Low Maternal Microbiota Sharing across Gut, Breast Milk and Vagina, as Revealed by 16S rRNA Gene and Reduced Metagenomic Sequencing

Importance of Selected Nutrients and Additives in the Feed of Pregnant Sows for the Survival of Newborn Piglets

This systematic review analyzed the effect of selected nutrients and additives in the feed of pregnant sows on the survival of newborn piglets. We analyzed 720 peer-reviewed publications in English in PubMed® and Web of Science®, dated July 2023 to January 2024, related to the effect of dietary supplementation with fatty acids and various percentages of protein, amino acids, and/or sources of dietary fiber on the offspring of gestating sows. While several papers evaluated the effect of nutrition on gestating sows, only a few delved into the distinct feeding strategies required at each stage of gestation to meet the NRC's nutritional requirements for maternal tissue gain and postnatal neonatal survival and growth. This body of research suggests that as gestation progresses the sow's nutritional requirements increase, as the NRC established, to satisfy their own metabolic needs and those of their fetuses. Additional research is needed to determine an optimal feeding strategy.

Analysis of microbial composition and sharing in low-biomass human milk samples: a comparison of DNA isolation and sequencing techniques

Human milk microbiome studies are currently hindered by low milk bacterial/human cell ratios and often rely on 16S rRNA gene sequencing, which limits downstream analyses. Here, we aimed to find a method to study milk bacteria and assess bacterial sharing between maternal and infant microbiota. We tested four DNA isolation methods, two bacterial enrichment methods and three sequencing methods on mock communities, milk samples and negative controls. Of the four DNA isolation kits, the DNeasy PowerSoil Pro (PS) and MagMAX Total Nucleic Acid Isolation (MX) kits provided consistent 16S rRNA gene sequencing results with low contamination. Neither enrichment method substantially decreased the human metagenomic sequencing read-depth. Long-read 16S-ITS-23S rRNA gene sequencing biased the mock community composition but provided consistent results for milk samples, with little contamination. In contrast to 16S rRNA gene sequencing, 16S-ITS-23S rRNA gene sequencing of milk, infant oral, infant faecal and maternal faecal DNA from 14 mother-infant pairs provided sufficient resolution to detect significantly more frequent sharing of bacteria between related pairs compared to unrelated pairs. In conclusion, PS or MX kit-DNA isolation followed by 16S rRNA gene sequencing reliably characterises human milk microbiota, and 16S-ITS-23S rRNA gene sequencing enables studies of bacterial transmission in low-biomass samples.

Effects of soybean hulls and corn stalk on the performance, colostrum composition and faecal microflora of pregnant sows

This study was conducted to investigate the effects of different supplementation levels of soybean hulls and corn stalk in high-fibre gestation diet on the performance, colostrum composition and faecal microbiota of sows. Forty first-farrowing Danish Landrace sows were randomly assigned to five dietary treatment groups. The control (CON, 3.15% crude fibre) group was fed a normal diet, and the treatment groups were soybean hulls low-fibre (SHL, 6.00% crude fibre) group, soybean hulls high-fibre (SHH, 8.00% crude fibre) group, corn stalk low-fibre (CSL, 6.00% crude fibre) group and corn stalk high-fibre (CSH, 8.00% crude fibre) group. The weaning weight of the litter and the average daily feed intake of the lactating sows in the SHL, SHH and CSH groups were higher than those in the CON group (p < 0.05). The immunoglobulin A and G levels of the colostrum in the SHL, SHH, CSL and CSH groups were higher than those in the CON group (p < 0.05), and the immunoglobulin M levels in the SHL, SHH and CSH groups were higher than those in the CON group (p < 0.05). The abundance of Proteobacteria at the phylum level in the CON group was higher than that in the CSL, CSH and SHH groups (p < 0.05). The abundance of Lactobacillaceae at the family level in the SHH and CSL groups were higher than that in the CON group (p < 0.05). The abundance of Lactobacillus at the genus level in the SHH and CSL groups were higher than that in the CON group (p < 0.05). In conclusion, SHH group had the best effect, and the optimal crude fibre level in the gestation diet of sows is 8%.

Firmicutes, Bacteroidetes and Actinobacteria in Human Milk and Maternal Adiposity

The main objective was to explore the relationship between the microbiota of human milk and adiposity in Mexican mothers during the first lactation stage. Methods: Seventy lactating women were included. Adiposity by anthropometric measurements and by bioelectric impedance was obtained. The donation of human milk was requested, from which bacterial DNA was extracted and qPCR of the 16S region was performed. The Mann–Whitney U test, Spearman and Pearson correlations, and multiple linear regressions models were also calculated. Results: The median percentage of Bacteroidetes had a direct and significant correlation with normal adiposity, current BMI, waist circumference, and body fat percentage. The correlation with current BMI became significantly inverse in women with BMI ≥ 25. In women with normal BMI, the percentage of Actinobacteria showed a direct and significant correlation with current BMI, waist circumference, and percentage of body fat. Multiple linear regressions showed that pre-pregnancy BMI was the variable with the highest predictive value with the Bacteroidetes phyla in normal BMI and in BMI ≥ 25. Conclusions: the adiposity of the woman before pregnancy and during lactation would have an important effect on the abundance of Bacteroidetes and Actinobacteria in human milk.

Metataxonomic Analysis of Milk Samples From SARS-CoV-2-Positive and SARS-CoV-2-Negative Women

Objective

To assess the impact of SARS-CoV-2 viral infection on the metataxonomic profile and its evolution during the first month of lactation.

Methods

Milk samples from 37 women with full-term pregnancies and mild SARS-CoV-2 infection and from 63 controls, collected in the first and fifth postpartum weeks, have been analyzed. SARS-CoV-2 RNA was assessed by reverse transcription polymerase chain reaction (RT-PCR) both in cases and controls. After DNA extraction, the V3-V4 hypervariable region of the gene 16S rRNA was amplified and sequenced using the MiSeq system of Illumina. Data were submitted for statistical and bioinformatics analyses after quality control.

Results

All the 1st week and 5th week postpartum milk samples were negative for SARS-CoV-2 RNA. Alpha diversity showed no differences between milk samples from the study and control group, and this condition was maintained along the observation time. Analysis of the beta-diversity also indicated that the study and control groups did not show distinct bacterial profiles. Staphyloccus and Streptococcus were the most abundant genera and the only ones that were detected in all the milk samples provided. Disease state (symptomatic or asymptomatic infection) did not affect the metataxonomic profile in breast milk.

Conclusion

These results support that in the non-severe SARS-CoV-2 pregnant woman infection the structure of the bacterial population is preserved and does not negatively impact on the human milk microbiota.

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data

The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic methods in recent years. In this paper, machine learning methods are used to analyze metagenomic sequencing data of acne, i.e., all kinds of lipids in the face skin. Firstly, lipids data of the diseased skin (DS) samples and the healthy skin (HS) samples of acne patients and the normal control (NC) samples of healthy person are, respectively, analyzed by using principal component analysis (PCA) and kernel principal component analysis (KPCA). Then, the lipids which have main influence on each kind of sample are obtained. In addition, a multiset canonical correlation analysis (MCCA) is utilized to get lipids which can differentiate the face skins of the above three samples. The experimental results show the machine learning methods can effectively analyze metagenomic sequencing data of acne. According to the results, lipids which only influence one of the three samples or the lipids which simultaneously have different degree of influence on these three samples can be used as indicators to judge skin statuses.

Forensic Analysis of Human Microbiome in Skin and Body Fluids Based on Geographic Location

High-throughput DNA sequencing technologies have facilitated the in silico forensic analysis of human microbiome. Specific microbial species or communities obtained from the crime scene provide evidence of human contacts and their body fluids. The microbial community is influenced by geographic, ethnic, lifestyle, and environmental factors such as urbanization. An understanding of the effects of these external stressors on the human microbiome and determination of stable and changing elements are important in selecting appropriate targets for investigation. In this study, the Forensic Microbiome Database (FMD) (http://www.fmd.jcvi.org) containing the microbiome data of various locations in the human body in 35 countries was used. We focused on skin, saliva, vaginal fluid, and stool and found that the microbiome distribution differed according to the body part as well as the geographic location. In the case of skin samples, Staphylococcus species were higher than Corynebacterium species among Asians compared with Americans. Holdemanella and Fusobacterium were specific in the saliva of Koreans and Japanese populations. Lactobacillus was found in the vaginal fluids of individuals in all countries, whereas Serratia and Enterobacter were endemic to Bolivia and Congo, respectively. This study is the first attempt to collate and describe the observed variation in microbiomes from the forensic microbiome database. As additional microbiome databases are reported by studies worldwide, the diversity of the applications may exceed and expand beyond the initial identification of the host.

The Relationship Between Breast Milk Components and the Infant Gut Microbiota

The assembly of the newborn's gut microbiota during the first months of life is an orchestrated process resulting in specialized microbial ecosystems in the different gut compartments. This process is highly dependent upon environmental factors, and many evidences suggest that early bacterial gut colonization has long-term consequences on host digestive and immune homeostasis but also metabolism and behavior. The early life period is therefore a "window of opportunity" to program health through microbiota modulation. However, the implementation of this promising strategy requires an in-depth understanding of the mechanisms governing gut microbiota assembly. Breastfeeding has been associated with a healthy microbiota in infants. Human milk is a complex food matrix, with numerous components that potentially influence the infant microbiota composition, either by enhancing specific bacteria growth or by limiting the growth of others. The objective of this review is to describe human milk composition and to discuss the established or purported roles of human milk components upon gut microbiota establishment. Finally, the impact of maternal diet on human milk composition is reviewed to assess how maternal diet could be a simple and efficient approach to shape the infant gut microbiota.

Fecal Microbiota Nutrient Utilization Potential Suggests Mucins as Drivers for Initial Gut Colonization of Mother-Child-Shared Bacteria

The nutritional drivers for mother-child sharing of bacteria and the corresponding longitudinal trajectory of the infant gut microbiota development are not yet completely settled. We therefore aimed to characterize the mother-child sharing and the inferred nutritional utilization potential for the gut microbiota from a large unselected cohort. We analyzed in depth gut microbiota in 100 mother-child pairs enrolled antenatally from the general population-based Preventing Atopic Dermatitis and Allergies in Children (PreventADALL) cohort. Fecal samples collected at gestational week 18 for mothers and at birth (meconium), 3, 6, and 12 months for infants were analyzed by reduced metagenome sequencing to determine metagenome size and taxonomic composition. The nutrient utilization potential was determined based on the Virtual Metabolic Human (VMH, www.vmh.life) database. The estimated median metagenome size was ∼150 million base pairs (bp) for mothers and ∼20 million bp at birth for the children. Longitudinal analyses revealed mother-child sharing (P < 0.05, chi-square test) from birth up to 6 months for 3 prevalent Bacteroides species (prevalence, >25% for all age groups). In a multivariate analysis of variance (ANOVA), the mother-child-shared Bacteroides were associated with vaginal delivery (1.7% explained variance, P = 0.0001). Both vaginal delivery and mother-child sharing were associated with host-derived mucins as nutrient sources. The age-related increase in metagenome size corresponded to an increased diversity in nutrient utilization, with dietary polysaccharides as the main age-related factor. Our results support host-derived mucins as potential selection means for mother-child sharing of initial colonizers, while the age-related increase in diversity was associated with dietary polysaccharides.IMPORTANCE The initial bacterial colonization of human infants is crucial for lifelong health. Understanding the factors driving this colonization will therefore be of great importance. Here, we used a novel high-taxonomic-resolution approach to deduce the nutrient utilization potential of the infant gut microbiota in a large longitudinal mother-child cohort. We found mucins as potential selection means for the initial colonization of mother-child-shared bacteria, while the transition to a more adult-like microbiota was associated with dietary polysaccharide utilization potential. This knowledge will be important for a future understanding of the importance of diet in shaping the gut microbiota composition and development during infancy.

The Microbiota of the Human Mammary Ecosystem

Human milk contains a dynamic and complex site-specific microbiome, which is not assembled in an aleatory way, formed by organized microbial consortia and networks. Presence of some genera, such as Staphylococcus, Streptococcus, Corynebacterium, Cutibacterium (formerly known as Propionibacterium), Lactobacillus, Lactococcus and Bifidobacterium, has been detected by both culture-dependent and culture-independent approaches. DNA from some gut-associated strict anaerobes has also been repeatedly found and some studies have revealed the presence of cells and/or nucleic acids from viruses, archaea, fungi and protozoa in human milk. Colostrum and milk microbes are transmitted to the infant and, therefore, they are among the first colonizers of the human gut. Still, the significance of human milk microbes in infant gut colonization remains an open question. Clinical studies trying to elucidate the question are confounded by the profound impact of non-microbial human milk components to intestinal microecology. Modifications in the microbiota of human milk may have biological consequences for infant colonization, metabolism, immune and neuroendocrine development, and for mammary health. However, the factors driving differences in the composition of the human milk microbiome remain poorly known. In addition to colostrum and milk, breast tissue in lactating and non-lactating women may also contain a microbiota, with implications in the pathogenesis of breast cancer and in some of the adverse outcomes associated with breast implants. This and other open issues, such as the origin of the human milk microbiome, and the current limitations and future prospects are addressed in this review.

A Scoping Review of Research on the Human Milk Microbiome

BACKGROUND

The human milk microbiome is an emerging scientific area. Careful, accurate collection and measurement for microbial sequencing is imperative. There is controversy about a core microbiome, and little is known about factors that influence composition. Even less known are ways that the milk microbiome might seed the infant gut and affect health.

RESEARCH AIM

The aim of this paper is to provide a critical appraisal of milk microbiome research. The four areas of critical appraisal were collection and measurement, composition, effects on composition, and potential health effects for infants related to the milk microbiome.

METHODS

Using a PRISMA-ScR scoping review, we reviewed sources of evidence extracted from PubMed, Web of Science, CINAHL, Academic Search Complete, and PSYCHINFO data sets using the following criteria: English language, published in past 6 years, primary data, and sequencing using Next Generation Sequencing. Charting of sources of evidence included authors, title, journal year, sample, design, and results. The research questions posed were: How is human milk collected and how are the microbes identified? What is the composition and what factors affect the human milk microbiome? What is the relationship of the human milk microbiome to infant biology and health?

RESULTS

The reviewed studies were quantitative, cross sectional, or longitudinal. A core microbiome may be present. The microbiome may seed the early infant gut and promote physiological functions and thus influence human health.

CONCLUSIONS

We have suggested concerns about collection and measurement that lead to gaps in knowledge generation, and mechanistic studies are lacking.

Dietary fiber and microbiota interaction regulates sow metabolism and reproductive performance

Dietary fiber is a critical nutrient in sow diet and has attracted interest of animal nutritionists for many years. In addition to increase sows’ satiety, dietary fiber has been found to involve in the regulation of multiple biological functions in the sow production. The interaction of dietary fiber and gut microbes can produce bioactive metabolites, which are of great significance to sows' metabolism and reproductive performance. This article reviewed the interaction between dietary fiber and gut microbes in regulating sows' gut microbial diversity, intestinal immune system, lactation, and production performance, with the aim to provide a new strategy for the use of dietary fiber in sow diets.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Milk Microbiota: What Are We Exactly Talking About?

The development of powerful sequencing techniques has allowed, albeit with some biases, the identification and inventory of complex microbial communities that inhabit different body sites or body fluids, some of which were previously considered sterile. Notably, milk is now considered to host a complex microbial community with great diversity. Milk microbiota is now well documented in various hosts. Based on the growing literature on this microbial community, we address here the question of what milk microbiota is. We summarize and compare the microbial composition of milk in humans and in ruminants and address the existence of a putative core milk microbiota. We discuss the factors that contribute to shape the milk microbiota or affect its composition, including host and environmental factors as well as methodological factors, such as the sampling and sequencing techniques, which likely introduce distortion in milk microbiota analysis. The roles that milk microbiota are likely to play in the mother and offspring physiology and health are presented together with recent data on the hypothesis of an enteromammary pathway. At last, this fascinating field raises a series of questions, which are listed and commented here and which open new research avenues.

Microbial Communities in Human Milk Relate to Measures of Maternal Weight

The process of breastfeeding exposes infants to bioactive substances including a diversity of bacteria from breast milk as well as maternal skin. Knowledge of the character of and variation in these microbial communities, as well as the factors that influence them, is limited. We aimed to identify profiles of breastfeeding-associated microbial communities and their association with maternal and infant factors. Bilateral milk samples were collected from women in the New Hampshire Birth Cohort Study at approximately 6 weeks postpartum without sterilization of the skin in order to capture the infant-relevant exposure. We sequenced the V4-V5 hypervariable region of the bacterial 16S rRNA gene in 155 human milk samples. We used unsupervised clustering (partitioning around medoids) to identify microbial profiles in milk samples, and multinomial logistic regression to test their relation with maternal and infant variables. Associations between alpha diversity and maternal and infant factors were tested with linear models. Four breastfeeding microbiome types (BMTs) were identified, which differed in alpha diversity and in Streptococcus, Staphylococcus, Acinetobacter, and Pseudomonas abundances. Higher maternal pre-pregnancy BMI was associated with increased odds of belonging to BMT1 [OR (95% CI) = 1.13 (1.02, 1.24)] or BMT3 [OR (95% CI) = 1.12 (1.01, 1.25)] compared to BMT2. Independently, increased gestational weight gain was related to reduced odds of membership in BMT1 [OR (95% CI) = 0.66 (0.44, 1.00) per 10 pounds]. Alpha diversity was positively associated with gestational weight gain and negatively associated with postpartum sample collection week. There were no statistically significant associations of breastfeeding microbiota with delivery mode. Our results indicate that the breastfeeding microbiome partitions into four profiles and that its composition and diversity is associated with measures of maternal weight.

Short communication: Intra- and inter-individual milk microbiota variability in healthy and infected water buffalo udder quarters

The concept that ruminant mammary gland quarters are anatomically and physiologically unrelated has been recently challenged by immunological evidence. How this interdependence reflects on individual quarter milk microbiota is unknown. The aim of the present study was to cover this gap by investigating the interdependence of quarters among the same mammary gland at the milk microbiota level using next-generation sequencing of the V4-16S rRNA gene. A total of 52 samples were included in this study and classified as healthy or affected by subclinical mastitis. Extraction of DNA, amplification of the V4-16S rRNA gene, and sequencing using Ion Torrent Personal Genome Machine (Thermo Fisher Scientific, Waltham, MA) were carried out. We found that the intra-individual variability was lower than the inter-individual one. The present findings further support at milk microbiota level the hypothesis of the interdependence of quarters, as previously demonstrated following immunological studies, suggesting that individual factors (e.g., immunity, genetics) may have a role in modulating milk microbiota.

Strong Multivariate Relations Exist Among Milk, Oral, and Fecal Microbiomes in Mother-Infant Dyads During the First Six Months Postpartum

BACKGROUND

Neonatal gastrointestinal (GI) bacterial community structure may be related to bacterial communities of the mother, including those of her milk. However, very little is known about the diversity in and relationships among complex bacterial communities in mother-infant dyads.

OBJECTIVE

Our primary objective was to assess whether microbiomes of milk are associated with those of oral and fecal samples of healthy lactating women and their infants.

METHODS

Samples were collected 9 times from day 2 to 6 mo postpartum from 21 healthy lactating women and their infants. Milk was collected via complete breast expression, oral samples via swabs, and fecal samples from tissue (mothers) and diapers (infants). Microbiomes were characterized using high-throughput sequencing of the 16S ribosomal RNA (rRNA) gene. Alpha and beta diversity indices were used to compare microbiomes across time and sample types. Membership and composition of microbiomes were analyzed using nonmetric multidimensional scaling and canonical correlation analysis (CCA). The contribution of various bacterial communities of the mother-infant dyad to both milk and infant fecal bacterial communities were estimated using SourceTracker2.

RESULTS

Bacterial community structures were relatively unique to each sample type. The most abundant genus in milk and maternal and infant oral samples was Streptococcus (47.1% ± 2.3%, 53.9% ± 1.3%, and 69.1% ± 1.8%, respectively), whereas Bacteroides were predominant in maternal and infant fecal microbiomes (22.9% ± 1.3% and 21.4% ± 2.4%, respectively). The milk microbiome was more similar to the infant oral microbiome than the infant fecal microbiome. However, CCA suggested strong associations between the complex microbial communities of milk and those of all other sample types collected.

CONCLUSIONS

These findings suggest complex microbial interactions between breastfeeding mothers and their infants and support the hypothesis that variation in the milk microbiome may influence the infant GI microbiome.

Bacteriophage Resistance Alters Antibiotic-Mediated Intestinal Expansion of Enterococci

Enterococcus faecalis is a human intestinal pathobiont with intrinsic and acquired resistance to many antibiotics, including vancomycin. Nature provides a diverse and virtually untapped repertoire of bacterial viruses, or bacteriophages (phages), that could be harnessed to combat multidrug-resistant enterococcal infections. Bacterial phage resistance represents a potential barrier to the implementation of phage therapy, emphasizing the importance of investigating the molecular mechanisms underlying the emergence of phage resistance. Using a cohort of 19 environmental lytic phages with tropism against E. faecalis, we found that these phages require the enterococcal polysaccharide antigen (Epa) for productive infection. Epa is a surface-exposed heteroglycan synthesized by enzymes encoded by both conserved and strain-specific genes. We discovered that exposure to phage selective pressure favors mutation in nonconserved epa genes both in culture and in a mouse model of intestinal colonization. Despite gaining phage resistance, epa mutant strains exhibited a loss of resistance to cell wall-targeting antibiotics. Finally, we show that an E. faecalis epa mutant strain is deficient in intestinal colonization, cannot expand its population upon antibiotic-driven intestinal dysbiosis, and fails to be efficiently transmitted to juvenile mice following birth. This study demonstrates that phage therapy could be used in combination with antibiotics to target enterococci within a dysbiotic microbiota. Enterococci that evade phage therapy by developing resistance may be less fit at colonizing the intestine and sensitized to vancomycin, preventing their overgrowth during antibiotic treatment.

Shaping Microbiota During the First 1000 Days of Life

The data obtained in prior studies suggest that early microbial exposition begins prior to conception and gestation. Given that the host-microbe interaction is shaped by the immune system response, it is important to understand the key immune system-microbiota relationship during the period from conception to the first years of life. The present work summarizes the available evidence concerning early microbiota exposure within the male and the female reproductive tracts at the point of conception and during gestation, focusing on the potential impact on infant development during the first 1000 days of life. Furthermore, we conclude that some dietary strategies including specific probiotics could become potentially valuable tools to modulate the gut microbiota during this early critical window of opportunity for targeted health outcomes throughout the entire lifespan.

An Exploratory Search for Potential Molecular Targets Responsive to the Probiotic Lactobacillus salivarius PS2 in Women With Mastitis: Gene Expression Profiling vs. Interindividual Variability

Probiotics constitute an attractive alternative in the battle against microbial infections. Oral administration of certain strains of lactobacilli isolated from human milk has resulted in an effective reduction of the bacterial load as well as an improvement of the mastitis-associated symptoms. Nevertheless, little is yet known about the potential molecular mechanisms and specific targets implicated in these effects. Transcriptomic profiling has been used to search for disease-associated and therapy-responsive molecules in different disorders and experimental models. We have applied for the first time a gene expression-based molecular approach to explore for potential targets responsive to intervention with a probiotic in: (i) breast milk somatic cells (n = 17) and (ii) blood leukocytes (n = 19). Women with mastitis ingested a new strain of lactobacilli, Lactobacillus salivarius PS2 (3 × capsules per day, each capsule contained ~9.5 log10 CFU) for 21 days. We applied Affymetrix microarrays and Taqman one-step quantitative reverse transcription PCR (RT-qPCR) to analyze and compare gene expression changes between samples pre- and post-treatment. Our results substantiate the involvement of inflammatory and cell-growth related pathways and genes in the breast milk somatic cells following the intake of L. salivarius PS2. Individual analyses of selected genes: (1) supported the upregulation of STC1 and IL19 and the downregulation of PLAUR and IFNGR1 in the somatic cells of the patients as potential targets responsive to the probiotic, (2) detected a lack of a relationship between the gene expression responses in the two types of cells, and (3) evidenced a substantial interindividual variability in the gene expression changes in both types of cells. Our study provides an insight into the essentiality of incorporating the study of tissue-specific interindividual molecular responsivity into future clinical intervention trials to further understand the complexity of human gene expression responses to therapy and the potentiality of selecting appropriate responsive targets.