 1 , 2 ] Both stages of life are extensively influenced by maternal environmental factors including diet and lifestyle.[ 3 ] In this sense, having a balanced diet during pregnancy and lactation promotes a counteracting effect in early life infections in the offspring.[ 1 ]
Dietary ingestion of prebiotics,[ 4 ] probiotics,[ 5 ] and synbiotics[ 6 ] are of interest for a healthy lifestyle. Synbiotics combine the beneficial effects of probiotics and prebiotics in stimulating the growth of probiotic microorganisms by providing them with the appropriate substrates. One of the most common cited benefits of synbiotics is the modulation of the immune system whereas at the same time they are able to inhibit pathogenic invasions.[ 7 ] Bifidobacteria combined with fructo‐oligosaccharides (FOS) and galacto‐oligosaccharides (GOS) is one of the most used synbiotic combination.[ 7 ]
Rotaviruses (RV) are the main etiological agent responsible for acute gastroenteritis in children under 5 years of age worldwide, associated with 20–30% of cases of diarrhea that require hospitalization.[ 8 ] The watery diarrhea is caused by the destruction of enterocytes, deregulation of liquid transport proteins, and disruption of tight junctions (TJs) between the epithelial cells.[ 9 ] To prevent RV infections, oral vaccines have been developed,[ 10 ] however, RV continues to cause more than 200 000 deaths annually, mainly in developing countries, due to the low rates of vaccination.[ 11 ]
For these reasons, it is necessary to develop alternatives to treat and prevent RV infections. It is known that the microbiota plays a role in modulating host immunity, especially against enteric pathogens. Therefore, RV infection could be controlled by boosting infant's immunity or promoting the presence of beneficial microbiota.[ 12 ] However, the use of supplements in mothers to prevent neonate's infections has not been properly studied. Thus, we aimed to evaluate the effect of a synbiotic supplementation to dams during gestation and lactation to counteract the RV infection in the offspring in early life. Clinical and molecular parameters associated to the RV‐induced diarrhea were evaluated.
2. Results
2.1. Growth Evolution
Pups’ body weight was monitored from day 2 to the end of the diarrhea period (Figure 1 ). SYN had lower birth weights (REF = 7.02 ± 0.15 and SYN = 6.14 ± 0.14), due to a higher number of pups/litter in the SYN group (13.0 ± 0.71 vs 10.0 ± 1.10) (p = 0.07). Therefore, the total weight gain adjusted for litter size was lower in SYN dams (9.72 ± 0.69) compared to REF dams (13.70 ± 1.08) (p = 0.01). However, the weight gain was not influenced due to the maternal supplementation during the study (Figure 1). The growth‐associated parameters and the relative organ sizes were not affected by the maternal intervention (Table S2, Supporting Information).
Figure 1.

Body weight gain of neonatal rats from day 2 to day 13 of life. Results are expressed as mean increase with respect to day 2 (%) ± standard error of the mean (SEM). (n = 36–39 until day 8 and 15–17 until day 13, coming from a three cohorts’ experimental design). One‐way ANOVA was used to observe significant differences: *p < 0.05 versus REF.
2.2. Hematological Variables
RV infection in the SYN group increased the total count of leucocytes, driven by elevated numbers of lymphocytes and granulocytes. In contrast, the red blood cell variables were not influenced by any of the interventions (Table S3, Supporting Information).
2.3. Clinical Evaluation
After RV inoculation, diarrhea was evaluated in terms of severity and incidence (Figure 2 ). RV infection resulted in mild diarrhea with an average score in both groups below 2.5 (Figure 2a). The severity curve of the SYN group was always below the REF one, however only on day 10 of life this result was significantly different between both groups. The mean
Figure 2.

Clinical indices of diarrhea. a) The diarrhea severity is measured by using the Diarrhea Index (DI), which involves grading fecal samples on a scale of 1–4 based on their color, texture, and amount. A DI score of 2 or greater indicates the presence of diarrhea, while scores below 2 indicate absence. b) S‐AUC: area under the severity curve. c) The incidence of diarrhea is indicated by the percentage of animals with diarrhea (%DA), which is calculated based on the percentage of animals in each group that have a DI score of 2 or higher. d) I‐AUC: area under the incidence curve. (n = 15–17, coming from a three cohorts’ experimental design). One‐way ANOVA was used to observe significant differences: * p < 0.05 versus REF; # p < 0.1 versus REF.
S‐AUC was calculated as a good indicator of the global process and pups whose mothers received the synbiotic showed a lower diarrhea S‐AUC than that of the REF group (Figure 2b).
During the period from day 4 to day 13, the percentage of animals with diarrhea (%DA) progressively increases, reaching a peak on day 9 in both groups, and then decreasing to almost no animals presenting diarrhea around day 12 (Figure 2c). Specifically, on day 6, a tendency to lower %DA in the SYN group (p = 0.06) was observed compared to the REF group, and on day 10, this effect was significant. The I‐AUC calculated as the overall incidence value show that the SYN group has a lower I‐AUC than the REF group, indicating a global reduction in the incidence of diarrhea because of the maternal synbiotic supplementation (Figure 2d).
Other variables associated to the severity, incidence and duration of the diarrhea were calculated (Table 1 ). The day displaying the maximum incidence was similar in both groups, around day 8, while the day achieving the maximum severity was achieved later in the SYN group. Regarding the variables related to the duration of diarrhea studied, the first and the last day of diarrhea were similar between both groups. However, the duration of the diarrhea period and the days with diarrhea were significantly lower in the group supplemented with the SYN compared to the REF group, indicating the shortening symptoms effect of the intervention.
Table 1.
Clinical variables associated with the RV‐induced diarrhea.
| REF | SYN | |
|---|---|---|
| Incidence | ||
| Maximum incidence [%] | 44.4 | 41.38 |
| Day of maximum incidence | 7.67 ± 0.76 | 8.00 ± 0.45 |
| Severity | ||
| Maximum severity (1–4) | 2.27 ± 0.12 | 1.90 ± 0.13 |
| Day of maximum severity | 7.12 ± 0.27 | 7.97 ± 0.26 * |
| Duration | ||
| Beginning day of diarrhea | 7.28 ± 0.20 | 7.65 ± 0.25 |
| Final day of diarrhea | 9.05 ± 0.27 | 8.59 ± 0.27 |
| Diarrhea period [days] | 2.16 ± 0.24 | 1.64 ± 0.17 * |
| Days with diarrhea [days] | 1.49 ± 0.19 | 1.02 ± 0.13 * |
Data are expressed as mean ± SEM. (n = 15–17).
p < 0.05 versus REF.
2.4. Fecal Sample Analysis
The fecal elimination of the SA‐11 viral particles was quantified at day 6 (Figure 3 ). The SYN eliminated around 1 × 108 RV particles per mg of feces, similarly to the REF group, which clearance was 5 × 107 (p = 0.21) (Figure 3a). Additionally, the collected samples were separated into pre‐diarrhea period (pre‐D, day 4–5), diarrhea period (D, day 6–9), and post‐diarrhea period (post‐D, day 10‐13) (Figure 3b). As expected, during the RV infection the fecal weight increased with respect to the pre‐D period in both groups. At the end of the infectious process, in the post‐D period, the fecal weight was lower in the SYN pups than in the REF ones.
Figure 3.

Fecal samples analysis. a) The viral shedding was assessed at the peak of viral elimination (1 Day post‐infection [DPI]). b) The fecal weight, as an objective indicator of the severity of diarrhea, during the pre‐diarrhea (pre‐D), diarrhea (D), and post‐diarrhea (post‐D) periods. Data are expressed as mean ± SEM. (n = 15–17, coming from a three cohorts’ experimental design). One‐way ANOVA was used to observe significant differences: * p < 0.05 versus REF.
2.5. Anti‐RV Antibody Response
Anti‐RV antibody (Ab) response was assessed in plasma samples from pups at different time points, and in plasma and milk from dams (Figure 4 ). Maternal synbiotic supplementation had no effect on dams' specific anti‐RV levels in plasma or milk. Synbiotic supplementation did not alter the specific Ab production in pups either during the RV infection (day 8), at the end of lactation (day 21) or 1 week post‐weaning (day 28). Notably, a significant increase in total anti‐RV Ab was observed from 8‐ to 21‐day‐old animals, indicating a distinct Ab response during this period.
Figure 4.

Concentration of total anti‐RV antibodies in milk and plasma of pups and dams. Results are expressed in Arbitrary Units per mL. Data are expressed as mean ± SEM. (n = 15–17, coming from a three cohorts’ experimental design). Kruskal–Wallis was used to observe significant differences.
2.6. Pups Immunoglobulinome
The Ig profile of 8‐day‐old pups was examined in digested milk, mucosal (small intestine), and systemic (plasma) compartments (Figure 5 ). In pups' stomach milk obtained on day 8 (during RV infection), synbiotic supplementation did not induce a change in total IgM levels, whereas total IgA concentration was increased with respect to REF (Figure 5a). In the GW, IgM levels tended to increase (p = 0.06) in the SYN group, contrasting with unchanged sIgA levels (Figure 5b). Systemically, total IgM, IgA, and IgG concentrations in plasma remained unaffected (Figure 5c). However, IgG subtype analysis revealed decreased IgG1 and IgG2b proportions and increased IgG2c in the SYN group (Figure 5d). The overall profile was analyzed by non‐metric multi‐dimensional scaling (NMDS) (Figure 5e) and the Th1/Th2 ratio (Figure 5f). In the NMDS potential cluster differences (p = 0.09) between REF and SYN groups were found, while the Th1/Th2 ratio remained unchanged with the synbiotic supplementation.
Figure 5.

Immunoglobulin profile in pups at day 8 of life. a) Total levels of IgM and sIgA in digested milk. b) Total levels of IgM and sIgA in the gut wash (GW). c) Total Ig levels (IgM, IgA, and IgG) in plasma. d) Relative proportion of IgG subtypes (IgG1, IgG2a, IgG2b, IgG2c). e) Analysis of non‐parametric multidimensional scaling (NMDS) for the Ig profiles based on the Bray–Curtis distance. f) Analysis of the Th1/Th2 ratio. Data (a–e) are expressed ad mean ± SEM. Each point represents an animal (e) by ANOSIM test. (n = 15–17, coming from a three cohorts’ experimental design). One‐way ANOVA (a‐d, f) was used to observe significant differences: * p < 0.05 versus REF; # p < 0.1 versus REF. GW, gut wash.
2.7. Small Intestine Gene Expression
Biomarkers of the immune system and gut barrier function of the SI were studied by q‐PCR (Figure 6 ). During RV infection, maternal supplementation increased mRNA levels of Toll‐like receptors (Tlr2 and Tlr7) in the SYN group (Figure 6a). Synbiotic supplementation also enhanced the expression of genes associated with epithelial barrier function (Ocln, Muc2, and Muc3) (Figure 6b), while intestinal maturation markers (IgA, Blimp1, FcRn, and Afp) remained unaltered (Figure 6c).
Figure 6.

Effect of synbiotic supplementation on the intestinal gene expression. a) Toll‐like receptors. b) Intestinal barrier molecules. c) Intestinal maturation. Relative gene expression was calculated with respect to REF, which corresponded to 100% of transcription (represented with a horizontal dotted line). (n = 15–17, coming from a three cohorts’ experimental design). One‐way ANOVA was used to observe significant differences: *p < 0.05 versus REF. Afp, alpha‐fetoprotein; Blimp1, B‐lymphocyte‐induced maturation protein 1; FcRn, neonatal Fc receptor; IgA, immunoglobulin A; Muc2, mucin2; Muc3, mucin3; Ocln, occludin; Tlr, Toll‐like receptor.
2.8. Small Intestine Histology
The intestinal morphology was evaluated during the RV infection (Figure 7 ). Synbiotic supplementation exerted a trophic effect on the villi by increasing their height and area. The villi width also tended to be increased (p = 0.07) in the SYN group.
Figure 7.

Effect of synbiotic supplementation to dams on pups’ small intestine architecture. a) Representative images of histological sections of the small intestine stained with hematoxylin and eosin, 100×. b) Villi height. c) Villi area. d) Villi width. Data are expressed as mean ± SEM. (n = 15–17, coming from a three cohorts’ experimental design). Kruskal–Wallis was used to observe significant differences:* p < 0.05 versus REF; # p < 0.1 versus REF.
2.9. Cecal Microbiota composition
The impact of the RV infection on the cecal microbiota was analyzed at day 8 of pups’ life (Figure 8 ). No impact of maternal synbiotic intervention on the pup cecal microbial richness (Chao1 and observed species) and diversity (Shannon) (Figure 8a–c) was observed. Beta‐diversity showed two distinct microbial clusters depending on the maternal intervention (PERMANOVA test F‐value: 3.0566; R‐squared: 0.12706; p = 0.011, Figure 8d). The individual profiles showed that SYN intervention normalized the cecal microbial profile toward Escherichia coli/Shigella and Ligilactobacillus compared to REF (Figure S1, Supporting Information) and the LEfSe test also demonstrated the role of those two microbial genus depending on SYN intervention (Figure 8e). Additionally, the results of the bacteria proportions in terms of phylum, family, and genera were analyzed. On day 8 of life the beta diversity of the cecum was really low, the phylum bacteria proportions were mainly divided in Firmicutes and Proteobacteria, without being modified by the maternal synbiotic supplementation (Figure 8f). Regarding the family proportions, only a reduction of the Enterococcaceae was observed in the SYN group (Figure 8g). At genera levels, the maternal synbiotic supplementation increased the proportion of Escherichia/Shigella, and reduced the proportion of Enterococus and Enterobacter members (Figure 8h). DESEq tests showed the differential presence of specific microbial genus. Enterobacter was depleted (FDR p = 0.023) and enriched in E. coli/Shigella (FDR p = 0.06) in the SYN intervention. In addition, SYN intervention increased the presence of Streptococcus (FDR p < 0.001), Ruminococcus_gauvreauii_group (FDR p < 0.001); and Erysipelatoclostridium (FDR p < 0.001) in the pup cecum content (although relative abundances were lower than 1–0.50%). The tracking of the Bifidobacterium breve M‐16 V in the feces indicated that it was present in a 50% of the analyzed samples, being identified at 2 × 108 UFC mg−1.
Figure 8.

Cecal microbial alpha‐ and beta‐diversity of dams at weaning day. Microbial richness measured by a) number of observed species and b) Chao1 index. c) Microbial diversity measured by Shannon index. d) Beta diversity as a principal coordinate analysis (PCoA) plot based on Bray–Curtis dissimilarity. e) LEfSe test of Enterobacter and Escherichia Shigella. f) Relative proportions of cecal phylum. g) Main families present in the CC. h) Main genera present in the CC. Statistical testing was performed by PERMANOVA using Bray Curtis distances and the Mann–Whitney U test was used for alpha‐diversity indexes (a–d) and one‐way ANOVA (f–h) was used to observe significant differences: * p < 0.05 SYN versus REF. (n = 11–12, coming from a three cohorts’ experimental design). CC, cecal content.
3. Discussion
Breast milk (BM) serves as the primary source of immunological compounds, contributing to the protection of the newborn. Breastfed infants exhibit lower early‐life infection rates compared to formula‐fed infants,[ 25 ] a difference attributed to the bioactive compounds present in BM that enhance the adaptive immunity.[ 26 ] Recent studies have also investigated the impact of maternal nutrition during gestation and lactation on the development of[ 27 ] and the composition of milk.[ 28 ] For instance, maternal diet and probiotic intake influence milk immunoglobulin profile, increasing sIgA and modulating oligosaccharide levels.[ 15 , 29 , 30 ]
Maternal transmission of immunological components positively influences infant immune maturation and decreases early‐life infections.[ 31 ] However, little research has explored how enhancing maternal immunological status through diet affects infant development. Our study demonstrates that supplementation with B. breve M‐16 V and scGOS/lcFOS during gestation and lactation improves newborn immune responses, thereby reducing RV infection. These findings highlight the potential of maternal nutritional intervention to decrease the severity and incidence of infections in neonates, with synbiotic supplementation aiding in recovery.[ 12 ]
According to previous findings, the RV‐induced diarrhea was not accompanied by weight loss.[ 32 ] Furthermore, no variations were detected in relative organ weights, suggesting a safe influence of the synbiotic when administered to the mothers.
RV infection targets small intestine enterocytes, disrupting absorptive and fluid secretion functions, thus leading to diarrhea.[ 8 ] In this preclinical study, maternal synbiotic supplementation demonstrated efficacy in mitigating RV infection by reducing severity, incidence, and duration of diarrhea in the offspring. Previous RV infection model studies have observed an increase in watery feces, intestinal dysbiosis, and altered immune responses during RV infection.[ 12 , 17 , 23 ]
Probiotics and prebiotics, such as Lactobacillus, Bifidobacterium, Saccharomyces strains,[ 33 ] and scGOS/lcFOS, are used to alleviate diarrhea.[ 34 ] Their combination displays promising results in modulating and preventing RV gastroenteritis.[ 34 , 35 ] Our study confirms that synbiotic supplementation to dams enhances the immune systems of pups, ameliorating RV infection manifestations. This is an additional step forward to enhance the newborn health before birth to counteract early life infections. Maternal milk contains bioactive components that benefits the newborns and helps their immune system. In our study, the synbiotic supplementation increased the ability of BM to fight against the RV, however, as it is difficult to control the amount of milk that the pups ingested it cannot be discarded that this could have affected the resolution of the induced gastroenteritis. For that, to avoid the influence of the mother on the health of the offspring, different litters were used and all of them showed a better response to the infection with respect to the control animals.
Maternal synbiotic supplementation affected hematological variables, revealing higher total leucocyte counts in SYN pups. This increase was associated with elevated total lymphocytes and granulocytes during the RV infection. It is well known that viral infections typically induce lymphocytosis[ 36 ] and granulocytosis.[ 37 ] Thus, the observed increase is probably due to a higher mobilization that may be linked to a better resolution of the process in the SYN group.
During RV infection, innate and adaptive cells work together against the virus.[ 38 ] While plasma Ig composition remained relatively stable, NMDS analysis suggested potential differences in global Ig profiles between groups. However, the increase in IgG2c, which corresponds to IgG3c in mice, suggests an enhanced long‐term immunity and regulatory responses in neonatal intestine.[ 39 , 40 ] At the mucosa, sIgA offers protection by recognizing viral particles,[ 41 ] while mucosal IgM aids the initial humoral response and tissue homeostasis.[ 42 ] Our data revealed a potential effect to increase IgM levels without modifying the sIgA concentration, which is agreement with a proper initial response against the pathogen.
Although viral infections trigger humoral immune responses by producing specific Ab,[ 43 ] the synbiotic did not modify the specific anti‐RV Ab levels in the offspring. Moreover, maternal synbiotic supplementation did not induce either an increase in specific anti‐RV Ab levels in maternal plasma or milk, thus other mechanisms might be involved in the observed protective effects, such as changes in the BM composition. Specifically, our results indicate that synbiotic maternal supplementation increased total IgA levels in milk during the peak of the RV infection which could be the reason for the better response against the RV in the SYN group. Moreover, BM microbiota composition of the mothers at the weaning day was analyzed before[ 44 ] and showed a different profile. These changes in microbiota composition could also lead to the differences observed in the pup's microbiota composition or their response against the RV.
RV targets intestinal enterocytes,[ 9 ] inhibiting host immune responses[ 45 ] and modulating gene expression for viral replication.[ 46 ] Maternal synbiotic supplementation upregulated pup's intestinal Tlr2, Tlr7, Ocln, Muc2, and Muc3 expression. RV infections have been linked to TLR and mucin changes[ 47 , 48 ] and TJ disruption,[ 49 ] potentially reducing the mucus and tissue integrity. Probiotics improve the intestinal barrier by modulating TLR and TJ protein expression and mucin secretion. Thus, the overexpression of TLR, mucins, and TJ proteins in the SYN group indicates that maternal supplementation enhances the infant intestinal epithelial barrier function, contributing to viral defence.[ 50 ]
Furthermore, RV infection alters the small intestine architecture, reducing villi height.[ 51 ] Here, maternal synbiotic supplementation induced a trophic effect on small intestine, increasing villi height and area which may enhance nutrient and water absorption essential for a healthy maturation and for better fighting infections.[ 52 ]
At the peak of the infection, independently of the maternal intervention, Enterobacteriaceae family dominated in both groups, although a depletion in Enterococcaceae family proportion was observed in the SYN group. Additionally, the proportions of Escherichia/Shigella were higher in the SYN group while those of Enteroccocus and Enterobacter genera were lower. RV infection has been linked to an increase or a reduction in the Escherichia‐Shigella abundance.[ 53 ] Here, the maternal synbiotic supplementation was not able to counteract the RV‐induced effect. However, the reduction of the Enterococcus and Enterobacter was previously linked to other synbiotics.[54] Moreover, maternal synbiotic supplementation promoted the growth of Ligilactobacillus, which known for its antimicrobial activity.[ 55 ] Altogether, maternal synbiotic supplementation modulated the microbiota composition in early life, specifically herein contributing to reduce the RV incidence and severity.
Overall, this study shows that supplementation with B. breve M‐16 V and scGOS/lcFOS to dams during gestation and lactation improves the newborn's immune response and mitigates RV infection.
4. Experimental Section
Animals
Seven‐week‐old Lewis rats (16 females and 8 males) were obtained from Janvier Labs (La Plaine Saint Denis Cedex, France). After 1 week of acclimatization, the females were placed into the males' cages for 1 week, and then, females were separated again into individual cages. From the mating day, the female rats were divided into two experimental groups (reference [REF] and synbiotic [SYN]) and received the synbiotic supplementation (or vehicle) during gestation (21 days) and lactation (21 days). Additionally, since weaning, pups were supplemented for 1 extra week (day 28). The animals were given access to a commercial diet that corresponded to the American Institute of Nutrition 93G formulation[ 13 ] and water ad libitum. The rats were allowed to deliver naturally, and the day of birth was considered as day 1 for the pups. All litters were culled up to 10 pups per lactating dam. For that, on the one hand, pups from litters exceeding 10 were removed; and, on the other hand, litters with less than 10 pups received the necessary extra pups born the same day from mothers following the same intervention. The pups had free access to the nipples and rat diet throughout the study.
The animal room conditions, including temperature and humidity, were carefully controlled in a 12 h light–12 h dark cycle within a negative pressure chamber at the Animal Facility of the Diagonal Campus of the University of Barcelona (UB). Approval for all experimental procedures was obtained from the Ethics Committee for Animal Experimentation (CEEA) of the UB (Ref. 240/19) and from the Catalan Government (Ref.10933).
Experimental Design
Female rats were randomly assigned into two groups: REF (n = 8) or SYN (n = 8) distributed in three different cohorts with matching number of litters per treatment (REF and SYN) in each one (3, 3, 2 for first, second, and third cohorts, respectively). Nutritional intervention lasted from the first day of the gestation (G1) until the end of the lactation (L21). The SYN dams were orally administered once a day with 1 mL of the synbiotic containing 109 colony forming units (UFC) mL−1 of B. breve M‐16 V and scGOS/lcFOS during gestation and 1.5 mL during lactation. The REF dams received the matching volume of saline solution in the same conditions.
On day 5 of life, pups were inoculated with a RV strain (simian SA‐11) at 4 × 108 of 50% of the tissue culture infectious dose (TCID50)/rat. The SA‐11 provided by Enteric Virus Group (UB) was inoculated as previously described.[ 14 ] Animal body weight was monitored daily, and associated growth parameters such as the body mass index (BMI) and the Lee Index were also obtained on sampling days. A representative number of pups (four pups per litter) were euthanized on day 8 to evaluate the impact of maternal nutritional intervention during the RV infection. Additionally, the anti‐RV immunoglobulin (Ig) response was also studied in pups’ plasma at day 21 and day 28 (three pups per litter at each time), and also in dams’ plasma and milk at day 21. The milk extraction was performed as previously described.[ 15 ] The stomach content of day 8 was stored at −80 °C until use. On day 21, the rest of the pups of each litter (three pups) were directly supplemented with 0.2 mL of the synbiotic for 1 week (until day 28 of life).
Synbiotic Preparation
Daily administration of the synbiotic or vehicle was performed during the gestation and lactation periods in the same time frame each day. The synbiotic solution was prepared daily by mixing B. breve M‐16 V (109 CFU) with scGOS/lcFOS in physiological saline solution. The dose of scGOS/lcFOS (ratio 9:1) was 2% of an established daily food intake of 40 g. One mL of the synbiotic (109 CFU per rat per day) or saline solution was intra‐gastrically administered through an oral gavage during pregnancy, and after birth the volume was increased to 1.5 mL. For the pups—from day 21 of life until day 28 of life—the dose was fixed at 2 × 107 CFU per rat per day. All supplements were kindly provided by Danone Research & Innovation (Utrecht, The Netherlands). The control group received the same volume of saline.
Sample Collection
On day 8 of life, pups were anesthetized with ketamine (90 mg kg−1) and xylazine (10 mg kg−1; Bayer A.G., Leverkusen, Germany) and after euthanasia by diaphragm disruption and abdominal and thoracic cavity opening, blood, intestinal samples, and cecal content (CC) were collected and immediately processed or stored at −20 °C or −80 °C for future analysis. The weight of different organs was measured.
Blood samples were immediately analyzed using an automated hematologic analyzer (Spincell, MonLab Laboratories, Barcelona, Spain). Blood was also centrifuged (10 000 × g, 10 min, 4 °C) to obtain plasma for total Ig and anti‐RV Ig quantification.
SI samples were collected for gene expression analysis and Ig quantification. One cm of a central portion of the SI, corresponding to the last part of the jejunum, was conserved in RNAlater and frozen at −20 °C until PCR analysis. To obtain gut wash (GW), the remaining parts of the intestine were opened lengthwise, cut into 5 mm pieces, incubated with 2 mL of Phosphate Buffered Saline (PBS), and centrifuged.
Digested milk from the pups’ stomach was obtained and homogenized with PBS for Ig quantification. Cecal content was used for microbiota profiling.
Clinical Assessment
From the day prior to infection (day 4), until once the viral infection was solved (day 13), the RV‐induced diarrhea was monitored. Fecal samples were obtained by gently massaging the abdomen, then were weighted and frozen at −20 °C for further analysis. The severity of diarrhea was assessed by analyzing fecal weight and a scoring system ranging from 1 to 4 (diarrhea index [DI]). The scoring system was based on the color, texture, and the amount of fecal material obtained. Scores of 1 indicated normal feces and scores of 4 indicated a high amount of watery feces. Scores of 2 or higher indicated the presence of diarrhea, whereas scores below 2 indicated the absence of diarrhea.[ 14 ] Furthermore, other parameters associated to the diarrhea were calculated. The area under the curve of severity (S‐AUC), the incidence of diarrhea was expressed as the percentage of diarrheic feces (%DF), and the percentage of diarrheic animals (%DA) in each group. The AUC of the incidence (I‐AUC) of diarrhea during the whole period was measured as global values of incidence. The maximum incidence and severity were also calculated, which represent the highest values during the diarrhea period. The days when maximum incidence and maximum severity were achieved were also analyzed. Additionally, the interval between the beginning day of diarrhea and the final day of diarrhea was measured to calculate the diarrhea period for each animal, and finally the number of days with diarrhea within the diarrhea period was calculated (days with diarrhea).
Fecal SA‐11 Shedding
On day 6 of life, 1‐day post‐infection (DPI), the collected fecal samples were homogenized and centrifuged and the SA‐11 particles quantification was performed by ELISA.[ 16 ] For the standard curve, titrated dilutions of inactivated SA‐11 particles (from 106 to 104 per well) were used.
Specific Humoral Response and Immunoglobulin Quantification
Plasma, milk, and digested milk from stomach content of day 8 of life were used to quantify the total anti‐RV Ig (IgM, IgA, and IgG) by ELISA technique. The Ig assessment was performed as previously described.[ 17 ] Plasma samples were analyzed for IgA, IgM, IgG, and IgG isotypes (IgG1, IgG2a, IgG2b, IgG2c) using ProcartaPlex Multiplex immunoassay[ 18 ] at the Cytometry Service of the Scientific and Technological Centers of the University of Barcelona (CCiT‐UB). Th1 and Th2 responses were evaluated by adding the relative proportions of IgG subtypes, IgG2b + IgG2c for Th1 and IgG1 + IgG2a for Th2 associated response.
Secretory (s)IgA and IgM were quantified in digested milk and GW of day 8 pups. The quantification of both Igs was performed using the protocol previously described.[ 19 ]
Small Intestine Gene Expression
RNA extraction from SI samples frozen in RNAlater was performed in a FastPrep‐24 instrument (MP biomedicals, Illkirch, France) and the RNeasy Mini Kit (Qiagen, Madrid, Spain). cDNA was obtained using TaqMan Reverse Transcription Reagents (Applied Biosystems, AB, Weiterstadt, Germany). Real Time (RT)—PCR was performed using the ABI Prism 7900 HT quantitative RT‐PCR system (AB).
The specific TaqMan primers AB used and the housekeeping gene Gusb (β‐glucuronidase) were specified in the Table S1, Supporting Information. Data were analyzed using the −2ΔΔCt method.[ 20 ] The data were presented as the percentage of expression in each experimental group normalized to the mean value obtained for the REF group, which was set at 100%.
The identification of B. breve M 16‐V was conducted in the feces on day 10 and 11 and in CC on day 21 of life.[ 21 ] The Taq‐Man‐based forward, reverse, and probe sequences were designed by Phavichitr et al.[ 22 ]
Small Intestine Histology
The central section of the SI was fixed in 4% formalin for 24 h, then rinsed with PBS, dehydrated in a graded series of ethanol and xylol, and at the end embedded in melted paraffin (Merck, Madrid, Spain). Hematoxylin‐eosin (HE) staining was performed on 5 µm‐thick paraffin sections. Representative photos were taken at 100× in an Olympus BX41 microscope. Villi height, width, and area were measured with the Image J software (Image Processing and Analysis in Java, Bethesda, MD, USA).[ 23 ]
Cecal Microbiota Profiling
Total DNA was isolated from CC samples using an automated assisted method based on magnetic beads (Maxwell RSC Instrument coupled with Maxwell RSC Pure Food GMO and authentication kit, Promega, Spain), lysozyme (20 mg mL−1), and mutanolysin (5 U mL−1) for 60 min at 37 °C and a preliminary step of cell disruption with 3 µm diameter glass beads during 1 min at 6 m s−1 by a bead beater FastPrep 24–5 G Homogenizer (MP Biomedicals). DNA was purified using the DNA Purification Kit (Macherey‐Nagel, Duren, Germany) and the final DNA concentration was measured using Qubit 2.0 Fluorometer (Life Technology, Carlsbad, CA, USA). Microbial profiling was assessed by amplicon V3–V4 variable region of the 16S rRNA gene. Libraries were prepared following the 16S rDNA gene Metagenomic Sequencing Library Preparation Illumina protocol (Cod. 15044223 Rev. A). The libraries were then sequenced using 2× 300 bp paired‐end run on a MiSeq‐Illumina platform (FISABIO sequencing service, Valencia, Spain). Negative and positive mock (Zymobiomics) communities were also included. Bioinformatic processing and analysis were performed as detailed in Figure S1, Supporting Information.
Statistical Analysis
SPSS Statistics 22.0 software (SPSS Inc., Chicago, IL, USA) was employed for statistical analysis. Normality and homogeneity of variance were assessed with Shapiro‐Wilk and Levene tests, respectively. Data meeting these underwent one‐way ANOVA, while non‐normally distributed and unequal data underwent Kruskal–Wallis (p < 0.05). Spearman correlation coefficients were calculated to explore variable associations. Non‐metric multidimensional scaling (NMDS) in Rstudio with the “vegan” package[ 24 ] uncovered sample similarities based on immune factor composition, and “envfit” function was applied to evaluate factors' associations (p < 0.05).
Conflict of Interest
The authors declare no conflict of interest.
Author Contributions
M.J.R.‐L., M.C.C. and F.J.P.‐C.; formal analysis and investigation, L.S.‐F., K.R‐A, M.M‐C., M.C., M.J.R.‐L., F.J.P.‐C.; writing‐original draft, L.S.‐F.; funding acquisition, M.C.C and F.J.P.‐C. All authors have contributed to the manuscript revision and agreed to the published version of the manuscript. M.C.C and F.J.P.‐C share senior authorship.
Supporting information
Supporting information
Acknowledgements
The research described in this paper was supported by LaMarató‐TV3 (DIM‐2‐ELI, ref. 2018–27/30‐31). The authors would like to express their gratitude to Paula Cabré for her assistance. The authors are grateful to Danone Research & Innovation for providing the synbiotic mix. INSA‐UB is a Maria de Maeztu Unit of Excellence (Grant CEX2021‐001234‐M) and IATA‐CSIC a Severo Ochoa Excellence Center (Grant CEX2021‐001189‐S) funded by MICIN/AEI/FEDER, UE.
Sáez‐Fuertes L., Rio‐Aige K., Massot‐Cladera M., Castell M., Knipping K., Garssen J., Bourdet‐Sicard R., Rodríguez‐Lagunas M. J., Collado M. C., Pérez‐Cano F. J., Bifidobacterium breve M‐16 V and scGOS/lcFOS Supplementation to Dams Ameliorates Infant Rotavirus Infection in Early Life. Mol. Nutr. Food Res. 2024, 68, 2400377. 10.1002/mnfr.202400377
Data Availability Statement
Data available on request from the authors
References
- 1. Ramakrishnan U., Grant F., Goldenberg T., Zongrone A., Martorell R., Paediatr. Perinat. Epidemiol. 2012, 26, 285. [DOI] [PubMed] [Google Scholar]
- 2. Erlebacher A., Annu. Rev. Immunol. 2013, 31, 387. [DOI] [PubMed] [Google Scholar]
- 3. Koletzko B., Godfrey K. M., Poston L., Szajewska H., Van Goudoever J. B., De Waard M., Brands B., Grivell R. M., Deussen A. R., Dodd J. M., Patro‐Golab B., Zalewski B. M., Ann. Nutr. Metab. 2019, 74, 93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Gibson G. R., Hutkins R., Sanders M. E., Prescott S. L., Reimer R. A., Salminen S. J., Scott K., Stanton C., Swanson K. S., Cani P. D., Verbeke K., Reid G., Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 491. [DOI] [PubMed] [Google Scholar]
- 5. Hill C., Guarner F., Reid G., Gibson G. R., Merenstein D. J., Pot B., Morelli L., Canani R. B., Flint H. J., Salminen S., Calder P. C., Sanders M. E., Nat. Rev. Gastroenterol. Hepatol. 2014, 11, 506. [DOI] [PubMed] [Google Scholar]
- 6. Swanson K. S., Gibson G. R., Hutkins R., Reimer R. A., Reid G., Verbeke K., Scott K. P., Holscher H. D., Azad M. B., Delzenne N. M., Sanders M. E., Nat. Rev. Gastroenterol. Hepatol. 2020, 17, 687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Săsăran M. O., Mărginean C. O., Adumitrăchioaiei H., Meliț L. E., Nutrients 2023, 15, 643. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Crawford S. E., Ramani S., Tate J. E., Parashar U. D., Svensson L., Hagbom M., Franco M. A., Greenberg H. B., O'Ryan M., Kang G., Desselberger U., Estes M. K., Nat. Rev. Dis. Primers 2017, 3, 17083. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Amimo J. O., Raev S. A., Chepngeno J., Mainga A. O., Guo Y., Saif L., Vlasova A. N., Front. Immunol. 2021, 12, 793841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Esona M. D., Gautam R., Clin. Lab. Med. 2015, 35, 363. [DOI] [PubMed] [Google Scholar]
- 11. Burnett E., Parashar U. D., Tate J. E., J. Infect. Dis. 2020, 222, 1731. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Rigo‐Adrover M., Saldaña‐Ruíz S., van Limpt K., Knipping K., Garssen J., Knol J., Franch A., Castell M., Pérez‐Cano F. J., Eur. J. Nutr. 2017, 56, 1657. [DOI] [PubMed] [Google Scholar]
- 13. Reeves P. G., Nielsen F. H., Fahey G. C., J. Nutr. 1993, 123, 1939. [DOI] [PubMed] [Google Scholar]
- 14. Pérez‐Cano F. J., Castell M., Castellote C., Franch À., Pediatr. Res. 2007, 62, 658. [DOI] [PubMed] [Google Scholar]
- 15. Azagra‐Boronat I., Tres A., Massot‐Cladera M., Franch À., Castell M., Guardiola F., Pérez‐Cano F. J., Rodríguez‐Lagunas M. J., J. Dairy Sci. 2020, 103, 2982. [DOI] [PubMed] [Google Scholar]
- 16. Rigo‐Adrover M., Pérez‐Berezo T., Ramos‐Romero S., Van Limpt K., Knipping K., Garssen J., Knol J., Franch À., Castell M., Pérez‐Cano F. J., Br. J. Nutr. 2017, 117, 209. [DOI] [PubMed] [Google Scholar]
- 17. Azagra‐Boronat I., Massot‐Cladera M., Knipping K., Garssen J., Ben Amor K., Knol J., Franch À., Castell M., Rodríguez‐Lagunas M. J., Pérez‐Cano F. J., Nutrients 2020, 12, 498. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Ruiz‐Iglesias P., Massot‐Cladera M., Rodríguez‐Lagunas M. J., Franch À., Camps‐Bossacoma M., Castell M., Pérez‐Cano F. J., Front. Nutr. 2022, 9, 861533. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Massot‐Cladera M., Franch À., Castellote C., Castell M., Pérez‐Cano F. J., Nutrients 2013, 5, 3272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Pérez‐Cano F. J., Ramírez‐Santana C., Molero‐Luís M., Castell M., Rivero M., Castellote C., Franch À., J. Lipid Res. 2009, 50, 467. [DOI] [PubMed] [Google Scholar]
- 21. Gil‐Campos M., López M. Á., Rodriguez‐Benítez M. V., Romero J., Roncero I., Linares M. D., Maldonado J., López‐Huertas E., Berwind R., Ritzenthaler K. L., Navas V., Sierra C., Sempere L., Geerlings A., Maldonado‐Lobón J. A., Valero A. D., Lara‐Villoslada F., Olivares M., Pharmacol. Res. 2012, 65, 231. [DOI] [PubMed] [Google Scholar]
- 22. Phavichitr N., Wang S., Chomto S., Tantibhaedhyangkul R., Kakourou A., Intarakhao S., Jongpiputvanich S., Wongteerasut A., Ben‐Amor K., Martin R., Ting S., Suteerojntrakool O., Visuthranukul C., Piriyanon P., Roeselers G., Knol J., Sci. Rep. 2021, 11, 3534. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Azagra‐Boronat I., Massot‐Cladera M., Knipping K., Van't Land B., Stahl B., Garssen J., José Rodríguez‐Lagunas M., Franch À., Castell M., Pérez‐Cano F. J., Front. Cell Infect. Microbiol. 2018, 8, 372. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Dixon P., J. Vegetation Sci. 2003, 14, 927. [Google Scholar]
- 25. Krawczyk A., Lewis M. G., Venkatesh B. T., Nair S. N., Indian J. Pediatr. 2016, 83, 220. [DOI] [PubMed] [Google Scholar]
- 26. Martin C. R., Ling P. R., Blackburn G. L., Nutrients 2016, 8, 279.27187450 [Google Scholar]
- 27. Malek L., Netting M., Makrides M., World Rev. Nutr. Diet 2022, 124, 189. [DOI] [PubMed] [Google Scholar]
- 28. Ares Segura S., Arena Ansótegui J., Marta Díaz‐Gómez N., An Pediatr (Barc). 2016, 84, 347.e1. [DOI] [PubMed] [Google Scholar]
- 29. Rio‐Aige K., Azagra‐Boronat I., Castell M., Selma‐Royo M., Collado M. C., Rodríguez‐Lagunas M. J., Pérez‐Cano F. J., Nutrients 2021, 13, 1810. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Seppo A. E., Kukkonen A. K., Kuitunen M., Savilahti E., Yonemitsu C., Bode L., Järvinen K. M., JAMA Pediatr. 2019, 173, 286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Wang S., Ryan C. A., Boyaval P., Dempsey E. M., Ross R. P., Stanton C., Trends Microbiol. 2020, 28, 28. [DOI] [PubMed] [Google Scholar]
- 32. Massot‐Cladera M., Del Mar Rigo‐Adrover M., Herrero L., Franch À., Castell M., Vulevic J., Pérez‐Cano F. J., Lagunas M. J. R., Cells 2022, 11, 1669. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Szajewska H., Canani R. B., Guarino A., Hojsak I., Indrio F., Kolacek S., Orel R., Shamir R., Vandenplas Y., Van Goudoever J. B., Weizman Z., J. Pediatr. Gastroenterol. Nutr. 2016, 62, 495. [DOI] [PubMed] [Google Scholar]
- 34. Li M., Monaco M. H., Wang M., Comstock S. S., Kuhlenschmidt T. B., Fahey G. C., Miller M. J., Kuhlenschmidt M. S., Donovan S. M., ISME J. 2014, 8, 1609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Gonzalez‐Ochoa G., Flores‐Mendoza L. K., Icedo‐Garcia R., Gomez‐Flores R., Tamez‐Guerra P., Arch. Microbiol. 2017, 199, 953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Pereira I., George T. I., Arber D. A., Atlas of Peripheral Blood: the Primary Diagnostic Tool 2011, p. 194.
- 37. Flores‐Torres A. S., Salinas‐Carmona M. C., Salinas E., Rosas‐Taraco A. G., Viral Immunol. 2019, 32, 198. [DOI] [PubMed] [Google Scholar]
- 38. Hakim M. S., Ding S., Chen S., Yin Y., Su J., van der Woude C. J., Fuhler G. M., Peppelenbosch M. P., Pan Q., Wang W., Virus Res. 2018, 253, 28. [DOI] [PubMed] [Google Scholar]
- 39. Weström B., Arévalo Sureda E., Pierzynowska K., Pierzynowski S. G., Pérez‐Cano F. J., Front. Immunol. 2020, 11, 1153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Harmer N. J., Chahwan R., Virulence 2016, 7, 623. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Blutt S. E., Miller A. D., Salmon S. L., Metzger D. W., Conner M. E., Mucosal Immunol. 2012, 5, 712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Chen K., Magri G., Grasset E. K., Cerutti A., Nat. Rev. Immunol. 2020, 20, 427. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Netea M. G., Schlitzer A., Placek K., Joosten L. A. B., Schultze J. L., Cell Host Microbe 2019, 25, 13. [DOI] [PubMed] [Google Scholar]
- 44. Sáez‐Fuertes L., Kapravelou G., Grases‐Pintó B., Massot‐Cladera M., Bernabeu M., Knipping K., Garssen J., Bourdet‐Sicard R., Castell M., Rodríguez‐Lagunas M. J., Collado M. C., Pérez‐Cano F. J., Front. Immunol. 2024, 15, 1418594. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Ding S., Zhu S., Ren L., Feng N., Song Y., Ge X., Li B., Flavell R. A., Greenberg H. B., Elife 2018, 7, e39494. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Sáez‐Fuertes L., Azagra‐Boronat I., Massot‐Cladera M., Knipping K., Garssen J., Franch À., Castell M., Pérez‐Cano F. J., Rodríguez‐Lagunas M. J., Nutrients 2023, 15, 1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Boshuizen J. A., Reimerink J. H. J., Korteland‐Van Male A. M., Van Ham V. J. J., Bouma J., Gerwig G. J., Koopmans M. P. G., Büller H. A., Dekker J., Einerhand A. W. C., Virology 2005, 337, 210. [DOI] [PubMed] [Google Scholar]
- 48. Ge Y., Mansell A., Ussher J. E., Brooks A. E. S., Manning K., Wang C. J. H., Taylor J. A., J. Virol. 2013, 87, 11160. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Tugizov S., Tissue Barriers 2021, 9, 1943274. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Zhang Y., Zhu X., Yu X., Novák P., Gui Q., Yin K., Front. Nutr. 2023, 10, 1120168. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Salim A. F., Phillips A. D., Walker‐Smith J. A., Farthing M. J. G., Gut 1995, 36, 231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Kai Y., Biophys. J. 2021, 120, 699. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Kim S. H., Choi Y., Miguel M. A., Lee S. J., Lee S. S., Lee S. S., Vet. Sci. 2023, 10, 496.37624283 [Google Scholar]
- 54. Ślizewska K., Chlebicz A., FEMS Microbiol. Lett. 2019, 366, fnz157. [DOI] [PubMed] [Google Scholar]
- 55. Mu Y., Zhang C., Jin C. Z., Li T., Jin F. J., Lee H. G., Jin L., LWT 2024, 193, 115765. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting information
Data Availability Statement
Data available on request from the authors
