Journal of Animal Science, 2022, 100, 1–19 https://doi.org/10.1093/jas/skac163 Advance access publication 4 May 2022 Non Ruminant Nutrition Potential effect of two Bacillus probiotic strains on performance and fecal microbiota of breeding sows and their piglets Mireia Saladrigas-García,†, David Solà-Oriol,†, Sergi López-Vergé,†, Matilde D’Angelo,† Maria Carmen Collado,‡ Bea Nielsen,|| Martin Faldyna,$ José Francisco Pérez,†, and Susana M. Martín-Orúe†,1 † Department of Animal and Food Sciences, Animal Nutrition and Welfare Service, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain ‡ Department of Biotechnology, Institute of Agrochemistry and Food Technology–National Research Council (IATA-CSIC), Valencia 49860, Spain || Chr.Hansen A/S, Hoersholm 2970, Denmark $ Veterinary Research Institute, Brno 62132, Czech Republic Corresponding author: susana.martin@uab.cat 1 Abstract The effect of long-term administration of two Bacillus strains was tested on 98 breeding sows and their litters allotted into three treatments: a control group (CON); supplemented with 5 × 108 cfu/kg B. subtilis − 541 (BSU); or with 5 × 108 cfu/kg B. amyloliquefaciens − 516 (BAM). Reproductive and performance variables were recorded over three cycles with 56 dams remaining through the third lactation. Blood and fecal samples were taken longitudinally from 12 sows per treatment on days 8 and 21 of the third lactation and milk samples were taken on day 21. Feces from one piglet per litter was sampled on days 21 and 33 and jejunal gene expression was assessed in two piglets on day 21. Changes in fecal microbiota were assessed by 16S rRNA gene sequencing (Illumina MiSeq) and gene expression by Open-Array technology. Metabolomic responses were analyzed in milk by NMR and Ig-G and Ig-A specific antibodies were determined by ELISA. No significant differences were observed on feed intake, body weight, or fat mobilization of the sows. However, a significant increase in the total number of piglets born was observed in supplemented sows. Although the increase was seen from the first cycle with BAM, improvements were not seen with BSU until the third cycle. BAM also increased the number of born-alive and weaned piglets. NMR analysis showed an impact of BAM on milk composition. No differences were found in milk or blood immunoglobulins. A different structure of the fecal microbiota was found in supplemented sows, with changes across phylum, family, and genus. These changes were greater at day 8, suggesting a relevant role of probiotics establishing a new intestinal balance after labor. Shifts in the microbiota were also seen in the piglets, with a clearer impact post-weaning than in suckling. In this regard, correlations between microbial groups of sows and piglets showed a higher link with weaned (d33) than with suckling pigs (d21), reinforcing the idea of an early maternal carry-over. No changes due to treatment in jejunal gene expression were detected; however, piglet size had a clear impact on different genes. In summary, the addition of both probiotics, and particularly Bacillus amyloliquefaciens, demonstrated potential benefits on the prolificacy of sows. Daily feeding of Bacillus amyloliquefaciens resulted in an increase in the number of weaned piglets. The high correlations between the compositions of the microbiota of sows and their piglets are evidence of maternal imprinting, with effects lasting beyond weaning. Lay Summary The aim of the present study was to determine if the inclusion of probiotic microorganisms in the mother’s diet during gestation and the lactation period is capable of modifying the performance of mothers and piglets and the possible effect on the intestinal health of piglets after separation from the mother. For this, 98 females were distributed in three experimental treatments: a control diet, or the same diet in which one of two probiotic strains to be tested (Bacillus subtilis or Bacillus amyloliquefaciens) were incorporated. The experimental diets were administered during pregnancy and the lactation phase for three consecutive productive cycles. Among the most striking results, it is worth highlighting the impact of probiotic treatments on the reproductive performance of sows. Both supplemented groups showed a higher number of total piglets per sow. Furthermore, sows that received the Bacillus amyloliquefaciens diet showed a significant increase in the number of live-born piglets. Probiotic supplementation also showed effects on the fecal microbiota composition of the mothers and their piglets. Changes in the composition of sow milk were also observed. In summary, results demonstrated the potential benefits of supplementing probiotics, and particularly a strain of Bacillus amyloliquefaciens, to improve prolificacy, modulate the intestinal microbial composition, and improve the performance of piglets during lactation. Key words: Bacillus subtilis, Bacillus amyloliquefaciens, microbiota, piglet, probiotic, sow Abbreviations: ADFI, average daily feed intake; ADG, average daily gain; ANOSIM, analysis of similarities; ASV, amplicon sequence variant; BW, body weight; cDNA, complementary deoxyribonucleic acid; CLDN15, claudin-15; CFU, colony-forming unit; CSS, cumulative sum scaling; DADA2, divisive amplicon denoising algorithm 2; DNA, deoxyribonucleic acid; EFSA, European Food Safety Authority; ELISA, enzyme-linked immunosorbent assay; ETEC, enterotoxigenic Escherichia coli; HSP27, heat shock protein 27; HSPB1, heat shock protein family B member 1; HTS, high-throughput sequencing; IgA, immunoglobulin A; IgG, immunoglobulin G; IGF1R, insulin-like growth factor 1 receptor; IUGR, intrauterine growth restricted; LBW, low birth weight; LPS, lipopolysaccharide; NMDS, non-metric multidimensional scaling; NMR, nuclear magnetic resonance; NRC, National Research Council; PCR, polymerase chain reaction; PERMANOVA, Received January 13, 2022 Accepted April 29, 2022. © The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com 2 Journal of Animal Science, 2022, Vol. 100, No. 6 permutational analysis of variance; PLS-DA, partial least-squares discriminant analysis; PRRS, porcine reproductive and respiratory syndrome; RNA, ribonucleic acid; rRNA, ribosomal ribonucleic acid; RT-PCR, quantitative reverse transcription polymerase chain reaction; SCFA, short-chain fatty acids; TSP, sodium-3ʹ- trimethylsilylpropionate-2,2,3,3-d4; UPGMA, unweighted pair-wise grouping method with hierarchical arithmetic mean grouping; VIP, variable importance in projection; ZnO, zinc oxide Introduction performance of sows and their litters. The impact of supple- Current intensive production systems have the constant chal- mentation on the fecal microbiota of sows and piglets, the lenge of achieving high rates of reproductive success from composition of milk during lactation, maternal transfer of their sows. The use of probiotics has emerged as a promising passive immunity, and jejunal gene expression of the piglets strategy to improve the reproductive performance of sows by were assessed. increasing feed consumption along with lactation, reducing fat mobilization, promoting milk production, and increasing Materials and Methods litter weight (Alexopoulos et al., 2004; Böhmer et al., 2006; Kritas et al., 2015; Hayakawa et al., 2016; Zhang et al., The present study was conducted according to EFSA admin- 2020). Moreover, several studies have also shown that when istrative/technical guidance, and Commission Regulation probiotics are administered to sows, positive effects can be (EC) No. 429/2008 on detailed rules for the implementa- also seen in the performance of piglets, with increases in rates tion of Regulation (EC) No. 1831/2003 of the European of growth (Kritas et al., 2015; Betancur et al., 2021; Crespo- Parliament and of the Council as regards the preparation and Piazuelo et al., 2021) and reduction in the clinical signs of the presentation of applications and the assessment and the post-weaning diarrhea (Alexopoulos et al., 2004; Taras et al., authorization of feed additives. Procedures, documentation, 2005; Taras et al., 2006; Betancur et al., 2021). Although the equipment, and records were examined in order to assure mechanisms of action have not yet been fully elucidated, these that the study was performed following the regulations speci- benefits could have been derived from a beneficial modulation fied herein and with the protocol and relevant standard oper- of the intestinal microbiota of nursing piglets by their moth- ating procedures. ers. In fact, probiotics have been demonstrated to be trans- Moreover, the housing, management, husbandry, and ferred from the mother to the piglet through contact with slaughtering conditions of the animals used in the present maternal feces (Jadamus et al., 2001; Kenny et al., 2011). study conformed to the European Union Guidelines (Directive Moreover, modulation of the maternal microbiota with pro- 2010/63/EU), and all experimental procedures were approved biotics could also have an impact on the intestinal health beforehand by the Animal and Human Experimental Ethical of their piglets (Baker et al., 2013; Davis et al., 2020; Lan Committee of Universitat Autònoma de Barcelona (permit and Kim, 2020). The initial development of the microbiota no. CEEAH 3817). of piglets is fundamentally dependent on their intimate con- tact with their sow (Konstantinov et al., 2006; Thompson et Animals and housing al., 2008; Mach et al., 2015), and this process plays a crucial The present study was carried out on a commercial pig farm role in the development of the neonatal immune system with with an average herd size of 1150 sows in the province of implications throughout the life of the piglets (Hansen et al., Lleida, Spain. A total of 98 Danbred (Landrace x Yorkshire) 2012; Everaert et al., 2017; Ferret-Bernard and Le Huërou- hyperprolific sows started the first cycle and were fed the Luron, 2019; Jiang et al., 2019). experimental diets during three complete reproductive cycles. Bacillus sp. strains have been largely studied as probi- The sows were allocated to three treatments in such a way that otic candidates to be supplemented in pigs. Previous works sows in all groups were similar in terms of parity (2.8 ± 0.14) of Larsen et al. (2014) did an exhaustive screening between and dam body weight (211.8 ± 1.10 kg). 245 Bacillus sp. isolates looking for potential probiotics to Breeding dams were allocated to individual crates in the be used as feed additives in pig feed. Some of these selected service barn where they were inseminated, and pregnancy strains, particularly Bacillus amyloliquefaciens, were shown was confirmed at approximately 30–35 d of gestation. to improve apparent ileal digestibility of amino acids and Pregnant sows were then moved to the gestation barn, where gross energy in growing pigs (Blavi et al., 2019). Moreover, they were group-housed (pens of 10 dams/pen) until approx- strains of Bacillus subtilis were also demonstrated to enhanced imately 110 d gestation when dams were moved to indi- growth rate and improve gut barrier function of weaned pigs vidual farrowing crates in farrowing rooms (5 rooms of 10 experimentally infected with pathogenic E. coli (He et al., pens). Within 24 h after farrowing, all stillborn, dead, splay- 2020), also influencing their mucosal transcriptomic profile legged, and moribund piglets were removed from the study, (Luise et al., 2019). This inhibitory effect, against pathogens leaving only healthy piglets suckling the sow. Cross-fostering like E. coli, could be explained by the production of antimi- to equalize litter size was carried out within 24–48 h after crobial peptides and an increased mucin production of goblet farrowing and further movements were accepted if required cells (Bravo-Santano et al., 2020). due to the common farm management, but only within the Although the potential benefits of supplementing the same treatment groups. After piglets were weaned, dams diets of sows with Bacillus sp. probiotics are well doc- were kept in individual crates until estrus. Each farrowing umented in the literature, the relevance of commercial pen had a farrowing crate on a partially slatted floor with a husbandry conditions and long-term administration of heated floor pad for piglets. Water was provided ad libitum probiotics are unreported. from nipple drinkers. Each unit was lit by daylight (via win- Therefore, the present study aimed to evaluate the effect of dows) and artificial light (non-programmable). Ventilation supplying 5 × 108 cfu/kg feed of viable spores of two Bacillus was via single, variable-speed fans linked to temperature sen- probiotic strains (Bacillus subtilis—541 and Bacillus amy- sors. The temperature inside the buildings was automatically loliquefaciens—516) during three consecutive cycles, on the controlled. Saladrigas-García et al. 3 Diets and experimental treatments in separate silos. Basal gestation feeds were delivered daily by Sows were fed standard gestation and lactation feeds. All automatic feeders. Lactation feeds were delivered manually nutrients were supplied at normal concentrations, not from bulk silos using barrows with scales (three different bar- exceeding EU maximum permitted content of trace minerals rows for CON, BSU, and BAM). or vitamins. Diets were calculated to be iso-nutritive, meet- Piglet creep feed was mixed into mash as a single lot then ing NRC nutrient requirements recommended for sows and split into three aliquots (CON, BSU, and BAM). Bacillus sub- suckling piglets (NRC, 2012). Sow and piglet feed formu- tilis and Bacillus amyloliquefaciens base premix (minimum lae and calculated analyses are presented in Supplementary guaranteed of 1.25 × 109 CFU/g) was added to approximately Tables S1 and S2. 50 kg of each BSU or BAM aliquot and remixed to homo- For the entire study period, sows were offered pelleted geneous dispersion. No probiotic was supplemented for the feeds. At service, dams were fed 1.8 to 2.0 kg/d. From service 3rd cycle in the creep feed. Piglet creep feeds were packed in to day 35 of gestation, dams were fed 2.9 to 3.0 kg/d. From 40-kg bags. days 35 to 114 of gestation, dams were fed 2.6 to 2.8 kg/d. Feeds and top-dressings were made and stored cool and dry In lactation, sows were not fed on the day of farrowing. Sows until required for feeding. Lactation and gestation diets, piglet were fed 1, 1.7, 2.4, 3.2, and 4 kg/d from 1 to 5 d post-far- creep feeds, and sow gestation top-dressings were analyzed row, and then ad libitum to appetite. Daily feed intake was before use to confirm viability of the probiotics. adjusted according to body condition, assessed via back fat, measured every 3 wk by ultrasound scanner (AV-3000V Experimental procedure Digital Handheld Electronic B Ultrasound Scanner, AMBISEA The study was started with 98 dams in the first cycle and Technology Corp., Ltd; Hong Kong, China). Backfat thickness finished with 56 in the third cycle. Reproductive performance was measured 6 cm from the midline at the height of the last of the sows was recorded during each of the three cycles, doc- rib, always by the same person. Daily feed was then decreased umenting the total number of piglets born (alive or dead), for dams considered too fat and increased for dams consid- the number of piglets born alive, the number of stillborn and ered too thin. Dams were fed twice daily in service, once daily mummified piglets, the cross-fostering between litters, the in gestation, twice daily for the first 5 d of lactation, and then number of piglets weaned, and mortality for both sows and ad libitum to appetite. Top dressings were added to service/ piglets. Performance of the piglets, i.e., birth weight, weight gestation feeds of the experimental treatments at the first daily after cross-fostering, weaning weight, and average daily gain feeding, added to the automatic feeder doser. For individual (ADG), was collected during the first and second cycles of feed intake monitoring, each gestating pen was equipped with the farm trial. The performance of the sow including the evo- enough mechanical free access self-closing semi-cage without lution in body weight (BW), the average daily feed intake pneumatic actuators (Rotecna, Spain), as previously reported (ADFI), and the back-fat thickness were recorded throughout by Reyes-Camacho et al. (2020). Suckling piglets were offered the first two cycles. From the 98 dams that initially started the creep mash feed from approximately 7 d of age to weaning at study (33 in CON, 32 in BSU, and 33 in BAM) from wean/ approximately 23 d of age, minimum 21 d. service and during gestation, 76 of them continued for the Two experimental treatments were tested (BSU and BAM) second cycle (27 in CON, 25 in BSU, and 24 in BAM) from in which different probiotic strains were added to the con- wean/service and during gestation. For the third and final trol diet (CON). Probiotic-supplemented diets were given productive, cycle only 56 dams (21 in CON, 17 in BSU, and to corresponding sows throughout gestation and lactation 18 in BAM) from wean/service and during gestation remained of three consecutive cycles. Piglets from the BSU and BAM in the study. The main reasons for sow removal (presented groups received the appropriate probiotics in the creep-feed. in Supplementary Table S4) were exclusion due to repetition All sow and piglet control diets were formulated with no (most frequent), culling due to claw lesion, abortion, or death. added antibiotics, organic acids, polysaccharides, or probiot- Samples from milk, feces, and blood from the sows, and ics. The strains were selected for survival in the gastrointes- feces, blood, and jejunum tissue from the piglets were taken tinal tract, pH and bile resistance, and pathogen inhibition from 12 sows per treatment and their litters during the third characteristics, primarily E. coli and C. perfringens. In addi- cycle. Eight and 21 d after parturition, sows from each treat- tion, the safety of the strains was evaluated by genotypic ment (n = 12/treatment) were sampled for blood and feces. and phenotypic methods for antimicrobial resistance genes On day 21 after parturition, milk samples were collected fol- and virulence factors. For the BSU treatment, the diet was lowing the usual procedure (with oxytocin) shortly after a supplemented with 5 × 108 cfu/kg feed of viable spores of basic udder cleaning procedure to remove leftover feces (if Bacillus subtilis—541, and for the BAM treatment, the diet necessary). From each sow, one 15-mL tube was collected and was supplemented with 5 × 108 cfu/kg feed of viable spores stored at −20 °C. Blood samples were collected from the tail. of Bacillus amyloliquefaciens—516. The addition of probiotic The tubes containing blood samples were centrifuged (2,500 strains in the gestation diets was done by top-dressing (150 g × g, 15 min) and serum collected was stored at −20 °C until on top of every kg feed) and for lactation diets, probiotics analysis. Feces were collected by stimulating the defecation were included in the final diets. The intended dosage and the into small bags and stored at −20 °C. periods of administration of top-dressings are specified in Feces from one random piglet from each of the sampled Supplementary Table S3. Each ton of gestation top-dressing sows (n = 12) were collected on days 21 (before weaning) was produced by adding 3.1 kg of B. subtilis or B. amyloliq- and 33 of life (12 d after weaning) (not necessarily the same uefaciens base premix to a 50-kg aliquot of cornmeal, mixing, pig). Feces were obtained by digital stimulation and stored and then adding to 946.9-kg basal gestation feed, and then in small bags at −20 °C. Moreover, for tissue sampling, two mixing to ensure homogeneity. Top-dressings were then pel- piglets from 8 sows per treatment (n = 16) of medium- and leted at 65 °C and packed in 25-kg bags. Lactation feeds were small-size were humanly euthanized by intravenous injec- mixed, pelleted at 65 °C, trucked in bulk, and stored on-farm tion of sodium pentobarbital (140 mg/kg, Euthasol, Ecuphar, 4 Journal of Animal Science, 2022, Vol. 100, No. 6 Belgium) on day 21. Jejunum samples (approximately 1 cm2) instrument, including cluster generation and paired-end were collected into tubes with RNAlater (Deltalab, Rubí, sequencing. Spain), which were left overnight in the refrigerator and put in the freezer (−20 °C) the next day. 16S rRNA gene sequencing bioinformatics The sequence reads generated by the 16S rRNA were pro- Analytical procedures cessed, aligned, and categorized independently using the Immune response Divisive Amplicon Denoising Algorithm 2 or DADA2 (Callahan et al., 2016), which was run as an R script (in R The assessment of the possible impact of the experimental v.4.0.2) using its R package (dada2 v.1.16.0). treatments on the immune response was performed by quan- When reads were de-duplicated, amplicon sequence variants tification of specific immunoglobulin concentrations in serum (ASV) were inferred. After building the ASV table (“makeSe- and milk samples collected from the sows. On this, it should quenceTable” function) and removing chimeras (“removeBi- be noted that the farm was PRRS positive and stable and meraDenovo” command), taxonomy was assigned using the the sows were vaccinated with Aujeszky. Concentrations of SILVA reference database (v138) provided by the SILVA web IgG and IgA antibodies specific for Aujeszky and PRRS were service (Quast et al., 2013). determined by enzyme-linked immunosorbent assays (ELISA). Commercial pig ELISA quantitation kits were used (INgezim Jejunal gene expression PRRS and ADV ELISA Kits from INGENASA, Madrid, Spain) Gene expression was quantified by RT-qPCR to study the following the manufacturer’s recommendations. expression of 56 genes in piglet jejunum samples by a custom- ized Open Array Real-Time PCR Platform (OpenArray plate) Metabolomic analysis of the milk on QuantStudio 12K Flex Real-Time PCR system (Applied Milk samples were processed as detailed previously (Gómez- Biosystems, Foster City, CA) as described by González-Solé Gallego et al., 2018). Milk samples were thawed, carefully et al. (2020). For that total RNA was extracted using the mixed by inversion, and then centrifuged at 14000 rpm for Ambion RiboPure Kit (Life Technologies, Carlsbad), accord- 20 min at 4 °C. The fat layer was removed, and whey milk ing to the manufacturer’s protocol. RNA was analyzed was transferred to a clean Falcon tube and centrifuged again; using a NanoDrop 1000A spectrophotometer (NanoDrop this procedure was repeated twice until a clear supernatant Technologies Inc., Wilmington, DE) to determine if it satisfied was obtained. the minimum purity and integrity standards for total RNA For Proton Nuclear Magnetic Resonance (NMR) analysis, quality. Ten microliters of total RNA (100 ng/µL) were used whey milk samples (455 µL) were mixed with 45 µL of sodi- for cDNA synthesis with the High-Capacity cDNA Reverse um-3ʹ-trimethylsilylpropionate-2,2,3,3-d4 (TSP) dissolved in Transcription Kit (Applied Biosystems, Foster City, CA). The deuterium oxide and placed in a 5-mm NMR tube. The final resulting cDNA was subjected to a PCR amplification fol- concentration of TSP in each sample was 2.5 mM. All spec- lowed by a real-time q-PCR reaction using the manufacturer’s tra were recorded in a Bruker Avance DRX 600 spectrometer TaqMan PreAmp Master Mix Kit Protocol (Life Technologies, (Bruker GmbH, Rheinstetten, Germany) operating at a 1H Foster City, CA). frequency of 600.13 MHz. Metabolite spin systems and res- onances were identified by using literature data and the com- Statistical methods mercial resonances database Chenomx NMR Suite Profiler Data are presented as means and standard deviations. The (Chenomx NMR Suite 8.1, Alberta, Canada). The spectra experimental unit for statistical purposes was the dam and were manually phase corrected and baseline adjusted, refer- its litter. Significant differences were declared at P ≤ 0.05, enced to TSP, and normalized to the total aliphatic spectral whereas 0.05 > P ≤ 0.10 was considered near significant area (0.50 and 4.40 ppm) to eliminate differences in metabo- trends. lite total concentration. Signals belonging to identified metab- olites were integrated and quantified using semi-automated Performance 1 H-NMR signal deconvolution routines in MestReNova 8.1. The statistical analysis of sow performance was performed Concentrations of final metabolites were calculated in arbi- using the GLM, MIXED, and GENMOD procedures of the trary units as the area under the peak. statistical package SAS (SAS Institute Inc., Cary, NC) with the following model: Yij = μ + αi + βj + αβij + εijk, where Yij Fecal microbiota was the parameter for the observations; μ was the general The fecal DNA was extracted (250 mg of each fecal sam- mean of all observations; αi was the effect of the experimen- ple) using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, tal treatments (CON, BSU, BAM); βj was the reproductive Germany) according to the manufacturer’s instructions fol- cycle effect; αβij was the interaction between the experimen- lowing the optimization steps. Concentration and purity of tal treatments and the cycle number; and ε ~ N (0, σ2ε) was DNA were checked with a NanoDrop ND-1000 spectropho- the unexplained random error. The same model was used for tometer (NanoDrop Technologies, Wilmington, DE). For 16S the statistical analysis of piglet performance. rRNA gene high-throughput sequencing, amplicon libraries were prepared using Nextera XT Index Kits 16S V3–V4 Immune response Amplicon-Seq Kit (Illumina, San Diego, CA). The analysis of the immunomodulatory effects (Igs in serum For sequencing on the MiSeq instrument, the generated and milk samples) was performed using statistical package libraries were placed in the reagent cartridge and loaded on R (R Core Team, 2021) The following model was used: Yi = the instrument along with the flow cell. The MiSeq Reagent μ + αi + εi, where Yi was the variable for the observations; Kit V2 (500-cycle) (Illumina, San Diego, CA) was used. All μ was the general mean of all observations; αi was the effect subsequent steps were performed on the MiSeq Illumina of the experimental treatments (CON, BSU, BAM); and ε~N Saladrigas-García et al. 5 (0, σ2ε) was the unexplained random error. When treatment SIMCA 14.1 software. A permutation test was performed to effects were established, the mean comparison was adjusted check the overfitting of the PLS-DA models. The multivar- with the Tukey–Kramer test. iate chemometric models were cross-validated with 10-fold Leave-one-out cross-validation; in each run, 10% of the data Microbiota were left out of the training and used to test the model. The whole cross-validation process was run 10 times. The spectral The patterns of fecal microbial diversity within the ASV regions responsible for the classification of the models were table were analyzed using a custom bioinformatics pipeline identified using the variable importance in projections (VIP) implemented in R 4.0.2 (http://www.r-project.org). Support coefficients obtained during PLS-DA. (Spectral regions with for DADA2 in R was achieved through the phyloseq pack- high VIP coefficients are more important in providing class age (v.1.32.0; available at https://joey711.github.io/phyloseq/; separation during analysis, whereas those with very small VIP McMurdie and Holmes, 2013). Alpha diversity metrics were coefficients provide little contribution to classification.) calculated using the phyloseq “estimate_richness” function from the rarefied ASV tables and using the microbiome pack- Gene expression age (v.1.10.0) (Lahti et al., 2017). The observed species, the The statistical analysis of gene expression was performed Chao1 index, the Simpson and inverse Simpson metrics, and in open-source R (R Core Team, 2021) using the DCrt data the Shannon diversity measures were estimated. For beta diver- matrix. Data were previously normalized with the reference sity, measurements were calculated using the Whittaker index genes. Firstly, and for each gene, normality tests were per- (Whittaker, 1960) and the betadisper () function of the vegan formed with shapiro.test (R stats package). Genes with nor- package (v.2.5.6) (Oksanen et al., 2013) using relative abun- mal distributions were analyzed with an ANOVA, whereas dances. To compare any differential effects, an ANOVA analy- the genes with non-normal distributions were analyzed with sis was performed for alpha richness and diversity with R stats a Kruskal–Wallis test. For ANOVA, the following model was package using the following model: Yij = μ + αi + βj + αβij + used: Yij = μ + αi + εij, where Yij was the parameter for the εijk, where Yij was the parameter for the observations; μ was observations; μ was the general mean of all observations; αi the general mean of all observations; αi was the effect of the was the effect of the experimental treatments (CON, BSU, experimental treatments (CON, BSU, BAM); βj was the sam- BAM); βj was weight block effect (medium or small size); pling day (d8 or d21 for sows and d21 or d33 for piglets); αβij αβij was the interaction between the experimental treatments was the interaction between the experimental treatments and and block of weight; and ε~N (0, σ2ε) was the unexplained sampling day; and ε~N (0, σ2ε) was the unexplained random random error. Finally, the P-values were adjusted by the error. Non-metric multidimensional scaling (NMDS), analysis Benjamini-Hochberg FDR method and Tukey tests were per- of similarities (ANOSIM), permutational analysis of variance formed for each gene if significance was observed. (PERMANOVA), and unweighted pair-wise grouping method with hierarchical arithmetic mean grouping (UPGMA), all based on the distance of Bray–Curtis, were carried out for the Results ordering and analysis of beta diversity. The normalization of Sow and litter performance the raw counts was performed using cumulative sum scaling During the two first cycles, the average BW of sows prior to (CSS) (Paulson et al., 2013a) and the differential abundance farrowing and at weaning were 269.6 ± 38.67 kg (expressed analysis was performed following the metagenomeSeq pack- as mean ± standard deviation) and 231.3 ± 35.14 kg, respec- age (v.1.30.0) (Paulson et al., 2013b). Taxa were aggregated tively. The average back-fat thickness was 17.6 ± 3.95 mm at phylum, family, and genus levels and expressed as compo- prior to farrowing and 14.1 ± 3.62 mm at weaning, and the sitional data. Relative abundances were used to plot taxon bodyweight loss during lactation was 38.3 ± 17.40 kg. The abundances, whereas raw family and genera counts were used average daily feed intake was 2.6 ± 0.02 kg per day during to correlate sow-piglet microbiota. A Pearson correlation was gestation and was 5.8 ± 1.16 kg per day during lactation. performed in R 4.0.2 through the stats package. Mother-piglet Days weaning to estrus were 4.1 ± 0.58 d. No differences samples were correlated by sampling day as follows: day 8 were observed between treatments. post-partum with suckling piglets (day 21), day 8 post-partum The effects of the experimental treatments on farrowing with weaned piglets (day 33), day 21 post-partum with suck- performance during the three consecutive cycles are presented ling piglets (day 21), and day 21 post-partum with weaned in Table 1. Regarding differences between reproductive cycles, piglets (day 33). Significant differences were declared at P ≤ a significant increase in the number of weaned piglets at the 0.05 (the adjusted P for differential abundance analysis). third cycle (P = 0.038) and also in weaning weight along time (P = 0.004) was observed. Regarding probiotic supplementa- Metabolomics tion, Bacillus amyloliquefaciens (BAM) significantly increased Chemometrics statistical analysis for the metabolo- the number of total piglets per sow compared to CON mic approach of the milk was performed using in-house (P = 0.008) and BSU showed intermediate values. The number MATLAB scripts and the PLS_Toolbox 8.0.2 (Eigenvector of piglets born alive and the number of piglets weaned were Research, Inc., Wenatchee, WA) statistical multivariate anal- also increased by BAM compared to CON (P = 0.029 and ysis library. Principal component analysis (PCA) was applied P = 0.025, respectively). No significant interaction between to NMR spectra data sets. Principal components were chosen cycle and treatments was observed. to explain at least 70% of the variance. The loading plots of Piglet performance data were monitored during the first the corresponding principal components were used to detect two cycles and are presented in Table 2. A significant increase the positions of most discriminative variables in the NMR in weaning BW, ADG, and consumption of creep feed was spectra. To maximize the separation between samples, partial observed in the second productive cycle concomitant with a least-squares discriminant analysis (PLS-DA) was applied with trend towards a lower BW at birth. No significant changes 6 Journal of Animal Science, 2022, Vol. 100, No. 6 Table 1. Effect of Bacillus subtilis (BSU) and Bacillus amyloliquefaciens (BAM) on sows’ farrowing performance during the three complete productive cycles Parameter1 Productive cycle Treatment2 1st 2nd 3rd SEM P CON BSU BAM SEM P No. of total piglets 18.7 19.7 20.3 0.33 0.125 18.3 a 19.5 ab 20.7 b 0.33 0.009 No. of piglets born alive 15.8 16.4 16.7 0.27 0.405 15.7a 15.7a 17.4b 0.27 0.009 No. of stillborn piglets 1.9 2.1 2.4 0.15 0.418 1.8 2.5 2.1 0.15 0.129 No. of mummified piglets 1.0 1.2 1.2 0.11 0.558 0.9 1.3 1.2 0.11 0.215 No. of piglets weaned 13.9xy 13.8x 14.3y 0.09 0.038 13.9a 13.6a 14.4b 0.09 0.001 Means within a row with different superscripts differ (P < 0.05). a,b, x,y 1 Cycle 1: 98 dams (33 in CON, 32 in BSU and 33 in BAM) from wean/service and during gestation and 78 dams (27 in CON, 25 in BSU and 26 in BAM) during lactation. Cycle 2: 76 dams (27 in CON, 25 in BSU and 24 in BAM) from wean/service and during gestation and 56 dams (21 in CON, 17 in BSU and 18 in BAM) during lactation. Cycle 3: 56 dams (21 in CON, 17 in BSU and 18 in BAM) from wean/service and during gestation and 45 dams (17 in CON, 12 in BSU and 16 in BAM) during lactation. 2 Treatments: CON = Control (no supplementation); BSU = 5 × 108 CFU/kg feed of Bacillus subtilis; BAM = 5 × 108 CFU/kg feed of Bacillus amyloliquefaciens. No interaction effect (Productive cycle x treatment) was found significant. Table 2. Effect of Bacillus subtilis (BSU) and Bacillus amyloliquefaciens (BAM) on piglet performance during the first two productive cycles Parameter1 Productive cycle SEM P Treatment SEM P 1st 2nd CON BSU BAM BW birth (all piglets), g 1300x 1222y 20.01 0.060 1290 1299 1210 37.5 0.145 BW after cross-fostering, g 1371 1319 20.22 0.228 1372 1384 1325 37.1 0.450 BW weaning, g 4863a 5739b 96.7 <0.001 5621a 5085b 5360ab 163.2 0.044 ADG, g/d 150 172 3.27 0.001 169 153 164 0.04 0.138 Creep feed FI, g/d/litter 29.0 34.1 0.57 <0.001 31.4 31.5 32.0 0.03 0.917 Mortality rate, % 3.65 2.77 0.432 0.348 3.09x 3.46x 1.66y 0.327 0.085 Pig loss rate, % 5.02 4.35 0.548 0.655 4.07ab 6.38a 3.03b 0.268 0.038 CON, Control; BSU, Bacillus subtilis; BAM, Bacillus amyloliquefaciens; BW, body weight; ADG, daily gain; FI, feed intake. 1 Cycle 1: 98 dams (33 in CON, 32 in BSU and 33 in BAM) from wean/service and during gestation and 78 dams (27 in CON, 25 in BSU and 26 in BAM) during lactation. Cycle 2: 76 dams (27 in CON, 25 in BSU and 24 in BAM) from wean/service and during gestation and 56 dams (21 in CON, 17 in BSU and 18 in BAM) during lactation. Different superscripts in sameroware significant or trending (a/b: P ≤ 0.05; x/y 0.05 < P ≤ 0.10). No interaction effect (Productive cycle x treatment) was found significant. related to the treatments were found in piglet BW at birth, and to CON, dietary supplementation with BAM significantly any possible differences in litter weight were balanced after decreased the serological titers of IgG specific for Aujeszky cross-fostering. During the studied cycles, Bacillus subtilis at day 21 (ANOVA P = 0.009) and tended to decrease sero- (BSU) was associated with a lower weight of piglets at wean- logical titers of IgG and IgA specific for Aujeszky at day 8 ing compared to CON (P = 0.015) and numerical differences after farrowing (P = 0.089 and P = 0.097, respectively). No in average daily gain (ADG) although differences did not reach other trend or a significant difference was found in concentra- statistical significance (P = 0.138). Estimated amounts of aver- tions of IgG specific for PRRS or any of the immunoglobulins age daily creep feed intake (ADFI) were not different among determined in milk. treatments. Supplementation of sows with Bacillus amyloliq- uefaciens (BAM) tended to reduce the mortality rate of piglets Differences in milk metabolites among compared to CON (P = 0.082) and significantly decreased the interventions rate of loss of piglets when compared to BSU (P = 0.024). In The global metabolic profile of a total of 40 milk samples this sense, pig loss includes both the piglets that died during taken 21 d after parturition was analyzed (n = 15 for CON, lactation and the culled piglets that had to be removed during n = 11 for BSU, and n = 14 for BAM) by partial least squares the study. No significant interaction between cycles and treat- discriminant analysis (PLS-DA). As a result, no differences ments was found for the performance of piglets. were found in the PLS-DA between groups. Nevertheless, the PLS-DA analysis showed a bigger dispersion in the samples Immune response from CON and BSU while samples from BAM seemed more Specific concentrations of IgG and IgA for Aujeszky and con- centered. When the analysis was performed by comparing centrations of IgG for PRRS in serum and milk samples from separately each treatment to control (Figure 1), two clusters the sows at days 8 and 21 are presented in Table 3. Compared could be identified when comparing BSU to CON. Saladrigas-García et al. 7 In addition to the PLS-DA, the possible impact of exper- Sow fecal microbiota imental treatments on particular metabolites was evaluated. The global structure, dynamics, and functionality of sow Supplementary Table S5 shows the list of milk metabolites fecal microbial populations were analyzed on days 8 and that were identified in sow milk samples and were selected 21 after parturition by high-throughput sequencing. As due to their relevance in the VIP coefficients. Among them, a result, the NMDS based on the Bray–Curtis distance of there were identified amino acids and derivatives, sugars relative abundance of ASV showed a distinct microbial and derivatives, and fatty acid-associated metabolites. The structure related to treatments on day 8 post-farrowing most abundant metabolite was lactose, followed by UDP-N- (PERMANOVA: P = 0.026; ANOSIM: P = 0.018), reaching acetylglucosamine, creatine phosphate, UDP-galactose, and a statistical trend on day 21 post-farrowing (PERMANOVA: glycoprotein. P = 0.058; ANOSIM: P = 0.074). As for the different time points, the NMDS showed a clear clustering of samples by Table 3. IgG and IgA specific for Aujeszky and PRRS determined by day (PERMANOVA: P < 0.001; ANOSIM: P = 0.001) with ELISA in serum samples and sows’ milk on days 8 and 21 after farrowing more dispersed samples on day 8 after parturition (Figure 2). The alpha diversity indexes of sow fecal samples are pre- Parameter, in AU2 Treatment1 RSE P sented in Table 4. In general terms, there was a significant CON BSU BAM increase in the species richness (ANOVA P = 0.046) and Chao1 index (P = 0.046) from d8 to d21 after farrowing. Serum d8 Concerning the dietary treatments, BSU and BAM treatments IgG Aujeszky 2.15 2.02 1.91 0.322 0.074 showed a significantly lower alpha diversity on d8 postpar- IgA Aujeszky 0.30 0.24 0.20 0.134 0.082 tum when compared with CON sows. However, on d21 only IgG PRRS 0.39 0.47 0.35 0.196 0.760 BSU treatment showed a lower alpha diversity compared to Serum d21 CON. Regarding beta diversity, no difference was detected with the Whittaker’s index between sampling days (0.525 IgG Aujeszky 2.26a 2.19a 1.95b 0.256 0.003 and 0.499, for d8 and d21 after farrowing, respectively, P = IgA Aujeszky 0.31 0.48 0.18 0.198 0.233 0.135) nor treatments (0.489, 0.523, and 0.522, for CON, IgG PRRS 0.42 0.38 0.38 0.201 0.559 BSU, and BAM, respectively, P = 0.177). Milk d8 The composition of the fecal microbiota of the sows both IgG Aujeszky 0.85 0.81 0.88 0.304 0.911 at the phylum and family level is presented in Supplementary IgA Aujeszky 0.47 0.61 0.44 0.253 0.914 Table S6. Regarding differences in taxonomic groups IgG PRRS 0.07 0.08 0.07 0.013 0.767 between sampling days (Figure 3 and Supplementary Table Milk d21 S6), a greater relative abundance of the Erysipelotrichaceae and Peptostreptococcaceae families was observed on IgG Aujeszky 0.47 0.60 0.50 0.154 0.551 day 21 postpartum. There was also a greater abundance IgA Aujeszky 0.36 0.36 0.24 0.204 0.146 of Muribaculaceae and a decrease in the abundance of IgG PRRS 0.06 0.06 0.06 0.004 0.894 Enterobacteriaceae and Bifidobacteriaceae when compared with day 8 after farrowing. Moreover, some statistical dif- Means within a row with different superscripts differ (P < 0.05). a,b 1 Treatment: CON, Control; BSU, Bacillus subtilis; BAM, Bacillus ferences were observed in families with a lower magnitude of amyloliquefaciens. representation, such as p-2534-18B5 or Selenomonadaceae, 2 AU, Absorbance units. which showed higher values on day 21. At the genus level, Figure 1. Partial least squares discriminant analysis (PLS-DA) scores plot scaling NMR data from CON and BSU (a); and projection of samples from BAM (b). CON = Control; BSU = Bacillus subtilis; BAM = Bacillus amyloliquefaciens. 8 Journal of Animal Science, 2022, Vol. 100, No. 6 Figure 2. NMDS of the relative abundances of ASV in sow fecal content based on Bray-Curtis distance (stress = 0.157) and grouped by sampling day (d8 after farrowing vs. d21 after farrowing). In order to facilitate the distinction between experimental treatments from (a), the same NMDS figure has been placed in parallel as (b) with the three diets highlighted in color. Table 4. Alpha diversity values obtained in each sampling day both on sows and their offspring Sows Index d8 SEM P d21 SEM P CON BSU BAM CON BSU BAM Observed species 2180a 1340b 1455b 145.26 0.032 2219 1568 2492 176.61 0.100 Chao1 2195 a 1353 b 1466b 146.11 0.033 2235 1585 2509 177.40 0.102 Shannon 7.09a 6.54b 6.47b 0.115 0.038 6.89 6.60 6.91 0.082 0.250 Simpson 0.999a 0.997b 0.996b 0.001 0.286 0.997 0.997 0.998 0.000 0.670 Piglets Index d21 SEM P d33 SEM P CON BSU BAM CON BSU BAM Observed species 1321 x 787 y 1475 x 125.98 0.081 834 1047 1004 72.79 0.438 Chao1 1324x 789y 1478x 125.96 0.081 838 1052 1008 72.72 0.429 Shannon 6.39a 6.02b 6.42a 0.072 0.049 5.90 6.28 6.29 0.152 0.457 Simpson 0.997 0.996 0.997 0.000 0.180 0.993 0.995 0.997 0.001 0.556 The Observed species, Chao1, Shannon, and Simpson indices are presented. The values obtained in each sampling day are presented separately, differentiating between treatments and with their corresponding Pvalue. Different superscripts in same row are significant or trending (a/b: P ≤ 0.05; x/y 0.05 < P ≤ 0.10). some butyrate- and methane-producing microorganisms Regarding particular genera (Figure 4b), BSU and BAM were found in significantly greater abundance at day 21 promoted lower abundances of Bacteroides (P = 0.001), postpartum, such as Lachnospiraceae (group NK3A20), Faecalibacterium (P = 0.002), Phascolarctobacterium Coprococcus, Methanosphaera, Prevotellaceae (group UCG- (P = 0.012), Prevotella (P = 0.003), Blautia (P < 0.001), Dorea 004), or Butyricicoccus. (P = 0.005), and Roseburia (P = 0.003) compared to CON and The impact of the experimental treatments on particular higher relative abundances of the genus Sarcina (P = 0.041). taxonomic groups was analyzed by sampling day since sig- On day 21 after farrowing, differences were only observed for nificant effects between days after farrowing were observed. the Enterococcaceae family (P < 0.001), with lower relative The impact of experimental treatments was higher on day abundances in BSU and BAM groups, and three minor genera. 8 than on day 21. On day 8, BSU and BAM showed lower abundances of Prevotellaceae (metagenomeSeq P = 0.007), Piglet fecal microbiota Lachnospiraceae (P = 0.037), Ruminococcaceae (P = 0.002), The analysis of the piglets’ fecal microbiota on days 21 and and Bacteroidaceae (P = 0.001) than CON (Figure 4a). 33 of life showed that weaning promoted an evident change Saladrigas-García et al. 9 Figure 3. Differentially abundant taxa at family level from sow fecal content [ln change coefficients (2log) and FDR-adjusted P < 0.05] between d08 and d21 samplings. Only significant taxa with greater relative abundance than 0.05% are presented; positive and negative values indicate greater and lower abundance, respectively, in d21 animals; taxa are sorted by level of significance (from higher to lower). in the ecosystem with significant differences between suck- Regarding the impact of supplementing probiotics to the ling (d21) and weaned (d33) piglets (ENVFIT: P < 0.001; sow on particular microbial taxa of piglets, Supplementary PERMANOVA: P < 0.001; ANOSIM: P = 0.001) as it shows Figure S1 shows the bar plots for relative abundances of the the NMDS of the relative abundances of ASV based on Bray– main families of each experimental treatment on both sam- Curtis distance in Figure 5. The administration of probiotic pling days. Most of the changes produced by the treatments supplemented diets to their mothers was not associated were observed at minor taxa (<0.5%) and a greater effect with structural changes in piglets’ fecal community during was observed after weaning. During lactation (d21), only a suckling (ENVFIT: P = 0.470; PERMANOVA: P = 0.209; higher relative abundance of Campylobacteraceae (metage- ANOSIM: P = 0.388) or after weaning (ENVFIT: P = 0.886; nomeSeq P = 0.043) and its respective genus, Campylobacter PERMANOVA: P = 0.882; ANOSIM: P = 0.999). was observed in both groups supplemented with the probi- Concerning alpha diversity (Table 4), weaning promoted otic (0.19%, 0.84%, and 0.81%, for CON, BSU, and BAM, a trend for a lower species richness at d33 (1224 vs. 951 for respectively, P = 0.0345). After weaning (d33), however, BSU observed species, ANOVA P = 0.090; and 1226 vs. 955 for and BAM piglets presented lower abundances of p-2534- Chao1, P = 0.092; for d21 and d33, respectively) and a signif- 18B5 than CON (2.38%, 1.19%, and 1.87%, for CON, BSU, icant lower Simpson index (0.997 vs. 0.994 for d21 and d33, and BAM, respectively, P = 0.041) and greater abundances respectively, P = 0.027). Regarding treatments, a tendency to of Ruminococcaceae (2.51%, 4.25%, and 5.40%, for CON, lower species richness (observed species and Chao1 indexes) BSU and BAM, respectively, P = 0.019). Finally, BAM piglets and a significantly decreased Shannon index alpha diversity showed greater abundances of Bacteroidales BS11 gut group were observed with BSU compared to CON and BAM at d21. (0.00%, 0.00%, and 0.64%, for CON, BSU, and BAM, respec- No significant changes were detected at d33. Regarding beta tively, P = 0.003) and F082 (0.01%, 0.001%, and 0.57%, diversity, distances increased significantly after weaning com- for CON, BSU, and BAM, respectively, P = 0.019). The ln pared to suckling piglets (0.539 and 0.595, for suckling and change coefficients in those families significantly modified by weaned piglets, respectively, P = 0.006); however, no signifi- the treatments can be seen in Figure 7. At the genus level, no cant changes were observed between treatments during lacta- significant differences were observed except for minor taxa. tion (P = 0.916) or after weaning (P = 0.351). To study the hypothesis of maternal transfer and the role The composition of the fecal microbiota of the piglets both of the mother in the early gut colonization of the piglets, sow at the phylum and family level is presented in Supplementary family and genus microbiota were correlated with those of Table S7. The weaning process promoted significant changes their piglets. As a result, a high number of significant posi- in several taxonomic groups (phylum, family, and genus, tive correlations were observed between the microbiota of the Supplementary Tables S7 and S8). As seen in Figure 6, the dams and the microbiota of the weaned piglets, whereas no increase of families such as Prevotellaceae, Spirochaetaceae, moderate nor high negative correlations were found at fam- and Enterobacteriaceae was observed after weaning, ily nor genus level. Table 5 shows those significant positive whereas families like Lactobacillaceae, Lachnospiraceae, correlations (families and genera) with correlation sizes from Bacteroidaceae, and Clostridiaceae decreased. 0.7 to 1.0. 10 Journal of Animal Science, 2022, Vol. 100, No. 6 Figure 4. Differentially abundant taxa from fecal content (ln change and FDR-adjusted P < 0.05) on day 8 after farrowing between: BSU vs. CON, and BAM vs. CON at family (a) and genus (b) level. Only significant taxa with greater relative abundance than 0.05% are presented; positive and negative values indicate greater and lower abundance, respectively; the average relative abundance of each taxa is expressed in % below the family or genus name; taxa are sorted by level of significance (from higher to lower). Saladrigas-García et al. 11 Figure 5. NMDS of the relative abundances of ASV in piglet fecal content based on Bray–Curtis distance (stress = 0.169) during lactation (d21 of life) and after weaning (d33 of life and d12 after weaning). In order to facilitate the distinction between experimental treatments in (a), the same NMDS figure has been placed in parallel as (b) with the three diets highlighted in color. Interestingly no high correlations were found between the maternal butyric fermentation genera such as Butyricimonas, sow microbiota 1 wk after farrowing (d8) and the piglets at Blautia, Megasphaera, Prevotella, with other butyric fermen- the end of lactation (d21). However, some microbial groups of tation genera in piglets, such as Coprococcus, Megasphaera, the sow at d8 showed to be correlated with the microbiota of pig- Prevotellaceae (NK3B31 group), and Ruminococcaceae lets at d33. The highest correlated families in the weaned piglets UCG-002 and UCG-008. Sow’s microbial genera at day 21 (d33) with mother microbiota early after birth (d8) belonged to postpartum also showed similar significant high correlations the Firmicutes and Proteobacteria phyla, including families such with piglet’s genera at days 8 and 33. Because of the rele- as Enterobacteriaceae, Pasteurellaceae, Selenomonadaceae, vance of the genera, it should be remarked the significant Veillonellaceae, and Peptostreptococcaceae. The minoritary high correlations between Akkermansia in the mothers and Atopobiaceae family from Actinobacteria phylum also showed Campylobacter (d21) and CAG-873 and Succinivibrio (d33) to be correlated to sow’s microbiota. genera in the piglets. Microbiota of sows at day 21 postpartum also showed sig- nificant high correlations (>0.7) with those of weaned piglets Intestinal gene expression (d33). In this case, Selenomonadaceae and Veillonellaceae Detailed results of jejunal gene expression of medium- and families showed also to be correlated with different micro- small-sized piglets can be found in Supplementary Table S9 for bial families in the sows and particularly Succinivibrionaceae the 51 genes that could be quantitatively determined. Despite family showed to be correlated to Akkermansiaceae, some numerical differences in some genes between treatments, Anaerovoracaceae, Oligosphaeraceae, Peptococcaceae, and there was no significant effect associated with the sows’ Spirochaetaceae families in the mothers. dietary treatments, as shown in Figure 8. However, significant Only two high positive correlations were found when differences were observed when comparing gene expressions comparing microbiota of sows and piglets at d21, involving according to piglet size (medium- or small-sized) regardless Akkermansiaceae and Streptococcaceae families in the sow of the treatment. Small-sized piglets showed up-regulated that correlated to the piglets’ Campylobacteraceae family. expression of IGF1R (Insulin-like growth factor 1 receptor; At the genus level, and in a similar way to the previous ANOVA P = 0.052); HSP27 (Heat shock protein 27; ANOVA level, a greater number of correlations were found between P = 0.038); and CLDN15 (Claudin-15; ANOVA P = 0.052) the dams (both at days 8 and 21 postpartum) and the genes compared to medium-sized piglets. No interaction was weaned piglets. On day 8 postpartum, a high correlation was found between sow’s dietary treatment and piglet size. observed between the maternal genera Alloprevotella and Terrisporobacter and the genus Escherichia/Shigella of the Discussion piglet and also between the Megasphaera genera of the sows and their piglets. Likewise, several moderate positive cor- In recent years, dietary supplementation of sows with probiot- relations were observed between Lactobacillus and various ics has gained considerable attention due to their potential to 12 Journal of Animal Science, 2022, Vol. 100, No. 6 Figure 6. Differentially abundant taxa from fecal content (ln change and FDR-adjusted P < 0.05) between d21 and d33 samplings. Only significant taxa with greater relative abundance than 1.5% are presented; positive and negative values indicate greater and lower abundance, respectively, in d33 animals; the mean average relative abundance of each taxa is expressed in % between brackets; taxa are sorted by level of significance (from higher to lower). improve reproductive performance (Barba-Vidal et al., 2019). Impact of probiotics on sow performance Particularly, different strains of Bacillus spp. have been shown Several studies in the literature have pointed out that supple- to increase feed consumption in lactation, reduce fat mobiliza- mentation of sows with Bacillus spp. probiotics during gesta- tion, promote milk production, increase litter weight, promote tion and lactation may increase feed consumption, promote digestive health, and inhibit pathogenic bacteria (Alexopoulos milk production, and reduce the mobilization of reserves, et al., 2004; Böhmer et al., 2006; Stamati et al., 2006; Larsen et improving body condition at the end of lactation (Jeong et al., al., 2014; Kritas et al., 2015; Hayakawa et al., 2016; Blavi et al., 2015; Kritas et al., 2015; Hayakawa et al., 2016; Menegat et 2019; Luise et al., 2019; He et al., 2020). Although higher milk al., 2019). Moreover, a reduction in the weaning-estrus inter- production or improved economy of fat reserves of the sow val has also been reported (Alexopoulos et al., 2004; Böhmer could be behind these effects, other modes of action, related to et al., 2006; Kritas et al., 2015; Hayakawa et al., 2016). In differential early events in the life of the piglets, could also be the present study, however, we were not able to find such involved. In this regard, modulation of the maternal intestinal improvements. This is consistent with the findings of other microbiota by probiotics could determine changes in the pro- authors (Zhang et al., 2020; Hu et al., 2021). Variability in cess of early microbial colonization of the gastrointestinal tract the response between studies could be due to differences in of piglets with beneficial implications throughout their lives. the probiotic strains used but could also be due to differences Currently, the crucial role of early events in the development in the management of the animals, age, or breeds of the sows, of the neonatal immune system is largely recognized (Hansen the health status of the farm, or the environmental conditions. et al., 2012) and appropriate development of the intestinal Despite not finding improvements in feed intake or mobi- microbiota is considered as a key point with potential bene- lization of reserves, these results clearly show an increase in fits throughout the productive life of the pig (Nowland et al., prolificacy, in terms of total number of piglets per sow, partic- 2019). In this work, we assess the potential benefits of two pro- ularly when supplementing BAM. The enhancement of litter biotic Bacillus strains, when supplemented to sows, trying to size with Bacillus spp. probiotics has been also described by give some light on those mechanisms that could explain the many other authors (Alexopoulos et al., 2004; Taras et al., improvements reported in the progeny. 2005; Stamati et al., 2006; Taras et al., 2006; Baker et al., Saladrigas-García et al. 13 Figure 7. Differentially abundant taxa from fecal content (ln change and FDR-adjusted p < 0.05) of weaned piglets (d33) between: BSU vs. CON, and BAM vs. CON at family level. Only significant taxa with greater relative abundance than 0.05% are presented; positive and negative values indicate greater and lower abundance, respectively, in d33 animals; the mean average relative abundance (d33 only) of each family is expressed in % below the family name; taxa are sorted by level of significance (from higher to lower). 2013; Apic et al., 2014; Jeong et al., 2015). This could be Impact of probiotics on sow fecal microbiota and due to an improvement in the rates of ovulation and con- maternal milk ception, and/or early embryonic maturation. Therefore, based In general terms, the impact of the probiotic treatment on on maternal performance, our results suggest that it should sow microbiota was observed from day 8 post-farrowing with be enough to supplement the probiotics from mating to con- reductions in biodiversity and significant changes in particular firmed gestation (1st third of gestation) since the only impact microbial groups with both treatments, although changes were on performance was the increased prolificity. Moreover, this more evident with BAM. PERMANOVA analysis also showed outcome might be more important in conventional genetic that the impact of treatments was clearer on day 8 than on day lines than in hyperprolific genetic lines. Interestingly, rela- 21. The apparent higher impact of probiotics on the microbial tionships between intestinal microbiota and reproductive ecosystem on d8 could have been due to the higher dispersion success have been described by some authors in zoo animals, of mothers’ microbiota shortly after labor. During gestation, even identifying some potentially probiotic bacteria species the microbiota undergoes many changes (Liu et al., 2019a), (Antwis et al., 2019). Nasiri et al. (2018) also demonstrated and after farrowing probably needs to establish a new equilib- that supplementing lactating dairy cows with live yeast cul- rium. It is in this process that probiotics could have a relevant ture had a positive impact on the hormonal profile, pro- role in speeding up this transition and preventing transient moting the development of larger ovulatory follicles. These dysbiosis. In consonance with other authors (Zhang et al., improvements in fertility could have been mediated by a mod- 2020), α-diversity was decreased by both probiotics on day ulation of the immune response. In this regard Bhandari et al. 8 and only by BSU on day 21. Although in general terms, an (2016) described in a mouse model how a probiotic strain of increase in biodiversity is regarded as a positive sign of a more Lactobacillus plantarum could ameliorate the inflammatory robust and resilient ecosystem (Sommer et al., 2017), the sup- induced infertility associated with an LPS challenge. plementation with probiotics was not necessarily associated Few authors have focused their studies on evaluating with an increase in biodiversity. Grazul et al. (2016) showed in the potential additional effects of long-term administra- mice how in a disturbed microbiota, following antibiotic treat- tion of probiotics on the reproductive performance of sows. ment, the administration of probiotics did not alleviate the Although in our study the interaction (treatment x cycle) did loss of diversity and even was associated with a lower number not show any significant effect on any of the measured vari- of microbial species in the recovery phase. It is reasonable to ables, it is true that the beneficial impact of the treatments on think that probiotic intervention can be related to a reduction the number of born piglets showed a differential numerical in the complexity of the microbiota ecosystem, at least tran- evolution across cycles. Although with BAM the increase in sitionally, due to the constant arrival of high numbers of such the number of total and born alive piglets was improved from particular microorganisms. This could be particularly true in the first cycle, for the BSU treatment, differences were only a scenario of transient disequilibrium which occurs postpar- observed from the third cycle (21.4 vs. 18.2 total piglets, P tum. From this scenario, a transient reduction in biodiversity = 0.034), suggesting that for a positive impact of this probi- could be regarded as a positive sign, if the ecosystem is effec- otic on prolificacy, long-term administration of at least three tively driven by the probiotic to a new beneficial equilibrium, cycles would be necessary. thereby preventing dysbiosis. 14 Journal of Animal Science, 2022, Vol. 100, No. 6 Table 5. Significant high correlations (from 0.7 to 1.0) obtained from the comparison among sows’ (d08 and 21 after farrowing) and piglets’ (d21 and d33 of life) fecal microbiota (families and genera) Sow taxa Piglet taxa cor value P d8 sow vs. d21 piglet No high correlation values found neither at family nor genus level d8 sow vs. d33 piglet Family Muribaculaceae Atopobiaceae 0.767 <0.001 Selenomonadaceae Atopobiaceae 0.794 <0.001 Veillonellaceae Atopobiaceae 0.832 <0.001 Peptostreptococcaceae Enterobacteriaceae 0.716 <0.001 Peptostreptococcaceae Pasteurellaceae 0.724 <0.001 Veillonellaceae Selenomonadaceae 0.729 <0.001 Coriobacteriaceae Veillonellaceae 0.743 <0.001 Muribaculaceae Veillonellaceae 0.755 <0.001 Selenomonadaceae Veillonellaceae 0.815 <0.001 Veillonellaceae Veillonellaceae 0.773 <0.001 Genus CAG-873 Bacteroides 0.743 <0.001 Alloprevotella Escherichia/Shigella 0.807 <0.001 Terrisporobacter Escherichia/Shigella 0.766 <0.001 Megasphaera Megasphaera 0.858 <0.001 d21 sow vs. d21 piglet Family Akkermansiaceae Campylobacteraceae 0.742 <0.001 Streptococcaceae Campylobacteraceae 0.776 <0.001 Genus Akkermansia Campylobacter 0.742 <0.001 Streptococcus Campylobacter 0.774 <0.001 d21 sow vs. d33 piglet Family p-251-o5 Selenomonadaceae 0.720 <0.001 Akkermansiaceae Succinivibrionaceae 0.740 <0.001 Anaerovoracaceae Succinivibrionaceae 0.706 <0.001 Bacteroidales BS11 gut group Succinivibrionaceae 0.744 <0.001 Oligosphaeraceae Succinivibrionaceae 0.749 <0.001 Peptococcaceae Succinivibrionaceae 0.809 <0.001 Spirochaetaceae Succinivibrionaceae 0.726 <0.001 Paludibacteraceae Veillonellaceae 0.758 <0.001 Genus Akkermansia CAG-873 0.763 <0.001 Lachnospiraceae NK4A136 CAG-873 0.764 <0.001 Treponema CAG-873 0.712 <0.001 Actinomyces Megasphaera 0.845 <0.001 Fusobacterium Megasphaera 0.780 <0.001 Akkermansia Succinivibrio 0.745 <0.001 Family XIII AD3011 Succinivibrio 0.704 <0.001 Treponema Succinivibrio 0.727 <0.001 Regarding taxonomic changes promoted by probiotics on Another important aspect of the impact of probiotics on the sow fecal microbiota, one of the most reported effects the mothers’ microbiota is that although BAM and BSU of Bacillus spp. probiotics has been an increase in numbers did modify the same microbial groups, BAM changes were of Lactobacillus and a decrease in numbers of Escherichia of greater magnitude than those reported for BSU and they coli (Baker et al., 2013; Kritas et al., 2015; Hayakawa et al., fundamentally occurred on day 8 postpartum. As described 2016; Hu et al., 2021); however, no significant changes in above, this could be related to a better modulation of the these groups were observed in our study. It is important to digestive balance of the dams during the transition process consider here the methodological differences between studies. after farrowing that could have led to an improvement in Despite limitations in the method, results of sequenc- the early colonization process of the piglets during the first ing showed significant changes in particular taxonomic days after delivery. The transition of animals to an improved groups. The changes observed were somehow similar microbial environment, driven by their mothers, could be to those described by Zhang et al. (2020) in reproduc- behind the lower mortality and pig loss rate documented in tive sows supplemented with a Bacillus subtilis strain. the BAM group. Differences were found on Prevotellaceae, Lachnospiraceae, Some probiotics have also been reported to modulate the Ruminococcaceae, and Bacteroidaceae families that were immune response of the sow herd (Medina et al., 2007) or decreased with probiotic supplementation on d8 after even litter immunity (Scharek-Tedin et al., 2015; Hayakawa farrowing. et al., 2016). The inclusion of B. subtilis in lactating sows has Saladrigas-García et al. 15 Figure 8. Mean DCrt expression of all the genes analyzed sorted by dietary treatment. Genes have been grouped by function with different background colors. CON = Control; BSU = Bacillus subtilis; BAM = Bacillus amyloliquefaciens. been reported to be beneficial for milk production and increase of the sow. Furthermore, the mother’s imprinting on the piglet the concentration of IgG (Ayala et al., 2016). Moreover, in could occur even before its birth. In a recent study, micro- fecal samples, probiotic administration has been reported to bial colonization of the spiral colon occurred in stillborn pigs, slightly increase the total IgA concentration (Hayakawa et al., suggesting microbial exposure before birth (Nowland et al., 2016). However, in this work, we were not able to demon- 2021). In this context, supplementing sows with E. faecium strate any improvement in the immune response based on and Bacillus-based probiotics during the previous month to Aujeszky and PRRS-specific IgG and IgA levels considering labor has been reported to modify the fecal microbiota of the that the farm was PRRS positive and stable and the sows were mother with some translated impact on their litters (Baker et vaccinated with Aujeszky. The absence of significant effects al., 2013; Starke et al., 2013; Kritas et al., 2015). Moreover, does not eliminate a possible impact of the probiotics on the B. subtilis probiotic-fed sow progenies have been reported to immune response of the sows, given the potential inadequacy show a similar fecal microbial population than their mothers of the selected methodology to detect those changes. (Menegat et al., 2019). Therefore, one of the main purposes Probiotic strains could have also benefited the composition of this study was to evaluate the impact of probiotics fed to of milk. In this regard, the supplementation with probiotics sows on the establishment of the microbiota of their piglets. during gestation and lactation has been reported to induce Results showed that the diversity and community structure beneficial effects on the milk composition of rats (Azagra- of fecal microbiota were in consonance with the predominant Boronat et al., 2020). In the present study, the dietary sup- taxa described previously for healthy piglets. Bacteroidetes, plementation with Bacillus amyloliquefaciens (BAM) was Firmicutes and Proteobacteria constituted the three predom- associated with a more similar milk composition between inant phyla, both pre- and post-weaning, as reported in sev- animals compared to CON and BSU. Changes in milk compo- eral studies (Hu et al., 2016; Chen et al., 2017; Holman et sition could be mediated by changes in the metabolic response al., 2017; Li et al., 2018; Saladrigas-García et al., 2021b). of the sow induced by the changes promoted by probiotics in Moreover, and in agreement with previous studies (Saladrigas- their gut microbiota. Actually, the more stable composition García et al., 2021a), the weaning process promoted signifi- of BAM sows’ milk shows some parallelism with the closer cant changes in considerable taxonomic groups. clustering of the gut microbiota of BAM mothers on day 8 Regarding the impact of supplementing probiotics to the postpartum. sows, although we were not able to detect significant structural From the metabolite profile identified in milk samples, sev- changes in piglets’ fecal community, we were able to show eral metabolites were consistent with the existing literature. changes in some particular microbial groups, particularly after Choline, creatine, creatinine, lactose, sn-glycerophosphocho- weaning. After weaning (d33), both probiotic strains were line, taurine, and UDP-galactose have all been detected by associated with significant increases in Ruminococcaceae and different authors in the analysis of the metabolomic profile also p-2534-18B5 families although other microbial groups of sow milk (Curtasu et al., 2016; Picone et al., 2018; Tan et showed a differential impact. It is interesting to note that most al., 2018). of the changes were detected after weaning, suggesting that the changes induced on weaning piglets would not be mediated by Maternal microbial imprinting a direct impact of the sow’s probiotic-modulated microbiota, The natural exposure of piglets to sow’s feces, together with but by a differential response of the animals to the post-wean- the possibility of an entero-mammary route for microbial ing stressors due to a different sequence of colonization along transfer (Jost et al., 2014; Chen et al., 2018; Jiang et al., 2019; the first days of life. As we did not analyze microbiota of the Liu et al., 2019b), opens the possibility of gut microbiota piglet up to day 21 of life, we cannot confirm this hypothe- modulation in the piglet through probiotic supplementation sis; however, it should be said here that the biggest changes 16 Journal of Animal Science, 2022, Vol. 100, No. 6 induced by the probiotic treatments on the sow’s microbiota et al., 2016; Hu et al., 2021), results are not always positive were observed 8 days after delivery, with a clearer impact of and some others did not find significant changes in the pig- BAM supplemented diets. let’s performance (Böhmer et al., 2006; Menegat et al., 2019; Considering the hypothesis that a change in the mother’s Davis et al., 2020; Menegat et al., 2020). In our study, results microbiota during the first days postpartum may have a greater suggest that the administration of any of the probiotic strains impact on the piglet’s microbiota in later stages, the correla- was not able to increase weight gain along lactation, with sim- tion between sow-litter microbiota was analyzed. A greater ilar weaning weights for BAM compared to CON and even number of significant positive correlations were observed lower weights with BSU. The lower weaning weights regis- between the microbiota of the dams (d8 and 21) and the tered with Bacillus subtilis (BSU) could initially be associated microbiota of the weaned piglets (d33). All of the significant with the observed increased litter size, although this adverse high correlations obtained were positive and between taxo- impact on body weight was not in BAM piglets. Different nomic groups which shared similar functionalities. For exam- studies have described a negative linear correlation between ple, maternal butyric fermentation genera such as Blautia, litter size and piglet weight at birth (Zhang et al., 2020) due to Megasphaera, or Prevotella correlated highly with other the higher competition between embryos for uterine resources butyric fermentation genera in piglets, such as Coprococcus, and that could have an impact on piglet thriving along with or the same Megasphaera or Prevotella. Similarly, genera con- lactation. However, in our study, despite larger litters, BSU sidered negative for intestinal health such as Terrisporobacter piglets showed similar weights at birth compared to CON correlated positively with Escherichia/Shigella in piglets. piglets. Lower gains during lactation could also be due to Also, it is interesting to remark the significant correlations higher competition for the udders and a lower intake of milk; found between the genera Akkermansia in the sows at d21 however, this should be discarded since litters were balanced and genera Succinivibrio and Prevotella sp.-CAG-873 in the through cross-fostering. Lower weaning weights registered piglets at d33. The genera Akkermansia has been reported to with the BSU treatment would seem therefore associated with be universally distributed in the gut of the animal kingdom a lower ability of these piglets to cope with the challenges and has been considered to contribute to a healthy mucus-as- of the lactation period. Actually, with BSU treatment, pig sociated microbiota composition (Belzer and de Vos, 2012). loss rate showed the highest values, and the mortality rate Moreover, it has recently been shown beneficial to the host by was also significantly higher compared to BAM. We could restoring gut barrier function and reducing adiposity in pigs hypothesize that the lower maternal carry-over reported for (Everard et al., 2013; Yang et al., 2018). In addition to these this probiotic, compared to BAM, would not have equal ben- benefits, changes in the Akkermansia genus in the dams could efit on the intestinal health and immunocompetence of piglets also affect the development of microbial groups of interest to compensate for the challenge of larger litters. Contrary, in the piglets. Succinivibrio and Prevotella genera are associ- the supplementation with Bacillus amyloliquefaciens (BAM) ated with the fermentation of complex carbohydrates and are could have improved the health status of piglets consider- likely important contributors towards the establishment of a ing the lower mortality rate (trend) and the similar weaning more mature microbiota. weight compared to CON despite the highest litter sizes. It is The importance of the mother-effect defining a particular also fair to note that with BAM the number of weaned piglets microbiota composition in the nursing piglet was also evi- was also significantly increased with almost one more piglet denced by Mu et al. (2019) analyzing the early-life microbi- per litter. It is difficult to give a clear explanation for these ota succession in pigs using a cross-fostering piglet model. evident positive effects of BAM on the performance of piglets Therefore, maternal environmental factors (diet composition, but, as stated above, we could hypothesize that a better mod- probiotic treatment, etc.), that induce changes in maternal ulation of the microbiota of the mothers, especially during microbiota, may have huge effects on offspring gut physiol- the first days after delivery (d8 post-partum), when the sows’ ogy (Kelly and Conway, 2005). microbiota is still reestablishing, could have had a benefit on However, we were not able to find any significant impact the intestinal colonization of the piglet promoting a better of the probiotic strains on the jejunal expression of the genes training of the immune system. Previous works of Blavi et al. selected. This does not discard that probiotic supplementa- (2019) comparing both strains also showed a clearer impact tion could have had induced changes in the expression or of B. amyloliquefaciens on ileal apparent digestibility in other genes or tissues. growing pigs that could suggest a higher comparative impact Despite the lack of the impact of the sows’ dietary treatments of this strain on the intestinal environment and functionality. on jejunal gene expression, differences were found according In conclusion, both tested probiotic strains supplemented to the piglet size (medium or small-sized within the same lit- to reproductive sows were demonstrated a significant ter). Small-sized piglets showed up-regulated expressions of impact on prolificacy. Although with Bacillus amyloliquefa- IGF1R, HSP27, and CLDN15 that could suggest a greater ciens—516 (BAM) the benefits were observed from the first genetic effort necessary in smaller piglets to increase their gut reproductive cycle, with Bacillus subtilis—541 (BSU) the maturity and robustness and their intestinal differentiation. improvements were not seen until the third complete pro- ductive cycle. Moreover, B. amyloliquefaciens (BAM) also Piglet performance during lactation increased the survival of piglets at birth and the number of The impact of sow probiotic supplementation on litter per- piglets at weaning. The most relevant changes on mothers’ formance is variable in the literature. Despite many stud- intestinal microbiota were observed a few days after delivery ies reporting improvements in growth rates, the number of (d8 postpartum), suggesting the relevant role of probiotics weaned piglets, and reduction of clinical signs of diarrhea on the establishment of a new intestinal balance after labor. when supplementing Bacillus spp. probiotics (Alexopoulos et Microbial shifts were also observed in the piglets, with a al., 2001; Alexopoulos et al., 2004; Taras et al., 2005; Stamati clearer impact during the post-weaning than in the lactation et al., 2006; Baker et al., 2013; Kritas et al., 2015; Hayakawa period. In this regard, correlations between the microbial Saladrigas-García et al. 17 groups of the mothers and the piglets were higher with Azagra-Boronat, I., A. Tres, M. Massot-Cladera, A. Franch, M. Castell, the microbiota of the weaned piglet (d33) compared to the F. Guardiola, F. J. Pérez-Cano, and M. J. Rodríguez-Lagunas. 2020. suckling pig (d21), reinforcing the idea of an early maternal Lactobacillus fermentum CECT5716 supplementation in rats carry-over. Tested probiotic strains were also shown some during pregnancy and lactation impacts maternal and offspring lipid profile, immune system and microbiota. Cells 9(3):575–595. impact on milk composition. In summary, results demon- doi:10.3390/cells9030575. strate the potential benefits of supplementing probiotics, Baker, A. A., E. Davis, J. D. Spencer, R. Moser, and T. Rehberger. 2013. and particularly a strain of Bacillus amyloliquefaciens, to The effect of a Bacillus-based direct-fed microbial supplemented to improve prolificacy, re-establish mother gut microbiota after sows on the gastrointestinal microbiota of their neonatal piglets. J. labor, reinforce maternal imprinting and improve the perfor- Anim. Sci. 91:3390–3399. doi:10.2527/jas.2012-5821. mance of piglets during lactation. Barba-Vidal, E., S. M. Martín-Orúe, and L. Castillejos. 2019. Practi- cal aspects of the use of probiotics in pig production: a review. Livest. Sci. 223:84–96. doi: 10.1016/j.livsci.2019.02.017. Avail- Supplementary Data able from: https://www.sciencedirect.com/science/article/pii/ Supplementary data are available at Journal of Animal Science S1871141318302646. Belzer, C., and W. M. de Vos. 2012. Microbes inside—from diversi- online. ty to function: the case of Akkermansia. ISME J. 6:1449–1458. doi:10.1038/ismej.2012.6. Betancur, C., Y. Martínez, G. Tellez-Isaias, R. Castillo, and X. Ding. Acknowledgments 2021. Effect of oral administration with Lactobacillus plantarum This research was co-funded by the Ministry of Economy, CAM6 strain on sows during gestation-lactation and the derived Industry, and Competitiveness (MINECO) of Spain (project impact on their progeny performance. S. Chen, editor. Mediators code AGL2016-75463-R) within the framework of Proyectos Inflamm. 2021:6615960. doi:10.1155/2021/6615960. I+D+I Convocatoria RETOS 2016 and the State Plan for Bhandari, P., P. Rishi, and V. Prabha. 2016. Positive effect of probi- otic Lactobacillus plantarum in reversing LPS-induced infertility Scientific and Technical Research and Innovation. M.S. re- in a mouse model. J. Med. Microbiol. 65:345–350. doi:10.1099/ ceived an FPI grant from the Spanish Ministry of Science and jmm.0.000230. Innovation (grant number BES-2017-080018). M.D. received Blavi, L., J. N. Jørgensen, and H. H. Stein. 2019. Effects of Bacillus support from Opening Sphere UAB-CEI to Postdoctoral amyloliquefaciens and Bacillus subtilis on ileal digestibility of Fellows (project H2020-MSCA-COFUND-2014). M.F. re- AA and total tract digestibility of CP and gross energy in diets ceived financial support from the Ministry of Agriculture of fed to growing pigs. J. Anim. Sci. 97:727–734. doi:10.1093/jas/ the Czech Republic (QK1810463). D.S.O. received financial sky432. support from the UAB-Banco de Santander Talent Program. Böhmer, B. M., W. Kramer, and D. A. Roth-Maier. 2006. Dietary probi- We also thank Chr.Hansen A/S for providing the material otic supplementation and resulting effects on performance, health (probiotics) to carry out this trial. status, and microbial characteristics of primiparous sows. J. Anim. Physiol. Anim. Nutr. (Berl). 90:309–315. doi:10.1111/j.1439- 0396.2005.00601.x. Conflict of Interest Statement Bravo-Santano, N., E. Juncker Boll, L. Catrine Capern, T. M. Cieplak, E. Keleszade, M. Letek, and A. Costabile. 2020. Comparative eval- The authors declare no real or perceived conflicts of interest. uation of the antimicrobial and mucus induction properties of selected Bacillus strains against enterotoxigenic Escherichia coli. Antibiot 9(12):849–859. doi:10.3390/antibiotics9120849. Literature Cited Callahan, B. J., P. J. McMurdie, M. J. Rosen, A. W. Han, A. J. A. John- Alexopoulos, C., I. E. Georgoulakis, A. Tzivara, S. K. Kritas, A. Sio- son, and S. P. Holmes. 2016. DADA2: high-resolution sample in- chu, and S. C. Kyriakis. 2004. Field evaluation of the efficacy of ference from Illumina amplicon data. Nat. Methods 13:581–583. a probiotic containing Bacillus licheniformis and Bacillus subtilis doi:10.1038/nmeth.3869. spores, on the health status and performance of sows and their lit- Chen, L., Y. Xu, X. Chen, C. Fang, L. Zhao, and F. Chen. 2017. The ma- ters. J. Anim. Physiol. Anim. Nutr. (Berl) 88:381–392. doi:10.1111/ turing development of gut microbiota in commercial piglets during j.1439-0396.2004.00492.x. the weaning transition. Front. Microbiol. 8:1–13. doi:10.3389/ Alexopoulos, C., A. Karagiannidis, S. K. Kritas, C. Boscos, I. E. Geor- fmicb.2017.01688. Available from: http://journal.frontiersin.org/ goulakis, and S. C. Kyriakis. 2001. Field evaluation of a bioreg- article/10.3389/fmicb.2017.01688/full. ulator containing live Bacillus cereus spores on health status and Chen, X., J. Xu, E. Ren, Y. Su, and W. Zhu. 2018. Co-occurrence performance of sows and their litters. J. Vet. Med. Ser. A 48:137– of early gut colonization in neonatal piglets with microbiota 145. doi:10.1046/j.1439-0442.2001.00342.x. in the maternal and surrounding delivery environments. An- Antwis, R. E., K. L. Edwards, B. Unwin, S. L. Walker, and S. Shultz. 2019. aerobe 49:30–40. doi:10.1016/j.anaerobe.2017.12.002. Avail- Rare gut microbiota associated with breeding success, hormone me- able from: http://www.sciencedirect.com/science/article/pii/ tabolites and ovarian cycle phase in the critically endangered eastern S1075996417302251. black rhino. Microbiome 7:27. doi:10.1186/s40168-019-0639-0. Crespo-Piazuelo, D., G. E. Gardiner, S. Ranjitkar, M. A. Bouwhuis, R. Apic, I., B. Savic, I. Stancic, M. Zivkov-Balas, J. Bojkovski, S. Jovanovic, Ham, J. P. Phelan, A. Marsh, and P. G. Lawlor. 2021. Maternal supple- I. Radovic, D. Zvekic, and Z. Maksimovic. 2014. Litters health sta- mentation with Bacillus altitudinis spores improves porcine offspring tus and growth parameters in the sows feeding diets supplemented growth performance and carcass weight. Br. J. Nutr. 127(3):403–420. with probiotic Actisaf Sc 47® within pregnancy or lactation. In: doi:10.1017/S0007114521001203. Available from: https://www. Proceedings of the International Symposium on Animal Science. cambridge.org/core/journals/british-journal-of-nutrition/article/ Belgrade-Zemun, Serbia. abs/maternal-supplementation-with-bacillus-altitudinis-spores-im- Ayala, L., R. Bocourt, M. Castro, M. Martínez, and M. Herrera. 2016. proves-porcine-offspring-growth-performance-and-car- Effect of the probiotic additive Bacillus subtilis and their endo- cass-weight/0B55BCFAB97EA75CB0C7D354DC8224EC. spores on milk production and immune response of lactating sows. Curtasu, M. V., P. K. Theil, and M. S. Hedemann. 2016. Metabolomic Cuba. J. Agric. Sci. 49:71–74. Available from: https://cjascience. profiles of colostrum and milk from lactating sows. J. Anim. Sci. com/index.php/CJAS/article/view/550. 94:272–275. doi:10.2527/jas.2015-9769. 18 Journal of Animal Science, 2022, Vol. 100, No. 6 Davis, E., J. Christianson, S. Anderson, T. Rehberger, and J. Sawall. Jeong, J., J. Kim, S. Lee, and I. Kim. 2015. Evaluation of Bacillus sub- 2020. Administration of a Bacillus probiotic to sows improves tilis and Lactobacillus acidophilus probiotic supplementation on growth response and health of their progeny after weaning. J. reproductive performance and noxious gas emission in sows. Ann. Anim. Sci. 98:93. Anim. Sci. 15:699–710. doi: 10.1515/aoas-2015-0018. Available Everaert, N., S. Van Cruchten, B. Weström, M. Bailey, C. Van Ginneken, from: https://content.sciendo.com/view/journals/aoas/15/3/arti- T. Thymann, and R. Pieper. 2017. A review on early gut maturation cle-p699.xml. and colonization in pigs, including biological and dietary factors Jiang, L., C. Feng, S. Tao, N. Li, B. Zuo, D. Han, and J. Wang. 2019. affecting gut homeostasis. Anim. Feed Sci. Technol. 233:89–103. Maternal imprinting of the neonatal microbiota colonization in in- doi: 10.1016/j.anifeedsci.2017.06.011. . https://www.sciencedirect. trauterine growth restricted piglets: a review. J. Anim. Sci. Biotech- com/science/article/pii/S037784011631063X. nol. 10:88. doi:10.1186/s40104-019-0397-7. Everard, A., C. Belzer, L. Geurts, J. P. Ouwerkerk, C. Druart, L. B. Bin- Jost, T., C. Lacroix, C. P. Braegger, F. Rochat, and C. Chassard. dels, Y. Guiot, M. Derrien, G. G. Muccioli, N. M. Delzenne, et al. 2014. Vertical mother–neonate transfer of maternal gut bacte- 2013. Cross-talk between Akkermansia muciniphila and intestinal ria via breastfeeding. Environ. Microbiol. 16:2891–2904. doi: epithelium controls diet-induced obesity. Proc. Natl. Acad. Sci. 10.1111/1462-2920.12238. 110:9066 LP–9069071. doi:10.1073/pnas.1219451110. Available Kelly, D., and S. Conway. 2005. Bacterial modulation of mucosal in- from: http://www.pnas.org/content/110/22/9066.abstract. nate immunity. Mol. Immunol. 42:895–901. doi:10.1016/j.mo- Ferret-Bernard, S., and I. Le Huërou-Luron. 2019. Development of limm.2004.12.003. the intestinal immune system in young pigs? Role of the microbi- Kenny, M., H. Smidt, E. Mengheri, and B. Miller. 2011. Probiot- al environment. In: The suckling and weaned piglet. Wageningen, ics—do they have a role in the pig industry? Animal 5:462–470. Netherlands: Wageningen Academic Publishers. p. 159–177 SE–6. doi:10.1017/S175173111000193X. Available from: https://www. Available from: https://doi.org/10.3920/978-90-8686-894-0_6 sciencedirect.com/science/article/pii/S175173111000193X. Gómez-Gallego, C., J. M. Morales, D. Monleón, E. du Toit, H. Kumar, Konstantinov, S. R., A. A. Awati, B. A. Williams, B. G. Miller, P. Jones, C. K. M. Linderborg, Y. Zhang, B. Yang, E. Isolauri, S. Salminen, et al. R. Stokes, A. D. L. Akkermans, H. Smidt, and W. M. De Vos. 2006. 2018. Human breast milk NMR metabolomic profile across spe- Post-natal development of the porcine microbiota composition and cific geographical locations and its association with the milk mi- activities. Environ. Microbiol. 8:1191–1199. doi:10.1111/j.1462- crobiota. Nutrients 10(10):1355–1375. doi:10.3390/nu10101355. 2920.2006.01009.x. González-Solé, F., L. Criado-Mesas, C. Villodre, W. C. García, M. Farré, Kritas, S. K., T. Marubashi, G. Filioussis, E. Petridou, G. Christodou- E. Borda, F. J. Pérez-Cano, J. M. Folch, D. Solà-Oriol, and J. F. Pérez. lopoulos, A. R. Burriel, A. Tzivara, A. Theodoridis, and M. Písko- 2020. Porcine Digestible Peptides (PDP) in weanling diets regulates riková. 2015. Reproductive performance of sows was improved the expression of genes involved in gut barrier function, immune by administration of a sporing bacillary probiotic (Bacillus sub- response and nutrient transport in nursery pigs. Anim. an open ac- tilis C-3102). J. Anim. Sci. 93:405–413. doi:10.2527/jas.2014- cess J. from MDPI. 10:2368. doi:10.3390/ani10122368. Available 7651. from: https://pubmed.ncbi.nlm.nih.gov/33321976. Lahti, L., S. Shetty, T. Blake, and J. Salojarvi. 2017. Microbiome R pack- Grazul, H., L. L. Kanda, and D. Gondek. 2016. Impact of probiotic sup- age. London (UK): Tools Microbiome Anal. R. plements on microbiome diversity following antibiotic treatment Lan, R., and I. Kim. 2020. Enterococcus faecium supplementation in of mice. Gut Microbes 7:101–114. doi:10.1080/19490976.2016. sows during gestation and lactation improves the performance of 1138197. sucking piglets. Vet. Med. Sci. 6:92–99. doi:10.1002/vms3.215. Hansen, C. H. F., D. S. Nielsen, M. Kverka, Z. Zakostelska, K. Klimeso- Larsen, N., L. Thorsen, E. N. Kpikpi, B. Stuer-Lauridsen, M. D. Can- va, T. Hudcovic, H. Tlaskalova-Hogenova, and A. K. Hansen. tor, B. Nielsen, E. Brockmann, P. M. F. Derkx, and L. Jespersen. 2012. Patterns of early gut colonization shape future immune re- 2014. Characterization of Bacillus spp. strains for use as probiotic sponses of the host. PLoS One 7:e34043–e34043. doi:10.1371/ additives in pig feed. Appl. Microbiol. Biotechnol. 98:1105–1118. journal.pone.0034043. doi:10.1007/s00253-013-5343-6. Hayakawa, T., T. Masuda, D. Kurosawa, and T. Tsukahara. 2016. Di- Li, Y., Y. Guo, Z. Wen, X. Jiang, X. Ma, and X. Han. 2018. Weaning etary administration of probiotics to sows and/or their neonates stress perturbs gut microbiome and its metabolic profile in piglets. improves the reproductive performance, incidence of post-wean- Sci. Rep. 8:1–12. doi:10.1038/s41598-018-33649-8. ing diarrhea and histopathological parameters in the intestine of Liu, H., C. Hou, N. Li, X. Zhang, G. Zhang, F. Yang, X. Zeng, Z. weaned piglets. Anim. Sci. J. 87:1501–1510. doi:10.1111/asj.12565. Liu, and S. Qiao. 2019a. Microbial and metabolic alterations in He, Y., C. Jinno, K. Kim, Z. Wu, B. Tan, X. Li, R. Whelan, and Y. Liu. gut microbiota of sows during pregnancy and lactation. FASEB J. 2020. Dietary Bacillus spp. enhanced growth and disease resistance 33:4490–4501. doi:10.1096/fj.201801221RR. of weaned pigs by modulating intestinal microbiota and systemic Liu, H., X. Zeng, G. Zhang, C. Hou, N. Li, H. Yu, L. Shang, X. Zhang, immunity. J. Anim. Sci. Biotechnol. 11:101. doi:10.1186/s40104- P. Trevisi, F. Yang, et al. 2019b. Maternal milk and fecal microbes 020-00498-3. guide the spatiotemporal development of mucosa-associated mi- Holman, D. B., B. W. Brunelle, J. Trachsel, and H. K. Allen. 2017. Me- crobiota and barrier function in the porcine neonatal gut. BMC ta-analysis to define a core microbiota in the swine gut. mSystems Biol. 17:106. doi:10.1186/s12915-019-0729-2. 2:1–14. doi:10.1128/msystems.00004-17. Luise, D., M. Bertocchi, V. Motta, C. Salvarani, P. Bosi, A. Luppi, F. Hu, J., Y. H. Kim, and I. H. Kim. 2021. Effects of two bacillus strains Fanelli, M. Mazzoni, I. Archetti, G. Maiorano, et al. 2019. Ba- probiotic supplement on reproduction performance, nutrient di- cillus sp. probiotic supplementation diminish the Escherichia gestibility, blood profile, fecal score, excreta odor contents and coli F4ac infection in susceptible weaned pigs by influencing the fecal microflora in lactation sows, and growth performance in intestinal immune response, intestinal microbiota, and blood me- sucking piglets. Livest. Sci. 244:104293. doi: 10.1016/j.livs- tabolomics. J. Anim. Sci. Biotechnol. 10:74. doi:10.1186/s40104- ci.2020.104293 . https://www.sciencedirect.com/science/article/pii/ 019-0380-3. S1871141319315306. Mach, N., M. Berri, J. Estellé, F. Levenez, G. Lemonnier, C. Denis, J. Hu, J., Y. Nie, J. Chen, Y. Zhang, Z. Wang, Q. Fan, and X. Yan. 2016. J. Leplat, C. Chevaleyre, Y. Billon, J. Doré, et al. 2015. Early-life Gradual changes of gut microbiota in weaned miniature piglets. establishment of the swine gut microbiome and impact on host phe- Front. Microbiol. 7:1–15. doi:10.3389/fmicb.2016.01727. notypes. Environ. Microbiol. Rep. 7:554–569. doi:10.1111/1758- Jadamus, A., W. Vahjen, and O. Simon. 2001. Growth behaviour of 2229.12285. a spore forming probiotic strain in the gastrointestinal tract of McMurdie, P. J., and S. Holmes. 2013. Phyloseq: an R package for re- broiler chicken and piglets . Arch. für Tierernaehrung. 54:1–17. producible interactive analysis and graphics of microbiome census doi:10.1080/17450390109381962. data. PLoS One 8. doi:10.1371/journal.pone.0061217. Saladrigas-García et al. 19 Medina, M., E. Izquierdo, S. Ennahar, and Y. Sanz. 2007. Differential Saladrigas-García, M., M. D’Angelo, H. -L. Ko, P. Nolis, Y. Ra- immunomodulatory properties of Bifidobacterium logum strains: mayo-Caldas, J. M. Folch, P. Llonch, D. Solà-Oriol, J. F. Pérez, and relevance to probiotic selection and clinical applications. Clin. Exp. S. M. Martín-Orúe. 2021a. Understanding host-microbiota interac- Immunol. 150:531–538. doi:10.1111/j.1365-2249.2007.03522.x. tions in the commercial piglet around weaning. Sci. Rep. 11:23488. Menegat, M. B., J. M. DeRouchey, J. C. Woodworth, S. S. Dritz, M. doi:10.1038/s41598-021-02754-6. D. Tokach, and R. D. Goodband. 2019. Effects of Bacillus subtilis Saladrigas-García, M., M. D’Angelo, H. -L. Ko, S. Traserra, P. Nolis, C-3102 on sow and progeny performance, fecal consistency, and Y. Ramayo-Caldas, J. M. Folch, P. Vergara, P. Llonch, J. F. Pérez, fecal microbes during gestation, lactation, and nursery periods. J. et al. 2021b. Early socialization and environmental enrichment of Anim. Sci. 97:3920–3937. doi:10.1093/jas/skz236. lactating piglets affects the caecal microbiota and metabolomic re- Menegat, M. B., J. M. DeRouchey, J. C. Woodworth, M. D. Tokach, sponse after weaning. Sci. Rep. 11:6113. doi:10.1038/s41598-021- R. D. Goodband, and S. S. Dritz. 2020. Effects of oral administra- 85460-7. tion of Bacillus subtilis C-3102 to nursing piglets on preweaning Scharek-Tedin, L., S. Kreuzer-Redmer, S. O. Twardziok, B. Siepert, R. growth performance, fecal consistency, and fecal microbes. J. Swine Klopfleisch, K. Tedin, J. Zentek, and R. Pieper. 2015. Probiotic Heal. Prod. 28:12–20. treatment decreases the number of CD14-expressing cells in por- Mu, C., G. Bian, Y. Su, and W. Zhu. 2019. Differential effects of breed cine milk which correlates with several intestinal immune parame- and nursing on early-life colonic microbiota and immune status as ters in the piglets. Front. Immunol. 6:108. Available from: https:// revealed in a cross-fostering piglet model. Appl. Environ. Microbi- www.frontiersin.org/article/10.3389/fimmu.2015.00108. ol. 85(9):2510–2518. doi:10.1128/AEM.02510-18. Sommer, F., J. M. Anderson, R. Bharti, J. Raes, and P. Rosenstiel. 2017. Nasiri, A. H., A. Towhidi, M. Shakeri, M. Zhandi, M. Dehghan-Bana- The resilience of the intestinal microbiota influences health and daky, and M. G. Colazo. 2018. Effects of live yeast dietary supple- disease. Nat. Rev. Microbiol. 15:630–638. doi:10.1038/nrmi- mentation on hormonal profile, ovarian follicular dynamics, and cro.2017.58. reproductive performance in dairy cows exposed to high ambient Stamati, S., C. Alexopoulos, A. Siochu, K. Saoulidis, and S. C. Kyriakis. temperature. Theriogenology 122:41–46. doi:10.1016/j.theriog- 2006. Probiosis in sows by administration of Bacillus toyoi spores enology.2018.08.013. Available from: https://www.sciencedirect. during late pregnancy and lactation: effect on their health status/ com/science/article/pii/S0093691X18306393. performance and on litter characteristics. Int. J. Probiotics Prebi- Nowland, T. L., R. N. Kirkwood, V. A. Torok, K. J. Plush, and M. D. otics. 1:33. Barton. 2021. Characterisation of early microbial colonisers within Starke, I. C., R. Pieper, K. Neumann, J. Zentek, and W. Vahjen. 2013. the spiral colon of pre- and post-natal piglets. Life (Basel, Switzer- Individual responses of mother sows to a probiotic Enterococ- land) 11(4):312–326. doi:10.3390/life11040312. cus faecium strain lead to different microbiota composition Nowland, T., K. Plush, M. Barton, and R. Kirkwood. 2019. Develop- in their offspring. Benef. Microbes 4:345–356. doi:10.3920/ ment and function of the intestinal microbiome and potential impli- BM2013.0021. Available from: https://www.wageningenacademic. cations for pig production. Animals 9:76. doi:10.3390/ani9030076. com/doi/10.3920/BM2013.0021. Available from: https://www.mdpi.com/2076-2615/9/3/76. Tan, C., Z. Zhai, X. Ni, H. Wang, Y. Ji, T. Tang, W. Ren, H. Long, B. NRC. 2012. Nutrient requirements of swine. Eleventh R. National Deng, J. Deng, et al. 2018. Metabolomic profiles reveal potential Academies Press, Washington, DC. factors that correlate with lactation performance in sow milk. Sci. Oksanen, J., F. G. Blanchet, M. Friendly, R. Kindt, P. Legendre, D. Mc- Rep. 8:10712. doi:10.1038/s41598-018-28793-0. Glinn, P. R. Minchin, R. B. O’Hara, G. L. Simpson, et al. 2013. Taras, D., W. Vahjen, M. Macha, and O. Simon. 2005. Response of Package “vegan.” Community Ecol. Package version. 2:1–295. performance characteristics and fecal consistency to long-lasting Paulson, J. N., O. C. Stine, H. C. Bravo, and M. Pop. 2013a. Differ- dietary supplementation with the probiotic strain Bacillus cere- ential abundance analysis for microbial marker-gene surveys. Nat. us var. toyoi to sows and piglets. Arch. Anim. Nutr. 59:405–417. Methods 10:1200. doi:10.1080/17450390500353168. Paulson, J. N., H. Talukder, M. Pop, and H. C. Bravo. 2013b. metage- Taras, D., W. Vahjen, M. Macha, and O. Simon. 2006. Performance, nomeSeq: statistical analysis for sparse high-throughput sequencing. diarrhea incidence, and occurrence of Escherichia coli virulence Bioconductor Packag. 1:1–191. Available from: http://biocon- genes during long-term administration of a probiotic Enterococ- ductor.jp/packages/2.14/bioc/vignettes/metagenomeSeq/inst/doc/ cus faecium strain to sows and piglets. J. Anim. Sci. 84:608–617. metagenomeSeq.pdf. doi:10.2527/2006.843608x. Picone, G., M. Zappaterra, D. Luise, A. Trimigno, F. Capozzi, V. Motta, Thompson, C. L., B. Wang, and A. J. Holmes. 2008. The immediate en- R. Davoli, L. Nanni Costa, P. Bosi, and P. Trevisi. 2018. Metabo- vironment during postnatal development has long-term impact on lomics characterization of colostrum in three sow breeds and its gut community structure in pigs. ISME J. 2:739–748. doi:10.1038/ influences on piglets’ survival and litter growth rates. J. Anim. Sci. ismej.2008.29. Biotechnol. 9:23. doi:10.1186/s40104-018-0237-1. Whittaker, R. H. 1960. Vegetation of the Siskiyou mountains, Oregon Quast, C., E. Pruesse, P. Yilmaz, J. Gerken, T. Schweer, P. Yarza, J. Pe- and California. Ecol. Monogr. 30:279–338. doi:10.2307/1943563. plies, and F. O. Glöckner. 2013. The SILVA ribosomal RNA gene Available from: https://esajournals.onlinelibrary.wiley.com/doi/ database project: improved data processing and web-based tools. abs/10.2307/1943563. Nucleic Acids Res. 41:D590–D596. doi:10.1093/nar/gks1219. Yang, H., Y. Xiang, K. Robinson, J. Wang, G. Zhang, J. Zhao, and Y. R Core Team. 2021. R: A language and environment for statistical com- Xiao. 2018. Gut microbiota is a major contributor to adiposity puting. R Foundation for Statistical Computing, Vienna, Austria. in pigs. Front. Microbiol. 9:3045. doi:10.3389/fmicb.2018.03045. https://www.R-project.org/. Available from: https://www.frontiersin.org/article/10.3389/ Reyes-Camacho, D., E. Vinyeta, J. F. Pérez, T. Aumiller, L. Criado, L. fmicb.2018.03045. M. Palade, I. Taranu, J. M. Folch, M. A. Calvo, J. D. Van der Klis, Zhang, Q., J. Li, M. Cao, Y. Li, Y. Zhuo, Z. Fang, L. Che, S. Xu, B. et al. 2020. Phytogenic actives supplemented in hyperprolific sows: Feng, Y. Lin, et al. 2020. Dietary supplementation of Bacillus effects on maternal transfer of phytogenic compounds, colostrum subtilis PB6 improves sow reproductive performance and reduc- and milk features, performance and antioxidant status of sows and es piglet birth intervals. Anim. Nutr. 6:278–287. doi: 10.1016/j. their offspring, and piglet intestinal gene expression. J. Anim. Sci. aninu.2020.04.002. Available from: https://www.sciencedirect. 98. doi:10.1093/jas/skz390. com/science/article/pii/S2405654520300615.