β-mannanase-supplemented diets reduced by 85 kcal of metabolizable energy/kg containing xylanase promotes benefits in fecal alpha diversity in lactating sows

β-mannanase-supplemented diets reduced by 85 kcal of metabolizable energy/kg containing xylanase promotes benefits in fecal alpha diversity in lactating sows | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article β-mannanase-supplemented diets reduced by 85 kcal of metabolizable energy/kg containing xylanase promotes benefits in fecal alpha diversity in lactating sows Janaína Paolucci Sales Lima, Eliane Fátima Rocha Engelsing, Jansller Luiz Genova, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4449417/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Enzyme-supplemented diets can influence the intestinal microbiome in an intricate interplay with the immune system. The effects of β-mannanase supplementation in metabolizable energy (ME)-reduced diets containing xylanase were investigated on cytokine profile and fecal microbiota in lactating sows (n = 60, 248.4 ± 2.4 kg) assigned in a randomized block design to 1 of 3 dietary treatments: a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Serum cytokines concentrations were determined on day 18 of lactation. On day 21, fecal microbiota composition was characterized by 16S rRNA gene sequencing. Sows on CD85 had higher alpha diversity richness than CD100 based on the Simpson index. Acutalibacteraceae family was more abundant in sows fed CD100 than CD85 but CAG-508 and NSJ_53 families exhibited higher abundance in sows fed CD85 than CD100. Fimenecus genus exhibited lower abundance in sows on CD85 compared to CD40 or CD100. In conclusion, a diet supplemented with β-mannanase reduced by 85 kcal/kg containing xylanase during lactation can inhibit harmful bacteria, leading to changes in fecal alpha diversity in sows. Biological sciences/Microbiology/Communities Biological sciences/Immunology/Cytokines Biological sciences/Zoology/Animal physiology anti-inflammatory cytokines carbohydrases exogenous enzymes fecal microbiota lactating sows pro-inflammatory cytokines Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Plant-based ingredients commonly used in pig diets contain significant amounts of antinutritional compounds (e.g. β-mannans, xylans, trypsin inhibitors, antigenic factors and phytates) 1 , 2 , 3 . These components are not effectively digested by the pig's endogenous enzymes. To mitigate their adverse effects, exogenous enzymes are supplemented to diets to improve digestion and absorption of nutrients in non-ruminant animals 4 , 5 , 6 . Furthermore, this nutritional strategy enhances the digestibility of nutrients and the gain to feed ratio 6 , allowing a reduction in ME in the diet formulation. Lactation constitutes a critical phase in the reproductive cycle of sows, in which high dietary requirements for maintenance, growth, and milk production increase the risk of undue mobilization of body reserves. Additionally, it is imperative to understand the changes during lactation when implementing nutritional strategies, offering specific insights into potential effects on the health of sows and their progeny. Therefore, supplementing β-mannanase can be a viable strategy to mitigate the restrictions that limit feed digestion (e.g. feeding pattern and lactation capacity) in lactating sows. Previously, it was reported that dietary supplementation of β-mannanase increased nutrient digestibility and mitigated body weight loss in lactating sows 7 . Previous studies involving pig 5 , 8 and piglets 3 have attributed the decrease in immune response induced by dietary intake and the consequent reduction in energy expenditure for immune system activation to the hydrolysis of β-mannans. Furthermore, there are discrepancies regarding the xylanase's role in the release of phytic acid and its ability to modulate the proliferation of pathogenic microorganisms by reducing the viscosity of digesta in pig 9 , 10 . Considering the available evidence, the impact of dietary supplementation with exogenous enzymes in ME-reduced diets, alone or in combination, on favorable aspects of the immune response and the fecal microbiota in sows remains uncertain. Notably, ME-reduced diets have previously been documented to induce alterations in the fecal microbiome in pig, regardless of combined enzymes on microbial population abundance 6 . This reflects the ability of β-mannanase-xylanase supplementation to promote favorable conditions for intestinal microbial ecology. For example, improving the digestibility of targeted non-starch polysaccharides (arabinoxylan, mannans) 10 and promoting diversity beneficial bacteria 11 , resulting in beneficial modulation of the intestinal microbiota. This modulation manifests itself as a reduction in pathogenic bacteria and attenuated intestinal inflammation, as evidenced by studies conducted by Kiarie et al. 8 , who assessed the effect of β-mannanase supplementation and Genova et al. 6 , 11 , who tested the combined effect of these enzymes in diets fed to pig. Thus, dietary supplementation with β-mannanase-xylanase may hold economic, environmental, nutritional and health impact. Here, the study was conducted based on the hypothesis that supplementation of β-mannanase in ME-reduced diets containing xylanase would save energy content by acting on antinutrients compounds, reflecting changes in the cytokine profile and fecal microbiome. Therefore, this study aimed to assess the associated effects of these enzymes in diets with reduced ME on the profile of the fecal microbiota and cytokine concentrations in lactating sows. Results Serum cytokine concentrations It was no difference ( P > 0.05) among dietary treatments on serum cytokines concentrations in lactation sows (Fig. 1 ). Conversely, the cytokines IL-12/IL-23p40 exhibited the highest concentration among all evaluated (Fig. 2 ). Sows fed CD40 diet showed serum concentrations of cytokines of 74.86 pg/mL for IL-1β, 9.497 pg/mL for IL-4, 119.1 pg/mL for IL-6, 4.231 pg/mL for IL-8/CXCL8, 20.20 pg/mL for IL-10, 167.6 pg/mL for IL-12/IL23p40, 1.481 pg/mL for IFN-α, 3.761 pg/mL for IFN-γ, and 84.60 pg/mL for TNF-α. Sows fed CD85 diet showed serum concentrations of cytokines of 48.09 pg/mL for IL-1β, 8.280 pg/mL for IL-4, 83.43 pg/mL for IL-6, 18.200 pg/mL for IL-8/CXCL8, 39.07 pg/mL for IL-10, 150.6 pg/mL for IL-12/IL23p40, 0.6210 pg/mL for IFN-α, 4.253 pg/mL for IFN-γ, and 90.39 pg/mL for TNF-α. In the group fed CD100 diet, serum concentrations of cytokines were 113.10 pg/mL for IL-1β, 11.580 pg/mL for IL-4, 81.90 pg/mL for IL-6, 3.520 pg/mL for IL-8/CXCL8, 2.832 pg/mL for IL-10, 126.0 for IL-12/IL23p40, 1.069 pg/mL for IFN-α, 3.263 pg/mL for IFN-γ, and 107.1 pg/mL for TNF-α. Fecal microbiota Sows fed CD85 diet present ( P = 0.014) higher alpha diversity richness than those fed CD100 diet based on the Simpson index (0.98 vs. 0.97, Fig. 3 D). The remain alpha diversity indices was not altered by the diets (Chao1, observed OTUs, Fisher, Simpson's, Shannon, and Pielou) (Fig. 3 ). No effect was observed on beta diversity assessed using the Bray-Curtis ( P = 0.527), Jaccard ( P = 0.526), UniFrac ( P = 0.687), and Weighted UniFrac ( P = 0.547) parameters (Fig. 4 ). The phyla, classes, orders, families, genera, and species with an average relative abundance above 2% in at least one of the tested groups were depicted in the graphs. In the fecal samples analyzed, the most abundant phylum was Firmicutes followe by Bacteroidota, Spirochaetota, Actinobacteriota, and Cyanobacteria (Fig. 5 A). In addition, the classes Clostridia, Bacilli, Bacteroidia, Negativicutes, Spirochaetia, Coriobacteriia, and Vampirovibrionia showed the highest abundances (Fig. 5 B). The most abundant orders were Christensenellales, Oscillospirales, Peptostreptococcales, Clostridiales, Lachnospirales, Bacteroidales, TANB77, Lactobacillales, Treponematales, Coriobacteriales, Haloplasmatales_A, Gastranaerophilales, and Erysipelotrichales (Fig. 5 C). The families with the highest relative abundance were Peptostreptococcaceae, Clostridiaceae, Oscillospiraceae, Lachnospiraceae, CAG-74, CAG-508, Treponemataceae, Lactobacillaceae, Muribaculaceae, Ruminococcaceae, Acutalibacteraceae, Turicibacteraceae, NSJ-53, Christensenellaceae, Gastranaerophilaceae, Erysipelotrichaceae, and Bacteroidaceae (Fig. 5 D). The most abundant genera were Clostridium , Terrisporobacter , CAG-83 , Romboutsia , Sodaliphilus, GCA-900199385 , Limivicinus , Onthenecus , Limosilactobacillus , Turicibacter , Merdicola , Fimivivens , and Fimenecus (Fig. 5 E). Species that showed relative abundance were Sodaliphilus sp004557565 , GCA-900199385 sp900322155 , Clostridium baratii , Limivicinus sp002320035 , Onthenecus sp900199405 , Turicibacter sp001543345 , CAG-83 sp900549395 , NSJ-53 sp014384795 , NSJ-63 sp014384805 , Merdicola sp001915925 , Firmivivens sp900113995 , Clostridium butyricum , Fimenecus sp004556705 (Fig. 5 F). No significant difference was observed between the groups for Firmicutes:Bacteroidetes ratio (Fig. 6 ). The families exhibited significant differences between the CD85 vs. CD100 diets. The Acutalibacteraceae family was more abundant in sows fed CD100 diet than in those fed CD85 diet ( P = 0.044, Fig. 7 A). In addition, sows fed CD85 diet had a higher abundance of the CAG_508 ( P = 0.012, Fig. 7 B) and NSJ_53 ( P = 0.044, Fig. 7 C) families than those fed the CD100 diet. The Fimenecus genus exhibited lower abundance in sows that received the CD85 dietary treatment compared to sows fed CD40 ( P = 0.007, Fig. 8 A) or CD100 diets ( P = 0.005, Fig. 8 A), while the NSJ-53 genus showed higher abundance in sows fed CD85 diet than in those fed CD100 diet ( P = 0.044, Fig. 8 B). Similarly, these results followed for the Fimenecus sp004556705 (Fig. 9 A) and NSJ-53 sp014384795 (Fig. 9 B) species. Discussion Serum cytokine concentrations Cytokine concentrations can be used to differentiate between normal physiological processes and pathological processes (e.g. inflammation) 12 . Investigating the variability in sows' cytokine profiles can provide valuable information, because cytokines play crucial roles in immune response and inflammation regulation and, therefore, maintaining their equilibrium is pivotal for health and fortification against microbial dysbiosis. However, the present study demonstrated that β-mananase supplementation in ME-reduced diets containing xylanase had no effect on the concentrations of these signaling molecules in the serum of lactating sows. Overall, this can be justified because the connection between dietary enzymes and host reactions depends on the impact of specific substrates on the physiology of digestion and how exogenous dietary enzymes can alter the degradation or modification of these substrates in the gastrointestinal tract 8 , affecting immune responses at the blood level. The impact of improving the energy matrix did not interfere with the animal's immune status, which can be substantial; for example, sows fed a diet with a low ratio of starch and fat significantly increased the contents of IL-1β, IL-6, and TNF-α in plasma samples during parturition 13 . It is reasonable to infer that when formulating the diet, components related to the construction of the immune system should be considered, particularly focusing on dietary strategies that could potentially lead to excessive immune activation and hinder animal production efficiency 14 . This indicates that immune system activation comes at a significant cost, resulting in increased production of immune cells and signaling molecules, as well as reduced efficiency in affected tissues, which ultimately impairs the body's ability to utilize nutrients for protein deposition. Systematic review showed that β-mannanase supplementation reduced the inflammatory responses caused by β-mannan and released prebiotic-like products in the intestinal tract 8 . In this context, the pro-inflammatory IL-12/23p40 was used to assess the activation of innate immune response and possible cytokine storm 15,16 . Therefore, they stimulate the production of other cytokines across different cells are categorized as level 1 cytokines 17 . In the present study, regardless of the diets, there was a marked increase in IL-12/23p40 concentrations. As a result, we hypothesized that this could be indicative of clinical symptoms. Splichalova and Splichal 18 reported a positive correlation between concentrations of the pro-inflammatory cytokine IL-12/23p40 and clinical symptoms of enteric infection and sepsis. In the context of the connection between the immune system and the fecal microbiota, multiple investigations have substantiated the impact of cytokines, for example, previous studies 19,20 suggest that the immune system actively controls and regulates the fecal microbiota. This regulation is influenced by factors such as gender and specific cytokines, with the strongest interactions observed in the intestine 21 . Therefore, in the present study, our hypothesis that β-mannanase supplementation could modify the abundance, diversity and composition of the fecal microbiome in lactating sows was confirmed, although this did not reflect changes in serum cytokine concentrations. Fecal microbiota The fecal microbiota is influenced by several factors including host genetics 22 , diet 23 , and the immune system 24 . The microbiota plays important roles on animal physiology including inflammation process, metabolic syndromes 25 , energy metabolism 26 , and immune responses 27 . The present study showed that the β-mannanase supplementation in ME-reduced diets containing xylanase had an impact on the diversity of fecal microbial communities. The fecal microbial communities of lactating sows fed CD85 diet exhibited higher alpha diversity compared to those fed CD100. This indicates that there is a positive correlation between the microbiota composition and alpha diversity of the sow intestinal microbiota and factors such as nutrient digestibility (e.g. the mechanisms of action of exogenous enzymes), average daily gain, and body weight 28,29 . Consistent with this, Vojinovic et al. 30 provided insights into the role of the microbiota in metabolism and support the potential of the intestinal microbiota as a target for therapeutic and preventive interventions. Additionally, evaluating the relationship between the Firmicutes and Bacteroidetes phyla in the fecal microbiota of lactating sows, they did not suffer the effects of the tested treatments. Regardless of the diet, the phylum-level analysis of the microbiota revealed that the Firmicutes phylum was predominant with a relative abundance of over 80%. These results were similar to what others have observed in studies involving sows 1,31 . Furthermore, Turnbaugh et al. 32 demonstrated through research using a mouse model that an increase in Firmicutes is a means of enhancing the body's ability to acquire energy from the diet, a potential advantage in helping to prepare the body for the energy demands of lactation. Regardless of the diet, analysis of the microbiota at the class level revealed that the Clostridia class was predominant in all groups of lactating sows, which is consistent with the results of previous studies with sows 31,33 . Additionally, the Clostridia class of bacteria has a multitude of enzymes (e.g. butyryl-CoA:acetate-CoA transferase) that facilitate the breakdown of polysaccharides into short-chain fatty acids (SCFA). Consistently, research on Clostridium genera has shown that they can produce butyrate 34,35,36 and have associated butyrate with the prevention and treatment of intestinal disorders, by reducing inflammation in the host's intestine, allowing intestinal epithelial cells to use it as a source of energy 37 . Additionally, in this investigation, significant differences in the abundance of Clostridium CAG-508 were identified in lactating sows fed CD85 diet compared to those fed CD100. As a result, we hypothesize that this bacterium, which synthesizes SCFA, could provide a considerable portion of the energy needed by colonic epithelial cells and the intestinal immune system 38 , and it plays roles in anti-inflammatory responses and antioxidant processes. These findings further support the result of Cheng et al. 39 , who suggested the positive or negative correlation between alterations in gut microbiota composition and serum immune status in sows, hypothesizing that the interaction between intestinal microbiota and intestinal permeability may be one of the potential mechanisms linking intestinal microbiota to metabolic disorders in sows during early lactation. Sows fed the CD100 diet exhibited a higher relative abundance of the Acutalibacteraceae family compared to those fed the CD85 diet. Previous studies have suggested a positive correlation between the abundance of Acutalibacteraceae family and bile salt hydrolase-carrying bacteria in dairy cows 40 , an intestinal bacteria‐producing enzyme that has a negative impact on host fat digestion and energy harvest 41 . Our research hypothesized that the higher abundance of Acutalibacteraceae family in CD100-fed sows may enhance the hydrolysis of bile salts by their enzymes, potentially leading to reduced lipid absorption and loss of body weight. It is noteworthy that the microbial production of bile acids in pigs helps protect the intestinal mucosa, reduce inflammation, and regulate liver function 42 . However, the information available on the relevance of this family to the porcine intestinal microbiota is limited 43 . On the other hand, the sows fed the CD85 diet exhibited a higher relative abundance of the CAG-508 and NSJ_53 families compared to those fed the CD100 diet. The study on the intestinal mycobiota revealed that the CAG-508 bacterial family frequently interacts with fungi, suggesting complex interactions between bacteria and fungi in the gut of Caprinae animals 44 . It is reasonable to infer that our finding indicates potential relationships between the bacterial microbiota and the mycobiota. Consistent with this hypothesis, Yang et al. 45 further demonstrated that triple interactions among the intestinal microbiota, mycobiota, and host immunity can lead to targeted interventions and enhance the efficacy of interventions in the host's intestinal microbiome and immune system. NSJ 53 is a bacterium of the Christensenellaceae family. Previous experiments by Waters and Ley 46 and Alemán et al. 47 have suggested that Christensenellaceae, an intestinal commensal bacterial family, is a potential probiotic candidate for intervention. For example, researches have shown promising results for its potential intervention in obesity and inflammatory bowel diseases in the human intestine 46 , as well as its ability to influence fat and carbohydrate metabolism 47 . In general, we can infer that the CG-508 and NSJ_53 families play important roles in metabolic regulation and maintenance of intestinal homeostasis in pigs. After data analysis, it was concluded that the available information on the relevance of the Fimenecus genus to the pig gut microbiota is limited, especially on how it interacts with intestinal biodiversity and affects the host immune system. Therefore, further research is needed to clarify and understand how the Fimenecus genus relates to microbial composition. However, in studies on human fecal microbiota, the genus Fimenecus had high levels of pectin-degrading activities, including arabinases, galacturonases, and galacturonidases 48 . Therefore, regarding the potential of pectin for pig nutrition and health, Wiese 49 noted its potential to improve growth and general well-being, influencing the intestinal microbiome, the immune system and reducing the presence of pathogens and viruses. Analyzing the findings observed in this study, a potential explanation for these effects is that a diet containing β-mannanase and xylanase during the lactation period hinders the physiological activities of undesirable bacterial species, substantially altering upon analyzing the results of this study, it was deduced that a diet with xylanase (valorization of 40 kcal of ME/kg diet) and β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet) during lactation may inhibit harmful bacteria, leading to changes in fecal microbiota. Conclusions The present study proposes that the β-mannanase supplementation in diets reduced in 85 kcal metabolizable energy/kg containing xylanase fed to lactation sows to the positive impact of regulation of cytokines and exerts influence on the profile of the fecal microbiome. In addition, further research is needed to investigate the mechanisms underlying the regulation of the intestinal microbiota in lactating sows. Material and Methods Ethics statement The experiment was conducted on a commercial farm of Western Paraná (Toledo, PR, Brazil), in the weaned piglet production unit. The protocol for the experiment was approved by the Animal Use Committee of the University (nº 17-2022). All methods were carried out in accordance with relevant guidelines and regulations. All methods were reported in accordance with ARRIVE guidelines (https://arriveguidelines.org/arrive-guidelines). Animals, experimental design, housing and dietary treatments A total of 60 hybrid sows at 110 days of gestation (248.4 ± 2.4 kg BW) from a commercial lineage (Landrace × Large White) were selected for the study. The sows were housed in farrowing crates for a period of 26 days (5 days of acclimatization, and 21 days of lactation). Sows were allocated in a randomized block design to 1 of 3 dietary treatments, resulting in 15 animals per round, totaling 4 rounds with 5 crate replicates per treatment in each round and 1 sow per crate as the experimental unit. Sows were classified according to their BW as light-, medium-, or heavy-weight and farrowing order in 3 groups: P1, primiparous (13 sows); P2, sows with two or three farrowings (29 sows); and P3, sows with four or five farrowings (18 sows). The average farrowing order of sows was 2.8, 2.6, and 2.7 to the CD40, CD85, and CD100-fed group, respectively. Approximately 5 days before farrowing, sows were transferred into individual conventional farrowing crates (2.4 × 1.6 × 1.3 m) with slatted metal floor and equipped with front gutter feeders and nipple drinkers. A heated creep area (0.98 × 0.68 × 0.66 m) was accessible to piglets to maintain thermal comfort between 28°C and 32°C. The farrowing crates were installed in a commercial facility with a concrete floor and side curtains. The ambient temperature (25.3 ± 0.4°C) and relative humidity (60.0 ± 1.8%) was recorded throughout the experimental period using a datalogger (Vketech, model temperature instruments) positioned at the center of the facility. The experimental diets were corn and soybean meal-based with industrial amino acids, and formulated to meet the nutritional requirements of the animals 50 . The diets were provided in mash form varying only for soybean oil and inert (kaolin) contents (Table 1). The experimental diets were provided according to the reproductive phase of the sows, starting at 110 days of gestation and ending at 21 days of lactation. In the pre-partum period (5 days before farrowing), the feeding was controlled, providing 2 kg of diet per animal, once a day. Daily diet was previously weighed and stored in identified plastic bags. On parturition day, sows were not fed. Throughout lactation, sows were fed 4 times a day (07h30, 11h30, 14h00, and 17h30), and the average daily diet consumption was 7 kg. The tested dietary treatments were: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Table 1 . Composition of diets fed to lactating sows (as fed basis, %). a Content per kg of premix: vitamin A, 2080000 IU/kg; vitamin D 3 , 312000 IU/kg; vitamin E, 11700 IU/kg; vitamin K 3 , 520 mg/kg; vitamin B 1 , 260 mg/kg; vitamin B 2 , 1040 mg/kg; vitamin B 6 , 390 mg/kg; vitamin B 12 , 5200 mg/kg; niacin, 6500 mg/kg; pantathenic acid, 4160 mg/kg; folic acid, 260 mg/kg; biotin, 65 mg/kg; choline chloride, 156 g/kg; Zn oxide, 23.94 g/kg; Mn sulfate, 8820 mg/kg; Fe sulfate, 17.66 g/kg; Cu sulfate, 2640 mg/kg; iodine, 217.80 mg/kg; sodium selenite, 79.40 mg/kg; xylanase, 333.33 U/g. b Dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). c SID: Standardized ileal digestible. d STTD: Standardized total tract digestible. Ingredients (%) Experimental diets b CD40 CD85 CD100 Corn grain, 7.86% CP 55.43 55.43 55.43 Soybean meal, 45.4% CP 27.24 27.24 27.24 Whole soybeans, 36% CP 6.00 6.00 6.00 Sugar 3.00 3.00 3.00 Soybean oil 2.97 2.42 2.24 Fish meal, 53% CP 2.00 2.00 2.00 Dicalcium phosphate 1.61 1.61 1.61 Inert (kaolin) - 0.51 0.69 Calcitic limestone 0.45 0.45 0.45 Common salt, NaCl 0.44 0.44 0.44 Premix, mineral and vitamin supplement a 0.30 0.30 0.30 Adsorbent (Mycofix ® ) 0.20 0.20 0.20 L-lysine, 54.6% 0.177 0.177 0.177 DL-methionine, 99.5% 0.056 0.056 0.056 L-threonine, 96.8% 0.061 0.061 0.061 L-tryptophan, 99.0% 0.017 0.017 0.017 L-valine, 95.5% 0.049 0.049 0.049 β-mannanase - 0.030 0.030 Calculated chemical composition Metabolizable energy, kcal/kg 3.36 3.31 3.30 Crude protein, % 20.50 20.50 20.50 SID c l ysine, % 1.080 1.080 1.080 SID methionine + cysteine, % 0.602 0.602 0.602 SID threonine, % 0.700 0.700 0.700 SID tryptophan, % 0.240 0.240 0.240 SID valine, % 0.892 0.892 0.892 Total calcium, % 0.80 0.80 0.80 STTD d phosphorus, % 0.43 0.43 0.43 Total sodium, % 0.200 0.200 0.200 Starch, % 34.21 34.21 34.21 Crude fiber, % 2.99 2.99 2.99 Traits of the tested enzymes Xylanase (Sunhy Biology Co., Ltd, Wuhan, HB, China; registration no. PR-08978 03462) is a product derived from Trichoderma longibrachiatum with an enzyme activity of 10,000 U/g. One unit of xylanase refers to the quantity of enzyme capable of releasing 1 micromole of reducing sugar from a xylan solution (5 mg/mL) at 37°C with a pH 5.5 6,11 . β-mannanase (Elanco Animal Health, Inc., São Paulo, SP, Brazil; registration no. SP-59122 30011, Hemicell™ HT) is obtained from Paenibacillus lentus and possesses an enzyme activity of 160,000 U/g. One unit of β-mannanase is defined as the amount of enzyme required to release 0.72 mcg of reducing sugars (equivalent to D-mannose) per minute from goma locust (mannans concentration of 88%) at 40°C and pH 7.5 6,11 . Blood sampling and cytokine analyses The procedures adopted are in accordance with those described by Genova et al. 6,11 . The blood collection (no fasting) was performed on day 18 of lactation in 8 sows per treatment, using the collection technique via the cranial anterior vena cava, with a plastic syringe for the collection of 10 mL and 1.2 × 40 mm gauge needle. Samples were transferred to tubes (glass vacuum blood collection tube, Labingá; Maringá, PR, Brazil) without the addition of anticoagulants. Immediately, the samples were stored in thermal boxes (4°C) until the end of the blood sampling. Subsequently, the samples were stored at −80 ͦC and sent to the IMUNOVA private laboratory (Curitiba, PR, Brazil). The blood samples were centrifuged at 1,000 g for 10 min at room temperature, following which the serum was carefully collected. Serum cytokines concentration determined were: interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8/CXCL8), interleukin-12/interleukin-23 (IL-12/IL-23p40), interferon- α (IFN-α), interferon-γ (IFN-γ), tumor necrosis factor-α (TFN-α), interleukin-4 (IL-4), and interleukin-10 (IL-10) analyzed using specific ELISA kits (ThermoFisher Scientific, Vienna, Austria) according to the manufacturer’s instructions. Fecal sampling and microbiota On day 21 of lactation, approximately 10 g of fecal samples were manually collected from 8 sows per treatment. The samples were collected by rectal stimulation using swabs and placed in sterile Eppendorf-type tubes of 4 mL. Immediately, the sampled material was stored in thermal boxes (4°C) until the end of the collection period. Subsequently, the samples were stored at -80 °C until the analyses. A commercial Kit (ZR Fecal DNA MiniPrep © from Zymo Research) was used to extract DNA from fecal samples following the manufacturer’s instructions. DNA quality and quantification were evaluated using NanoDrop spectrophotometry (Thermo Scientific™). A segment of approximately 460 bases of the V3–V4 hypervariable region of the 16S ribosomal RNA gene was amplified using the 375F/805R primers for bacterial analysis, and the following PCR conditions: 95°C for 3 min; 25 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, followed by a step at 72°C for 5 min. The amplicons were ligated to Illumina® Nextera dual index barcodes under the following conditions: 95°C for 3 min; 8 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, followed by a step at 72°C for 5 min. The products were then purified, pooled together, and subsequently sequenced on the Illumina ® NextSeq sequencer 51 as paired-end reads of 300 bases. The readings obtained from the sequencer were analyzed in the quantitative insights into microbial ecology (QIIME 2) platform, following a workflow using both the forward and reverse sequences (R1 and R2) in bacterial analysis, including removal of low-quality sequences, filtration, removal of chimeras, and taxonomic classification. The sequences were classified into bacterial genera using amplicon sequence variants (ASVs), which involved comparing sequence homology against a database. To compare the amplicons of 16s rRNA gene regions, the 2022 update (Genome Taxonomy Database, GTDB 207 version) of the GTDB bacterial taxonomy database 51 was used, extracting in silico readings from the same amplified regions. To generate the classifications of bacterial communities through the identification of ASVs, 75,732 reads per sample were used for bacterial analysis, with all samples being analyzed. The minimum use of reads per sample aims to normalize the data and not statistically compare samples with different numbers of reads in each microbiome type. Families and higher classifications that had uppercase letters as suffixes represented non-monophyletic groupings in the reference phylogeny construction of GTDB, although there is evidence that such groups are monophyletic. Genera with the same suffix pattern were polyphyletic or subdivided according to the database's reference phylogeny. Species names can also have the same suffix pattern if they categorize a grouping that may contain ambiguity in the correct nomenclature 52 . Other codes present in the classifications (e.g. NSJ-53 or sp001543345) represented the first type material used as a reference for clustering in the respective operational taxonomic units (OTUs). Statistical procedures The analysis of serum cytokine profile was performed using GraphPad Prism software version 8. Outliers were identified via ROUT test (Q = 1%). The data were subjected to the Shapiro-Wilk normality test. Based on the results, if the data followed a Gaussian distribution, they were subjected to one-way analysis of variance, using Tukey's post hoc test for multiple comparisons. If the data did not follow a Gaussian distribution, they were subjected to the Kruskal-Wallis test followed by Dunn's post hoc. For both tests, a difference was considered significant when P < 0.05. The statistical analyses and graphs of the fecal microbiome were performed using the R software 53 . The statistical comparison between groups in alpha diversity analyses was conducted using the non-parametric Kruskal-Wallis test followed by Dunn's post hoc. Beta diversity was analyzed using permutational multivariate analysis of variance (PERMANOVA) in the QIIME2 pipeline, with 10,000 permutations. Alpha diversity analyses were calculated using the libraries "phyloseq" 54 , "vegan" 55 , and "Microbiome" 56 . To identify specific taxa that may have undergone modulation between the analyzed groups, differences in relative abundances were analyzed using the Kruskal-Wallis test with Dunn's post hoc at a 95% confidence level for lower taxonomic classifications: family, genus, and species. Declarations Acknowledgments We thank the efforts and support in the research from the Elanco Animal Health Incorporated Company, Universidade Estadual do Oeste do Paraná, Copagril Agroindustrial Cooperative, and the Universidade Federal de Viçosa. Author contributions PLOC: conceptualization, data curation, and project management. JLG, PLOC, CE and EFRE: methodology. JLG: software, statistical analysis and formal analysis. JPSL: writing—original draft preparation. PLOC and JLG: validation. EFRE, GLM, ALGT, AGB, ACT and LBA: investigation. JPSL, PSC, JLG, CE and PLOC: writing—review and editing. PLOC, STC, CE and MK: supervision. All authors contributed to the article and approved the submitted version. Data availability statement The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Additional Information Competing interests The authors declare no conflicts of interest for this paper. Funding This project was funded by the Elanco Animal Health Incorporated Company. References Liu, H., Hou, C., Li, N., Zhang, X., Zhang, G., Yang, F., Zeng, X., Liu, Z. & Qiao, S. Microbial and metabolic alterations in gut microbiota of sows during pregnancy and lactation. Faseb 33, 4490–4501. https://doi.org/10.1096/fj.201801221RR (2019). Baker, J. T., Duarte, M. E., Holanda, D. M. & Kim, S. W. Friend or Foe? Impacts of dietary xylans, xylooligosaccharides, and xylanases on intestinal health and growth performance of monogastric animals. Animals 11, 609. http://dx.doi.org/10.3390/ani11030609 (2021). Vangroenweghe, F., Poulsen, K. & Thas, O. 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Paraná","correspondingAuthor":false,"prefix":"","firstName":"Silvana","middleName":"Teixeira","lastName":"Carvalho","suffix":""},{"id":314158625,"identity":"3c78abc8-e0a7-48a2-bc6f-3d599baa00b3","order_by":10,"name":"Marcos Kipper","email":"","orcid":"","institution":"Elanco Animal Health Incorporated Company","correspondingAuthor":false,"prefix":"","firstName":"Marcos","middleName":"","lastName":"Kipper","suffix":""},{"id":314158626,"identity":"318cc127-a869-4d1e-934d-d6af3d65f14c","order_by":11,"name":"Cinthia Eyng","email":"","orcid":"","institution":"Universidade Estadual do Oeste do Paraná","correspondingAuthor":false,"prefix":"","firstName":"Cinthia","middleName":"","lastName":"Eyng","suffix":""},{"id":314158627,"identity":"28ee1682-65e0-454e-9b71-718c1064a207","order_by":12,"name":"Paulo Levi Oliveira Carvalho","email":"","orcid":"","institution":"Universidade Estadual do Oeste do Paraná","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"Levi Oliveira","lastName":"Carvalho","suffix":""}],"badges":[],"createdAt":"2024-05-20 13:29:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4449417/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4449417/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58497091,"identity":"694d0d97-41f0-45fa-ae68-c073a99a4cb3","added_by":"auto","created_at":"2024-06-17 12:33:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":495091,"visible":true,"origin":"","legend":"\u003cp\u003eSerum cytokines concentrations on day 18 of lactation in 8 sows per treatment. Data were presented as means ± SEM. Differences in serum concentrations of (\u003cstrong\u003eA\u003c/strong\u003e) interleukin-1β (IL-1β), (\u003cstrong\u003eB\u003c/strong\u003e) interleukin-4 (IL-4), (\u003cstrong\u003eC\u003c/strong\u003e) interleukin-6 (IL-6), (\u003cstrong\u003eD\u003c/strong\u003e) interleukin-8 (IL-8/CXCL8), (\u003cstrong\u003eE\u003c/strong\u003e) interleukin-10 (IL-10), (\u003cstrong\u003eF\u003c/strong\u003e) interleukin-12/interleukin-23p40 (IL-12/IL23p40), (\u003cstrong\u003eG\u003c/strong\u003e) interferon-α (IFN-α), (\u003cstrong\u003eH\u003c/strong\u003e) interferon-γ (IFN-γ), and (\u003cstrong\u003eI\u003c/strong\u003e) tumoral necrosis factor-α (TNF-α) in sows fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/678bab0011637f11aeb49718.png"},{"id":58496722,"identity":"62d6193b-cfa7-4aba-a6a6-11e645efab35","added_by":"auto","created_at":"2024-06-17 12:25:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":219210,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of cytokines concentrations on day 18 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/22d7cf052b4ed5514a51d882.png"},{"id":58496721,"identity":"6aede2e3-6b21-468b-b3a8-661990a8c045","added_by":"auto","created_at":"2024-06-17 12:25:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":298181,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated alpha-diversity by Chao1 (\u003cstrong\u003eA\u003c/strong\u003e), Observed OTUs (\u003cstrong\u003eB\u003c/strong\u003e), Fisher Index (\u003cstrong\u003eC\u003c/strong\u003e), Simpson Index (\u003cstrong\u003eD\u003c/strong\u003e), Shannon Index (\u003cstrong\u003eE\u003c/strong\u003e), and Pielou's Evenness (\u003cstrong\u003eF\u003c/strong\u003e) on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Statistical comparison between groups was performed using the non-parametric Kruskal-Wallis test and Dunn's post hoc, with \u003cem\u003eP \u0026lt;\u003c/em\u003e 0.05.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/f44e73c30d49132732316ef9.png"},{"id":58497090,"identity":"193033cb-3ce0-4b00-989a-257b19f60236","added_by":"auto","created_at":"2024-06-17 12:33:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":767074,"visible":true,"origin":"","legend":"\u003cp\u003eBeta diversity estimated by the Bray-Curtis (\u003cstrong\u003eA\u003c/strong\u003e), Jaccard (\u003cstrong\u003eB\u003c/strong\u003e), UniFrac (\u003cstrong\u003eC\u003c/strong\u003e), and Weighted UniFrac (\u003cstrong\u003eD\u003c/strong\u003e) parameters on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/ccea3bc6bee55bacf5293e82.png"},{"id":58496724,"identity":"1002047f-8ff8-4ef4-80cd-7fb0ca46db6f","added_by":"auto","created_at":"2024-06-17 12:25:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":687896,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of phyla (\u003cstrong\u003eA\u003c/strong\u003e), classes (\u003cstrong\u003eB\u003c/strong\u003e), orders (\u003cstrong\u003eC\u003c/strong\u003e), families (\u003cstrong\u003eD\u003c/strong\u003e), genera (\u003cstrong\u003eE\u003c/strong\u003e), and species (\u003cstrong\u003eF\u003c/strong\u003e) presents on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/cc151b069c9989151dd958d0.png"},{"id":58497094,"identity":"a89f39d9-d961-448b-add0-375538626a35","added_by":"auto","created_at":"2024-06-17 12:33:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":106753,"visible":true,"origin":"","legend":"\u003cp\u003eFirmicutes:Bacteroidetes ratio (FBR) on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/335313855e1689a444913d7c.png"},{"id":58496725,"identity":"5cdf4257-003e-464b-9ee8-2a6252fc4da2","added_by":"auto","created_at":"2024-06-17 12:25:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":208703,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential abundance of taxa between groups for the Acutalibacteraceae (\u003cstrong\u003eA\u003c/strong\u003e), CAG_508 (\u003cstrong\u003eB\u003c/strong\u003e) and NSJ_53 (family code) (\u003cstrong\u003eC\u003c/strong\u003e) families on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Statistical tests were performed using the Kruskal-Wallis test and Dunn's post hoc, with \u003cem\u003eP \u0026lt;\u003c/em\u003e0.05.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/09fd8764406259ad09cf81b6.png"},{"id":58496727,"identity":"1d5b3ffa-cc6c-43cd-9e52-fc344db80708","added_by":"auto","created_at":"2024-06-17 12:25:29","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":193416,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential abundance of taxa between groups for the \u003cem\u003eFimenecus\u003c/em\u003e(\u003cstrong\u003eA\u003c/strong\u003e) and \u003cem\u003eNSJ_53\u003c/em\u003e (genus code) (\u003cstrong\u003eB\u003c/strong\u003e) genera on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Statistical tests were performed using the Kruskal-Wallis test and Dunn's post hoc, with \u003cem\u003eP \u0026lt;\u003c/em\u003e0.05.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/53f9cb47592cbd3802f67b14.png"},{"id":58496729,"identity":"6cd29418-14b4-4f01-9159-8fd80e1c5331","added_by":"auto","created_at":"2024-06-17 12:25:29","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":227946,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential abundance of taxa between treatments for the \u003cem\u003eFimenecus\u003c/em\u003e sp004556705 (\u003cstrong\u003eA\u003c/strong\u003e) and \u003cem\u003eNSJ-53\u003c/em\u003e sp014384795 (\u003cstrong\u003eB\u003c/strong\u003e) species on day 21 of lactation in 8 sows per treatment fed to 1 of 3 dietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Statistical tests were performed using the Kruskal-Wallis test and Dunn's post hoc, with \u003cem\u003eP \u0026lt;\u003c/em\u003e 0.05.\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/cbffc61276583b9a4caf3772.png"},{"id":59819455,"identity":"72b936ba-6969-4a94-a96c-ca509f1b068f","added_by":"auto","created_at":"2024-07-08 03:01:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4020619,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4449417/v1/de680a40-d85d-45c8-88ea-6e8c2f9ba5ec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"β-mannanase-supplemented diets reduced by 85 kcal of metabolizable energy/kg containing xylanase promotes benefits in fecal alpha diversity in lactating sows","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlant-based ingredients commonly used in pig diets contain significant amounts of antinutritional compounds (e.g. β-mannans, xylans, trypsin inhibitors, antigenic factors and phytates)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. These components are not effectively digested by the pig's endogenous enzymes. To mitigate their adverse effects, exogenous enzymes are supplemented to diets to improve digestion and absorption of nutrients in non-ruminant animals\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Furthermore, this nutritional strategy enhances the digestibility of nutrients and the gain to feed ratio\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, allowing a reduction in ME in the diet formulation.\u003c/p\u003e \u003cp\u003eLactation constitutes a critical phase in the reproductive cycle of sows, in which high dietary requirements for maintenance, growth, and milk production increase the risk of undue mobilization of body reserves. Additionally, it is imperative to understand the changes during lactation when implementing nutritional strategies, offering specific insights into potential effects on the health of sows and their progeny. Therefore, supplementing β-mannanase can be a viable strategy to mitigate the restrictions that limit feed digestion (e.g. feeding pattern and lactation capacity) in lactating sows.\u003c/p\u003e \u003cp\u003ePreviously, it was reported that dietary supplementation of β-mannanase increased nutrient digestibility and mitigated body weight loss in lactating sows\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Previous studies involving pig\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and piglets\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e have attributed the decrease in immune response induced by dietary intake and the consequent reduction in energy expenditure for immune system activation to the hydrolysis of β-mannans. Furthermore, there are discrepancies regarding the xylanase's role in the release of phytic acid and its ability to modulate the proliferation of pathogenic microorganisms by reducing the viscosity of digesta in pig\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Considering the available evidence, the impact of dietary supplementation with exogenous enzymes in ME-reduced diets, alone or in combination, on favorable aspects of the immune response and the fecal microbiota in sows remains uncertain.\u003c/p\u003e \u003cp\u003eNotably, ME-reduced diets have previously been documented to induce alterations in the fecal microbiome in pig, regardless of combined enzymes on microbial population abundance\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This reflects the ability of β-mannanase-xylanase supplementation to promote favorable conditions for intestinal microbial ecology. For example, improving the digestibility of targeted non-starch polysaccharides (arabinoxylan, mannans)\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and promoting diversity beneficial bacteria\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, resulting in beneficial modulation of the intestinal microbiota. This modulation manifests itself as a reduction in pathogenic bacteria and attenuated intestinal inflammation, as evidenced by studies conducted by Kiarie et al.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, who assessed the effect of β-mannanase supplementation and Genova et al.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, who tested the combined effect of these enzymes in diets fed to pig.\u003c/p\u003e \u003cp\u003eThus, dietary supplementation with β-mannanase-xylanase may hold economic, environmental, nutritional and health impact. Here, the study was conducted based on the hypothesis that supplementation of β-mannanase in ME-reduced diets containing xylanase would save energy content by acting on antinutrients compounds, reflecting changes in the cytokine profile and fecal microbiome. Therefore, this study aimed to assess the associated effects of these enzymes in diets with reduced ME on the profile of the fecal microbiota and cytokine concentrations in lactating sows.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSerum cytokine concentrations\u003c/h2\u003e \u003cp\u003eIt was no difference (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05) among dietary treatments on serum cytokines concentrations in lactation sows (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Conversely, the cytokines IL-12/IL-23p40 exhibited the highest concentration among all evaluated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSows fed CD40 diet showed serum concentrations of cytokines of 74.86 pg/mL for IL-1β, 9.497 pg/mL for IL-4, 119.1 pg/mL for IL-6, 4.231 pg/mL for IL-8/CXCL8, 20.20 pg/mL for IL-10, 167.6 pg/mL for IL-12/IL23p40, 1.481 pg/mL for IFN-α, 3.761 pg/mL for IFN-γ, and 84.60 pg/mL for TNF-α. Sows fed CD85 diet showed serum concentrations of cytokines of 48.09 pg/mL for IL-1β, 8.280 pg/mL for IL-4, 83.43 pg/mL for IL-6, 18.200 pg/mL for IL-8/CXCL8, 39.07 pg/mL for IL-10, 150.6 pg/mL for IL-12/IL23p40, 0.6210 pg/mL for IFN-α, 4.253 pg/mL for IFN-γ, and 90.39 pg/mL for TNF-α. In the group fed CD100 diet, serum concentrations of cytokines were 113.10 pg/mL for IL-1β, 11.580 pg/mL for IL-4, 81.90 pg/mL for IL-6, 3.520 pg/mL for IL-8/CXCL8, 2.832 pg/mL for IL-10, 126.0 for IL-12/IL23p40, 1.069 pg/mL for IFN-α, 3.263 pg/mL for IFN-γ, and 107.1 pg/mL for TNF-α.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFecal microbiota\u003c/h2\u003e \u003cp\u003eSows fed CD85 diet present (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.014) higher alpha diversity richness than those fed CD100 diet based on the Simpson index (0.98 vs. 0.97, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). The remain alpha diversity indices was not altered by the diets (Chao1, observed OTUs, Fisher, Simpson's, Shannon, and Pielou) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No effect was observed on beta diversity assessed using the Bray-Curtis (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.527), Jaccard (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.526), UniFrac (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.687), and Weighted UniFrac (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.547) parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe phyla, classes, orders, families, genera, and species with an average relative abundance above 2% in at least one of the tested groups were depicted in the graphs. In the fecal samples analyzed, the most abundant phylum was Firmicutes followe by Bacteroidota, Spirochaetota, Actinobacteriota, and Cyanobacteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In addition, the classes Clostridia, Bacilli, Bacteroidia, Negativicutes, Spirochaetia, Coriobacteriia, and Vampirovibrionia showed the highest abundances (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The most abundant orders were Christensenellales, Oscillospirales, Peptostreptococcales, Clostridiales, Lachnospirales, Bacteroidales, TANB77, Lactobacillales, Treponematales, Coriobacteriales, Haloplasmatales_A, Gastranaerophilales, and Erysipelotrichales (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The families with the highest relative abundance were Peptostreptococcaceae, Clostridiaceae, Oscillospiraceae, Lachnospiraceae, CAG-74, CAG-508, Treponemataceae, Lactobacillaceae, Muribaculaceae, Ruminococcaceae, Acutalibacteraceae, Turicibacteraceae, NSJ-53, Christensenellaceae, Gastranaerophilaceae, Erysipelotrichaceae, and Bacteroidaceae (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The most abundant genera were \u003cem\u003eClostridium\u003c/em\u003e, \u003cem\u003eTerrisporobacter\u003c/em\u003e, \u003cem\u003eCAG-83\u003c/em\u003e, \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eSodaliphilus, GCA-900199385\u003c/em\u003e, \u003cem\u003eLimivicinus\u003c/em\u003e, \u003cem\u003eOnthenecus\u003c/em\u003e, \u003cem\u003eLimosilactobacillus\u003c/em\u003e, \u003cem\u003eTuricibacter\u003c/em\u003e, \u003cem\u003eMerdicola\u003c/em\u003e, \u003cem\u003eFimivivens\u003c/em\u003e, and \u003cem\u003eFimenecus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Species that showed relative abundance were \u003cem\u003eSodaliphilus sp004557565\u003c/em\u003e, \u003cem\u003eGCA-900199385 sp900322155\u003c/em\u003e, \u003cem\u003eClostridium baratii\u003c/em\u003e, \u003cem\u003eLimivicinus sp002320035\u003c/em\u003e, \u003cem\u003eOnthenecus sp900199405\u003c/em\u003e, \u003cem\u003eTuricibacter sp001543345\u003c/em\u003e, \u003cem\u003eCAG-83 sp900549395\u003c/em\u003e, \u003cem\u003eNSJ-53 sp014384795\u003c/em\u003e, \u003cem\u003eNSJ-63 sp014384805\u003c/em\u003e, \u003cem\u003eMerdicola sp001915925\u003c/em\u003e, \u003cem\u003eFirmivivens sp900113995\u003c/em\u003e, \u003cem\u003eClostridium butyricum\u003c/em\u003e, \u003cem\u003eFimenecus sp004556705\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003eNo significant difference was observed between the groups for Firmicutes:Bacteroidetes ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The families exhibited significant differences between the CD85 vs. CD100 diets. The Acutalibacteraceae family was more abundant in sows fed CD100 diet than in those fed CD85 diet (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.044, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In addition, sows fed CD85 diet had a higher abundance of the CAG_508 (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.012, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) and NSJ_53 (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.044, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC) families than those fed the CD100 diet.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eFimenecus\u003c/em\u003e genus exhibited lower abundance in sows that received the CD85 dietary treatment compared to sows fed CD40 (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.007, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA) or CD100 diets (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.005, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA), while the \u003cem\u003eNSJ-53\u003c/em\u003e genus showed higher abundance in sows fed CD85 diet than in those fed CD100 diet (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.044, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Similarly, these results followed for the \u003cem\u003eFimenecus sp004556705\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA) and \u003cem\u003eNSJ-53 sp014384795\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB) species.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eSerum cytokine concentrations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCytokine concentrations can be used to differentiate between normal physiological processes and pathological processes (e.g. inflammation)\u003csup\u003e12\u003c/sup\u003e. Investigating the variability in sows\u0026apos; cytokine profiles can provide valuable information, because cytokines play crucial roles in immune response and inflammation regulation and, therefore, maintaining their equilibrium is pivotal for health and fortification against microbial dysbiosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, the present study demonstrated that \u0026beta;-mananase supplementation in ME-reduced diets containing xylanase had no effect on the concentrations of these signaling molecules in the serum of lactating sows. Overall, this can be justified because the connection between dietary enzymes and host reactions depends on the impact of specific substrates on the physiology of digestion and how exogenous dietary enzymes can alter the degradation or modification of these substrates in the gastrointestinal tract\u003csup\u003e8\u003c/sup\u003e, affecting immune responses at the blood level.\u003c/p\u003e\n\u003cp\u003eThe impact of improving the energy matrix did not interfere with the animal\u0026apos;s immune status, which can be substantial; for example, sows fed a diet with a low ratio of starch and fat significantly increased the contents of IL-1\u0026beta;, IL-6, and TNF-\u0026alpha; in plasma samples during parturition\u003csup\u003e13\u003c/sup\u003e. It is reasonable to infer that when formulating the diet, components related to the construction of the immune system should be considered, particularly focusing on dietary strategies that could potentially lead to excessive immune activation and hinder animal production efficiency\u003csup\u003e14\u003c/sup\u003e. This indicates that immune system activation comes at a significant cost, resulting in increased production of immune cells and signaling molecules, as well as reduced efficiency in affected tissues, which ultimately impairs the body\u0026apos;s ability to utilize nutrients for protein deposition.\u003c/p\u003e\n\u003cp\u003eSystematic review showed that \u0026beta;-mannanase supplementation reduced the inflammatory responses caused by \u0026beta;-mannan and released prebiotic-like products in the intestinal tract\u003csup\u003e8\u003c/sup\u003e. In this context, the pro-inflammatory IL-12/23p40 was used to assess the activation of innate immune response and possible cytokine storm\u003csup\u003e15,16\u003c/sup\u003e. Therefore, they stimulate the production of other cytokines across different cells are categorized as level 1 cytokines\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn the present study, regardless of the diets, there was a marked increase in IL-12/23p40 concentrations. As a result, we hypothesized that this could be indicative of clinical symptoms. Splichalova and Splichal\u003csup\u003e18\u0026nbsp;\u003c/sup\u003ereported a positive correlation between concentrations of the pro-inflammatory cytokine IL-12/23p40 and clinical symptoms of enteric infection and sepsis.\u003c/p\u003e\n\u003cp\u003eIn the context of the connection between the immune system and the fecal microbiota, multiple investigations have substantiated the impact of cytokines, for example, previous studies\u003csup\u003e19,20\u003c/sup\u003e suggest that the immune system actively controls and regulates the fecal microbiota. This regulation is influenced by factors such as gender and specific cytokines, with the strongest interactions observed in the intestine\u003csup\u003e21\u003c/sup\u003e. Therefore, in the present study, our hypothesis that \u0026beta;-mannanase supplementation could modify the abundance, diversity and composition of the fecal microbiome in lactating sows was confirmed, although this did not reflect changes in serum cytokine concentrations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFecal microbiota\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe fecal microbiota is influenced by several factors including host genetics\u003csup\u003e22\u003c/sup\u003e, diet\u003csup\u003e23\u003c/sup\u003e, and the immune system\u003csup\u003e24\u003c/sup\u003e. The microbiota plays important roles on animal physiology including inflammation process, metabolic syndromes\u003csup\u003e25\u003c/sup\u003e, energy metabolism\u003csup\u003e26\u003c/sup\u003e, and immune responses\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe present study showed that the \u0026beta;-mannanase supplementation in ME-reduced diets containing xylanase had an impact on the diversity of fecal microbial communities. The fecal microbial communities of lactating sows fed CD85 diet exhibited higher alpha diversity compared to those fed CD100. This indicates that there is a positive correlation between the microbiota composition and alpha diversity of the sow intestinal microbiota and factors such as nutrient digestibility (e.g. the mechanisms of action of exogenous enzymes), average daily gain, and body weight\u003csup\u003e28,29\u003c/sup\u003e. Consistent with this, Vojinovic et al.\u003csup\u003e30\u003c/sup\u003e provided insights into the role of the microbiota in metabolism and support the potential of the intestinal microbiota as a target for therapeutic and preventive interventions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, evaluating the relationship between the Firmicutes and Bacteroidetes phyla in the fecal microbiota of lactating sows, they did not suffer the effects of the tested treatments. Regardless of the diet, the phylum-level analysis of the microbiota revealed that the Firmicutes phylum was predominant with a relative abundance of over 80%. These results were similar to what others have observed in studies involving sows\u003csup\u003e1,31\u003c/sup\u003e. Furthermore, Turnbaugh et al.\u003csup\u003e32\u003c/sup\u003e demonstrated through research using a mouse model that an increase in Firmicutes is a means of enhancing the body\u0026apos;s ability to acquire energy from the diet, a potential advantage in helping to prepare the body for the energy demands of lactation.\u003c/p\u003e\n\u003cp\u003eRegardless of the diet, analysis of the microbiota at the class level revealed that the Clostridia class was predominant in all groups of lactating sows, which is consistent with the results of previous studies with sows\u003csup\u003e31,33\u003c/sup\u003e. Additionally, the Clostridia class of bacteria has a multitude of enzymes (e.g. butyryl-CoA:acetate-CoA transferase) that facilitate the breakdown of polysaccharides into short-chain fatty acids (SCFA). Consistently, research on Clostridium genera has shown that they can produce butyrate\u003csup\u003e34,35,36\u003c/sup\u003e and have associated butyrate with the prevention and treatment of intestinal disorders, by reducing inflammation in the host\u0026apos;s intestine, allowing intestinal epithelial cells to use it as a source of energy\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAdditionally, in this investigation, significant differences in the abundance of Clostridium CAG-508 were identified in lactating sows fed CD85 diet compared to those fed CD100. As a result, we hypothesize that this bacterium, which synthesizes SCFA, could provide a considerable portion of the energy needed by colonic epithelial cells and the intestinal immune system\u003csup\u003e38\u003c/sup\u003e, and it plays roles in anti-inflammatory responses and antioxidant processes. These findings further support the result of Cheng et al.\u003csup\u003e39\u003c/sup\u003e, who suggested the positive or negative correlation between alterations in gut microbiota composition and serum immune status in sows, hypothesizing that the interaction between intestinal microbiota and intestinal permeability may be one of the potential mechanisms linking intestinal microbiota to metabolic disorders in sows during early lactation.\u003c/p\u003e\n\u003cp\u003eSows fed the CD100 diet exhibited a higher relative abundance of the Acutalibacteraceae family compared to those fed the CD85 diet. Previous studies have suggested a positive correlation between the abundance of Acutalibacteraceae family and bile salt hydrolase-carrying bacteria in dairy cows\u003csup\u003e40\u003c/sup\u003e, an intestinal bacteria‐producing enzyme that has a negative impact on host fat digestion and energy harvest\u003csup\u003e41\u003c/sup\u003e. Our research hypothesized that the higher abundance of Acutalibacteraceae family in CD100-fed sows may enhance the hydrolysis of bile salts by their enzymes, potentially leading to reduced lipid absorption and loss of body weight. It is noteworthy that the microbial production of bile acids in pigs helps protect the intestinal mucosa, reduce inflammation, and regulate liver function\u003csup\u003e42\u003c/sup\u003e. However, the information available on the relevance of this family to the porcine intestinal microbiota is limited\u003csup\u003e43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOn the other hand, the sows fed the CD85 diet exhibited a higher relative abundance of the CAG-508 and NSJ_53 families compared to those fed the CD100 diet. The study on the intestinal mycobiota revealed that the CAG-508 bacterial family frequently interacts with fungi, suggesting complex interactions between bacteria and fungi in the gut of Caprinae animals\u003csup\u003e44\u003c/sup\u003e. It is reasonable to infer that our finding indicates potential relationships between the bacterial microbiota and the mycobiota. Consistent with this hypothesis, Yang et al.\u003csup\u003e45\u003c/sup\u003e further demonstrated that triple interactions among the intestinal microbiota, mycobiota, and host immunity can lead to targeted interventions and enhance the efficacy of interventions in the host\u0026apos;s intestinal microbiome and immune system.\u003c/p\u003e\n\u003cp\u003eNSJ 53 is a bacterium of the Christensenellaceae family. Previous experiments by Waters and Ley\u003csup\u003e46\u003c/sup\u003e and Alem\u0026aacute;n et al.\u003csup\u003e47\u003c/sup\u003e have suggested that Christensenellaceae, an intestinal commensal bacterial family, is a potential probiotic candidate for intervention. For example, researches have shown promising results for its potential intervention in obesity and inflammatory bowel diseases in the human intestine\u003csup\u003e46\u003c/sup\u003e, as well as its ability to influence fat and carbohydrate metabolism\u003csup\u003e47\u003c/sup\u003e. In general, we can infer that the CG-508 and NSJ_53 families play important roles in metabolic regulation and maintenance of intestinal homeostasis in pigs.\u003c/p\u003e\n\u003cp\u003eAfter data analysis, it was concluded that the available information on the relevance of the \u003cem\u003eFimenecus\u003c/em\u003e genus to the pig gut microbiota is limited, especially on how it interacts with intestinal biodiversity and affects the host immune system. Therefore, further research is needed to clarify and understand how the \u003cem\u003eFimenecus\u003c/em\u003e genus relates to microbial composition. However, in studies on human fecal microbiota, the genus \u003cem\u003eFimenecus\u003c/em\u003e had high levels of pectin-degrading activities, including arabinases, galacturonases, and galacturonidases\u003csup\u003e48\u003c/sup\u003e. Therefore, regarding the potential of pectin for pig nutrition and health, Wiese\u003csup\u003e49\u003c/sup\u003e noted its potential to improve growth and general well-being, influencing the intestinal microbiome, the immune system and reducing the presence of pathogens and viruses.\u003c/p\u003e\n\u003cp\u003eAnalyzing the findings observed in this study, a potential explanation for these effects is that a diet containing \u0026beta;-mannanase and xylanase during the lactation period hinders the physiological activities of undesirable bacterial species, substantially altering upon analyzing the results of this study, it was deduced that a diet with xylanase (valorization of 40 kcal of ME/kg diet) and \u0026beta;-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet) during lactation may inhibit harmful bacteria, leading to changes in fecal microbiota.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study proposes that the β-mannanase supplementation in diets reduced in 85 kcal metabolizable energy/kg containing xylanase fed to lactation sows to the positive impact of regulation of cytokines and exerts influence on the profile of the fecal microbiome. In addition, further research is needed to investigate the mechanisms underlying the regulation of the intestinal microbiota in lactating sows.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was conducted on a commercial farm of Western Paran\u0026aacute; (Toledo, PR, Brazil), in the weaned piglet production unit. The protocol for the experiment was approved by the Animal Use Committee of the University (n\u0026ordm; 17-2022). All methods were carried out in accordance with relevant guidelines and regulations. All methods were reported in accordance with ARRIVE guidelines (https://arriveguidelines.org/arrive-guidelines).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals, experimental design, housing and dietary treatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 60 hybrid sows at 110 days of gestation (248.4 \u0026plusmn; 2.4 kg BW) from a commercial lineage (Landrace\u0026thinsp;\u0026times;\u0026thinsp;Large White) were selected for the study. The sows were housed in farrowing crates for a period of 26 days (5 days of acclimatization, and 21 days of lactation).\u003c/p\u003e\n\u003cp\u003eSows were allocated in a randomized block design to 1 of 3 dietary treatments, resulting in 15 animals per round, totaling 4 rounds with 5 crate replicates per treatment in each round and 1 sow per crate as the experimental unit. Sows were classified according to their BW as light-, medium-, or heavy-weight and farrowing order in 3 groups: P1, primiparous (13 sows); P2, sows with two or three farrowings (29 sows); and P3, sows with four or five farrowings (18 sows). The average farrowing order of sows was 2.8, 2.6, and 2.7 to the CD40, CD85, and CD100-fed group, respectively.\u003c/p\u003e\n\u003cp\u003eApproximately 5 days before farrowing, sows were transferred into individual conventional farrowing crates (2.4 \u0026times; 1.6 \u0026times; 1.3 m) with slatted metal floor and equipped with front gutter feeders and nipple drinkers. A heated creep area (0.98 \u0026times; 0.68 \u0026times; 0.66 m) was accessible to piglets to maintain thermal comfort between 28\u0026deg;C and 32\u0026deg;C. The farrowing crates were installed in a commercial facility with a concrete floor and side curtains. The ambient temperature (25.3 \u0026plusmn; 0.4\u0026deg;C) and relative humidity (60.0 \u0026plusmn; 1.8%) was recorded throughout the experimental period using a datalogger (Vketech, model temperature instruments) positioned at the center of the facility.\u003c/p\u003e\n\u003cp\u003eThe experimental diets were corn and soybean meal-based with industrial amino acids, and formulated to meet the nutritional requirements of the animals\u003csup\u003e50\u003c/sup\u003e. The diets were provided in mash form varying only for soybean oil and inert (kaolin) contents (Table 1). The experimental diets were provided according to the reproductive phase of the sows, starting at 110 days of gestation and ending at 21 days of lactation. In the pre-partum period (5 days before farrowing), the feeding was controlled, providing 2 kg of diet per animal, once a day. Daily diet was previously weighed and stored in identified plastic bags. On parturition day, sows were not fed. Throughout lactation, sows were fed 4 times a day (07h30, 11h30, 14h00, and 17h30), and the average daily diet consumption was 7 kg.\u003c/p\u003e\n\u003cp\u003eThe tested dietary treatments were: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + \u0026beta;-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + \u0026beta;-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Composition of diets fed to lactating sows (as fed basis, %). \u003csup\u003ea\u003c/sup\u003eContent per kg of premix: vitamin A, 2080000 IU/kg; vitamin D\u003csub\u003e3\u003c/sub\u003e, 312000 IU/kg; vitamin E, 11700 IU/kg; vitamin K\u003csub\u003e3\u003c/sub\u003e, 520 mg/kg; vitamin B\u003csub\u003e1\u003c/sub\u003e, 260 mg/kg; vitamin B\u003csub\u003e2\u003c/sub\u003e, 1040 mg/kg; vitamin B\u003csub\u003e6\u003c/sub\u003e, 390 mg/kg; vitamin B\u003csub\u003e12\u003c/sub\u003e, 5200 mg/kg; niacin, 6500 mg/kg; pantathenic acid, 4160 mg/kg; folic acid, 260 mg/kg; biotin, 65 mg/kg; choline chloride, 156 g/kg; Zn oxide, 23.94 g/kg; Mn sulfate, 8820 mg/kg; Fe sulfate, 17.66 g/kg; Cu sulfate, 2640 mg/kg; iodine, 217.80 mg/kg; sodium selenite, 79.40 mg/kg; xylanase, 333.33 U/g. \u003csup\u003eb\u003c/sup\u003eDietary treatments: 1) a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), 2) CD40 + \u0026beta;-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and 3) CD40 + \u0026beta;-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). \u003csup\u003ec\u003c/sup\u003eSID: Standardized ileal digestible. \u003csup\u003ed\u003c/sup\u003eSTTD: Standardized total tract digestible.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.96296296296296%\" rowspan=\"2\"\u003e\n \u003cp\u003eIngredients (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.03703703703704%\" colspan=\"3\"\u003e\n \u003cp\u003eExperimental diets\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.014354066985646%\"\u003e\n \u003cp\u003eCD40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.014354066985646%\"\u003e\n \u003cp\u003eCD85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.97129186602871%\"\u003e\n \u003cp\u003eCD100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCorn grain, 7.86% CP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e55.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e55.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e55.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSoybean meal, 45.4% CP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e27.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e27.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e27.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eWhole soybeans, 36% CP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSugar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSoybean oil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eFish meal, 53% CP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eDicalcium phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eInert (kaolin)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCalcitic limestone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCommon salt,\u0026nbsp;NaCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003ePremix, mineral and vitamin supplement \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eAdsorbent\u0026nbsp;(Mycofix\u003csup\u003e\u0026reg;\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eL-lysine, 54.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eDL-methionine, 99.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eL-threonine, 96.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eL-tryptophan, 99.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eL-valine, 95.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003e\u0026beta;-mannanase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCalculated chemical composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eMetabolizable energy, kcal/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCrude protein, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e20.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e20.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e20.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSID\u003csup\u003ec l\u003c/sup\u003eysine, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e1.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e1.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e1.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSID methionine + cysteine, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSID threonine, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSID tryptophan, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSID valine, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eTotal calcium, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eSTTD\u003csup\u003ed\u003c/sup\u003e phosphorus, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eTotal sodium, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eStarch, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e34.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e34.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e34.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.07420494699647%\"\u003e\n \u003cp\u003eCrude fiber, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.190812720848056%\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54416961130742%\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eTraits of the tested enzymes\u003c/h2\u003e\n\u003cp\u003eXylanase (Sunhy Biology Co., Ltd, Wuhan, HB, China; registration no. PR-08978 03462) is a product derived from \u003cem\u003eTrichoderma longibrachiatum\u003c/em\u003e with an enzyme activity of 10,000 U/g. One unit of xylanase refers to the quantity of enzyme capable of releasing 1 micromole of reducing sugar from a xylan solution (5 mg/mL) at 37\u0026deg;C with a pH 5.5\u003csup\u003e6,11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026beta;-mannanase (Elanco Animal Health, Inc., S\u0026atilde;o Paulo, SP, Brazil; registration no. SP-59122 30011, Hemicell\u0026trade; HT) is obtained from Paenibacillus lentus and possesses an enzyme activity of 160,000 U/g. One unit of \u0026beta;-mannanase is defined as the amount of enzyme required to release 0.72 mcg of reducing sugars (equivalent to D-mannose) per minute from goma locust (mannans concentration of 88%) at 40\u0026deg;C and pH 7.5\u003csup\u003e6,11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood sampling and cytokine analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe procedures adopted are in accordance with those described by Genova et al.\u003csup\u003e6,11\u003c/sup\u003e. The blood collection (no fasting) was performed on day 18 of lactation in 8 sows per treatment, using the collection technique via the cranial anterior vena cava, with a plastic syringe for the collection of 10 mL and 1.2\u0026thinsp;\u0026times;\u0026thinsp;40 mm gauge needle. Samples were transferred to tubes (glass vacuum blood collection tube, Labing\u0026aacute;; Maring\u0026aacute;, PR, Brazil) without the addition of anticoagulants. Immediately, the samples were stored in thermal boxes (4\u0026deg;C) until the end of the blood sampling. Subsequently, the samples were stored at \u0026minus;80 ͦC and sent to the IMUNOVA private laboratory (Curitiba, PR, Brazil).\u003c/p\u003e\n\u003cp\u003eThe blood samples were centrifuged at 1,000 \u003cem\u003eg\u003c/em\u003e for 10 min at room temperature, following which the serum was carefully collected. Serum cytokines concentration determined were: interleukin-1\u0026beta; (IL-1\u0026beta;), interleukin-6 (IL-6), interleukin-8 (IL-8/CXCL8), interleukin-12/interleukin-23 (IL-12/IL-23p40), interferon- \u0026alpha; (IFN-\u0026alpha;), interferon-\u0026gamma; (IFN-\u0026gamma;), tumor necrosis factor-\u0026alpha; (TFN-\u0026alpha;), interleukin-4 (IL-4), and interleukin-10 (IL-10) analyzed using specific ELISA kits (ThermoFisher Scientific, Vienna, Austria) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFecal sampling and microbiota\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn day 21 of lactation, approximately 10 g of fecal samples were manually collected from 8 sows per treatment. The samples were collected by rectal stimulation using swabs and placed in sterile Eppendorf-type tubes of 4 mL. Immediately, the sampled material was stored in thermal boxes (4\u0026deg;C) until the end of the collection period. Subsequently, the samples were stored at -80 \u0026deg;C until the analyses.\u003c/p\u003e\n\u003cp\u003eA commercial Kit (ZR Fecal DNA MiniPrep\u003csup\u003e\u0026copy;\u003c/sup\u003e from Zymo Research) was used to extract DNA from fecal samples following the manufacturer\u0026rsquo;s instructions. DNA quality and quantification were evaluated using NanoDrop spectrophotometry (Thermo Scientific\u0026trade;). A segment of approximately 460 bases of the V3\u0026ndash;V4 hypervariable region of the 16S ribosomal RNA gene was amplified using the 375F/805R primers for bacterial analysis, and the following PCR conditions: 95\u0026deg;C for 3 min; 25 cycles of 95\u0026deg;C for 30 s, 55\u0026deg;C for 30 s, and 72\u0026deg;C for 30 s, followed by a step at 72\u0026deg;C for 5 min. The amplicons were ligated to Illumina\u0026reg; Nextera dual index barcodes under the following conditions: 95\u0026deg;C for 3 min; 8 cycles of 95\u0026deg;C for 30 s, 55\u0026deg;C for 30 s, and 72\u0026deg;C for 30 s, followed by a step at 72\u0026deg;C for 5 min. The products were then purified, pooled together, and subsequently sequenced on the Illumina\u003csup\u003e\u0026reg;\u003c/sup\u003e NextSeq sequencer\u003csup\u003e51\u003c/sup\u003e as paired-end reads of 300 bases.\u003c/p\u003e\n\u003cp\u003eThe readings obtained from the sequencer were analyzed in the quantitative insights into microbial ecology (QIIME 2) platform, following a workflow using both the forward and reverse sequences (R1 and R2) in bacterial analysis, including removal of low-quality sequences, filtration, removal of chimeras, and taxonomic classification. The sequences were classified into bacterial genera using amplicon sequence variants (ASVs), which involved comparing sequence homology against a database. To compare the amplicons of 16s rRNA gene regions, the 2022 update (Genome Taxonomy Database, GTDB 207 version) of the GTDB bacterial taxonomy database\u003csup\u003e51\u003c/sup\u003e was used, extracting in silico readings from the same amplified regions.\u003c/p\u003e\n\u003cp\u003eTo generate the classifications of bacterial communities through the identification of ASVs, 75,732 reads per sample were used for bacterial analysis, with all samples being analyzed. The minimum use of reads per sample aims to normalize the data and not statistically compare samples with different numbers of reads in each microbiome type.\u003c/p\u003e\n\u003cp\u003eFamilies and higher classifications that had uppercase letters as suffixes represented non-monophyletic groupings in the reference phylogeny construction of GTDB, although there is evidence that such groups are monophyletic. Genera with the same suffix pattern were polyphyletic or subdivided according to the database\u0026apos;s reference phylogeny. Species names can also have the same suffix pattern if they categorize a grouping that may contain ambiguity in the correct nomenclature\u003csup\u003e52\u003c/sup\u003e. Other codes present in the classifications (e.g. \u003cem\u003eNSJ-53\u003c/em\u003e or sp001543345) represented the first type material used as a reference for clustering in the respective operational taxonomic units (OTUs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of serum cytokine profile was performed using GraphPad Prism software version 8. Outliers were identified via ROUT test (Q\u0026thinsp;=\u0026thinsp;1%). The data were subjected to the Shapiro-Wilk normality test. Based on the results, if the data followed a Gaussian distribution, they were subjected to one-way analysis of variance, using Tukey\u0026apos;s post hoc test for multiple comparisons. If the data did not follow a Gaussian distribution, they were subjected to the Kruskal-Wallis test followed by Dunn\u0026apos;s post hoc. For both tests, a difference was considered significant when \u003cem\u003eP \u0026lt;\u003c/em\u003e 0.05.\u003c/p\u003e\n\u003cp\u003eThe statistical analyses and graphs of the fecal microbiome were performed using the R software\u003csup\u003e53\u003c/sup\u003e. The statistical comparison between groups in alpha diversity analyses was conducted using the non-parametric Kruskal-Wallis test followed by Dunn\u0026apos;s post hoc. Beta diversity was analyzed using permutational multivariate analysis of variance (PERMANOVA) in the QIIME2 pipeline, with 10,000 permutations. Alpha diversity analyses were calculated using the libraries \u0026quot;phyloseq\u0026quot;\u003csup\u003e54\u003c/sup\u003e, \u0026quot;vegan\u0026quot;\u003csup\u003e55\u003c/sup\u003e, and \u0026quot;Microbiome\u0026quot;\u003csup\u003e56\u003c/sup\u003e. To identify specific taxa that may have undergone modulation between the analyzed groups, differences in relative abundances were analyzed using the Kruskal-Wallis test with Dunn\u0026apos;s post hoc at a 95% confidence level for lower taxonomic classifications: family, genus, and species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the efforts and support in the research from the Elanco Animal Health Incorporated Company, Universidade Estadual do Oeste do Paran\u0026aacute;, Copagril Agroindustrial Cooperative, and the Universidade Federal de Vi\u0026ccedil;osa.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePLOC: conceptualization, data curation, and project management. JLG, PLOC, CE and EFRE: methodology. JLG: software, statistical analysis and formal analysis. JPSL: writing\u0026mdash;original draft preparation. PLOC and JLG: validation. EFRE, GLM, ALGT, AGB, ACT and LBA: investigation. JPSL, PSC, JLG, CE and PLOC: writing\u0026mdash;review and editing. PLOC, STC, CE and MK: supervision. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest for this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis project was funded by the Elanco Animal Health Incorporated Company.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLiu, H., Hou, C., Li, N., Zhang, X., Zhang, G., Yang, F., Zeng, X., Liu, Z. \u0026amp; Qiao, S. 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Introduction to the microbiome R package. \u003cem\u003eBioconductor\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18129/B9.bioc.microbiome\u003c/span\u003e\u003cspan address=\"10.18129/B9.bioc.microbiome\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"anti-inflammatory cytokines, carbohydrases, exogenous enzymes, fecal microbiota, lactating sows, pro-inflammatory cytokines","lastPublishedDoi":"10.21203/rs.3.rs-4449417/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4449417/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnzyme-supplemented diets can influence the intestinal microbiome in an intricate interplay with the immune system. The effects of β-mannanase supplementation in metabolizable energy (ME)-reduced diets containing xylanase were investigated on cytokine profile and fecal microbiota in lactating sows (n\u0026thinsp;=\u0026thinsp;60, 248.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 kg) assigned in a randomized block design to 1 of 3 dietary treatments: a control diet containing xylanase (valorization of 40 kcal of ME/kg diet, CD40), CD40\u0026thinsp;+\u0026thinsp;β-mannanase (0.3 g/kg, valorization of 45 kcal ME/kg diet, CD85), and CD40\u0026thinsp;+\u0026thinsp;β-mannanase (0.3 g/kg, valorization of 60 kcal ME/kg diet, CD100). Serum cytokines concentrations were determined on day 18 of lactation. On day 21, fecal microbiota composition was characterized by 16S rRNA gene sequencing. Sows on CD85 had higher alpha diversity richness than CD100 based on the Simpson index. Acutalibacteraceae family was more abundant in sows fed CD100 than CD85 but CAG-508 and NSJ_53 families exhibited higher abundance in sows fed CD85 than CD100. \u003cem\u003eFimenecus\u003c/em\u003e genus exhibited lower abundance in sows on CD85 compared to CD40 or CD100. In conclusion, a diet supplemented with β-mannanase reduced by 85 kcal/kg containing xylanase during lactation can inhibit harmful bacteria, leading to changes in fecal alpha diversity in sows.\u003c/p\u003e","manuscriptTitle":"β-mannanase-supplemented diets reduced by 85 kcal of metabolizable energy/kg containing xylanase promotes benefits in fecal alpha diversity in lactating sows","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-17 12:25:23","doi":"10.21203/rs.3.rs-4449417/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05dae478-fa7f-4b45-9c2f-9cceb9b4cc24","owner":[],"postedDate":"June 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33226652,"name":"Biological sciences/Microbiology/Communities"},{"id":33226653,"name":"Biological sciences/Immunology/Cytokines"},{"id":33226654,"name":"Biological sciences/Zoology/Animal physiology"}],"tags":[],"updatedAt":"2024-07-08T02:53:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-17 12:25:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4449417","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4449417","identity":"rs-4449417","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}