Breast Milk Bacteria: The Key to Regulating Defecation Frequency Changes in Infants

Breast Milk Bacteria: The Key to Regulating Defecation Frequency Changes in Infants | 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 Breast Milk Bacteria: The Key to Regulating Defecation Frequency Changes in Infants Yongkun Huang, Yuanyuan Zhang, Kai Liu, Yan Chen, Zhen-Rong Xie, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4146767/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 Breastfeeding can significantly impact the establishment of the infant's intestinal microbiota. In this study, we hypothesized that maternal breast milk bacteria were associated with variations in defecation frequency in infants aged 1 to 6 months who were exclusively breastfed, and we sought to identify potential breast milk microbiota diagnostic markers. 102 exclusively breastfed infants aged at 1 to 6 months were enrolled in the study. Then, we collected their mothers' breast milk as samples for 16S rRNA sequencing evaluation of microbiotas. The results revealed a clear distinction between the three groups regarding microbiota structures and compositions. Changes were observed in the various species and genera, and the breast milk microbiota features Hydrogenobacteria , Serratia , and Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium were confirmed as potential biomarkers for regulating the change in neonate defecation frequency. This study demonstrates a significant correlation between the frequency of defecation in exclusively breastfed infants and the microbiota in their mothers' milk. It was discovered that the human breast milk microbiota may play a significant metabolic role in amino acids and oligosaccharides during its colonization in infants' intestines, which influences their defecation frequency. Our research provides new evidence and hypotheses regarding the association between infant defecation frequency and breast milk microbiome. Trial Registration This trial was registered on 22/12/2023 at www.chictr.org.cn as ChiCTR2300078973. Biological sciences/Microbiology Health sciences/Medical research breastmilk microbiome lactation frequency of infant defecation Figures Figure 1 Figure 2 Figure 3 Introduction Some exclusively breastfed infants can have more frequent daily stools 1–3 . Simultaneously, the prevalence of infrequent stools in exclusively breastfed infants (some of whom have no bowel movements or infrequent stools for several days) was clinically common in the outpatient department 4 . Recent research indicates that lactation is one of the most influential factors in establishing the diversity of the infant's intestinal microbiota 5–8 . In addition, Shin, SP, and colleagues 9 demonstrate that Lactobacillus gasseri BNR17 isolated from breast milk enhanced the mean defecation frequency of diarrhea-predominant irritable bowel syndrome (IBS-D) by stimulating gut-friendly bacteria. According to the studies cited above, by modulating the intestinal microbiota in infants, the breast milk microbiota may alter the frequency of defecation. Therefore, we hypothesize that maternal breast milk bacteria are associated with variations in defecation frequency in infants aged 1 to 6 months who are exclusively breastfed, thereby identifying potential breast milk microbiota diagnostic markers. In the meantime, this study has an important implication for developing infant medical food and formula milk additives that can mitigate variations in infant defecation frequency. Consuming prebiotics identical to those found in human breast milk can alter a baby's defecation pattern by preserving the microecological equilibrium of their intestinal microbiota 10 . IBS-D in children treated with synbiotic preparation could significantly alleviate intestinal symptoms 11 . In addition, some studies have demonstrated that supplementation with galacto-oligosaccharide formula milk increases the beneficial bacteria, short-chain fatty acids, and defecation frequency in infants while inhibiting the pathogenic bacteria 12,13 . Moreover, breast milk contains proteins that govern the intestinal microbiota and immune system 14,15 . Another objective of this study was to examine the breast milk microbiota associated with infant defecation and predict their involvement in metabolic pathways and functional proteins. Results Microbiota in Breast Milk Linked to Variable Infant Defecation Frequency Tables 1 and 2 describe the characteristics of mothers and infants, respectively. Age and fecal characteristics of exclusively breastfed infants differed substantially among the three groups based on defecation frequency, and the frequency of bowel movements was significantly associated with stool consistency ( P 0.05; Table 1 , 2 ). Table 1 Descriptive Characteristics of the Breastfed Infants Characteristics DI (n = 37) DN (n = 31) DD (n = 34) P Value Age, median (IQR), days 50 (38, 94) 56 (42, 120) 90 (50, 150) 0.02 Female, No. (%) 16 (43) 16 (42) 15 (44) 0.76 Parity, median (IQR) 1 (1, 2) 1 (1, 2) 1 (1, 2) 0.58 Delivery mode, No. (%) Vaginal delivery 32 (86) 25 (81) 29 (85) 0.52 Cesarean section 5 (14) 6 (19) 5 (15) Fecal characteristics, No. (%) Hard 1 (3) 0 (0) 1 (3) a 8 times per day 24 (65) 18 (58) 16 (47) 0.28 6–8 times per day 10 (27) 10 (32) 17 (50) < 6 times per day 3 (8) 3 (10) 1 (3) a Gamma rank correlation coefficient:0.8309. Table 2 Descriptive Characteristics of the Nursing Mothers Characteristics DI (n = 37) DN (n = 37) DD (n = 34) P Value Age, mean (SD), years 30 (4) 31 (4) 30 (3) 0.1 Pre-pregnancy BMI, mean (SD), Kg/m2 21 (2) 21 (3) 20 (3) 0.54 Parturient BMI, mean (SD), Kg/m2 26 (3) 25 (3) 26 (3) 0.67 Emptying status of the breast, No. (%) Bilateral emptying 5 (14) 7 (23) 5 (15) 0.37 Unilateral emptying 23 (62) 19 (61) 26 (76) Neither side is emptying 9 (24) 5 (16) 3 (9) Mood, No. (%) Enjoyable 21 (57) 13 (42) 18 (53) 0.31 Not bad 15 (41) 18 (58) 13 (38) Dysphoric and scared 1 (2) 0 (0) 1 (3) Depressive 0 (0) 0 (0) 2 (6) Total sleeping times, No. (%) 10 hours per day 2 (5) 1 (3) 5 (15) Monthly income, No. (%) ¥ 4000 14 (38) 12 (39) 21 (62) The RDA analyses were then used to investigate the effects of various factors (the age of infant-mother pairs, infant fecal characteristics, breastfeeding frequency, mother sleeping periods, and family income were selected from Tables 1 and 2 as P < 0.3 factors). Notably, RDA analyses reveal that infant defecation frequency and fecal characteristics both resulted in variations in microbiota composition (FDR < 0.05; Fig. 1 d). Comparative Analysis of the Microbiota Structure in Breast Milk Among Three Groups Observed species and Shannon index were used to calculate the alpha diversity of human breast milk microbiota in three groups, and no significant differences were found ( P > 0.05; Fig. 1 b). Through PCoA analysis, we observed a substantial difference in microbiota composition between three groups ( P < 0.001; Fig. 1 c). Sample coordinates for the same body site did not wholly overlap among the three groups (DI vs. DN, DD vs. DN), indicating that variations in defecation frequency were related to the microbiota in human breast milk. At the phylum level, milk samples were dominated by Proteobacteria, Firmicutes, and Actinobacteria. Firmicutes and Bacteroidetes had the highest relative abundance in the DD group, while Proteobacteria had the highest close plenty in the DN group (Firmicutes, P = 0.0022; Bacteroidetes, P = 0.0428; Proteobacteria: P = 0.0224; Supplementary Figure S1 or Supplementary Table S1 ). Burkholderia-Caballeronia-Paraburkholderia , Serratia , Streptococcus , and Staphylococcus were the most prevalent genera in all samples. Specifically, the relative abundance of the bacterial genera Akkermansia , Roseburia , Lachnospiraceae_unclassified , and Ruminococcus_1 was substantially more significant in the DI group than in the DN group, followed by the DD group. In contrast, the relative abundance of Aerococcus , Rothia , Citrobacter , Catellicoccus , and Gemella was the opposite ( P < 0.05; Fig. 1 a or Supplementary Table S2). Seclction of Significant Charateristics Relating to Changes in Defecation Frequency To further identify the variation in beta diversity attributable to changes in stool frequency, we employed LEfSe analysis to present indicators of distinct groups. The DI group was enriched with Megasphaera , Escherichia-Shigella , Megamonas , Dechlorosoma , Bifidobacterium , Faecalibacterium , Lachnospiraceae_unclassified , and Geobacillus . Serratia , Rothia , Pseudacidovorax , and Dechloromonas were identified as members of the DN group. In addition, the DD group had a greater abundance of Burkholderia-Caballeronia-Paraburkholderia , Staphylococcus , Faecalibacterium , Hydrogenophilus , Comamonas , Megasphaera , Phascolarctobacterium , Dechlorosoma , Bifidobacterium , Aeribacillus , Geobacillus , Bacillus , and Blautia than the DN group. Other microorganisms that accumulated in DN breast milk were Serratia , Raoultella , Phyllobacterium , Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium , Pseudacidovorax , and Herbaspirillum (Fig. 2 a). The ROC model was then applied to predict the potential biomarkers based on the top 5 relative abundances of shared human breast milk genera between the DI and DN groups and the DD and DN groups. Among all samples and relative metadata, as indicated in Fig. 2 b, Hydrogenophilus , Serratia , and Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium in breast milk had the most potent predictive effect when discriminating to the DD and the DN samples ( Hydrogenophilus :AUC = 0.7856; Serratia: AUC = 0. 7633; Allorhizobium-Neorhizobium-Pararhizobium- Rhizobium: AUC = 0.7111; Fig. 2 b). In the same line, we discovered that Bifidobacterium and Megamonas distinguished the DI group more effectively ( Bifidobacterium: AUC = 0.6626; Megamonas: AUC = 0.6513; Fig. 2 b). Analyses of Correlation Between Breast Milk Microbiota and Factors In human breast milk, the microbiota microbes share the same microenvironment and interact. Consequently, co-network simulation was carried out utilizing microbiome analysis. Serratia comprised the nucleus of the co-network' DI group, followed by Allorhizobium-Neorhizobium-Pararhizobium- Rhizobium , Raoultella , and Herbaspirillum . In the meantime, the DN group's main genera, Herbaspirillum , Phyllobacterium , Raoultella , Pseudacidovorax etc., shared close relationships. (| r| > 0.07, FDR < 0.05; Supplementary Figure S2). As shown in Fig. 1 d, frequent defecation is positively associated with Megamonas , Megasphaera , Blautia , and Akkermansia in breast milk, whereas it is negatively associated with Staphylococcus , Dechlorosoma , Bifidobacterium , Rothia, Catellicoccus , in addition to Citrobacter . Catellicoccus and Akkermansia are positively associated with more watery feces, whereas Megamonas , Blautia , Megasphaera , Staphylococcus , Dechlorosoma , Bifidobacterium , Citrobacter , and Rothia are negatively associated with the fecal consistency index (FDR < 0.05; Fig. 1 d). Relationships Between Breast Milk Microbiota and Various Functions and Phenotypes Comparing the DI group to the DD group, the proportion of most genes involved in amino acid biosynthesis was significantly higher in the DD group than in the DN group, whereas the DN group had a higher proportion of most genes involved in amino acid degradation and D-galacturonate degradation (FDR < 0.05; Fig. 3 a). Then we predicted their functions on infant defecation frequency by determining whether target breast milk microbes possessed critical enzymes implicated in distinct metabolic pathways. Ten genes displayed same trends, with their abundances increasing in the DI group and decreasing in the DD group ( P < 0.05; Supplementary Table S3). According to the Spearman's correlation coefficient, represented as a heatmap, we discovered that ten distinct genes were consistently positively associated with Serratia , Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium , Raoultella , and Herbaspirillum . Positive correlations were observed between Phyllobacterium and COG3733, EC:1.4.3.21, K00276, etc. In addition, Akkermansia had a positive correlated with EC:1.4.3.21, K00276, K18144, etc. (| r| > 0.3, FDR < 0.05; Fig. 3 b). The BugBase analysis revealed that taxonomic samples from the DI and DD groups had substantially higher Anaerobic phenotypes than those from the DN group ( P < 0.05; Supplementary Table S4). Based on their co-network, this coefficient was also used to assess the relationship between breast milk microbiota and various phenotypes. Intriguingly, the higher Anaerobic phenotype of DD and DI breast milk was associated with increased Bifidobacterium levels in both DD and DI groups. Phyllobacterium , on the other hand, was negatively correlated with the anaerobic phenotype (| r| > 0.5, FDR < 0.05; Fig. 3 c). Discussion Having ruled out other confounding factors based on RDA analysis, our research determined that infant defecation frequency had the most significant influence on milk microbial structure variability, followed by stool characteristics. PCoA demonstrated a distinct separation in the structure of breast milk microbiota between the three groups (with a more similar microbiota composition of each sample in the DI group compared to the DD and DN groups). The prevalent milk phyla were then determined to be Firmicutes and Actinobacteria. Firmicutes and Bacteroidetes were most abundance in the group with reduced defecation frequency, while Proteobacteria were most abundant in the standard group. Proteobacteria and Firmicutes were the predominant fecal microbiota of infants aged at 1 to 6 months who were supplemented with breast milk, consistent with the findings of Drall, K.M 16 . A series of studies found that the abundance of Firmicutes and Bacteroidaceae was higher in the feces of children with constipation 17,18 . All of these findings indicate that lactation influences the colonization of infant gastrointestinal microbiota 19 . The mother's vivo dendritic cells accumulate their gastrointestinal microbiota and transfer it to the breast via blood and lymph 20 . After being transmitted to the infant's gastrointestinal tract through breastfeeding, the microbiota's effects will persist throughout the child's childhood 5 . Based on the LEfSe and ROC analyses, Hydrogenophilus , Serratia , and Allorhizobium-Neorhizobium-Pararhizobium- Rhizobium were identified as potential biomarkers for distinguishing the DD and DN groups; Furthermore, the DI and DD groups, the core regulatory role of breast milk feature microbiota was weaker than in the DN group. In addition, previous studies have confirmed that the differences and feature genus of this study are related to changes in defecation frequency, as follows: As is known, Akkermansia strains in human breast milk are mucin-degrading bacteria, and their genomes are equipped with Human milk oligosaccharides (HMOs) deconstruction related glycoside hydrolases; capacity to increase the defecation frequency and soften stool 21–23 ; and Therefore, the increased frequency and production of smoother feces in the DI group could be explained by the function of the Akkermansia in human breast milk. In addition, the catabolism of dietary amino acids mediated by Ruminococcus can enhance gastrointestinal transport and colonic secretion by improving serotonin biosynthesis in intestinal enterochromaffin cell 24 . Like Yang, J. et al., 25 our findings demonstrate that Ruminococcus positively correlates with feces frequency. By participating in the absorption of HMOs and converting aromatic amino acids into their lactic acid derivatives in the intestine, Bifidobacterium may cause an increase or decrease in the defecation frequency of infants, according to our findings 26–28 . In addition, Bifidobacterium and galactose-containing di- and oligosaccharides (GOS) in human milk may modulate the expression of serine protease inhibitors 29,30 . Galactose metabolism has been linked to Megamonas and has been shown to increase feces frequency and consistency 31,32 . Lachnospiraceae 33 is antagonistic to HMOs, Phascolarctobacterium 34 , Roseburia 35 , and Faecalibacterium 36 , and promotes short-chain fatty acid (SCFA) to increase the frequency of bowel movements 37 . The relationship between Citrobacter and Comamonas 38 , Aerococcus 39 , Escherichia-Shigella 40 , Blautia 41 , and Bacillus 42 and changes in defecation frequency in infants is consistent with several other studies. According to several contradictory studies, Serratia is detrimental to intestinal epithelial cells and can cause diarrhea in infants. Zhang, Z. et al. 43 demonstrated that fructooligosaccharides can increase the population of Megasphaera and decrease the incidence of diarrheal in piglets. Staphylococcus has a positive correlation with total oligosaccharide concentration 44 , and reducing this concentration can reduce the incidence of constipation in rodents 45 . The well-known beneficial bacterium Bifidobacterium can enhance children's bowel movements. Varied specimens, sample counts, sample collection, processing, analysis methods, and mixed infant age, diet and health status 46–50 may need to be corrected with this study. Besides, the above genera are involved in metabolizing oligosaccharides and amino acids. Relevant research has shown that the genera of Bifidobacterium 51 , Lachnospiraceae 52 , Roseburia 53 , Citrobacter 54 , Dechromomonas 55 , Akkermania 56 , Ruminococcus 57 , Phascolarctobacterium 58 , Bacillus 59 , Serratia, and Megasphaera all take part in the metabolism of amino acids. To demonstrate the biological significance of the distinct characteristics and microorganisms, we predicted their functions by determining whether critical enzymes involved in the metabolism of oligosaccharides and amino acids were related to the variation in defecation frequency. We then found the higher primary-amine oxidase key enzyme in the DI group matched to γ-Gammaproteobacteria–Enterobacteriaceae (subordinate genera include Serratia and Raoultella ) in the Kyoto Encyclopedia of Genes and Genomes (KEGG), this homeotic gene is involved in the metabolism of Glycine, serine, and threonine (map00260), Tyrosine metabolism (map00350) and Phenylalanine metabolism (map00360), in addition to other metabolic pathways. The findings of Riederer, M., and his colleagues 60 confirmed that a correlation between threonine in human milk and the abundance of Gammaproteobacteria, which has overlapped with our research, and they supported the possibility of an interaction between human milk-free amino acids and the composition of intestinal microbiota in early lactation infants. Indeed, a protein-rich diet is likely to increase beneficial amino acids in the cecum 61 . Casein is the most abundant milk protein; its conjugated protein is synthesized by combining a phospholipid bond with threonine and serine hydroxyl groups, thereby decreasing fecal frequency and drying out feces. Aminoacetone, a threonine metabolite, produces methylglyoxal upon activation of primary amine oxidase. Pyruvic acid salt produced by serine metabolism interacts with methylglyoxal production (map00260). The serine and threonine content of the DI group may be lower than that of the DN group, and the DN group's content is lower than that of the DD group. This is consistent with the findings of Xu, S, and others 62 who determined that Glycine, serine, and threonine metabolism is involved in persistent diarrhea in children. Edogawa, S, and coworkers 63 also confirmed that the paracellular permeability is increased, tight junction protein expression is decreased, and the presentation of phosphorylated myosin light chain is elevated in feces with high serine proteolytic activity, thereby increasing the permeability of intestinal mucosa and promoting more defecation. In the meantime, Law, GK, et al. 64 confirmed that threonine is used for intestinal mucous protein production and that a diet deficient in threonine will cause persistent diarrhea in piglets. While searching the KEGG database, we discovered that primary amine oxidase in DD group had a reduced annotation in function pathway of Tyrosine metabolism (map00350) and Phenylalanine metabolism (map00360), similar to Zhang, Q. et al.'s findings in rodents 65 . Therefore, the variation in the frequency of defecation in infants may be related with the regulation of the expression levels of primary amine oxidase implicated in the pathways of amino acid metabolism. Additionally, intestinal microorganisms can regulate the utilization of amino acids 66 , and dietary amino acids can also influence the composition of colonic microbiota and their metabolites 67 . Consequently, protein compounds in human milk can modulate the microbial composition of infants 68 . According to this investigation, primary amine oxidase is positively associated with Serratia. Further, we hypothesized that reduced level of Serratia in breast milk contribute to decreased gastrointestinal movements frequency in exclusively breastfed infants. In addition, we discovered that the relative abundance of Serratia in the DI and DN groups was substantially more significant than in the DD group. This study predicted that DI and DD [outcomes] have higher anaerobic phenotype [exposure factors] association with a higher relative abundance of Bifidobacterium [genotype] in human milk. Studies have confirmed that GOS substantially increased the frequency of defecation by producing anaerobic bacteria 69 . Meanwhile, Bifidobacterium , an anaerobic bacterium that can produce more butyric acid in the intestines, has been shown to reduce the frequency of defecation in exclusively breastfed infants 26 . This study hypothesizes that the change in defecation frequency in children aged 1 to 6 months who are exclusively breastfed may be related to the higher anaerobic phenotype of human breast milk, primarily influenced by the relatively high abundance of Bifidobacterium . Tang, W. et al. 70 discovered that breastfeeding can modulate infant gut microbiota, characterized by low levels of Gram-negative bacteria, to prevent Hirschsprung-associated enterocolitis. In subsequent isolation and cultivation of maternal microbiota, we can effectively prevent the growth environment of anaerobic bacteria to determine whether it can reduce the change in defecation frequency in exclusively breastfed infants. Conclusions This study is the first to propose potential links between breast milk microbiota and defecation frequency variations among exclusively breastfed infants aged 1–6 months. It sheds light on possible underlying mechanisms related to the metabolism of amino acids and D-galacturonate, offering new insights into human breast milk's impact on defecation frequency changes. In addition, we propose a prospective biomarker diagnostic method comprised of the human milk microorganisms Hydrogenophilus , Serratia , and Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium . Additionally, we discovered that the anaerobic genus Bifidobacterium in human milk is associated with a higher anaerobic phenotype in DD and DI breast milk and can be used to identify the DI group. Nevertheless, due to limitations in sample size and analysis methodologies, our results must be validated and investigated further using multiple data sources (including breast milk microbiota and infant intestinal microbiota) and large cohorts. In the future, we will use muti-Omics and whole microbiome association analysis to conduct in-depth research at numerous time points and isolate beneficial bacteria from breast milk microbiota using pure culture, laying the groundwork for developing an infant's exceptional medical food and infant formula milk. Methods Subjects and Sample Assemblage From August 2020 to August 2021, mother-infant pairs were enrolled at the First Affiliated Hospital of Kunming Medical University. We recruited 102 couples of fit mothers and infants. The inclusion criteria for infants were as follows: Age between 1 and 6 months Term infants of average weight No use of probiotics or antibiotics within the previous four weeks The exclusion criteria are as follows: There is no infectious diarrhea, biliary diseases, anorectal diseases, congenital neuro-muscular disease, metabolic and endocrine diseases, hereditary diseases, or drug-induced abnormal defecation. Stool frequency and traits must have changed significantly in the two weeks preceding the study. No severe eczema and cow’s-milk protein allergy. The corresponding mothers met the following criteria: Excellent physical and mental health during pregnancy and breastfeeding Healthy breast status No use of probiotics and antibiotics during pregnancy and breastfeeding The exclusion criteria are as follows: Absence of gestational diabetes mellitus, gestational hypertension, and hypothyroidism Absence of allergy Lack of anemia and malnutrition Absence of neuropsychiatric disorders Lack of medical family history Absence of poor habits The infants were divided three groups (DI, n = 37; DD, n = 34; and DN, n = 31) based on the frequency of defecation: those who defecated more than three times per day, those who defecated more than four days or required assistance, and those who defecated once within three days or less than three times (including three times) per day. All breast milk samples were collected manually with sterile gloves from the mother's breast before feeding the infant; the mother's breast was disinfected before milk collection; and the pieces were aliquoted into 10ml to 15ml sterile containers and stored − 80℃ until analysis. The clinical data of mothers and infants were collected through questionnaires. Table 1 , 2 provide a summary of this information. This study was approved by the Medicine Ethics Committee of the First Affiliated Hospital of Kunming Medical University (Protocol # (2023) L23-1). The trial was performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its later amendments. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. Participation was voluntary and participants were free to withdraw from the study at any stage. DNA Extraction, PCR Amplification, Library Preparation, and Sequencing of the 16S rRNA Gene All the human milk samples were transferred to a 37℃ thermostatic water immersion and then centrifuged at low speed (200g, 10 minutes) at a low rate. After centrifugation, the lower liquid was extracted with a 10.0ml aseptic syringe, avoiding the upper fat filtered through a 0.22um filter membrane. DNA extraction was performed by the E.Z.N.A.®Water DNA Kit according to the manufacturer's instructions, and then, the V3-4 region of 16S rDNA gene was amplified using barcoded primers (341F-5 ' -CCTACGGGNGGCWGCAG-3 ', 806R-5 ' -GACTACHVGGGCTAATCC-3 ' ) and the following conditions: 98°C(0:30) + [98°C(0:10) + 54°C(0:30) + 72°C(0:45)] 35 cycles + 72°C(10:00) . On a library, the PCR product was subsequently detected, recovered, and quantified 71 . The aggregated library was deposited on NovaSeq PE250 platform using a paired-end high-throughput sequencing protocol (2 x 250 bp). The fields of Bioinformatics Analysis The raw sequence reads (mean 44,339, standard deviation 12,614.06) were quality-filtered (fqtrim v0.94), de-noised, de-replicated, merged (FLASH v1.2.8), and checked for chimeric sequences (Vsearch software v2.3.4). Following DADA2 deduplication, we obtained a feature table and the feature sequences. The relative abundance of each Sample was computed after determining the bacterial taxonomy of DADA2 representative sequences using SILVA release 132 at 100 percent. The species' sequence alignment (Blast) was annotated (SILVA database). Alpha diversity and Beta diversity were analyzed using the QIIME2 procedure, and R (v2.15.3) was used to generate visual representations. Principal coordinates analysis (PCoA) was utilized to visualize and validate significant differences in the microbiota of human breast milk. Potential microbial biomarkers were identified using LefSe and Receiver-Operating Characteristic (ROC) analysis. Possible microbiome functional differences were assessed using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) and predicted using the enrichment of Metacyc pathway in the 16S rRNA gene profiles. We also assessed the association between factors, phenotypes, function, and bacterial genus using heatmap, network and Redundancy analysis (RDA). Statistical Analysis In addition, normally distributed variables were analyzed using the F test, and the Kruskal-Wallis test was used to compare groups for nonparametric tests. The χ 2 test evaluates the distinctions between binary independent variables and ordinal one-way dependent variables. Two-way ordinal categorical variables were analyzed with SPSS (v 25.0) using Trend χ 2 test, Fisher's exact test, and Gamma test. We adjusted for multiple testing using the Benjamini and Hochberg procedure with the false discovery rate (FDR). P -value and FDR < 0.05 (two-tailed) was selected as cutoffs. Declarations Acknowledgements: We thank the mothers that donated their milk samples for this project and the authors would also like to thank Hangzhou Lianchuan Biological information company for technical support. The Biobank and the Preventive Health Care of the First Affiliated Hospital of Kunming Medical University provided services supporting this work. Data Availability: The original sequencing data that support the finding of this study are available in the ResMan: http://www.medresman.org.cn/uc/projectsh/projectedit.aspx?proj=5347. All data analysed during this study are included in this published article (and its supplemental materials). The datasets are available from the corresponding author on reasonable request. Author Contributions: Yuanyuan Zhang, Yan Chen, Yunfei Xie, and Zhaoxia Xiong collected specimens. Yuanyuan Zhang, and Mei Liu performed laboratory sample analyses and data analyses. Yuanyuan Zhang wrote the manuscript. Yongkun Huang, and Zhenrong Xie planned and executed experimental trials. Kai Liu, Meng Li, Jingjing Xiong, and Zhanhua Li revised the manuscript, and all authors interpreted the data and revised the manuscript for important intellectual content and approved the final draft. Competing Interests: All the authors declare no conflict of interests. Funding/Support: This trial was initiated and planned by the researchers and funded by the National Natural Science Foundation of China (grant NO. 81960102). The study has no sponsor and was only supported by this public funding. The investigators received no fees from any industry. Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: No industry or commercially interested parties accessed the data before their publication. References Tunc, V. T., Camurdan, A. D., Ilhan, M. N., Sahin, F. & Beyazova, U. Factors associated with defecation patterns in 0-24-month-old children. Eur J Pediatr 167 , 1357–1362 (2008). Moretti, E., Rakza, T., Mestdagh, B., Labreuche, J. & Turck, D. The bowel movement characteristics of exclusively breastfed and exclusively formula fed infants differ during the first three months of life. Acta Paediatr 108 , 877–881 (2019). Çamurdan, A. D., Beyazova, U., Özkan, S. & Tunç, V. T. Defecation patterns of the infants mainly breastfed from birth till the 12th month: Prospective cohort study. Turk J Gastroenterol 25 Suppl 1 , 1–5 (2014). Courdent, M., Beghin, L., Akré, J. & Turck, D. Infrequent stools in exclusively breastfed infants. Breastfeed Med 9 , 442–445 (2014). Cioffi, C. C., Tavalire, H. F., Neiderhiser, J. M., Bohannan, B. & Leve, L. D. History of breastfeeding but not mode of delivery shapes the gut microbiome in childhood. PLoS One 15 , e0235223 (2020). Johnson, J. M., Adams, E. D. & O'Neal, P. V. Promoting and Protecting the Gastrointestinal Newborn Microbiome Through Breastfeeding Practices. J Perinat Neonatal Nurs 34 , 222–230 (2020). Pannaraj, P. S. et al. Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome. JAMA Pediatr 171 , 647–654 (2017). Liu, C. E. et al. Composition characteristics of the gut microbiota in infants and young children of under 6 years old between Beijing and Japan. Transl Pediatr 10 , 790–806 (2021). Shin, S. P. et al. A double blind, placebo-controlled, randomized clinical trial that breast milk derived- Lactobacillus gasseri BNR17 mitigated diarrhea-dominant irritable bowel syndrome. J Clin Biochem Nutr 62 , 179–186 (2018). Béghin, L. et al. Fermented infant formula (with Bifidobacterium breve C50 and Streptococcus thermophilus O65) with pre biotic oligosaccharides is safe and modulates the gut microbiota towards a microbiota closer to that of breastfed infants. Clin Nutr 40 , 778–787 (2021). Skrzydło-Radomańska, B. et al. The Effectiveness of Synbiotic Preparation Containing Lactobacillus and Bifidobacterium Probiotic Strains and Short Chain Fructooligosaccharides in Patients with Diarrhea Predominant Irritable Bowel Sy ndrome-A Randomized Double-Blind, Placebo-Controlled Study. Nutrients 12 , 1999 (2020). Ben, X. M. et al. Low level of galacto-oligosaccharide in infant formula stimulates growth of intestinal Bifidobacteria and Lactobacilli. World J Gastroenterol 14 , 6564–6568 (2008). Veereman-Wauters, G. et al. Physiological and bifidogenic effects of prebiotic supplements in infant formulae. J Pediatr Gastroenterol Nutr 52 , 763–771 (2011). Aparicio, M., Alba, C., Cam Public Health Area, P., Rodríguez, J. M. & Fernández, L. Microbiological and Immunological Markers in Milk and Infant Feces for Common Gastrointestinal Disorders: A Pilot Study. Nutrients 12 , 634 (2020). Li, N. et al. Human milk and infant formula modulate the intestinal microbiota and immune systems of human microbiota-associated mice. Food funct 12 , 2784–2798 (2021). Drall, K. M. et al. Clostridioides difficile Colonization Is Differentially Associated With Gut Microbiome Profiles by Infant Feeding Modality at 3–4 Months of Age. Front Immunol 10 , 2866 (2019). Kim, M. C. et al. Effects of ID-HWS1000 on the Perception of Bowel Activity and Microbiome in Subjects with Functional Constipation: A Randomized, Double-Blind Placebo-Controlled Study. J Med Food 24 , 883–893 (2021). Niu, J. et al. Evolution of the Gut Microbiome in Early Childhood: A Cross-Sectional Study of Chinese Children. Front Microbiol 11 , 439 (2020). Fehr, K. et al. Breastmilk Feeding Practices Are Associated with the Co-Occurrence of Bacteria in Mothers' Milk and the Infant Gut: the CHILD Cohort Study. Cell Host Microbe 28 , 285–297.e284 (2020). Lemaire, M., Le Huërou-Luron, I. & Blat, S. Effects of infant formula composition on long-term metabolic health. J Dev Orig Health Dis 9 , 573–589 (2018). Luna, E. et al. Utilization Efficiency of Human Milk Oligosaccharides by Human-Associated Akkermansia Is Strain Dependent. Appl Environ Microbiol 88 , e0148721 (2022). Parschat, K., Melsaether, C., Jäpelt, K. R. & Jennewein, S. Clinical Evaluation of 16-Week Supplementation with 5HMO-Mix in Healthy-Term Human Infants to Determine Tolerability, Safety, and Effect on Growth. Nutrients 13 , 2871 (2021). Toporovski, M. S., de Morais, M. B., Abuhab, A. & Crippa Júnior, M. A. Effect of Polydextrose/Fructooligosaccharide Mixture on Constipation Symptoms in Children Aged 4 to 8 Years. Nutrients 13 , 1634 (2021). Zhai, L. et al. Ruminococcus gnavus plays a pathogenic role in diarrhea-predominant irritable bowel syndrome by increasing serotonin biosynthesis. Cell host microbe 31 , 33–44.e35 (2023). Yang, J. et al. Involvement of mucosal flora and enterochromaffin cells of the caecum and descending colon in diarrhoea-predominant irritable bowel syndrome. BMC Microbiol 21 , 316 (2021). Nocerino, R. et al. The therapeutic efficacy of Bifidobacterium animalis subsp. lactis BB-12® in infant colic: A randomised, double blind, placebo-controlled trial. Aliment Pharmacol Ther 51 , 110–120 (2020). McKeen, S. et al. Infant Complementary Feeding of Prebiotics for the Microbiome and Immunity. Nutrients 11 , 364 (2019). Laursen, M. F. et al. Bifidobacterium species associated with breastfeeding produce aromatic lactic acids in the infant gut. Nat Microbiol 6 , 1367–1382 (2021). Duboux, S. et al. Carbohydrate-controlled serine protease inhibitor (serpin) production in Bifidobacterium longum subsp. longum. Scientific reports 11 , 7236 (2021). McCarville, J. L. et al. A Commensal Bifidobacterium longum Strain Prevents Gluten-Related Immunopathology in Mice through Expression of a Serine Protease Inhibitor. Applied and environmental microbiology 83 , e01323-01317 (2017). Wu, D. T. et al. Dynamic changes of structural characteristics of snow chrysanthemum polysaccharides during in vitro digestion and fecal fermentation and related impacts on gut microbiota. Food Res Int 141 , 109888 (2021). Yu, T. et al. Effects of Prebiotics and Synbiotics on Functional Constipation. Am j med sci 353 , 282–292 (2017). Borewicz, K. et al. The association between breastmilk oligosaccharides and faecal microbiota in healthy breastfed infants at two, six, and twelve weeks of age. Scientific reports 10 , 4270 (2020). Zha, A. et al. The nanocomposites of modified attapulgite with vitamin E and mannan oligosaccharide regulated the intestinal epithelial barrier and improved intestinal microbiota composition to prevent diarrhea in weaned piglets. J sci food agric 103 , 5569–5577 (2023). Salem, F. et al. Gut microbiome in chronic rheumatic and inflammatory bowel diseases: Similarities and differences. United European Gastroenterol J 7 , 1008–1032 (2019). Nakashima, A. et al. The alga Euglena gracilis stimulates Faecalibacterium in the gut and contributes to increased defecation. Scientific reports 11 , 1074 (2021). Jalanka, J. et al. The Effect of Psyllium Husk on Intestinal Microbiota in Constipated Patients and Healthy Controls. Int J Mol Sci 20 , 433 (2019). Sugitani, Y. et al. Mucosa-associated gut microbiome in Japanese patients with functional constipation. J clin biochem nutr 68 , 187–192 (2021). Dong, H. et al. Microbiome Analysis Reveals the Attenuation Effect of Lactobacillus From Yaks on Diarrhea via Modulation of Gut Microbiota. Front Cell Infect Microbiol 10 , 610781 (2020). Afum, T. et al. Diarrhea-Causing Bacteria and Their Antibiotic Resistance Patterns Among Diarrhea Patients From Ghana. Front Microbiol 13 , 894319 (2022). Brunkwall, L., Ericson, U., Nilsson, P. M., Orho-Melander, M. & Ohlsson, B. Self-reported bowel symptoms are associated with differences in overall gut microbiota composition and enrichment of Blautia in a population-based cohort. Journal of gastroenterology and hepatology 36 , 174–180 (2021). Mu, Y. & Cong, Y. Bacillus coagulans and its applications in medicine. Benef microbes 10 , 679–688 (2019). Zhang, Z., Zhang, G., Zhang, S. & Zhao, J. Fructooligosaccharide Reduces Weanling Pig Diarrhea in Conjunction with Improving Intestinal Antioxid ase Activity and Tight Junction Protein Expression. Nutrients 14 , 512 (2022). Williams, J. E. et al. Relationships Among Microbial Communities, Maternal Cells, Oligosaccharides, and Macronutrients in Human Milk. J Hum Lact 33 , 540–551 (2017). Huang, J. et al. Pediococcus pentosaceus B49 from human colostrum ameliorates constipation in mice. Food Funct 11 , 5607–5620 (2020). Bode, L. et al. Human milk oligosaccharide concentration and risk of postnatal transmission of HIV through breastfeeding. Am j clin nutr 96 , 831–839 (2012). Asnicar, F. et al. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat med 27 , 321–332 (2021). Li, M., Wang, M. & Donovan, S. M. Early development of the gut microbiome and immune-mediated childhood disorders. Seminars in reproductive medicine 32 , 74–86 (2014). Martin, R. et al. Early-Life Events, Including Mode of Delivery and Type of Feeding, Siblings and Gender, Shape the Developing Gut Microbiota. PLoS One 11 , e0158498 (2016). Savino, F. et al. Faecal microbiota in breast-fed infants after antibiotic therapy. Acta paediatr 100 , 75–78 (2011). Liu, Z. et al. Integration of Transcriptome and Metabolome Reveals the Genes and Metabolites Involved in Bifidobacterium bifidum Biofilm Formation. Int J Mol Sci 22 , 7596 (2021). Chen, W., Yan, Q., Zhong, R. & Tan, Z. Amino acid profiles, amino acid sensors and transporters expression and intestinal microbiota are differentially altered in goats infected with Haemonchus contortus. Amino acids 55 , 371–384 (2023). Stražar, M. et al. The influence of the gut microbiome on BCG-induced trained immunity. Genome Biol 22 , 275 (2021). Baykara, S. G., Sürmeli, Y. & Şanlı-Mohamed, G. Purification and Biochemical Characterization of a Novel Thermostable Serine Protease from Geobacillus sp. GS53. Applied biochemistry and biotechnology 193 , 1574–1584 (2021). Wang, S., Ping, Q. & Li, Y. Comprehensively understanding metabolic pathways of protein during the anaerobic digestion of waste activated sludge. Chemosphere 297 , 134117 (2022). Ma, W. et al. Chronic paradoxical sleep deprivation-induced depression-like behavior, energy metabolism and microbial changes in rats. Life sciences 225 , 88–97 (2019). Liu, C. et al. The combination of microbiome and metabolome to analyze the cross-cooperation mechanism of Echinacea purpurea polysaccharide with the gut microbiota in vitro and in vivo . Food funct 13 , 10069–10082 (2022). Xie, L. et al. Effect of fecal microbiota transplantation in patients with slow transit constipation and the relative mechanisms based on the protein digestion and absorption pathway. J Transl Med 19 , 490 (2021). Tatsumi, M. et al. Development of a rapid and simple glycine analysis method using a stable glycine oxidase mutant. Analytical biochemistry 587 , 113447 (2019). Riederer, M. et al. Free threonine in human breast milk is related to infant intestinal microbiota composition. Amino acids 54 , 365–383 (2022). Yang, Y., Kumrungsee, T., Kuroda, M., Yamaguchi, S. & Kato, N. Feeding Aspergillus protease preparation combined with adequate protein diet to rats increases levels of cecum gut-protective amino acids, partially linked to Bifidobacterium and Lactobacillus . Bioscience biotechnology and biochemistry 83 , 1901–1911 (2019). Xu, S. & Wang, S. GC-MS and metabolomics analysis of amino acids, glucose and urinary metabolic pathways and characteristics in children with spleen-deficiency diarrhea. Cellular and molecular biology 66 , 125–130 (2020). Edogawa, S. et al. Serine proteases as luminal mediators of intestinal barrier dysfunction and symptom severity in IBS. Gut 69 , 62–73 (2020). Law, G. K., Bertolo, R. F., Adjiri-Awere, A., Pencharz, P. B. & Ball, R. O. Adequate oral threonine is critical for mucin production and gut function in neonatal piglets. American journal of physiology-gastrointestinal and liver physiology 292 , G1293-1301 (2007). Zhang, Q. et al. Effect of konjac glucomannan on metabolites in the stomach, small intestine and large intestine of constipated mice and prediction of the KEGG pathway. Food funct 12 , 3044–3056 (2021). He, X., Slupsky, C. M., Dekker, J. W., Haggarty, N. W. & Lönnerdal, B. Integrated Role of Bifidobacterium animalis subsp. lactis Supplementation in Gut Microbiota, Immunity, and Metabolism of Infant Rhesus Monkeys. mSystems 1 , e00128-00116 (2016). He, L. et al. Exogenous and Endogenous Serine Deficiency Exacerbates Hepatic Lipid Accumulation. Oxid med cell longev 2021 , 4232704 (2021). Gopalakrishna, K. P. & Hand, T. W. Influence of Maternal Milk on the Neonatal Intestinal Microbiome. Nutrients 12 , 823 (2020). Schoemaker, M. H. et al. Prebiotic Galacto-Oligosaccharides Impact Stool Frequency and Fecal Microbiota in Self-Reported Constipated Adults: A Randomized Clinical Trial. Nutrients 14 , 309 (2022). Tang, W. et al. Prospective study reveals a microbiome signature that predicts the occurrence of post-operative enter ocolitis in Hirschsprung disease (HSCR) patients. Gut Microbes 11 , 842–854 (2020). Logue, J. B. et al. Experimental insights into the importance of aquatic bacterial community composition to the degradation of dissolved organic matter. Isme j 10 , 533–545 (2016). Additional Declarations No competing interests reported. Supplementary Files Supplementalmaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4146767","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":293713445,"identity":"1cd60a64-2926-4482-86c6-e78a7f491ff1","order_by":0,"name":"Yongkun 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University","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-03-22 03:29:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4146767/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4146767/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55515300,"identity":"4e8dbf2c-f86d-41a9-891b-fd9ad4657ad2","added_by":"auto","created_at":"2024-04-29 13:08:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":478013,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4146767/v1/84b3abd409721b7d0e645f1c.jpg"},{"id":55513295,"identity":"26e378e8-4491-4d59-bd57-7a946c47ffa7","added_by":"auto","created_at":"2024-04-29 12:52:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":556787,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4146767/v1/a5d9cb94035c329c745b5ea7.jpg"},{"id":55514164,"identity":"67e1c5bf-5a20-4917-b871-7fde233b02b5","added_by":"auto","created_at":"2024-04-29 13:00:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":460087,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4146767/v1/bfe5f8b315d73f6122cf9a7a.jpg"},{"id":57399494,"identity":"49551bf5-0c81-45d5-ba3b-e941dfc0134d","added_by":"auto","created_at":"2024-05-30 07:49:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2413822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4146767/v1/08fbb613-416a-4560-b0c2-86d180f70916.pdf"},{"id":55513298,"identity":"b3a67e1b-21df-4337-99c4-debdf2ca5ed7","added_by":"auto","created_at":"2024-04-29 12:52:51","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":370802,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4146767/v1/d417c9795a055b747c21f1fe.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Breast Milk Bacteria: The Key to Regulating Defecation Frequency Changes in Infants","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSome exclusively breastfed infants can have more frequent daily stools\u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. Simultaneously, the prevalence of infrequent stools in exclusively breastfed infants (some of whom have no bowel movements or infrequent stools for several days) was clinically common in the outpatient department\u003csup\u003e4\u003c/sup\u003e. Recent research indicates that lactation is one of the most influential factors in establishing the diversity of the infant's intestinal microbiota\u003csup\u003e5\u0026ndash;8\u003c/sup\u003e. In addition, Shin, SP, and colleagues\u003csup\u003e9\u003c/sup\u003e demonstrate that \u003cem\u003eLactobacillus gasseri BNR17\u003c/em\u003e isolated from breast milk enhanced the mean defecation frequency of diarrhea-predominant irritable bowel syndrome (IBS-D) by stimulating gut-friendly bacteria. According to the studies cited above, by modulating the intestinal microbiota in infants, the breast milk microbiota may alter the frequency of defecation. Therefore, we hypothesize that maternal breast milk bacteria are associated with variations in defecation frequency in infants aged 1 to 6 months who are exclusively breastfed, thereby identifying potential breast milk microbiota diagnostic markers.\u003c/p\u003e \u003cp\u003eIn the meantime, this study has an important implication for developing infant medical food and formula milk additives that can mitigate variations in infant defecation frequency. Consuming prebiotics identical to those found in human breast milk can alter a baby's defecation pattern by preserving the microecological equilibrium of their intestinal microbiota\u003csup\u003e10\u003c/sup\u003e. IBS-D in children treated with synbiotic preparation could significantly alleviate intestinal symptoms\u003csup\u003e11\u003c/sup\u003e. In addition, some studies have demonstrated that supplementation with galacto-oligosaccharide formula milk increases the beneficial bacteria, short-chain fatty acids, and defecation frequency in infants while inhibiting the pathogenic bacteria\u003csup\u003e12,13\u003c/sup\u003e. Moreover, breast milk contains proteins that govern the intestinal microbiota and immune system\u003csup\u003e14,15\u003c/sup\u003e. Another objective of this study was to examine the breast milk microbiota associated with infant defecation and predict their involvement in metabolic pathways and functional proteins.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiota in Breast Milk Linked to Variable Infant Defecation Frequency\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e describe the characteristics of mothers and infants, respectively. Age and fecal characteristics of exclusively breastfed infants differed substantially among the three groups based on defecation frequency, and the frequency of bowel movements was significantly associated with stool consistency (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Other parameters did not differ between the three groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Characteristics of the Breastfed Infants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDI (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDN (n\u0026thinsp;=\u0026thinsp;31)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDD (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (IQR), days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (38, 94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (42, 120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (50, 150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery mode, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFecal characteristics, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft and Formed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoose/mushy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWatery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of breastfeeding, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;8 times per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;8 times per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 6 times per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Gamma rank correlation coefficient:0.8309.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Characteristics of the Nursing Mothers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDI (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDN (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDD (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean (SD), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy BMI, mean (SD), Kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParturient BMI, mean (SD), Kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmptying status of the breast, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilateral emptying\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnilateral emptying\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeither side is emptying\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMood, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnjoyable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysphoric and scared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepressive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal sleeping times, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 6 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;8 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u0026ndash;10 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 10 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly income, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u0026yen; 1200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026yen; 1200\u0026ndash;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026yen; 2500\u0026ndash;4000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; \u0026yen; 4000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe RDA analyses were then used to investigate the effects of various factors (the age of infant-mother pairs, infant fecal characteristics, breastfeeding frequency, mother sleeping periods, and family income were selected from Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.3 factors). Notably, RDA analyses reveal that infant defecation frequency and fecal characteristics both resulted in variations in microbiota composition (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eComparative Analysis of the Microbiota Structure in Breast Milk Among Three Groups\u003c/h2\u003e \u003cp\u003eObserved species and Shannon index were used to calculate the alpha diversity of human breast milk microbiota in three groups, and no significant differences were found (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Through PCoA analysis, we observed a substantial difference in microbiota composition between three groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Sample coordinates for the same body site did not wholly overlap among the three groups (DI vs. DN, DD vs. DN), indicating that variations in defecation frequency were related to the microbiota in human breast milk.\u003c/p\u003e \u003cp\u003eAt the phylum level, milk samples were dominated by Proteobacteria, Firmicutes, and Actinobacteria. Firmicutes and Bacteroidetes had the highest relative abundance in the DD group, while Proteobacteria had the highest close plenty in the DN group (Firmicutes, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0022; Bacteroidetes, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0428; Proteobacteria:\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0224; Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e or Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003eStaphylococcus\u003c/em\u003e were the most prevalent genera in all samples. Specifically, the relative abundance of the bacterial genera \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eRoseburia\u003c/em\u003e, \u003cem\u003eLachnospiraceae_unclassified\u003c/em\u003e, \u003cem\u003eand Ruminococcus_1\u003c/em\u003e was substantially more significant in the DI group than in the DN group, followed by the DD group. In contrast, the relative abundance of \u003cem\u003eAerococcus\u003c/em\u003e, \u003cem\u003eRothia\u003c/em\u003e, \u003cem\u003eCitrobacter\u003c/em\u003e, \u003cem\u003eCatellicoccus\u003c/em\u003e, and \u003cem\u003eGemella\u003c/em\u003e was the opposite (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ea or Supplementary Table S2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSeclction of Significant Charateristics Relating to Changes in Defecation Frequency\u003c/h2\u003e \u003cp\u003eTo further identify the variation in beta diversity attributable to changes in stool frequency, we employed LEfSe analysis to present indicators of distinct groups. The DI group was enriched with \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003eMegamonas\u003c/em\u003e, \u003cem\u003eDechlorosoma\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eLachnospiraceae_unclassified\u003c/em\u003e, and \u003cem\u003eGeobacillus\u003c/em\u003e. \u003cem\u003eSerratia\u003c/em\u003e, \u003cem\u003eRothia\u003c/em\u003e, \u003cem\u003ePseudacidovorax\u003c/em\u003e, and \u003cem\u003eDechloromonas\u003c/em\u003e were identified as members of the DN group. In addition, the DD group had a greater abundance of \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eHydrogenophilus\u003c/em\u003e, \u003cem\u003eComamonas\u003c/em\u003e, \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, \u003cem\u003eDechlorosoma\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eAeribacillus\u003c/em\u003e, \u003cem\u003eGeobacillus\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, and \u003cem\u003eBlautia\u003c/em\u003e than the DN group. Other microorganisms that accumulated in DN breast milk were \u003cem\u003eSerratia\u003c/em\u003e, \u003cem\u003eRaoultella\u003c/em\u003e, \u003cem\u003ePhyllobacterium\u003c/em\u003e, \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e, \u003cem\u003ePseudacidovorax\u003c/em\u003e, and \u003cem\u003eHerbaspirillum\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The ROC model was then applied to predict the potential biomarkers based on the top 5 relative abundances of shared human breast milk genera between the DI and DN groups and the DD and DN groups. Among all samples and relative metadata, as indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, \u003cem\u003eHydrogenophilus\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e in breast milk had the most potent predictive effect when discriminating to the DD and the DN samples (\u003cem\u003eHydrogenophilus :AUC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7856; \u003cem\u003eSerratia: AUC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0. 7633; \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium- Rhizobium: AUC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7111; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In the same line, we discovered that \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eMegamonas\u003c/em\u003e distinguished the DI group more effectively (\u003cem\u003eBifidobacterium: AUC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6626; \u003cem\u003eMegamonas: AUC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6513; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAnalyses of Correlation Between Breast Milk Microbiota and Factors\u003c/h2\u003e \u003cp\u003eIn human breast milk, the microbiota microbes share the same microenvironment and interact. Consequently, co-network simulation was carried out utilizing microbiome analysis. \u003cem\u003eSerratia\u003c/em\u003e comprised the nucleus of the co-network' DI group, followed by \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium- Rhizobium\u003c/em\u003e, \u003cem\u003eRaoultella\u003c/em\u003e, and \u003cem\u003eHerbaspirillum\u003c/em\u003e. In the meantime, the DN group's main genera, \u003cem\u003eHerbaspirillum\u003c/em\u003e, \u003cem\u003ePhyllobacterium\u003c/em\u003e, \u003cem\u003eRaoultella\u003c/em\u003e, \u003cem\u003ePseudacidovorax\u003c/em\u003e etc., shared close relationships. (|\u003cem\u003er|\u003c/em\u003e \u0026gt; 0.07, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Supplementary Figure S2).\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ed, frequent defecation is positively associated with \u003cem\u003eMegamonas\u003c/em\u003e, \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, and \u003cem\u003eAkkermansia\u003c/em\u003e in breast milk, whereas it is negatively associated with \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eDechlorosoma\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eRothia, Catellicoccus\u003c/em\u003e, in addition to \u003cem\u003eCitrobacter\u003c/em\u003e. \u003cem\u003eCatellicoccus\u003c/em\u003e and \u003cem\u003eAkkermansia\u003c/em\u003e are positively associated with more watery feces, whereas \u003cem\u003eMegamonas\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eDechlorosoma\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eCitrobacter\u003c/em\u003e, and \u003cem\u003eRothia\u003c/em\u003e are negatively associated with the fecal consistency index (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eRelationships Between Breast Milk Microbiota and Various Functions and Phenotypes\u003c/h2\u003e \u003cp\u003eComparing the DI group to the DD group, the proportion of most genes involved in amino acid biosynthesis was significantly higher in the DD group than in the DN group, whereas the DN group had a higher proportion of most genes involved in amino acid degradation and D-galacturonate degradation (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Then we predicted their functions on infant defecation frequency by determining whether target breast milk microbes possessed critical enzymes implicated in distinct metabolic pathways. Ten genes displayed same trends, with their abundances increasing in the DI group and decreasing in the DD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Supplementary Table S3). According to the Spearman's correlation coefficient, represented as a heatmap, we discovered that ten distinct genes were consistently positively associated with \u003cem\u003eSerratia\u003c/em\u003e, \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e, \u003cem\u003eRaoultella\u003c/em\u003e, and \u003cem\u003eHerbaspirillum\u003c/em\u003e. Positive correlations were observed between \u003cem\u003ePhyllobacterium\u003c/em\u003e and COG3733, EC:1.4.3.21, K00276, etc. In addition, \u003cem\u003eAkkermansia\u003c/em\u003e had a positive correlated with EC:1.4.3.21, K00276, K18144, etc. (|\u003cem\u003er|\u003c/em\u003e \u0026gt; 0.3, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThe BugBase analysis revealed that taxonomic samples from the DI and DD groups had substantially higher Anaerobic phenotypes than those from the DN group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Supplementary Table S4). Based on their co-network, this coefficient was also used to assess the relationship between breast milk microbiota and various phenotypes. Intriguingly, the higher Anaerobic phenotype of DD and DI breast milk was associated with increased \u003cem\u003eBifidobacterium\u003c/em\u003e levels in both DD and DI groups. \u003cem\u003ePhyllobacterium\u003c/em\u003e, on the other hand, was negatively correlated with the anaerobic phenotype (|\u003cem\u003er|\u003c/em\u003e \u0026gt; 0.5, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHaving ruled out other confounding factors based on RDA analysis, our research determined that infant defecation frequency had the most significant influence on milk microbial structure variability, followed by stool characteristics. PCoA demonstrated a distinct separation in the structure of breast milk microbiota between the three groups (with a more similar microbiota composition of each sample in the DI group compared to the DD and DN groups). The prevalent milk phyla were then determined to be Firmicutes and Actinobacteria. Firmicutes and Bacteroidetes were most abundance in the group with reduced defecation frequency, while Proteobacteria were most abundant in the standard group. Proteobacteria and Firmicutes were the predominant fecal microbiota of infants aged at 1 to 6 months who were supplemented with breast milk, consistent with the findings of Drall, K.M\u003csup\u003e16\u003c/sup\u003e. A series of studies found that the abundance of Firmicutes and Bacteroidaceae was higher in the feces of children with constipation\u003csup\u003e17,18\u003c/sup\u003e. All of these findings indicate that lactation influences the colonization of infant gastrointestinal microbiota\u003csup\u003e19\u003c/sup\u003e. The mother's vivo dendritic cells accumulate their gastrointestinal microbiota and transfer it to the breast via blood and lymph\u003csup\u003e20\u003c/sup\u003e. After being transmitted to the infant's gastrointestinal tract through breastfeeding, the microbiota's effects will persist throughout the child's childhood\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBased on the LEfSe and ROC analyses, \u003cem\u003eHydrogenophilus\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium- Rhizobium\u003c/em\u003e were identified as potential biomarkers for distinguishing the DD and DN groups; Furthermore, the DI and DD groups, the core regulatory role of breast milk feature microbiota was weaker than in the DN group. In addition, previous studies have confirmed that the differences and feature genus of this study are related to changes in defecation frequency, as follows: As is known, \u003cem\u003eAkkermansia\u003c/em\u003e strains in human breast milk are mucin-degrading bacteria, and their genomes are equipped with Human milk oligosaccharides (HMOs) deconstruction related glycoside hydrolases; capacity to increase the defecation frequency and soften stool\u003csup\u003e21\u0026ndash;23\u003c/sup\u003e; and Therefore, the increased frequency and production of smoother feces in the DI group could be explained by the function of the \u003cem\u003eAkkermansia\u003c/em\u003e in human breast milk. In addition, the catabolism of dietary amino acids mediated by \u003cem\u003eRuminococcus\u003c/em\u003e can enhance gastrointestinal transport and colonic secretion by improving serotonin biosynthesis in intestinal enterochromaffin cell\u003csup\u003e24\u003c/sup\u003e. Like Yang, J. et al.,\u003csup\u003e25\u003c/sup\u003e our findings demonstrate that \u003cem\u003eRuminococcus\u003c/em\u003e positively correlates with feces frequency. By participating in the absorption of HMOs and converting aromatic amino acids into their lactic acid derivatives in the intestine, \u003cem\u003eBifidobacterium\u003c/em\u003e may cause an increase or decrease in the defecation frequency of infants, according to our findings\u003csup\u003e26\u0026ndash;28\u003c/sup\u003e. In addition, \u003cem\u003eBifidobacterium\u003c/em\u003e and galactose-containing di- and oligosaccharides (GOS) in human milk may modulate the expression of serine protease inhibitors\u003csup\u003e29,30\u003c/sup\u003e. Galactose metabolism has been linked to \u003cem\u003eMegamonas\u003c/em\u003e and has been shown to increase feces frequency and consistency\u003csup\u003e31,32\u003c/sup\u003e. \u003cem\u003eLachnospiraceae\u003c/em\u003e\u003csup\u003e33\u003c/sup\u003e is antagonistic to HMOs, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e\u003csup\u003e34\u003c/sup\u003e, \u003cem\u003eRoseburia\u003c/em\u003e\u003csup\u003e35\u003c/sup\u003e, and \u003cem\u003eFaecalibacterium\u003c/em\u003e\u003csup\u003e36\u003c/sup\u003e, and promotes short-chain fatty acid (SCFA) to increase the frequency of bowel movements\u003csup\u003e37\u003c/sup\u003e. The relationship between \u003cem\u003eCitrobacter\u003c/em\u003e and \u003cem\u003eComamonas\u003c/em\u003e\u003csup\u003e38\u003c/sup\u003e, \u003cem\u003eAerococcus\u003c/em\u003e\u003csup\u003e39\u003c/sup\u003e, \u003cem\u003eEscherichia-Shigella\u003c/em\u003e\u003csup\u003e40\u003c/sup\u003e, \u003cem\u003eBlautia\u003c/em\u003e\u003csup\u003e41\u003c/sup\u003e, and \u003cem\u003eBacillus\u003c/em\u003e\u003csup\u003e42\u003c/sup\u003e and changes in defecation frequency in infants is consistent with several other studies. According to several contradictory studies, \u003cem\u003eSerratia\u003c/em\u003e is detrimental to intestinal epithelial cells and can cause diarrhea in infants. Zhang, Z. et al.\u003csup\u003e43\u003c/sup\u003e demonstrated that fructooligosaccharides can increase the population of \u003cem\u003eMegasphaera\u003c/em\u003e and decrease the incidence of diarrheal in piglets. \u003cem\u003eStaphylococcus\u003c/em\u003e has a positive correlation with total oligosaccharide concentration\u003csup\u003e44\u003c/sup\u003e, and reducing this concentration can reduce the incidence of constipation in rodents\u003csup\u003e45\u003c/sup\u003e. The well-known beneficial bacterium \u003cem\u003eBifidobacterium\u003c/em\u003e can enhance children's bowel movements. Varied specimens, sample counts, sample collection, processing, analysis methods, and mixed infant age, diet and health status\u003csup\u003e46\u0026ndash;50\u003c/sup\u003e may need to be corrected with this study. Besides, the above genera are involved in metabolizing oligosaccharides and amino acids. Relevant research has shown that the genera of \u003cem\u003eBifidobacterium\u003c/em\u003e\u003csup\u003e51\u003c/sup\u003e, \u003cem\u003eLachnospiraceae\u003c/em\u003e\u003csup\u003e52\u003c/sup\u003e, \u003cem\u003eRoseburia\u003c/em\u003e\u003csup\u003e53\u003c/sup\u003e, \u003cem\u003eCitrobacter\u003c/em\u003e\u003csup\u003e54\u003c/sup\u003e, \u003cem\u003eDechromomonas\u003c/em\u003e\u003csup\u003e55\u003c/sup\u003e, \u003cem\u003eAkkermania\u003c/em\u003e\u003csup\u003e56\u003c/sup\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e\u003csup\u003e57\u003c/sup\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e\u003csup\u003e58\u003c/sup\u003e, \u003cem\u003eBacillus\u003c/em\u003e\u003csup\u003e59\u003c/sup\u003e, Serratia, and \u003cem\u003eMegasphaera\u003c/em\u003e all take part in the metabolism of amino acids.\u003c/p\u003e \u003cp\u003eTo demonstrate the biological significance of the distinct characteristics and microorganisms, we predicted their functions by determining whether critical enzymes involved in the metabolism of oligosaccharides and amino acids were related to the variation in defecation frequency. We then found the higher primary-amine oxidase key enzyme in the DI group matched to γ-Gammaproteobacteria\u0026ndash;Enterobacteriaceae (subordinate genera include \u003cem\u003eSerratia\u003c/em\u003e and \u003cem\u003eRaoultella\u003c/em\u003e) in the Kyoto Encyclopedia of Genes and Genomes (KEGG), this homeotic gene is involved in the metabolism of Glycine, serine, and threonine (map00260), Tyrosine metabolism (map00350) and Phenylalanine metabolism (map00360), in addition to other metabolic pathways. The findings of Riederer, M., and his colleagues\u003csup\u003e60\u003c/sup\u003e confirmed that a correlation between threonine in human milk and the abundance of Gammaproteobacteria, which has overlapped with our research, and they supported the possibility of an interaction between human milk-free amino acids and the composition of intestinal microbiota in early lactation infants. Indeed, a protein-rich diet is likely to increase beneficial amino acids in the cecum\u003csup\u003e61\u003c/sup\u003e. Casein is the most abundant milk protein; its conjugated protein is synthesized by combining a phospholipid bond with threonine and serine hydroxyl groups, thereby decreasing fecal frequency and drying out feces. Aminoacetone, a threonine metabolite, produces methylglyoxal upon activation of primary amine oxidase. Pyruvic acid salt produced by serine metabolism interacts with methylglyoxal production (map00260). The serine and threonine content of the DI group may be lower than that of the DN group, and the DN group's content is lower than that of the DD group. This is consistent with the findings of Xu, S, and others\u003csup\u003e62\u003c/sup\u003e who determined that Glycine, serine, and threonine metabolism is involved in persistent diarrhea in children. Edogawa, S, and coworkers\u003csup\u003e63\u003c/sup\u003e also confirmed that the paracellular permeability is increased, tight junction protein expression is decreased, and the presentation of phosphorylated myosin light chain is elevated in feces with high serine proteolytic activity, thereby increasing the permeability of intestinal mucosa and promoting more defecation. In the meantime, Law, GK, et al.\u003csup\u003e64\u003c/sup\u003e confirmed that threonine is used for intestinal mucous protein production and that a diet deficient in threonine will cause persistent diarrhea in piglets. While searching the KEGG database, we discovered that primary amine oxidase in DD group had a reduced annotation in function pathway of Tyrosine metabolism (map00350) and Phenylalanine metabolism (map00360), similar to Zhang, Q. et al.'s findings in rodents\u003csup\u003e65\u003c/sup\u003e. Therefore, the variation in the frequency of defecation in infants may be related with the regulation of the expression levels of primary amine oxidase implicated in the pathways of amino acid metabolism. Additionally, intestinal microorganisms can regulate the utilization of amino acids\u003csup\u003e66\u003c/sup\u003e, and dietary amino acids can also influence the composition of colonic microbiota and their metabolites\u003csup\u003e67\u003c/sup\u003e. Consequently, protein compounds in human milk can modulate the microbial composition of infants\u003csup\u003e68\u003c/sup\u003e. According to this investigation, primary amine oxidase is positively associated with Serratia. Further, we hypothesized that reduced level of \u003cem\u003eSerratia\u003c/em\u003e in breast milk contribute to decreased gastrointestinal movements frequency in exclusively breastfed infants. In addition, we discovered that the relative abundance of Serratia in the DI and DN groups was substantially more significant than in the DD group.\u003c/p\u003e \u003cp\u003eThis study predicted that DI and DD [outcomes] have higher anaerobic phenotype [exposure factors] association with a higher relative abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e [genotype] in human milk. Studies have confirmed that GOS substantially increased the frequency of defecation by producing anaerobic bacteria\u003csup\u003e69\u003c/sup\u003e. Meanwhile, \u003cem\u003eBifidobacterium\u003c/em\u003e, an anaerobic bacterium that can produce more butyric acid in the intestines, has been shown to reduce the frequency of defecation in exclusively breastfed infants\u003csup\u003e26\u003c/sup\u003e. This study hypothesizes that the change in defecation frequency in children aged 1 to 6 months who are exclusively breastfed may be related to the higher anaerobic phenotype of human breast milk, primarily influenced by the relatively high abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e. Tang, W. et al. \u003csup\u003e70\u003c/sup\u003e discovered that breastfeeding can modulate infant gut microbiota, characterized by low levels of Gram-negative bacteria, to prevent Hirschsprung-associated enterocolitis. In subsequent isolation and cultivation of maternal microbiota, we can effectively prevent the growth environment of anaerobic bacteria to determine whether it can reduce the change in defecation frequency in exclusively breastfed infants.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study is the first to propose potential links between breast milk microbiota and defecation frequency variations among exclusively breastfed infants aged 1\u0026ndash;6 months. It sheds light on possible underlying mechanisms related to the metabolism of amino acids and D-galacturonate, offering new insights into human breast milk's impact on defecation frequency changes. In addition, we propose a prospective biomarker diagnostic method comprised of the human milk microorganisms \u003cem\u003eHydrogenophilus\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e. Additionally, we discovered that the anaerobic genus \u003cem\u003eBifidobacterium\u003c/em\u003e in human milk is associated with a higher anaerobic phenotype in DD and DI breast milk and can be used to identify the DI group. Nevertheless, due to limitations in sample size and analysis methodologies, our results must be validated and investigated further using multiple data sources (including breast milk microbiota and infant intestinal microbiota) and large cohorts. In the future, we will use muti-Omics and whole microbiome association analysis to conduct in-depth research at numerous time points and isolate beneficial bacteria from breast milk microbiota using pure culture, laying the groundwork for developing an infant's exceptional medical food and infant formula milk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubjects and Sample Assemblage\u003c/h2\u003e \u003cp\u003eFrom August 2020 to August 2021, mother-infant pairs were enrolled at the First Affiliated Hospital of Kunming Medical University. We recruited 102 couples of fit mothers and infants. The inclusion criteria for infants were as follows:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAge between 1 and 6 months\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTerm infants of average weight\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNo use of probiotics or antibiotics within the previous four weeks\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe exclusion criteria are as follows:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no infectious diarrhea, biliary diseases, anorectal diseases, congenital neuro-muscular disease, metabolic and endocrine diseases, hereditary diseases, or drug-induced abnormal defecation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStool frequency and traits must have changed significantly in the two weeks preceding the study.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNo severe eczema and cow\u0026rsquo;s-milk protein allergy.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe corresponding mothers met the following criteria:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eExcellent physical and mental health during pregnancy and breastfeeding\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHealthy breast status\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNo use of probiotics and antibiotics during pregnancy and breastfeeding\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe exclusion criteria are as follows:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAbsence of gestational diabetes mellitus, gestational hypertension, and hypothyroidism\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAbsence of allergy\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLack of anemia and malnutrition\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAbsence of neuropsychiatric disorders\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLack of medical family history\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAbsence of poor habits\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe infants were divided three groups (DI, n\u0026thinsp;=\u0026thinsp;37; DD, n\u0026thinsp;=\u0026thinsp;34; and DN, n\u0026thinsp;=\u0026thinsp;31) based on the frequency of defecation: those who defecated more than three times per day, those who defecated more than four days or required assistance, and those who defecated once within three days or less than three times (including three times) per day. All breast milk samples were collected manually with sterile gloves from the mother's breast before feeding the infant; the mother's breast was disinfected before milk collection; and the pieces were aliquoted into 10ml to 15ml sterile containers and stored \u0026minus;\u0026thinsp;80℃ until analysis.\u003c/p\u003e \u003cp\u003eThe clinical data of mothers and infants were collected through questionnaires. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provide a summary of this information.\u003c/p\u003e \u003cp\u003e This study was approved by the Medicine Ethics Committee of the First Affiliated Hospital of Kunming Medical University (Protocol # (2023) L23-1). The trial was performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its later amendments. Written informed consent to participate in this study was provided by the participants\u0026rsquo; legal guardian/next of kin. Participation was voluntary and participants were free to withdraw from the study at any stage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDNA Extraction, PCR Amplification, Library Preparation, and Sequencing of the 16S rRNA Gene\u003c/h2\u003e \u003cp\u003eAll the human milk samples were transferred to a 37℃ thermostatic water immersion and then centrifuged at low speed (200g, 10 minutes) at a low rate. After centrifugation, the lower liquid was extracted with a 10.0ml aseptic syringe, avoiding the upper fat filtered through a 0.22um filter membrane. DNA extraction was performed by the E.Z.N.A.\u0026reg;Water DNA Kit according to the manufacturer's instructions, and then, the \u003cem\u003eV3-4\u003c/em\u003e region of 16S rDNA gene was amplified using barcoded primers \u003cem\u003e(341F-5\u003c/em\u003e'\u003cem\u003e-CCTACGGGNGGCWGCAG-3\u003c/em\u003e', \u003cem\u003e806R-5\u003c/em\u003e'\u003cem\u003e-GACTACHVGGGCTAATCC-3\u003c/em\u003e'\u003cem\u003e)\u003c/em\u003e and the following conditions: \u003cem\u003e98\u0026deg;C(0:30) + [98\u0026deg;C(0:10)\u0026thinsp;+\u0026thinsp;54\u0026deg;C(0:30)\u0026thinsp;+\u0026thinsp;72\u0026deg;C(0:45)] 35 cycles\u0026thinsp;+\u0026thinsp;72\u0026deg;C(10:00)\u003c/em\u003e. On a library, the PCR product was subsequently detected, recovered, and quantified\u003csup\u003e71\u003c/sup\u003e. The aggregated library was deposited on NovaSeq PE250 platform using a paired-end high-throughput sequencing protocol (2 x 250 bp).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe fields of Bioinformatics Analysis\u003c/h2\u003e \u003cp\u003eThe raw sequence reads (mean 44,339, standard deviation 12,614.06) were quality-filtered (fqtrim v0.94), de-noised, de-replicated, merged (FLASH v1.2.8), and checked for chimeric sequences (Vsearch software v2.3.4). Following DADA2 deduplication, we obtained a feature table and the feature sequences. The relative abundance of each Sample was computed after determining the bacterial taxonomy of DADA2 representative sequences using SILVA release 132 at 100 percent. The species' sequence alignment (Blast) was annotated (SILVA database).\u003c/p\u003e \u003cp\u003eAlpha diversity and Beta diversity were analyzed using the QIIME2 procedure, and R (v2.15.3) was used to generate visual representations. Principal coordinates analysis (PCoA) was utilized to visualize and validate significant differences in the microbiota of human breast milk. Potential microbial biomarkers were identified using LefSe and Receiver-Operating Characteristic (ROC) analysis. Possible microbiome functional differences were assessed using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) and predicted using the enrichment of Metacyc pathway in the 16S rRNA gene profiles. We also assessed the association between factors, phenotypes, function, and bacterial genus using heatmap, network and Redundancy analysis (RDA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eIn addition, normally distributed variables were analyzed using the F test, and the Kruskal-Wallis test was used to compare groups for nonparametric tests. The χ\u003csup\u003e2\u003c/sup\u003e test evaluates the distinctions between binary independent variables and ordinal one-way dependent variables. Two-way ordinal categorical variables were analyzed with SPSS (v 25.0) using Trend χ\u003csup\u003e2\u003c/sup\u003e test, Fisher's exact test, and Gamma test. We adjusted for multiple testing using the Benjamini and Hochberg procedure with the false discovery rate (FDR). \u003cem\u003eP\u003c/em\u003e-value and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed) was selected as cutoffs.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e We thank the mothers that donated their milk samples for this project and the authors would also like to thank Hangzhou Lianchuan Biological information company for technical support. The Biobank and the Preventive Health Care of the First Affiliated Hospital of Kunming Medical University provided services supporting this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e The original sequencing data that support the finding of this study are available in the ResMan: http://www.medresman.org.cn/uc/projectsh/projectedit.aspx?proj=5347. All data analysed during this study are included in this published article (and its supplemental materials). The datasets are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Yuanyuan Zhang, Yan Chen,\u0026nbsp;Yunfei Xie, and Zhaoxia Xiong\u0026nbsp;collected specimens. Yuanyuan Zhang, and\u0026nbsp;Mei Liu\u0026nbsp;performed laboratory sample analyses and data analyses. Yuanyuan Zhang wrote the manuscript. Yongkun Huang, and\u0026nbsp;Zhenrong Xie\u0026nbsp;planned and executed experimental trials.\u0026nbsp;Kai Liu, Meng Li, Jingjing Xiong, and Zhanhua Li\u0026nbsp;revised the manuscript, and all authors interpreted the data and revised the manuscript for important intellectual content and approved the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eAll the authors declare no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support:\u003c/strong\u003e This trial was initiated and planned by the researchers and funded by the National Natural Science Foundation of China (grant NO. 81960102). The study has no sponsor and was only supported by this public funding. The investigators received no fees from any industry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of the Funder/Sponsor:\u0026nbsp;\u003c/strong\u003eThe funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer:\u0026nbsp;\u003c/strong\u003eNo industry or commercially interested parties accessed the data before their publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTunc, V. T., Camurdan, A. D., Ilhan, M. N., Sahin, F. \u0026amp; Beyazova, U. Factors associated with defecation patterns in 0-24-month-old children. \u003cem\u003eEur J Pediatr\u003c/em\u003e \u003cstrong\u003e167\u003c/strong\u003e, 1357\u0026ndash;1362 (2008).\u003c/li\u003e\n\u003cli\u003eMoretti, E., Rakza, T., Mestdagh, B., Labreuche, J. \u0026amp; Turck, D. The bowel movement characteristics of exclusively breastfed and exclusively formula fed infants differ during the first three months of life. \u003cem\u003eActa Paediatr\u003c/em\u003e \u003cstrong\u003e108\u003c/strong\u003e, 877\u0026ndash;881 (2019).\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;amurdan, A. D., Beyazova, U., \u0026Ouml;zkan, S. \u0026amp; Tun\u0026ccedil;, V. T. Defecation patterns of the infants mainly breastfed from birth till the 12th month: Prospective cohort study. \u003cem\u003eTurk J Gastroenterol\u003c/em\u003e \u003cstrong\u003e25 Suppl 1\u003c/strong\u003e, 1\u0026ndash;5 (2014).\u003c/li\u003e\n\u003cli\u003eCourdent, M., Beghin, L., Akr\u0026eacute;, J. \u0026amp; Turck, D. Infrequent stools in exclusively breastfed infants. \u003cem\u003eBreastfeed Med\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 442\u0026ndash;445 (2014).\u003c/li\u003e\n\u003cli\u003eCioffi, C. C., Tavalire, H. F., Neiderhiser, J. M., Bohannan, B. \u0026amp; Leve, L. D. History of breastfeeding but not mode of delivery shapes the gut microbiome in childhood. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, e0235223 (2020).\u003c/li\u003e\n\u003cli\u003eJohnson, J. M., Adams, E. D. \u0026amp; O'Neal, P. V. Promoting and Protecting the Gastrointestinal Newborn Microbiome Through Breastfeeding Practices. \u003cem\u003eJ Perinat Neonatal Nurs\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 222\u0026ndash;230 (2020).\u003c/li\u003e\n\u003cli\u003ePannaraj, P. S. \u003cem\u003eet al.\u003c/em\u003e Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome. \u003cem\u003eJAMA Pediatr\u003c/em\u003e \u003cstrong\u003e171\u003c/strong\u003e, 647\u0026ndash;654 (2017).\u003c/li\u003e\n\u003cli\u003eLiu, C. E. \u003cem\u003eet al.\u003c/em\u003e Composition characteristics of the gut microbiota in infants and young children of under 6 years old between Beijing and Japan. \u003cem\u003eTransl Pediatr\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 790\u0026ndash;806 (2021).\u003c/li\u003e\n\u003cli\u003eShin, S. P. \u003cem\u003eet al.\u003c/em\u003e A double blind, placebo-controlled, randomized clinical trial that breast milk derived-\u003cem\u003eLactobacillus gasseri\u003c/em\u003e BNR17 mitigated diarrhea-dominant irritable bowel syndrome. \u003cem\u003eJ Clin Biochem Nutr\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 179\u0026ndash;186 (2018).\u003c/li\u003e\n\u003cli\u003eB\u0026eacute;ghin, L. \u003cem\u003eet al.\u003c/em\u003e Fermented infant formula (with Bifidobacterium breve C50 and Streptococcus thermophilus O65) with pre biotic oligosaccharides is safe and modulates the gut microbiota towards a microbiota closer to that of breastfed infants. \u003cem\u003eClin Nutr\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 778\u0026ndash;787 (2021).\u003c/li\u003e\n\u003cli\u003eSkrzydło-Radomańska, B. \u003cem\u003eet al.\u003c/em\u003e The Effectiveness of Synbiotic Preparation Containing \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e Probiotic Strains and Short Chain Fructooligosaccharides in Patients with Diarrhea Predominant Irritable Bowel Sy ndrome-A Randomized Double-Blind, Placebo-Controlled Study. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1999 (2020).\u003c/li\u003e\n\u003cli\u003eBen, X. M. \u003cem\u003eet al.\u003c/em\u003e Low level of galacto-oligosaccharide in infant formula stimulates growth of intestinal Bifidobacteria and Lactobacilli. \u003cem\u003eWorld J Gastroenterol\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 6564\u0026ndash;6568 (2008).\u003c/li\u003e\n\u003cli\u003eVeereman-Wauters, G. \u003cem\u003eet al.\u003c/em\u003e Physiological and bifidogenic effects of prebiotic supplements in infant formulae. \u003cem\u003eJ Pediatr Gastroenterol Nutr\u003c/em\u003e \u003cstrong\u003e52\u003c/strong\u003e, 763\u0026ndash;771 (2011).\u003c/li\u003e\n\u003cli\u003eAparicio, M., Alba, C., Cam Public Health Area, P., Rodr\u0026iacute;guez, J. M. \u0026amp; Fern\u0026aacute;ndez, L. Microbiological and Immunological Markers in Milk and Infant Feces for Common Gastrointestinal Disorders: A Pilot Study. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 634 (2020).\u003c/li\u003e\n\u003cli\u003eLi, N. \u003cem\u003eet al.\u003c/em\u003e Human milk and infant formula modulate the intestinal microbiota and immune systems of human microbiota-associated mice. \u003cem\u003eFood funct\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 2784\u0026ndash;2798 (2021).\u003c/li\u003e\n\u003cli\u003eDrall, K. M. \u003cem\u003eet al. Clostridioides difficile\u003c/em\u003e Colonization Is Differentially Associated With Gut Microbiome Profiles by Infant Feeding Modality at 3\u0026ndash;4 Months of Age. \u003cem\u003eFront Immunol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 2866 (2019).\u003c/li\u003e\n\u003cli\u003eKim, M. C. \u003cem\u003eet al.\u003c/em\u003e Effects of ID-HWS1000 on the Perception of Bowel Activity and Microbiome in Subjects with Functional Constipation: A Randomized, Double-Blind Placebo-Controlled Study. \u003cem\u003eJ Med Food\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 883\u0026ndash;893 (2021).\u003c/li\u003e\n\u003cli\u003eNiu, J. \u003cem\u003eet al.\u003c/em\u003e Evolution of the Gut Microbiome in Early Childhood: A Cross-Sectional Study of Chinese Children. \u003cem\u003eFront Microbiol\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 439 (2020).\u003c/li\u003e\n\u003cli\u003eFehr, K. \u003cem\u003eet al.\u003c/em\u003e Breastmilk Feeding Practices Are Associated with the Co-Occurrence of Bacteria in Mothers' Milk and the Infant Gut: the CHILD Cohort Study. \u003cem\u003eCell Host Microbe\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 285\u0026ndash;297.e284 (2020).\u003c/li\u003e\n\u003cli\u003eLemaire, M., Le Hu\u0026euml;rou-Luron, I. \u0026amp; Blat, S. Effects of infant formula composition on long-term metabolic health. \u003cem\u003eJ Dev Orig Health Dis\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 573\u0026ndash;589 (2018).\u003c/li\u003e\n\u003cli\u003eLuna, E. \u003cem\u003eet al.\u003c/em\u003e Utilization Efficiency of Human Milk Oligosaccharides by Human-Associated \u003cem\u003eAkkermansia\u003c/em\u003e Is Strain Dependent. \u003cem\u003eAppl Environ Microbiol\u003c/em\u003e \u003cstrong\u003e88\u003c/strong\u003e, e0148721 (2022).\u003c/li\u003e\n\u003cli\u003eParschat, K., Melsaether, C., J\u0026auml;pelt, K. R. \u0026amp; Jennewein, S. Clinical Evaluation of 16-Week Supplementation with 5HMO-Mix in Healthy-Term Human Infants to Determine Tolerability, Safety, and Effect on Growth. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 2871 (2021).\u003c/li\u003e\n\u003cli\u003eToporovski, M. S., de Morais, M. B., Abuhab, A. \u0026amp; Crippa J\u0026uacute;nior, M. A. Effect of Polydextrose/Fructooligosaccharide Mixture on Constipation Symptoms in Children Aged 4 to 8 Years. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 1634 (2021).\u003c/li\u003e\n\u003cli\u003eZhai, L. \u003cem\u003eet al.\u003c/em\u003e Ruminococcus gnavus plays a pathogenic role in diarrhea-predominant irritable bowel syndrome by increasing serotonin biosynthesis. \u003cem\u003eCell host microbe\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 33\u0026ndash;44.e35 (2023).\u003c/li\u003e\n\u003cli\u003eYang, J. \u003cem\u003eet al.\u003c/em\u003e Involvement of mucosal flora and enterochromaffin cells of the caecum and descending colon in diarrhoea-predominant irritable bowel syndrome. \u003cem\u003eBMC Microbiol\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 316 (2021).\u003c/li\u003e\n\u003cli\u003eNocerino, R. \u003cem\u003eet al.\u003c/em\u003e The therapeutic efficacy of Bifidobacterium animalis subsp. lactis BB-12\u0026reg; in infant colic: A randomised, double blind, placebo-controlled trial. \u003cem\u003eAliment Pharmacol Ther\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 110\u0026ndash;120 (2020).\u003c/li\u003e\n\u003cli\u003eMcKeen, S. \u003cem\u003eet al.\u003c/em\u003e Infant Complementary Feeding of Prebiotics for the Microbiome and Immunity. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 364 (2019).\u003c/li\u003e\n\u003cli\u003eLaursen, M. F. \u003cem\u003eet al.\u003c/em\u003e Bifidobacterium species associated with breastfeeding produce aromatic lactic acids in the infant gut. \u003cem\u003eNat Microbiol\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 1367\u0026ndash;1382 (2021).\u003c/li\u003e\n\u003cli\u003eDuboux, S. \u003cem\u003eet al.\u003c/em\u003e Carbohydrate-controlled serine protease inhibitor (serpin) production in Bifidobacterium longum subsp. longum. \u003cem\u003eScientific reports\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 7236 (2021).\u003c/li\u003e\n\u003cli\u003eMcCarville, J. L. \u003cem\u003eet al.\u003c/em\u003e A Commensal Bifidobacterium longum Strain Prevents Gluten-Related Immunopathology in Mice through Expression of a Serine Protease Inhibitor. \u003cem\u003eApplied and environmental microbiology\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, e01323-01317 (2017).\u003c/li\u003e\n\u003cli\u003eWu, D. T. \u003cem\u003eet al.\u003c/em\u003e Dynamic changes of structural characteristics of snow chrysanthemum polysaccharides during in vitro digestion and fecal fermentation and related impacts on gut microbiota. \u003cem\u003eFood Res Int\u003c/em\u003e \u003cstrong\u003e141\u003c/strong\u003e, 109888 (2021).\u003c/li\u003e\n\u003cli\u003eYu, T. \u003cem\u003eet al.\u003c/em\u003e Effects of Prebiotics and Synbiotics on Functional Constipation. \u003cem\u003eAm j med sci\u003c/em\u003e \u003cstrong\u003e353\u003c/strong\u003e, 282\u0026ndash;292 (2017).\u003c/li\u003e\n\u003cli\u003eBorewicz, K. \u003cem\u003eet al.\u003c/em\u003e The association between breastmilk oligosaccharides and faecal microbiota in healthy breastfed infants at two, six, and twelve weeks of age. \u003cem\u003eScientific reports\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 4270 (2020).\u003c/li\u003e\n\u003cli\u003eZha, A. \u003cem\u003eet al.\u003c/em\u003e The nanocomposites of modified attapulgite with vitamin E and mannan oligosaccharide regulated the intestinal epithelial barrier and improved intestinal microbiota composition to prevent diarrhea in weaned piglets. \u003cem\u003eJ sci food agric\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, 5569\u0026ndash;5577 (2023).\u003c/li\u003e\n\u003cli\u003eSalem, F. \u003cem\u003eet al.\u003c/em\u003e Gut microbiome in chronic rheumatic and inflammatory bowel diseases: Similarities and differences. \u003cem\u003eUnited European Gastroenterol J\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 1008\u0026ndash;1032 (2019).\u003c/li\u003e\n\u003cli\u003eNakashima, A. \u003cem\u003eet al.\u003c/em\u003e The alga Euglena gracilis stimulates Faecalibacterium in the gut and contributes to increased defecation. \u003cem\u003eScientific reports\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 1074 (2021).\u003c/li\u003e\n\u003cli\u003eJalanka, J. \u003cem\u003eet al.\u003c/em\u003e The Effect of Psyllium Husk on Intestinal Microbiota in Constipated Patients and Healthy Controls. \u003cem\u003eInt J Mol Sci\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 433 (2019).\u003c/li\u003e\n\u003cli\u003eSugitani, Y. \u003cem\u003eet al.\u003c/em\u003e Mucosa-associated gut microbiome in Japanese patients with functional constipation. \u003cem\u003eJ clin biochem nutr\u003c/em\u003e \u003cstrong\u003e68\u003c/strong\u003e, 187\u0026ndash;192 (2021).\u003c/li\u003e\n\u003cli\u003eDong, H. \u003cem\u003eet al.\u003c/em\u003e Microbiome Analysis Reveals the Attenuation Effect of \u003cem\u003eLactobacillus\u003c/em\u003e From Yaks on Diarrhea \u003cem\u003evia\u003c/em\u003e Modulation of Gut Microbiota. \u003cem\u003eFront Cell Infect Microbiol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 610781 (2020).\u003c/li\u003e\n\u003cli\u003eAfum, T. \u003cem\u003eet al.\u003c/em\u003e Diarrhea-Causing Bacteria and Their Antibiotic Resistance Patterns Among Diarrhea Patients From Ghana. \u003cem\u003eFront Microbiol\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 894319 (2022).\u003c/li\u003e\n\u003cli\u003eBrunkwall, L., Ericson, U., Nilsson, P. M., Orho-Melander, M. \u0026amp; Ohlsson, B. Self-reported bowel symptoms are associated with differences in overall gut microbiota composition and enrichment of Blautia in a population-based cohort. \u003cem\u003eJournal of gastroenterology and hepatology\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 174\u0026ndash;180 (2021).\u003c/li\u003e\n\u003cli\u003eMu, Y. \u0026amp; Cong, Y. \u003cem\u003eBacillus coagulans\u003c/em\u003e and its applications in medicine. \u003cem\u003eBenef microbes\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 679\u0026ndash;688 (2019).\u003c/li\u003e\n\u003cli\u003eZhang, Z., Zhang, G., Zhang, S. \u0026amp; Zhao, J. Fructooligosaccharide Reduces Weanling Pig Diarrhea in Conjunction with Improving Intestinal Antioxid ase Activity and Tight Junction Protein Expression. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 512 (2022).\u003c/li\u003e\n\u003cli\u003eWilliams, J. E. \u003cem\u003eet al.\u003c/em\u003e Relationships Among Microbial Communities, Maternal Cells, Oligosaccharides, and Macronutrients in Human Milk. \u003cem\u003eJ Hum Lact\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 540\u0026ndash;551 (2017).\u003c/li\u003e\n\u003cli\u003eHuang, J. \u003cem\u003eet al.\u003c/em\u003e Pediococcus pentosaceus B49 from human colostrum ameliorates constipation in mice. \u003cem\u003eFood Funct\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 5607\u0026ndash;5620 (2020).\u003c/li\u003e\n\u003cli\u003eBode, L. \u003cem\u003eet al.\u003c/em\u003e Human milk oligosaccharide concentration and risk of postnatal transmission of HIV through breastfeeding. \u003cem\u003eAm j clin nutr\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e, 831\u0026ndash;839 (2012).\u003c/li\u003e\n\u003cli\u003eAsnicar, F. \u003cem\u003eet al.\u003c/em\u003e Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. \u003cem\u003eNat med\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 321\u0026ndash;332 (2021).\u003c/li\u003e\n\u003cli\u003eLi, M., Wang, M. \u0026amp; Donovan, S. M. Early development of the gut microbiome and immune-mediated childhood disorders. \u003cem\u003eSeminars in reproductive medicine\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 74\u0026ndash;86 (2014).\u003c/li\u003e\n\u003cli\u003eMartin, R. \u003cem\u003eet al.\u003c/em\u003e Early-Life Events, Including Mode of Delivery and Type of Feeding, Siblings and Gender, Shape the Developing Gut Microbiota. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, e0158498 (2016).\u003c/li\u003e\n\u003cli\u003eSavino, F. \u003cem\u003eet al.\u003c/em\u003e Faecal microbiota in breast-fed infants after antibiotic therapy. \u003cem\u003eActa paediatr\u003c/em\u003e \u003cstrong\u003e100\u003c/strong\u003e, 75\u0026ndash;78 (2011).\u003c/li\u003e\n\u003cli\u003eLiu, Z. \u003cem\u003eet al.\u003c/em\u003e Integration of Transcriptome and Metabolome Reveals the Genes and Metabolites Involved in \u003cem\u003eBifidobacterium bifidum\u003c/em\u003e Biofilm Formation. \u003cem\u003eInt J Mol Sci\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 7596 (2021).\u003c/li\u003e\n\u003cli\u003eChen, W., Yan, Q., Zhong, R. \u0026amp; Tan, Z. Amino acid profiles, amino acid sensors and transporters expression and intestinal microbiota are differentially altered in goats infected with Haemonchus contortus. \u003cem\u003eAmino acids\u003c/em\u003e \u003cstrong\u003e55\u003c/strong\u003e, 371\u0026ndash;384 (2023).\u003c/li\u003e\n\u003cli\u003eStražar, M. \u003cem\u003eet al.\u003c/em\u003e The influence of the gut microbiome on BCG-induced trained immunity. \u003cem\u003eGenome Biol\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 275 (2021).\u003c/li\u003e\n\u003cli\u003eBaykara, S. G., S\u0026uuml;rmeli, Y. \u0026amp; Şanlı-Mohamed, G. Purification and Biochemical Characterization of a Novel Thermostable Serine Protease from Geobacillus sp. GS53. \u003cem\u003eApplied biochemistry and biotechnology\u003c/em\u003e \u003cstrong\u003e193\u003c/strong\u003e, 1574\u0026ndash;1584 (2021).\u003c/li\u003e\n\u003cli\u003eWang, S., Ping, Q. \u0026amp; Li, Y. Comprehensively understanding metabolic pathways of protein during the anaerobic digestion of waste activated sludge. \u003cem\u003eChemosphere\u003c/em\u003e \u003cstrong\u003e297\u003c/strong\u003e, 134117 (2022).\u003c/li\u003e\n\u003cli\u003eMa, W. \u003cem\u003eet al.\u003c/em\u003e Chronic paradoxical sleep deprivation-induced depression-like behavior, energy metabolism and microbial changes in rats. \u003cem\u003eLife sciences\u003c/em\u003e \u003cstrong\u003e225\u003c/strong\u003e, 88\u0026ndash;97 (2019).\u003c/li\u003e\n\u003cli\u003eLiu, C. \u003cem\u003eet al.\u003c/em\u003e The combination of microbiome and metabolome to analyze the cross-cooperation mechanism of \u003cem\u003eEchinacea purpurea\u003c/em\u003e polysaccharide with the gut microbiota \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. \u003cem\u003eFood funct\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 10069\u0026ndash;10082 (2022).\u003c/li\u003e\n\u003cli\u003eXie, L. \u003cem\u003eet al.\u003c/em\u003e Effect of fecal microbiota transplantation in patients with slow transit constipation and the relative mechanisms based on the protein digestion and absorption pathway. \u003cem\u003eJ Transl Med\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 490 (2021).\u003c/li\u003e\n\u003cli\u003eTatsumi, M. \u003cem\u003eet al.\u003c/em\u003e Development of a rapid and simple glycine analysis method using a stable glycine oxidase mutant. \u003cem\u003eAnalytical biochemistry\u003c/em\u003e \u003cstrong\u003e587\u003c/strong\u003e, 113447 (2019).\u003c/li\u003e\n\u003cli\u003eRiederer, M. \u003cem\u003eet al.\u003c/em\u003e Free threonine in human breast milk is related to infant intestinal microbiota composition. \u003cem\u003eAmino acids\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 365\u0026ndash;383 (2022).\u003c/li\u003e\n\u003cli\u003eYang, Y., Kumrungsee, T., Kuroda, M., Yamaguchi, S. \u0026amp; Kato, N. Feeding \u003cem\u003eAspergillus\u003c/em\u003e protease preparation combined with adequate protein diet to rats increases levels of cecum gut-protective amino acids, partially linked to \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e. \u003cem\u003eBioscience biotechnology and biochemistry\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 1901\u0026ndash;1911 (2019).\u003c/li\u003e\n\u003cli\u003eXu, S. \u0026amp; Wang, S. GC-MS and metabolomics analysis of amino acids, glucose and urinary metabolic pathways and characteristics in children with spleen-deficiency diarrhea. \u003cem\u003eCellular and molecular biology\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 125\u0026ndash;130 (2020).\u003c/li\u003e\n\u003cli\u003eEdogawa, S. \u003cem\u003eet al.\u003c/em\u003e Serine proteases as luminal mediators of intestinal barrier dysfunction and symptom severity in IBS. \u003cem\u003eGut\u003c/em\u003e \u003cstrong\u003e69\u003c/strong\u003e, 62\u0026ndash;73 (2020).\u003c/li\u003e\n\u003cli\u003eLaw, G. K., Bertolo, R. F., Adjiri-Awere, A., Pencharz, P. B. \u0026amp; Ball, R. O. Adequate oral threonine is critical for mucin production and gut function in neonatal piglets. \u003cem\u003eAmerican journal of physiology-gastrointestinal and liver physiology\u003c/em\u003e \u003cstrong\u003e292\u003c/strong\u003e, G1293-1301 (2007).\u003c/li\u003e\n\u003cli\u003eZhang, Q. \u003cem\u003eet al.\u003c/em\u003e Effect of konjac glucomannan on metabolites in the stomach, small intestine and large intestine of constipated mice and prediction of the KEGG pathway. \u003cem\u003eFood funct\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 3044\u0026ndash;3056 (2021).\u003c/li\u003e\n\u003cli\u003eHe, X., Slupsky, C. M., Dekker, J. W., Haggarty, N. W. \u0026amp; L\u0026ouml;nnerdal, B. Integrated Role of \u003cem\u003eBifidobacterium animalis\u003c/em\u003e subsp. \u003cem\u003elactis\u003c/em\u003e Supplementation in Gut Microbiota, Immunity, and Metabolism of Infant Rhesus Monkeys. \u003cem\u003emSystems\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, e00128-00116 (2016).\u003c/li\u003e\n\u003cli\u003eHe, L. \u003cem\u003eet al.\u003c/em\u003e Exogenous and Endogenous Serine Deficiency Exacerbates Hepatic Lipid Accumulation. \u003cem\u003eOxid med cell longev\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, 4232704 (2021).\u003c/li\u003e\n\u003cli\u003eGopalakrishna, K. P. \u0026amp; Hand, T. W. Influence of Maternal Milk on the Neonatal Intestinal Microbiome. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 823 (2020).\u003c/li\u003e\n\u003cli\u003eSchoemaker, M. H. \u003cem\u003eet al.\u003c/em\u003e Prebiotic Galacto-Oligosaccharides Impact Stool Frequency and Fecal Microbiota in Self-Reported Constipated Adults: A Randomized Clinical Trial. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 309 (2022).\u003c/li\u003e\n\u003cli\u003eTang, W. \u003cem\u003eet al.\u003c/em\u003e Prospective study reveals a microbiome signature that predicts the occurrence of post-operative enter ocolitis in Hirschsprung disease (HSCR) patients. \u003cem\u003eGut Microbes\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 842\u0026ndash;854 (2020).\u003c/li\u003e\n\u003cli\u003eLogue, J. B. \u003cem\u003eet al.\u003c/em\u003e Experimental insights into the importance of aquatic bacterial community composition to the degradation of dissolved organic matter. \u003cem\u003eIsme j\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 533\u0026ndash;545 (2016).\u003c/li\u003e\n\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":"breastmilk microbiome, lactation, frequency of infant defecation","lastPublishedDoi":"10.21203/rs.3.rs-4146767/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4146767/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreastfeeding can significantly impact the establishment of the infant's intestinal microbiota. In this study, we hypothesized that maternal breast milk bacteria were associated with variations in defecation frequency in infants aged 1 to 6 months who were exclusively breastfed, and we sought to identify potential breast milk microbiota diagnostic markers. 102 exclusively breastfed infants aged at 1 to 6 months were enrolled in the study. Then, we collected their mothers' breast milk as samples for 16S rRNA sequencing evaluation of microbiotas. The results revealed a clear distinction between the three groups regarding microbiota structures and compositions. Changes were observed in the various species and genera, and the breast milk microbiota features \u003cem\u003eHydrogenobacteria\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e were confirmed as potential biomarkers for regulating the change in neonate defecation frequency. This study demonstrates a significant correlation between the frequency of defecation in exclusively breastfed infants and the microbiota in their mothers' milk. It was discovered that the human breast milk microbiota may play a significant metabolic role in amino acids and oligosaccharides during its colonization in infants' intestines, which influences their defecation frequency. Our research provides new evidence and hypotheses regarding the association between infant defecation frequency and breast milk microbiome.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis trial was registered on 22/12/2023 at \u003ca href=\"http://www.chictr.org.cn\" target=\"_blank\"\u003ewww.chictr.org.cn\u003c/a\u003e as ChiCTR2300078973.\u003c/p\u003e","manuscriptTitle":"Breast Milk Bacteria: The Key to Regulating Defecation Frequency Changes in Infants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 12:52:46","doi":"10.21203/rs.3.rs-4146767/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":"9d8d9f3a-f620-4d91-9928-26b710d33cd9","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30955923,"name":"Biological sciences/Microbiology"},{"id":30955924,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2024-05-30T07:41:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 12:52:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4146767","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4146767","identity":"rs-4146767","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}