Exclusively Breastfed Infant Microbiota Develops over Time and Is Associated with Human Milk Oligosaccharide Intakes

Temporal development of maternal and infant microbiomes during early life impacts short- and long-term infant health. This study aimed to characterize bacterial dynamics within maternal faecal, human milk (HM), infant oral, and infant faecal samples during the exclusive breastfeeding period and to document associations between human milk oligosaccharide (HMO) intakes and infant oral and faecal bacterial profiles. Maternal and infant samples (n = 10) were collected at 2−5, 30, 60, 90 and 120 days postpartum and the full-length 16S ribosomal RNA (rRNA) gene was sequenced. Nineteen HMOs were quantitated using high-performance liquid chromatography. Bacterial profiles were unique to each sample type and changed significantly over time, with a large degree of intra- and inter-individual variation in all sample types. Beta diversity was stable over time within infant faecal, maternal faecal and HM samples, however, the infant oral microbiota at day 2−5 significantly differed from all other time points (all p < 0.02). HMO concentrations and intakes significantly differed over time, and HMO intakes showed differential associations with taxa observed in infant oral and faecal samples. The direct clinical relevance of this, however, is unknown. Regardless, future studies should account for intakes of HMOs when modelling the impact of HM on infant growth, as it may have implications for infant microbiota development.

25 Years of Research in Human Lactation: From Discovery to Translation

Researchers have recently called for human lactation research to be conceptualized as a biological framework where maternal and infant factors impacting human milk, in terms of composition, volume and energy content are studied along with relationships to infant growth, development and health. This approach allows for the development of evidence-based interventions that are more likely to support breastfeeding and lactation in pursuit of global breastfeeding goals. Here we summarize the seminal findings of our research programme using a biological systems approach traversing breast anatomy, milk secretion, physiology of milk removal with respect to breastfeeding and expression, milk composition and infant intake, and infant gastric emptying, culminating in the exploration of relationships with infant growth, development of body composition, and health. This approach has allowed the translation of the findings with respect to education, and clinical practice. It also sets a foundation for improved study design for future investigations in human lactation.

Impact of expression mode and timing of sample collection, relative to milk ejection, on human milk bacterial DNA profiles

AIM

To investigate the impact of expression mode: electric breast pump or hand expression, and timing of sample collection: pre- and post-milk ejection on human milk (HM) bacterial DNA profiles.

METHODS AND RESULTS

Three HM samples from the same breast were collected from 30 breastfeeding mothers: a pre-milk ejection pump-expressed sample (pre-pump), a post-milk ejection pump-expressed sample (post-pump) and a post-milk ejection hand-expressed sample (post-hand). Full-length 16S rRNA gene sequencing was used to assess milk bacterial DNA profiles. Bacterial profiles did not differ significantly based on mode of expression nor timing of sample collection. No significant differences were detected in the relative abundance of any OTUs based on expression condition (pre-pump/ post-pump and post-pump/post-hand) with univariate linear mixed-effects regression analyses (all P-values > 0·01; α = 0·01). Similarly, no difference in richness was observed between sample types (number of observed OTUs: post-pump/post-hand P = 0·13; pre-pump/post-pump P = 0. 45).

CONCLUSION

Bacterial DNA profiles of HM did not differ according to either expression method or timing of sample collection.

SIGNIFICANCE AND IMPACT OF THE STUDY

Hand or pump expression can be utilized to collect samples for microbiome studies. This has implications for the design of future HM microbiome studies.

DNA extraction method influences human milk bacterial profiles

AIMS

To evaluate four DNA extraction methods to elucidate the most effective method for bacterial DNA recovery from human milk (HM).

METHODS AND RESULTS

Human milk DNA was extracted using the following methods: (i) Qiagen MagAttract Microbial DNA Isolation Kit (kit QM), (ii) Norgen Milk Bacterial DNA Isolation Kit (kit NM), (iii) Qiagen MagAttract Microbiome DNA/RNA Isolation Kit (kit MM) and (iv) TRIzol LS Reagent (method LS). The full-length 16S rRNA gene was sequenced. Kits MM and method LS were unable to extract detectable levels of DNA in 9/11 samples. Detectable levels of DNA were recovered from all samples using kits NM (mean = 0·68 ng μl^-1 ) and QM (mean = 0·55 ng μl^-1 ). For kits NM and QM, the greatest number of reads were associated with Staphylococcus epidermidis, Streptococcus vestibularis, Propionibacterium acnes, Veillonella dispar and Rothia mucilaginosa. Contamination profiles varied substantially between kits, with one bacterial species detected in negative extraction controls generated with kit QM and six with kit NM.

CONCLUSIONS

Kit QM is the most suitable of the kits tested for the extraction of bacterial DNA from human milk.

SIGNIFICANCE AND IMPACT OF THE STUDY

Choice of extraction method impacts the efficiency of bacterial DNA extraction from human milk and the resultant bacterial community profiles generated from these samples.

Characterization of the bacterial microbiome in first-pass meconium using propidium monoazide (PMA) to exclude nonviable bacterial DNA

Numerous studies have reported bacterial DNA in first-pass meconium samples, suggesting that the human gut microbiome is seeded prior to birth. However, these studies have not been able to discriminate between DNA from living bacterial cells, DNA from dead bacterial cells or cell-free DNA. Here we have used propidium monoazide (PMA) together with 16S rRNA gene sequencing to determine whether there are intact bacterial cells in the fetal gut. DNA was extracted from first-pass meconium (n = 5) and subjected to 16S rRNA gene sequencing with/without PMA treatment. All meconium samples, regardless of PMA treatment, contained detectable levels of bacterial DNA; however, treatment with PMA prior to DNA extraction decreased the DNA yield by approximately 20%. PMA-treated meconium samples did not differ significantly from untreated samples in terms of observed number of OTUs (P = 0·945); although they did differ taxonomically, with around one quarter of OTUs identified in untreated samples only, suggesting that they have originated from cell-free/nonviable DNA. The mean Sørensen coefficient for treated vs untreated samples was 0·527. Our findings suggest that the fetal gut is seeded with intact bacterial cells prior to birth. This is an important finding, as exposure to live bacteria during gestation might have a significant impact on the developing fetus. SIGNIFICANCE AND IMPACT OF THE STUDY: DNA-based microbiome studies performed using 16S rRNA gene sequencing are limited by their inability to discriminate between live bacterial cells, dead bacterial cells and cell-free DNA. Here we use propidium monoazide (PMA) to exclude nonviable bacteria from microbiome analysis of first-pass meconium samples and thereby reveal that the majority of the purported fetal gut microbiome is from intact bacterial cells. This work demonstrates the importance of excluding nonviable bacteria when analysing the microbial community in low-biomass samples such as meconium.

Re: "Amniotic fluid from healthy term pregnancies does not harbor a detectable microbial community" (2018) 6:87, https://doi.org/10.1186/s40168-018-0475-7

A recent publication by Lim et al. 2018 (Amniotic fluid from healthy term pregnancies does not harbor a detectable microbial community) strongly concluded that the microbiome of amniotic fluid primarily originates from reagent contamination. However, upon closer inspection of the methods used and data presented in this study, in particular the supplementary data, such conclusions do not appear to be supported by the results. We outline such methodological/data interpretation concerns and invite the authors to discuss these.

Identification and removal of contaminating microbial DNA from PCR reagents: impact on low-biomass microbiome analyses

Reagent-derived contamination can compromise the integrity of microbiome data, particularly in low microbial biomass samples. This contamination has recently been attributed to the 'kitome' (contamination introduced by the DNA extraction kit), prior to which attention was mostly paid to potential contamination introduced by PCR reagents. In this study, we assessed the proportion to which our DNA extraction kit and PCR master mix introduce contaminating microbial DNA to bacterial microbial profiles generated by 16S rRNA gene sequencing. Utilizing a commercial dsDNase treatment protocol to decontaminate the PCR master mix, we demonstrated that the vast majority of contaminating DNA was derived from the PCR master mix. Importantly, this contamination was almost completely eliminated using the simple dsDNase treatment, resulting in a 99% reduction in contaminating bacterial reads. We suggest that dsDNase treatment of PCR reagents should be explored as a simple and effective way of reducing contamination in low-biomass microbiome studies and producing more robust and reliable data. SIGNIFICANCE AND IMPACT OF THE STUDY: Reagent contamination with microbial DNA is a major problem in microbiome studies of low microbial biomass samples. Levels of such contaminating DNA often outweigh what is present in the sample and heavily confound subsequent data analysis. Previous studies have suggested this contamination is primarily derived from DNA extraction kits. Here, we identified the PCR master mix as the primary source of contamination, and showed that enzymatic removal of the contamination drastically reduced the blank signal and improved precision. Decontamination of PCR master mixes may have the potential to improve the sensitivity and accuracy of low-biomass microbiome studies.