The authors have declared that no competing interests exist.
Conceived and designed the experiments: LAN-R ALM NDH. Performed the experiments: LAN-R OAB MAH. Analyzed the data: LAN-R DGL. Wrote the paper: DGL LAN-R. Development of the Bioinformatics analysis plan: DGL LAN-R. Bioinformatics analysis: DGL. qPCR experimental design: DGL NDH MAH LAN-R. Design and execution of the milk fat globule processing experiments and identification of intact cells within the milk fat layer: OAB ALM NDH LAN-R. Constructive feedback on each draft of the manuscript: OAB ALM MAH NDH.
Aware of the important benefits of human milk, most U.S. women initiate breastfeeding but difficulties with milk supply lead some to quit earlier than intended. Yet, the contribution of maternal physiology to lactation difficulties remains poorly understood. Human milk fat globules, by enveloping cell contents during their secretion into milk, are a rich source of mammary cell RNA. Here, we pair this non-invasive mRNA source with RNA-sequencing to probe the milk fat layer transcriptome during three stages of lactation: colostral, transitional, and mature milk production. The resulting transcriptomes paint an exquisite portrait of human lactation. The resulting transcriptional profiles cluster not by postpartum day, but by milk Na:K ratio, indicating that women sampled during similar postpartum time frames could be at markedly different stages of gene expression. Each stage of lactation is characterized by a dynamic range (105-fold) in transcript abundances not previously observed with microarray technology. We discovered that transcripts for isoferritins and cathepsins are strikingly abundant during colostrum production, highlighting the potential importance of these proteins for neonatal health. Two transcripts, encoding β-casein (CSN2) and α-lactalbumin (LALBA), make up 45% of the total pool of mRNA in mature lactation. Genes significantly expressed across all stages of lactation are associated with making, modifying, transporting, and packaging milk proteins. Stage-specific transcripts are associated with immune defense during the colostral stage, up-regulation of the machinery needed for milk protein synthesis during the transitional stage, and the production of lipids during mature lactation. We observed strong modulation of key genes involved in lactose synthesis and insulin signaling. In particular, protein tyrosine phosphatase, receptor type, F (PTPRF) may serve as a biomarker linking insulin resistance with insufficient milk supply. This study provides the methodology and reference data set to enable future targeted research on the physiological contributors of sub-optimal lactation in humans.
Breastfeeding provides numerous benefits for both mother and infant
Research into the biology of human lactation has been seriously impeded by the impracticality and ethical concerns of obtaining systematic samples of mammary tissue from lactating woman. However, there is an intriguing workaround–human milk secreted during lactation is a rich source of mammary epithelial cell RNA. As lipid droplets exit the mammary epithelial cell, they are enveloped by cell membrane and secreted into milk as membrane-bound globules of fat. About 3–8% of human milk fat globules contain mammary epithelial cell cytoplasmic remnants, including RNA, captured during milk fat globule formation and secretion
With the advent of RNA sequencing (RNA-Seq) it is now possible to characterize the gene expression of milk-producing cells with highly sensitive detail. In contrast to microarray technology, RNA-Seq can accurately quantify both very low and very high abundance transcripts, as well as detect novel transcripts
To date, RNA-Seq of the milk fat layer has not been reported and thus the extent to which RNA-Seq offers insights into the mammary transcriptome captured from this unique source is not known. Furthermore, it is unknown if the milk fat layer yields RNA purely of mammary epithelial cell origin, or if RNA from non-mammary epithelial sources is also present in the milk fat layer obtained from colostrum, transitional, or mature human milk.
In this paper, we describe the extraction and sequencing of high-quality RNA from the human milk fat layer over three stages of milk production, demonstrating the significance of defining lactation stage based on biochemical parameters (versus postpartum day). We then characterize the RNA-Seq transcriptome responsible for the production of biochemically-defined colostrum, transitional, and mature milk in humans, including: a) demonstrating how RNA-Seq captures the broad dynamic range of gene expression within the temporal context of secretory activation and lactation; b) functional enrichments of distinct gene expression trajectories; c) differential expression of insulin signaling genes; and d) differential expression of lactose synthesis genes. We identify key candidate genes that may control rate-limiting steps during lactation and outline future work in the endeavor to discover the biological underpinnings of poor lactation performance in women attempting to breastfeed.
We isolated milk fat layer mRNA from 55 fresh milk samples over 48 collections (Protocol-I: n = 24 on day 2 of lactation, with follow-up collection from n = 12 at 4–6 weeks postpartum; and Protocol-II: n = 12 convenience collections; see
Because the milk fat layer is an unconventional extracellular source of mRNA and its membrane is more fragile than cell membranes
We explored several methods to optimize milk RNA quality (see
Under the electron microscope, milk fat globules can be observed with crescents of cytosolic components, but never nuclei
We now describe our findings from sequencing the RNA isolated from 12 milk fat layer samples (colostrum, N = 2; transitional, N = 4; mature, N = 6).
An average of 25.5 million reads per sample was mapped to the human genome (range, 14.9 to 44.7 million). Gene expression intensity was normalized to Fragments per Kilobase of transcript per Million mapped reads (FPKM) and summarized at the gene level (e.g. all alternative splice variants counted as one gene, see
Symbol | FPKM | Gene Name | Function of encoded protein | |
1 | CSN2 | 18706 | Casein, beta | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
2 | LALBA | 16905 | Lactalbumin, alpha | Major milk protein and subunit of lactose synthase; forms HAMLET, a bioactive peptide that kills infected cells |
3 | CSN1S1 | 2503 | Casein, alpha s1 | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
4 | CSN3 | 2062 | Casein, kappa | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
5 | LTF | 1615 | Lactotransferrin | Milk protein, major iron binding protein in milk, has stage-specific anti-microbial properties |
6 | FTH1 | 1330 | Ferritin, heavy polypeptide 1 | Heavy subunit of ferritin, an intracellular iron binding protein |
7 | CSN1S2AP | 1172 | Casein, alpha s2-like A | Pseudogene |
8 | LYZ | 867 | Lysozyme | Milk protein with anti-microbial activity |
9 | SPP1 | 679 | Secreted phosphoprotein 1 | Milk protein, up-regulates interferon-gamma and IL-12 |
10 | TMSB10 | 654 | Thymosin, beta 10 | Function undefined |
11 | FASN | 562 | Fatty acid synthase | Catalyzes the synthesis of long chain fatty acids |
12 | TPT1 | 445 | Tumor protein, translationally-controlled 1 | Function undefined; possible role in cell migration |
13 | CEL | 415 | Carboxyl ester lipase (Bile salt stimulated lipase) | Milk protein, digestion and absorption of lipids |
14 | FABP3 | 340 | Fatty acid binding protein 3 | Arrest of mammary epithelial cell growth and proliferation |
15 | XDH | 316 | Xanthine dehydrogenase | Oxidative metabolism of purines; essential for envelopment of milk fat globules |
16 | ACTB | 249 | Actin, beta | Mammary epithelial cell motility, structure, and integrity |
17 | CD24 | 224 | CD24 molecule | Cell surface sialoglycoprotein |
18 | EEF1A1 | 218 | Eukaryotic translation elongation factor 1, alpha 1 | Subunit of elongation factor-1 complex, translation of proteins |
19 | PIGR | 182 | Polymeric immunoglobulin receptor | Binds immunoglobulins at basolateral surface of mammary epithelial cells; complex is transported across cell and secreted into milk |
20 | CHRDL2 | 176 | Chordin-like 2 | Possible regulator of myoblast or osteoblast differentiation or maturation. Role in mammary biology unknown. |
Source:
Symbol | FPKM | Gene Name | Function of encoded protein | |
1 | LALBA | 3833 | Lactalbumin, alpha | Major milk protein and subunit of lactose synthase; forms HAMLET, a bioactive peptide that kills infected cells |
2 | CSN2 | 3833 | Casein, beta | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
3 | FTH1 | 1727 | Ferritin, heavy polypeptide 1 | Heavy subunit of ferritin, an intracellular iron binding protein |
4 | CSN1S1 | 1177 | Casein, alpha s1 | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
5 | LTF | 763 | Lactotransferrin | Milk protein, major iron binding protein in milk, has stage-specific anti-microbial properties |
6 | CSN3 | 735 | Casein, kappa | Major milk protein; source of bioactive peptides and amino acids; with other caseins, forms micelles to transport calcium |
7 | TPT1 | 603 | Tumor protein, translationally-controlled 1 | Function unknown; may play a role in maintaining genomic integrity in response to DNA-damaging agents |
8 | EEF1A1 | 517 | Eukaryotic translation elongation factor 1, alpha 1 | Subunit of elongation factor-1 complex, translation of proteins |
9 | TMSB10 | 476 | Thymosin, beta 10 | Function unknown |
10 | RPL13AP5 | 412 | Ribosomal protein L13AP5 | Ribosomal protein |
11 | FASN | 373 | Fatty acid synthase | Catalyzes the synthesis of long chain fatty acids |
12 | RPS28 | 362 | Ribosomal protein S28 | Ribosomal protein |
13 | RPL19 | 360 | Ribosomal protein L19 | Ribosomal protein |
14 | RPL7A | 353 | Ribosomal protein L7A | Ribosomal protein |
15 | RPL3 | 345 | Ribosomal protein L3 | Ribosomal protein |
16 | CSN1S2AP | 345 | Casein, alpha s2-like A | Pseudogene |
17 | RPL41 | 322 | Ribosomal protein L41 | Ribosomal protein |
18 | EEF2 | 315 | Eukaryotic translation elongation factor 2 | Subunit of elongation factor-2 complex, translation of proteins |
19 | RPS2 | 314 | Ribosomal protein S2 | Ribosomal protein |
20 | RPLP1 | 308 | Ribosomal protein LP1 | Ribosomal protein |
Source:
Symbol | FPKM | Gene Name | Function of encoded protein | |
1 | FTL | 2512 | Ferritin, light polypeptide | Light subunit of ferritin, an intracellular iron binding protein |
2 | CTSD | 1090 | Cathepsin D | Lysosomal aspartyl protease; may assist digestion of milk proteins |
3 | FTH1 | 902 | Ferritin, heavy polypeptide 1 | Heavy subunit of ferritin, an intracellular iron binding protein |
4 | CD74 | 705 | CD74 molecule, major histocompatibility complex, class II invariant chain | Regulates antigen presentation for immune response; cell surface receptor for the cytokine macrophage migration inhibitory factor (MIF) which controls survival pathways and cell proliferation |
5 | APOE | 591 | Apolipoprotein E | Essential for the normal catabolism of triglyceride-rich lipoprotein constituents; also interacts with many immunological processes |
6 | PSAP | 585 | Prosaposin | A glycoprotein precursor for 4 cleavage products: saposins A, B, C, and D, which facilitate the catabolism of glycosphingolipids with short oligosaccharide groups |
7 | B2M | 485 | Beta-2-microglobulin | Serum protein found in association with the major histocompatibility complex class I heavy chain on the surface of nearly all nucleated cells |
8 | LALBA | 434 | Lactalbumin, alpha | Major milk protein and subunit of lactose synthase; forms HAMLET, a peptide that kills infected cells |
9 | CSN2 | 393 | Casein, beta | Major milk protein; source of bioactive peptides and amino acids. With other caseins, forms micelle to transport calcium. |
10 | TMSB10 | 357 | Thymosin, beta 10 | Function unknown |
11 | ACTB | 333 | Actin, beta | Mammary epithelial cell motility, structure, and integrity |
12 | IFI30 | 309 | Interferon, gamma-inducible protein 30 | Expressed constitutively in antigen-presenting cells and induced by gamma-interferon in other cell types |
13 | CTSB | 299 | Cathepsin B | Lysosomal cysteine proteinase; an amyloid precursor protein secretase; involved in the proteolytic processing of amyloid precursor protein; may assist digestion of milk proteins |
14 | VIM | 245 | Vimentin | A member of the intermediate filament family; highly expressed in fibroblasts |
15 | CD68 | 206 | CD68 molecule | Transmembrane glycoprotein that is highly expressed by human monocytes and tissue macrophages |
16 | APOC1 | 201 | Apolipoprotein C1 | Expressed primarily in the liver; activated when monocytes differentiate into macrophages |
17 | TPT1 | 182 | Tumor protein, translationally-controlled 1 | Function unknown; may play a role in maintaining genomic integrity in response to DNA-damaging agents |
18 | LYZ | 182 | Lysozyme | Milk protein with anti-microbial activity |
19 | GPNMB | 178 | Glycoprotein nmb | A type I transmembrane glycoprotein; may be involved in growth delay and reduction of metastatic potential |
20 | EEF1A1 | 177 | Eukaryotic translation elongation factor 1, alpha 1 | Subunit of elongation factor-1 complex; translation of proteins |
Source:
RNA sequencing results are highly correlated with qPCR (see final results paragraph,
Stunningly, 45% of the milk fat layer mRNA during mature lactation represent just two milk protein genes: CSN2 and LALBA (
Each pie slice represents the proportion of the total mRNA pool attributed to expression of the labeled gene. The pie slice representing the most abundant transcript occurs at the 3′o-clock position with subsequent transcripts presented counter-clockwise in decreasing order of abundance; mRNAs from the most abundant human milk proteins–CSN2 and LALBA–are ranked highest, consistent with known mammary gland biology.
Given that a few abundant transcripts dominate the milk fat layer transcriptome during mature lactation, we suspected that microarray technology, in which high abundance transcripts saturate the signal, would be particularly handicapped in this biological context. Therefore, we compared our gene expression results with a supplemental data set representing the most highly expressed genes in a previous microarray study of the mature milk fat layer
Compared to mature lactation, the milk fat layer transcriptome during the transitional stage (
Each pie slice represents the proportion of the total mRNA pool attributed to expression of the labeled gene during transitional lactation. For direct comparison to
Each pie slice represents the proportion of the total mRNA pool attributed to expression of the labeled gene during the colostral stage. For direct comparison to
In contrast to mature lactation, the milk fat layer transcriptome during the colostral stage is predominated by transcripts for non-nutritive proteins–that is, proteins with a primary role
The specific roles of isoferritins in neonatal health remain unclear, but here we suggest two possibilities. In other biological contexts, ferritin primarily functions as an iron-storage molecule; however, colostrum ferritin appears to have little iron associated with it
To summarize, examination of the top genes expressed in our colostrum milk fat layer transcriptomes suggests that ferritins and digestive enzymes may be important components of newborn health
The most abundant transcripts in mature milk (
In all lactation stages, highly expressed genes are involved in mRNA translation; protein localization and transport within the cell; endocytosis; mRNA processing; protein modification; ATP biosynthesis; vesicle coating, targeting and budding; and the regulation of apoptosis. In other words, mammary genes are coordinately expressed to make, modify, package, and transport milk proteins; and to generate the ATP required for this massive protein factory.
While all stages of lactation are associated with protein synthesis, some biological functions are uniquely enriched within a specific lactation stage. During the colostral stage, highly expressed genes are uniquely enriched for immune-related function, particularly “leukocyte activation.” In transitional and mature samples, highly expressed genes are associated with the inhibition of protein ubiquitination (i.e., protects proteins from degradation) and with hormone receptor binding and signaling (i.e., response to milk producing hormones). Further, lipid and lipid cofactor biosynthesis are uniquely enriched in mature samples. Consistent with our expectations, these results suggest that immune defense is a hallmark of the colostral stage, massive development of the protein synthesis infrastructure and inhibition of protein degradation is a hallmark of the transitional stage, and massive synthesis of lipids is a hallmark of the mature stage (
During all stages of lactation, protein synthesis is a significant biological function of highly expressed genes. Immune defense is a hallmark of the colostral stage. The development of the protein synthesis infrastructure and inhibition of protein degradation begins during the transitional stage. Massive lipid synthesis is a hallmark of the mature stage.
Clustering analysis produced a dendogram in which lactation stage, as biochemically defined by Na:K ratio, emerges as the greatest overall difference in transcriptomes across samples (see
To test whether there was an effect of lactation stage on the expression of individual genes, we probed for differentially expressed genes using DESeq (see
Columns are clustered by sample and rows are clustered by gene. Dendogram height indicates distances between clusters in gene expression profiles. The heat map illustrates lower (white/yellow) to higher (orange/red) gene expression levels with distinct transcriptional profiles across lactation stages. Blue bars at the top of each column indicate lactation stage: dark blue = colostral; blue = transitional; and light blue = mature. From left to right, starting with ID 187, postpartum timing of sample collections are 41, 52, 52, 39, 56, and 49 hours; and 130, 33, 35, 40, 24, and 45 days. Similarly, starting with ID 187, Na:K ratios are 9.6, 5.5, 0.71, 0.70, 0.98, 1.15, 0.19, 0.30, 0.57, 0.41, 0.33, and 0.45.
The heat map illustrates that not all genes are steadily increased or decreased in the progression from colostrum to mature lactation. Therefore, we conducted a clustering analysis of all expressed genes to determine the primary gene expression trajectories. We systematically repeated the clustering analysis with increasing numbers of clusters to identify the minimally redundant set with the most clusters (see
As expected, genes associated with “cell cycle” (
The remaining clusters are more novel. N-glycan biosynthesis and sphingolipid metabolism are coordinately increased during colostral and mature stages relative to transitional (
The distinctly different clusters shown in
Finally,
In bovine and rodent models, insulin has recently been shown to play a central role in milk protein synthesis
Progressing from colostral to transitional lactation, among the 69 gene/gene family nodes represented on the KEGG insulin signaling pathway, 30 were up-regulated, 14 were down-regulated, and an additional 20 were robustly expressed (FPKM >0.5) but not significantly changed between colostral and transitional lactation (
Using a murine model, Berlato and Doppler
Further progressing from transitional to mature lactation, 5 gene/gene family nodes in the insulin signaling pathway were upregulated, 5 were downregulated, and an additional 49 were robustly expressed (FPKM >0.5), but not significantly changed between transitional and mature lactation (
Referring back to the heat map shown in
The rate of lactose synthesis is a key driver of milk production; however, “lactose synthesis” is not an annotated pathway. We manually constructed this pathway and overlaid our gene expression results (
The rate of lactose synthesis is an important driver of milk production level.
The most up-regulated and expressed gene in the lactose synthesis pathway is LALBA, increasing 10.2-fold from colostral to transitional lactation and 6.1-fold from transitional to mature lactation. This is to be expected given that in addition to being a member of the enzyme complex involved in the final step of lactose synthesis, LALBA is also the predominant whey protein in human milk.
Glucose is an important fuel source for the synthesis of lactose. The solute carrier family 2A genes (SLC2A, GLUT protein family) are involved in glucose (and other solute) transport across cell membranes. We detected expression of several SLC2A genes in the milk fat layer of mature samples (SLC2A1, 4, 5, 6, 8, 9, 10, 11, and 13). SLC2A1 is thought to be the primary route for glucose entry into the lactocyte across species based on reports from rodent and bovine studies
There are two potential sources of UDP-Galactose in the mammary epithelial Golgi, either through the uptake and metabolism of D-Galactose or D-Glucose. Our results show that both pathways are up-regulated between colostral and transitional stages. However, the more predominant route appears to originate with D-Glucose, as the enzymes unique to this pathway are up-regulated 5.9-fold (PGM1) and 8.2-fold (UGP2). In contrast, GALK1 is up-regulated 3.3-fold.
Similar to what we observed for the insulin signaling pathway, the strong up-regulation of the lactose synthesis pathway observed between colostral and transitional lactation stages is attenuated between transitional and mature lactation stages. Gene expression for the enzymes central to the synthesis of UDP-Glucose from D-Glucose (PGM1, UGP2, and NME2) are down-regulated, with only PGM1 attaining statistical significance (0.58 fold-change, mature vs. transitional,
To confirm our RNA-Seq findings using a different assay, we probed the following genes of interest in 4 samples from mature lactation using qPCR: the major milk protein genes (LALBA, CSN2), the gene most abundant in the mature milk fat layer transcriptome using microarray technology (CSN3, from Maningat et al.
Data derived from average of 4 milk fat layer samples obtained during mature lactation. Results are plotted on a log scale for both axes. X-axis: qPCR ΔCt (target gene, cycle threshold - geometric mean of endogenous genes, cycle threshold); Y-axis: RNA-seq FPKM (target gene FPKM/geometric mean of endogenous genes FPKM). Endogenous genes selected: ACTB, RPS18, SSH3. Correlation of gene expression measured by qPCR versus RNA-seq, R2 = 0.98,
Non-invasive sampling of the transcriptome of milk-producing cells via RNA secreted into human milk provides a powerful window into the biology of human lactation. In this paper, we explored several methodological issues in using human milk fat layer RNA for this purpose. We found that: a) lactation stage must be defined biochemically (such as Na:K ratio), not by day of lactation, b) lactation stage influences RNA quality, quantity, and potential immune cell contamination, c) immediate processing and hard, fast centrifugation yield better quality RNA, and d) additional washing of the milk fat layer is not necessary for the analysis of mature milk samples and does not decrease immune cell contamination in colostrum samples. We also found that RNA sequencing yields superior results compared to microarray experiments.
Our RNA-Seq results paint the most vivid portrait to date of the transcriptome responsible for human milk production. Strikingly, transcripts of β-casein and α-lactalbumin genes make up 45% of the total pool of mRNA during mature lactation. Consistent with known physiology, genes expressed during lactation are associated with making, modifying, transporting, and packaging these highly abundant milk proteins. Lactation-stage specific transcripts are associated with immune defense during the colostral stage, the up-regulation of massive milk protein synthesis during the transitional stage, and the full-scale production lipids and other factors during the mature stage of lactation. Furthermore, fundamentally different regulatory mechanisms appear to control milk production during the different stages of lactation. First, genes whose products participate in transcription and translation are differentially regulated across all three stages. Second, we see dramatic changes in the transcriptome even after the onset of copious milk production (e.g., transitional versus mature stage). Future experiments, utilizing the methods outlined in this paper, are needed to determine the comprehensive acute, long-term, local, and systemic mechanisms by which women produce milk in response to infant feeding patterns. For example, the effect of early milking frequency on “programming” milk production capacity has been explored in bovine models
Correlates of impaired insulin and glucose metabolism have recently been reported to be associated with poor lactation performance in women
In summary, we have presented the essential methodology, reference data set, and preliminary results derived from the RNA-Seq analysis of the human milk fat layer transcriptome across three stages of lactation. Our findings set the stage for future research on the biological contributors to poor lactation performance in women.
Fresh milk was collected from participants enrolled in one of two research protocols.
All participants provided written informed consent.
Participants were enrolled at a Cincinnati-area maternity hospital during their postpartum stay. On each recruiting morning (24 days between June 9– September 9, 2011), a maternity nurse identified mothers who were between 36–60 hours postpartum. Proceeding from a randomly ordered list, the nurse explained the study and screened mothers for the following eligibility criteria: English-speaking, currently breastfeeding, aged >18 years, without history of major breast surgery, healthy singleton infant, and telephone access for follow-up contact. Upon obtaining written informed consent, the nurse administered a breastfeeding assessment and then guided the study participant in collecting 2.5 mL of milk from each breast by mechanical breast expression using a sterile collection shield and container (
At 4–6 weeks postpartum, Protocol-I participants who were still lactating and not pregnant were asked to provide a follow-up milk sample during a morning visit to the Cincinnati Children’s Hospital Clinical Research Center. A 10 mL aliquot of fresh milk (
Women were recruited through posted announcements. After written informed consent, these participants provided a single, 10 mL aliquot of freshly expressed milk (
Fresh milk was aliquoted into three 2.0 mL tubes and spun in an Eppendorf MicroCentrifuge 5417R. After centrifugation of fresh milk, fat globule-enveloped mammary epithelial cell RNA will reside in the fat layer at the top of the tube and–presumably–extraneous RNA from intact cells (leukocytes, sloughed epithelial cells and stem cells) will reside in the cell pellet at the bottom of the tube, effectively separating the two sources of RNA
We followed the method described by Maningat
After a hard spin (15,000 g at 4°C), the milk fat layers were processed as in the soft spin protocol, above. The hard spin did not reduce RNA quality (see RNA isolation section, below), but it also did not reduce infiltration of the fat layer with intact cells, which were evident to the same degree as after a soft spin (not shown). We then proceeded to a milk fat washing protocol.
In this phase, milk fat layers were washed as follows. After a hard spin at a warmer temperature, (15,000 g at 12°C) the milk fat layers were transferred to a clean set of 3 tubes and re-suspended in 1 mL PBS+10 µM EDTA. After centrifuging again (15,000 g at 12°C), the milk fat layers from all 3 tubes were transferred to a single tube, re-suspended in 1 mL PBS, and centrifuged a final time (15,000 g at 12°C). The remaining milk fat layer was transferred into a single new tube to which 500 µL TRIzol® was added and stored at −80°C.
Under Zeiss florescent microscope, the washed method appeared to reduce the number of intact cells in colostrum samples and eliminate them from mature samples, but to definitively determine if washing was beneficial in removing infiltration of intact cell RNA, we sequenced both hard and washed milk fat samples. As part of this approach, some milk samples were split so that an aliquot was processed using the hard method and another using the washed method. We conducted both a targeted comparison of gene expression for immune cell markers (such as CD45, a cell surface marker unique to immune cells) and a global examination of differential gene expression by washing method.
Milk sodium concentration is a marker of tight junction closure between mammary epithelial cells; with the onset of secretory activation (stage II lactogenesis) milk sodium concentrations decrease sharply as potassium concentrations increase
Among the subset of participants in Protocol-I who agreed to a follow up visit at 4–6 weeks postpartum, we conducted an oral glucose tolerance test at the time of collecting a follow up milk sample. For this, participants arrived at our clinical research center after an 8–10 hour fast. We obtained blood samples at 0, 30, 60, 90 and 120 minutes after the participant consumed a standard 75 g glucose beverage. The samples were assayed for serum glucose (glucose oxidase method) and insulin (electro-chemi-luminescence immunoassay) concentrations at the Biochemistry Core Lab at Cincinnati Children’s Hospital. The results were used to calculate maternal insulin sensitivity (ISOGTT)
For all lipid samples we extracted and purified total RNA in batches of 16 using the PROMEGA Maxwell 16™ integrated system (Promega Corporation, Madison, WI). We assayed a 2 µL aliquot for RNA concentration, purity (rRNA 28 s∶18 s ratio), and quality (RNA Integrity Number (RIN)) using the Agilent 2100 Bioanalyzer (Santa Clara, CA).
We initially selected 16 purified RNA samples for paired-end sequencing based on these priorities: RIN ≥7.0 and RNA ≥10.0 ng/uL; paired samples across time points (Day 2 and mature) and split between washed and unwashed. In the Day 2 samples, sodium and potassium concentrations ranged between 6.2–90.9 mmol/L and 9.5–20.5 mmol/L, respectively; and Na:K ratio ranged between 0.42 (greater tight junction closure between mammary epithelial cells) to 9.62 (less tight junction closure). Only three Day 2 samples categorized as colostral stage were suitable for sequencing (RIN ≥7.0 and RNA >9.0 ng/uL) and all three were selected.
All gene expression results subsequent to washing protocol comparisons are based on a final set of 12 sequenced samples (N = 2 colostral, N = 4 transitional, and N = 6 mature) remaining after the exclusion of the unwashed partner in the split pairs (n = 1 colostral, n = 2 mature) and the exclusion of 1 transitional sample from a mastitic participant (ID = 158).
From the samples we selected for sequencing, the Gene Discovery core facility at Cincinnati Children’s Hospital prepared RNA-Seq libraries using the Illumina TruSeq RNA kit (Illumina, Inc., San Diego, CA) and performed sequencing on an Illumina HiSeq2000 with version 3 chemistry. Libraries were multiplexed in batches of 12 to ensure a minimum of 20 million 100 bp paired-end reads per sample. FASTQ files were de-multiplexed to assign reads to the originating sample. The data has been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE45669 (
Reads were mapped to the human genome assembly hg19 using TopHat
To facilitate other types of analyses, counts for each hg19 Ensembl gene were calculated by applying HTSeq-count (
To conduct clustering analyses, an R package, DESeq
To determine differentially expressed genes, DESeq’s nbinom test function was used to test the significance of the differences between the base means of the two conditions (e.g.,washed vs unwashed, colostral vs transitional, etc.). Differences with
We determined biological functions of gene sets of interest using the Functional Annotation Clustering tool within DAVID Bioinformatics Resources 6.7
We confirmed the RNA-Seq results for genes of interest with TaqMan qPCR. Total RNA from four mature milk fat fractions were synthesized into cDNA using the SuperScript® III First-strand Synthesis SuperMix (Invitrogen, Carlsbad, CA) according to manufacturer’s instructions. Samples were then ethanol precipitated to enhance purity of DNA. Genes of interest (n = 15) were validated using qPCR with Custom TaqMan® Array Plates in a 96-well format (Applied Biosystems, Carlsbad, CA). Details on the primer probes sets for these genes are provided in
Following the approach of Bionaz and Loor
To compare RNA-Seq results with qPCR for each gene of interest, RNASeq FPKM values were normalized to the FPKM geometric mean of the endogenous gene set (SSH3, ACTB, RPS18). We then determined the Pearson linear correlation coefficient (on a log scale) between the normalized qPCR-Ct and FPKM means across the 15 genes of interest. In this analysis, each gene is an observation, with two variables per gene: qPCR-Ct and FPKM. The values for these two variables, per observation, are the (log) normalized qPCR-Ct and FPKM means of the 4 individual samples.
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We would like to thank the mothers who donated their milk. We also thank Charla Payne, Beth VonLuehrte, Jeanne Kleiman, Erin Wagner and Anne Minter for sample collection; Barbara Davidson for staff supervision; Diana Taft for contributing to our initial identification of RNA and intact cells in the milk fat layer; Lawrence Dolan for supervising the oral glucose tolerance testing, Amy Lefevers, and Myra Johnson for sample processing; Donna Wuest for administrative support; David Newburg, Mike Burhans, Jeffrey Whitsett, and Susan Wert for technical insights; and the CCHMC Gene Discovery Core for RNA sequencing services.