Influence of Lactose Supplementation on Regulation of Streptococcus thermophilus on Gut Microbiota.

It has been found that Streptococcus thermophilus (S. thermophilus) influenced the gut microbiota and host metabolism with strain specificity in C57BL/6J mice in the previous study, though it remains unclear whether lactose as a dietary factor associated with dairy consumption is involved as the mediator in the interaction. In the present study, integrated analysis of 16S rRNA gene sequencing and untargeted metabolomics by liquid chromatography-mass spectrometry of fecal samples in C57BL/6J mice was applied to evaluate the effect of lactose on the regulation of gut microbiota by two S. thermophilus strains (4M6 and DYNDL13-4). The results showed that the influence of lactose supplementation on gut microbiota induced by S. thermophilus ingestion was strain-specific. Although two S. thermophilus strains ingestion introduced similar perturbations in the fecal microbiota and gut microbial metabolism, the regulation of DYNDL13-4 on the gut microbiota and metabolism was more affected by lactose than 4M6. More specifically, lactose and 4M6 supplementation mainly enriched pathways of d-glutamine and d-glutamate metabolism, alanine, aspartate, and glutamate metabolism, and tryptophan and phenylalanine metabolism in the gut, whereas 4M6 only enriched tryptophan and phenylalanine metabolism. DYNDL13-4-L (DYNDL13-4 with lactose) had significant effects on sulfur, taurine, and hypotaurine metabolism in the gut and on phenylalanine, tyrosine, tryptophan biosynthesis, and linoleic acid metabolism in serum relative to the DYNDL13-4. Our study demonstrated the strain-specific effect of lactose and S. thermophilus supplementation on gut microbiota and host metabolism. However, considering the complexity of the gut microbiota, further research is necessary to provide insights to facilitate the design of personalized fermented milk products as a dietary therapeutic strategy for improving host health.

Inoculation of Latilactobacillus sakei with Pichia kluyveri or Saccharomyces boulardii improves flavor compound profiles of salt-free fermented wheat-gluten: Effects from single strain inoculation.

Wheat-gluten, the protein-rich portion of wheat, can be processed to produce a highly savory sauce product after solid and liquid-state fermentation (SSF and LSF) with the inoculation of selected lactic acid bacteria (LAB) and yeast under salt-free condition. However, limited research has been done on the impact of different types of microbes in this process. This work studied the flavour impact on fermented wheat-gluten by the single inoculation of Latilactobacillus sakei or one yeast (Saccharomyces boulardii or Pichia kluyveri). Glucose was depleted during LSF in all treatments. Lactic acid production increased over time in L. sakei-fermented samples but not in yeast-fermented samples. Cysteine, serine and arginine remained low over LSF in L. sakei-fermented samples but increased in yeast-fermented samples. More fruity esters such as isoamyl acetate and isobutyl acetate were detected in samples fermented by P. kluyveri, while S. boulardii boosted the production of alcohols such as 3-methyl butanol and 2-phenylethyl alcohol. Principal component analysis revealed a clear difference in volatile profiles of the samples fermented with different strains. Therefore, the fermented sauce can potentially be processed into different flavor directions, and based on the flavor profile, be used in different food applications.

Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population.

BACKGROUND: The gut microbiome has proven to be an important factor affecting obesity; however, it remains a challenge to identify consistent biomarkers across geographic locations and perform precisely targeted modulation for obese individuals. RESULTS: This study proposed a systematic machine learning framework and applied it to 870 human stool metagenomes across five countries to obtain comprehensive regional shared biomarkers and conduct a personalized modulation analysis. In our pipeline, a heterogeneous ensemble feature selection diagram is first developed to determine an optimal subset of biomarkers through the aggregation of multiple techniques. Subsequently, a deep reinforcement learning method was established to alter the targeted composition to the desired healthy target. In this manner, we can realize personalized modulation by counterfactual inference. Consequently, a total of 42 species were identified as regional shared biomarkers, and they showed good performance in distinguishing obese people from the healthy group (area under curve (AUC) =0.85) when demonstrated on validation datasets. In addition, by pooling all counterfactual explanations, we found that Akkermansia muciniphila, Faecalibacterium prausnitzii, Prevotella copri, Bacteroides dorei, Bacteroides eggerthii, Alistipes finegoldii, Alistipes shahii, Eubacterium sp. _CAG_180, and Roseburia hominis may be potential broad-spectrum targets with consistent modulation in the multi-regional obese population. CONCLUSIONS: This article shows that based on our proposed machine-learning framework, we can obtain more comprehensive and accurate biomarkers and provide modulation analysis for the obese population. Moreover, our machine-learning framework will also be very useful for other researchers to further obtain biomarkers and perform counterfactual modulation analysis in different diseases.

An α type gluco-oligosaccharide from brown algae Laminaria japonica stimulated the growth of lactic acid bacteria encoding specific ABC transport system components.

Glucan is the most widely distributed glycan. Many probiotics such as lactic acid bacteria (LAB) encoded corresponding hydrolytic enzymes, which could use these glucans as energy substances. Brown alga is rich in glucan and has high edible and medicinal value, but research on its regulation to probiotics is not detailed enough. In this study, we determined a novel neutral α type gluco-oligosaccharide from the brown alga Laminaria japonica with a degree of polymerization (DP) of 2-8 and a structure that mainly consists of α-(1→4)-linked glycosidic bonds called Laminaria japonica gluco-oligosaccharide (LJGO). Fermentation in vitro and gene-phenotype correlation analyses revealed that LJGO selectively stimulated the growth of the LAB strain encoding a specific ATP-binding cassette (ABC) transport system in a GH13 gene cluster, with apparent differences among 14 tested species. Comparative genomics further revealed that this transport system is species-specific, implying a potential contribution to species evolution. Transcriptomic analysis based on LAB strains cultured on LJGO and 1H-NMR findings of LJGO residues after strain utilization showed that the GH13 gene cluster contains functional LAB genes involved in LJGO utilization. Further verification by gene knockout studies is needed to expand our findings.

Lactobacillus mucosae exerted different antiviral effects on respiratory syncytial virus infection in mice.

Respiratory syncytial virus (RSV) infection is a constant threat to the health of young children, and this is mainly attributed to the lack of effective prevention strategies. This study aimed to determine whether Lactobacillus (L.) mucosae, a potential probiotic, could protect against respiratory viral infection in a mouse model. Naive 3-4-week-old BALB/c mice were orally administered with three L. mucosae strains (2.5 × 108 CFU/mouse) 7 days before RSV infection (105 TCID50/mouse). Results showed that all three strains inhibited RSV replication and reduced the proportions of inflammatory cells, including granulocytes and monocytes in the blood. The L. mucosae M104R01L3 treatment maintained stable weight in mice and increased interferon (IFN)-ß and tumor necrosis factor (TNF)-α levels. The L. mucosae DCC1HL5 treatment increased interleukin (IL)-1ß and IL-10 levels. Moreover, the M104R01L3 and DCC1HL5 strains increased the proportions of Akkermansia, Alistipes, and Anaeroplasma which contributed to the advantageous modulation of the gut microbiota. Besides, L. mucosae affected the gut levels of short-chain fatty acids (SCFAs) that are important for the antiviral response. L. mucosae 1,025 increased acetate, propionate, and butyrate levels, whereas L. mucosae M104R01L3 increased the level of acetate in the gut. L. mucosae M104R01L3 may protect against viral infection by upregulating the IFN-ß levels in the lungs and its antiviral effect may be related to the increase of acetate levels in the gut. In conclusion, the three L. mucosae strains exerted antiviral effects against RSV infection by differentially regulating immune responses and intestinal micro-ecological balance. This study can provide a reference for studying the mechanisms underlying the antiviral effects of L. mucosae.

Efficacy and Safety of Lactobacillus reuteri CCFM1040 in Allergic Rhinitis and Asthma: A Randomized, Placebo-Controlled Trial.

The coexistence of allergic rhinitis (AR) and asthma reinforces the concept of "one airway, one disease," which has prompted the exploration for a single intervention to treat both diseases. Lactobacillus reuteri CCFM1040 (CCFM1040) was found to be an inhibitor of the common pathogenesis of AR and asthma in our previous studies. This study presented a randomized, placebo-controlled trial to investigate the clinical effects of CCFM1040 on both diseases. The total symptom score (TSS), the quality of life (QoL), and the modulation in the gut microbiota of patients with AR, the Asthma Control and Test (ACT) of patients with asthma, and the safety of both AR and asthma were measured. In patients with AR, CCFM1040 numerically decreased TSS, Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ), 3 nasal scores in TSS (nasal congestion, watery eyes, and rhinorrhea), and sleep and significantly improved (P = 0.014) non-nose/eye symptoms. The ACT score was numerically increased in patients with asthma (from partially controlled to well-controlled). Significant microbial (from class level to genus level) and metabolic differences (P < 0.05) were found in patients with AR. No adverse reactions were observed. No effect on the blood and urine routine indexes. CCFM1040 has a potential benefit on both diseases. Further studies based on these findings will help to optimize the management of AR and asthma.

Systems Biology of Gut Microbiota-Human Receptor Interactions: Toward Anti-inflammatory Probiotics.

The incidence and prevalence of inflammatory disorders have increased globally, and is projected to double in the next decade. Gut microbiome-based therapeutics have shown promise in ameliorating chronic inflammation. However, they are largely experimental, context- or strain-dependent and lack a clear mechanistic basis. This hinders precision probiotics and poses significant risk, especially to individuals with pre-existing conditions. Molecules secreted by gut microbiota act as ligands to several health-relevant receptors expressed in human gut, such as the G-protein coupled receptors (GPCRs), Toll-like receptor 4 (TLR4), pregnane X receptor (PXR), and aryl hydrocarbon receptor (AhR). Among these, the human AhR expressed in different tissues exhibits anti-inflammatory effects and shows activity against a wide range of ligands produced by gut bacteria. However, different AhR ligands induce varying host responses and signaling in a tissue/organ-specific manner, which remain mostly unknown. The emerging systems biology paradigm, with its powerful in silico tool repertoire, provides opportunities for comprehensive and high-throughput strain characterization. In particular, combining metabolic models with machine learning tools can be useful to delineate tissue and ligand-specific signaling and thus their causal mechanisms in disease and health. The knowledge of such a mechanistic basis is indispensable to account for strain heterogeneity and actualize precision probiotics.

Probiotic strains alleviated OVA-induced food allergy in mice by regulating the gut microbiota and improving the level of indoleacrylic acid in fecal samples.

Food allergy (FA) is a common immune disorder caused by food antigens. Probiotic strains showed alleviating effects on FA, such as the alleviation of FA pathological symptoms, serum OVA-sIgE levels, and the gut microbiota diversity and composition. The results showed that intragastric administration of Lactiplantibacillus plantarum CCFM1189, Limosilactobacillus reuteri CCFM1190, and Bifidobacterium longum CCFM1029 alleviated the weight loss and FA pathological symptoms of FA mice and decreased OVA-specific IgE and histamine (HIS) levels. CCFM1189 and CCFM1190 decreased IL-4, IL-5, and IL-13 levels, while CCFM1189 and CCFM 1029 decreased IL-17 levels. The gut microbiota analysis demonstrated that CCFM1189 increased the abundance of Akkermansia, while CCFM1190 improved immune regulation bacteria such as Faecalibaculum. CCFM1029 increased Bifidobacterium and the bacteria involved in short-chain fatty acid (SCFA) production, such as Dubosiella. L. plantarum CCFM1189 and L. reuteri CCFM1190 improved indoleacrylic acid levels in mouse fecal samples using untargeted metabolomics analysis. In conclusion, CCFM1189, CCFM1190, and CCFM1029 decreased Th2 immune responses and alleviated FA pathological symptoms by regulating the gut microbiota diversity and composition, and altering gut microbial metabolites, which could provide support in clinical tests and probiotic production in the future.

Can dietary patterns prevent cognitive impairment and reduce Alzheimer's disease risk: Exploring the underlying mechanisms of effects.

Alzheimer's disease (AD) is one of the fastest growing cognitive decline-related neurological diseases. To date, effective curative strategies have remained elusive. A growing body of evidence indicates that dietary patterns have significant effects on cognitive function and the risk of developing AD. Previous studies on the association between diet and AD risk have mainly focused on individual food components and specific nutrients, and the mechanisms responsible for the beneficial effects of dietary patterns on AD are not well understood. This article provides a comprehensive overview of the effects of dietary patterns, including the Mediterranean diet (MedDiet), dietary approaches to stop hypertension (DASH) diet, Mediterranean-DASH diet intervention for neurological delay (MIND), ketogenic diet, caloric restriction, intermittent fasting, methionine restriction, and low-protein and high-carbohydrate diet, on cognitive impairment and summarizes the underlying mechanisms by which dietary patterns attenuate cognitive impairment, especially highlighting the modulation of dietary patterns on cognitive impairment through gut microbiota. Furthermore, considering the variability in individual metabolic responses to dietary intake, we put forward a framework to develop personalized dietary patterns for people with cognitive disorders or AD based on individual gut microbiome compositions.

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.

The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this study, we considered the influence of geographical factors on the gut microbiome, and a total of 2604 filtered metagenomics data from the gut microbiome were used to construct an age prediction model. Then, we developed an ensemble model with multiple heterogeneous algorithms and combined species and pathway profiles for multi-view learning. By integrating gut microbiome metagenomics data and adjusting host confounding factors, the model showed high accuracy (R2 = 0.599, mean absolute error = 8.33 years). Besides, we further interpreted the model and identify potential biomarkers for the aging process. Among these identified biomarkers, we found that Finegoldia magna, Bifidobacterium dentium, and Clostridium clostridioforme had increased abundance in the elderly. Moreover, the utilization of amino acids by the gut microbiome undergoes substantial changes with increasing age which have been reported as the risk factors for age-associated malnutrition and inflammation. This model will be helpful for the comprehensive utilization of multiple omics data, and will allow greater understanding of the interaction between microorganisms and age to realize the targeted intervention of aging.

A multiphase dietetic protocol incorporating an improved ketogenic diet enhances weight loss and alters the gut microbiome of obese people.

The prevalence of obesity and its associated diseases is increasing. In the current study, 15 obese subjects took part in a 12-week multiphase dietetic protocol incorporating an improved ketogenic diet (MDP-i-KD) (KYLLKS 201806). We investigated the effects of the MDP-i-KD on the anthropometric parameters and the gut microbiota of obese subjects. Our results showed that the MDP-i-KD led to significant reductions in body mass index in obese subjects. The MDP-i-KD significantly decreased the relative abundance of the Lachnospiraceae_ND3007_group, the Eubacterium_hallii_group, and Pseudomonas and Blautia. In addition, gut microbiota co-occurrence networks in obese subjects were restructured to a more healthy condition after weight loss. These results show that the MDP-i-KD enhanced weight loss, which may be associated with dietary-induced changes in the gut microbiome. Our results emphasise the importance of determining the interaction between the host and microbial cells to comprehensively understand the mechanism by which diet affects host physiology and the microbiota.

Gut microbiome status of urban and rural Filipino adults in relation to diet and metabolic disorders.

Here, we aim to understand the condition of the gut microbiome of Filipino adults in relation to their diet and metabolic status. Compared to rural Albay (n = 67), the gut microbiome of subjects living in urban Manila (n = 25) was more colonized by the order Clostridiales, which was negatively correlated with host carbohydrate consumption. Principal component analysis using the genus composition of the 92 total subjects indicated four microbiome types: one type driven by Prevotella, which was associated with high rice consumption and mainly consisted of healthy Albay subjects, one Clostridiales-driven group containing a number of type 2 diabetes mellitus (T2D) subjects from both Manila and Albay who showed lower butyrate levels in association with a decrease in Mediterraneibacter faecis, and the other two types showing dysbiosis-like microbiomes with Lactobacillus and Bifidobacterium overgrowth, with a high ratio of T2D and obese subjects. Multivariate logistic regression analysis suggested high dietary energy intake, and two Veillonellaeae genera, Dialister and Megasphaera, as T2D risk factors, while Prevotella and M. faecis as anti-T2D factors. In conclusion, low-carbohydrate diets restructured the Prevotella-driven gut microbiome, which may predispose Filipino people with high energy diet to T2D.

A low molecular weight brown algae Laminaria japonica glycan modulation of gut microbiota and body weight in mice.

Brown algae glycan from Laminaria japonica (LJNP) is a heterogeneous glycan with two apparent molecular weights of 1.1 and 37.3 kDa, and is mainly composed of α ß-glucan and a few fucosyl residues. To explore the regulation of gut microbiota and the host, LJNP and 2'-fucosyllactose (2'FL) were compared to investigate their effect on mice via oral administration. Using metagenomic and metabolomic analyses, we found that 2'FL mainly relied on Adlercreutzia equolifaciens and Akkermansia muciniphila to improve gut amino acid and bile acid metabolism, whereas LJNP mainly drove Bacteroides vulgatus and Bacteroides uniformis to regulate gut amino acid metabolism and glycometabolism. Moreover, LJNP showed a weight loss effect and better protection of the intestinal barrier than 2'FL. We further employed LJNP and 2'FL on a germ-free mice model. Interestingly, the body weight management was not microbiome mediated. This study showed that LJNP can ameliorate the intestinal barrier through modulation of the gut microbiota, maintain the blood glucose level, and regulate body weight and the antioxidant function. Although the benefits of LJNP on host health were partly revealed, mechanisms such as the weight loss effect require further study.

Comparative Genomic Analysis of Bifidobacterium bifidum Strains Isolated from Different Niches.

The potential probiotic benefits of Bifidobacterium bifidum have received increasing attention recently. We used comparative genomic analysis to explore the differences in the genome and the physiological characteristics of B. bifidum isolated from the fecal samples of Chinese adults and infants. The relationships between genotypes and phenotypes were analyzed to assess the effects of isolation sources on the genetic variation of B. bifidum. The phylogenetic tree results indicated that the phylogeny of B. bifidum may be related to the geographical features of its isolation source. B. bifidum was found to have an open pan-genome and a conserved core genome. The genetic diversity of B. bifidum is mainly reflected in carbohydrate metabolism- and immune/competition-related factors, such as the glycoside hydrolase gene family, bacteriocin operons, antibiotic resistance genes, and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas. Additionally, the type III A CRISPR-Cas system was discovered in B. bifidum for the first time. B. bifidum strains exhibited niche-specific characteristics, and the results of this study provide an improved understanding of the genetics of this species.

Evaluation of Tetracycline Resistance and Determination of the Tentative Microbiological Cutoff Values in Lactic Acid Bacterial Species.

Lactic acid bacteria (LAB) are widely used as probiotics in the food industry owing to their beneficial effects on human health. However, numerous antibiotic resistance genes have been found in LAB strains, especially tetracycline resistance genes. Notably, the potential transferability of these genes poses safety risks. To comprehensively evaluate tetracycline resistance in LAB, we determined the tetracycline susceptibility patterns of 478 LAB strains belonging to four genera and eight species. By comparing phenotypes with genotypes based on genome-wide annotations, five tetracycline resistance genes, tet(M), tet(W/N/W), tet(L), tet(S), and tet(45), were detected in LAB. Multiple LAB strains without tetracycline resistance genes were found to be resistant to tetracycline at the currently recommended cutoff values. Thus, based on the minimum inhibitory concentrations of tetracycline for these LAB strains, the species-specific microbiological cutoff values for Lactobacillus (para)gasseri, Lactobacillus johnsonii, and Lactobacillus crispatus to tetracycline were first developed using the Turnidge, Kronvall, and eyeball methods. The cutoff values for Lactiplantibacillus plantarum were re-established and could be used to better distinguish susceptible strains from strains with acquired resistance. Finally, we verified that these five genes play a role in tetracycline resistance and found that tet(M) and tet(W/N/W) are the most widely distributed tetracycline resistance genes in LAB.

Predicting the Role of the Human Gut Microbiome in Constipation Using Machine-Learning Methods: A Meta-Analysis.

(1) Background: Constipation is a common condition that affects the health and the quality of life of patients. Recent studies have suggested that the gut microbiome is associated with constipation, but these studies were mainly focused on a single research cohort. Thus, we aimed to construct a classification model based on fecal bacterial and identify the potential gut microbes' biomarkers. (2) Methods: We collected 3056 fecal amplicon sequence data from five research cohorts. The data were subjected to a series of analyses, including alpha- and beta-diversity analyses, phylogenetic profiling analyses, and systematic machine learning to obtain a comprehensive understanding of the association between constipation and the gut microbiome. (3) Results: The alpha diversity of the bacterial community composition was higher in patients with constipation. Beta diversity analysis evidenced significant partitions between the two groups on the base of gut microbiota composition. Further, machine learning based on feature selection was performed to evaluate the utility of the gut microbiome as the potential biomarker for constipation. The Gradient Boosted Regression Trees after chi2 feature selection was the best model, exhibiting a validation performance of 70.7%. (4) Conclusions: We constructed an accurate constipation discriminant model and identified 15 key genera, including Serratia, Dorea, and Aeromonas, as possible biomarkers for constipation.

Mindfulness Awareness Practice (MAP) to Prevent Dementia in Older Adults with Mild Cognitive Impairment: Protocol of a Randomized Controlled Trial and Implementation Outcomes.

BACKGROUND: With an aging population, developing non-pharmacological interventions (NPIs) to delay dementia has become critical. Apart from cognitive decline, dementia is associated with multiple pathophysiology, including increased oxidative stress, dysregulated gene expressions, cytokine, neurotrophin, and stress markers, telomere shortening, and deteriorations in brain connectivity. Although mindfulness practices have been proposed to ameliorate these biological changes, no empirical studies were conducted. We thus aimed to investigate the effects of mindfulness awareness practice (MAP) to prevent cognitive decline and improve peripheral biomarkers in community-dwelling older adults diagnosed with mild cognitive impairment (MCI). METHODS/DESIGN: This was a single-blinded and parallel-group randomized controlled trial with two arms (intervention and active control arms), conducted over nine months. A total of 60 consenting community-dwelling older adults diagnosed with MCI were planned to be randomized in a 1:1 ratio to either the MAP or the Health Education Program (HEP). Interventions were performed weekly for the initial 12 weeks, and monthly for the subsequent six months. Outcome measures were assessed at baseline, 3-month, and 9-month post-intervention by blinded assessors. Primary outcomes were neurocognitive tests, comprehensive peripheral biomarkers, and brain imaging scans. Secondary outcomes included basic health screening measures, affective symptoms, and measures of physical functions. Linear-mixed models were used to examine the effects of MAP on these outcome measures. SIGNIFICANCE: This is the first randomized controlled trial to systematically investigate the effects of a mindfulness intervention in improving cognitive functions and various biomarkers in community-dwelling older adults diagnosed with MCI. Our findings have the potential to inform mindfulness intervention as a novel approach to delay dementia.

Chinese gut microbiota and its associations with staple food type, ethnicity, and urbanization.

The gut microbiota could affect human health and disease. Although disease-associated microbiota alteration has been extensively investigated in the Chinese population, a nationwide Chinese gut microbiota baseline is still lacking. Here we performed 16 S rRNA gene sequencing on fecal samples from 2678 healthy Chinese individuals, who belonged to eight ethnic groups and resided in 63 counties/cities of 28 provinces. We identified four enterotypes, three of which were enriched for Prevotella, Bacteroides, and Escherichia, respectively, whereas the fourth one had no dominant genus. By assessing the association between the gut microbiota and 20 variables belonging to six categories, geography, demography, diet, urbanization, lifestyle, and sampling month, we revealed that geography explained the largest microbiota variation, and clarified the distinct patterns in the associations with staple food type, ethnicity, and urban/rural residence. Specifically, the gut microbiota of Han Chinese and ethnic minority groups from the same sites was more alike than that of the same ethnic minority groups from different sites. Individuals consuming wheat as staple food were predicted to have more microbial genes involving in glucan 1,3-beta-glucosidase and S-adenosyl-L-methionine biosynthesis than those who consumed rice, based on functional prediction. Besides, an appreciable effect of urbanization on decreased intra-individual diversity, increased inter-individual diversity, and increased proportion of the Bacteroides enterotype was observed. Collectively, our study provided a nationwide gut microbiota baseline of the Chinese population and knowledge on important covariates, which are fundamental to translational microbiota research.

The Species-Level Composition of the Fecal Bifidobacterium and Lactobacillus Genera in Indonesian Children Differs from That of Their Mothers.

The infant gut microbiota plays a critical role in early life growth and derives mainly from maternal gut and breast milk. This study aimed to analyze the differences in the gut microbiota, namely Bifidobacterium and Lactobacillus communities at species level among breast milk as well as maternal and infant feces at different time points after delivery. Fifty-one mother-infant pairs from Indonesia were recruited, and the breast milk and maternal and infant feces were collected and analyzed by high throughput sequencing (16S rRNA, Bifidobacterium groEL and Lactobacillus groEL genes). PCoA results showed bacterial composition was different among breast milk and maternal and infant feces within the first two years. The abundance of Bifidobacterium and Bacteroides were significantly higher in infant feces compared to their maternal feces from birth to two years of age, and maternal breast milk within six months after birth (p < 0.05), whereas the abundance of Blautia, Prevotella, and Faecalibacterium was higher in maternal feces compared to that in breast milk within six months and infant feces within one year after birth, respectively (p < 0.05). The relative abundances of Bacteroides and Lactobacillus was higher and lower in infant feces compared to that in maternal feces only between one and two years of age, respectively (p < 0.05). For Bifidobacterium community at species level, B. adolescentis, B. ruminantium, B. longum subsp. infantis, B. bifidum, and B. pseudolongum were identified in all samples. However, the profile of Bifidobacterium was different between maternal and infant feces at different ages. The relative abundances of B. adolescentis and B. ruminantium were higher in maternal feces compared to those in infant feces from birth to one year of age (p < 0.05), while the relative abundances of B. longum subsp. infantis and B. bifidum were higher in infant feces compared to those in maternal feces beyond three months, and the relative abundance of B. pseudolongum was only higher in infant feces between three and six months (p < 0.05). For Lactobacillus community, L. paragasseri showed higher relative abundance in infant feces when the infant was younger than one year of age (p < 0.05). This study showed bacterial composition at the genus level and Bifidobacterium and Lactobacillus communities at the species level were stage specific in maternal breast milk as well as and maternal and infant feces.