This month’s issue features mammary cells, antibodies in human milk, and the Milk Composition Database.

The Fifteen Lives of Mammary Cells Mammary cells are highly dynamic during the lactation cycle (the period before pregnancy to after weaning).

New technology measured activities of thousands of genes in tens of thousands of individual mammary epithelial cells during the lactation cycle to discover new cell types.

Fifteen types of mammary epithelial cells were identified.

New insights were gained into the origins of cells contributing to the lactation cycle, mammary tissue “memory” of the first lactation cycle, and breast cancer.

How do mammary cells change and gain the ability to make milk at each birth? Scientists, at present, only have

fragmentary information and little detail about the hierarchy of mammary cells contributing to the lactation cycle

beginning at each pregnancy. A cellular hierarchy is like a family tree. It shows the relationships between different

types of cells i.e., who begat whom. Knowledge of cellular

hierarchies in mammary tissue could help answer many difficult questions. Which cells (progenitor cells) give rise to

the cells that make milk or cells that form part of the mammary tissue structure supporting lactation? How do

mammary epithelial cells cease producing milk after weaning? Which mammary cells develop into breast cancer

and why? Recently, a group of investigators produced a massive molecular resource that may help answer these and many other questions relating to mammary

tissue function [1]. Importantly, the investigators made the resource available to all scientists to maximize

its potential for additional discoveries.

The Scientific Challenge

Milk is exquisitely tailored to suit a newborn offspring’s rapid growth and developmental requirements

while also protecting it from microbial infections. Thus, milk provides newborn offspring with an enormous head-start in life until they reach the stage when they can feed themselves. The challenge for scientists is

to better understand how a mother’s mammary tissue is prepared during pregnancy for lactation after birth, and then how lactation is turned off after weaning of offspring, with the whole lactation cycle

beginning again at the next pregnancy. There are also important practical reasons why scientists want to

better understand the regulation of mammary tissue functions. This knowledge is crucial for improving the efficiency of milk production in dairy cows, and it may also lead to new ways to treat human breast

cancer.

Mammary Tissue is Unlike Other Tissues

Mammary tissue is very different from other tissues, just ask any mother. The mammary tissue of an

adult female undergoes amazing cellular changes during pregnancy, lactation, and weaning. This cycle of cellular changes means that mammary tissue has unusually rapid cell turnover (high rates of cell death

and new cells formed), which is repeated at each pregnancy. Many of these cellular changes are triggered

by hormonal changes during pregnancy and after birth. The highly dynamic cellular state in mammary tissue during the lactation cycle contrasts with most other tissues, like liver, brain, and muscle, which

simply focus on the maintenance of cells contributing to a fully developed and relatively constant physiological function. Also, unlike most other tissues, mammary tissue develops its primary function, the

SPLASH! ® milk science update August 2019 Issue

potential for lactation, after puberty. This timing is relatively late in the developmental programs that underpin the physiology of most tissues. Somewhat mysteriously, a mother’s mammary tissue becomes

more efficient at producing milk after the first pregnancy and lactation cycle [2, 3]. How does this occur?

Dynamic Cellular Changes in Mammary Tissue

Current knowledge of cellular changes occurring in mammary tissue during the lactation cycle was initially

gained by microscopic examination of the stained tissue about 50 years ago. This approach gave a low-resolution view of the cellular dynamics occurring during the lactation cycle, which involves changes in

mammary epithelial cells, blood cells, immune cells, and fat cells [4]. These cells work together to change

mammary tissue during the lactation cycle. Epithelial cells line the surfaces of milk ducts that drain sac-like alveoli in mammary tissue, and are the cells that produce milk. Scientists at the beginning of the new

millennium then discovered specific proteins present on or within mammary tissue cells that could be used as markers of different types of cells [5-7]. The early cell markers are equivalent to the logos on different

cars that, for example, identify a Ford, Alfa Romeo, or Toyota but not a specific model. Subsequently, additional cell markers were used to identify subsets of mammary epithelial cells, many of which also

underwent dramatic changes in the lactation cycle [5, 8]. Mammary epithelial cells sometimes transform into continuously growing cells that form a tumor through processes that are unclear but may involve

deregulated cellular progenitors of mammary epithelial cells [5, 9].

Some cell markers identified progenitor cells of mammary epithelial cells [5, 8]. The role of a progenitor

cell is to provide cell replacements in a tissue and thereby maintain or change a tissue’s physiological functions. A progenitor cell is a little like a stem cell, but unlike a stem cell, it does not indefinitely replace

itself. It can also only generate a limited range of other cell types. A mammary progenitor cell in the right circumstances can change (differentiate) into a specific subtype of mammary epithelial cell. Cell markers

identifying progenitor cells can also be used by scientists to map cell hierarchies, which are fundamental for understanding the cellular changes in the lactation cycle and the origins of breast cancer cells [5-7].

However, scientific progress in this area of research over the last decade became slower and more

difficult. There could be additional subtypes of cells lurking unidentified in mammary tissue because scientists do not have simple and specific markers for these cells. It’s hard to find something if you don’t

know it exists! There must be a better way.

A Cellular Fingerprint of Gene Activities

Recently, a group of investigators based at the University of Cambridge and the nearby Wellcome Sanger

Institute in the United Kingdom took a very different approach to characterize the different types of cells in mammary tissue during the mouse lactation cycle [1]. The investigators exploited the mouse model of

lactation, as it has become very useful for deciphering the complexities of cell hierarchies and the

identification of progenitor cells in other tissues. Instead of relying on cell markers for cell-type identification, the investigators inferred cell types based on the activities of thousands of genes within

each of about 23,000 mammary epithelial cells isolated from mammary tissue. The technology used by the investigators strikingly picked up pace about three years ago when the ability to efficiently isolate

individual cells was combined with very high throughput measurement of gene activities from individual cells. Gene activity is the ability of each gene to produce a messenger RNA molecule (mRNA), which

carries a unique blueprint used by the cell to synthesize a specific protein. Different cell types produce different quantities of common mRNAs as well as some unique mRNAs. Thus, the profile of thousands of

mRNAs within a cell acts like a fingerprint that provides a very accurate means of identifying similar or

different cell types. The mammary tissue samples were collected by the investigators before first pregnancy, at mid-pregnancy, at peak lactation, and after weaning. The investigators isolated individual

epithelial cells from each tissue sample and then determined their mRNA profiles.

Fifteen “Clusters” of Mammary Epithelial Cells

Bach and colleagues produced a huge amount of data using the new single-cell RNA sequencing

technology to generate mRNA profiles for tens of thousands of mammary cells [1]. The investigators’ analysis of the data was very informative. They identified 15 “clusters” of epithelial cells involved in the

lactation cycle using the mRNA profiles. The “clusters” are equivalent to different functional types of

epithelial cells. Bach and colleagues noted that few of the “clusters” corresponded with a unique cell marker [1]. This conclusion highlighted the coarse nature of previous studies using cell markers and the

much greater cell-resolving power used in the current analysis. Bach and colleagues concluded that combinations of some of the “clusters” identified epithelial cells with well-known functions, thereby

providing strong proof that the research strategy had worked well. The investigators also inferred hierarchical relationships between different epithelial cell “clusters” across the lactation cycle i.e., they

inferred which cells were progenitors of other cell types. This result was a particularly useful discovery.

Bach and colleagues’ major conclusion was that instead of the presence of discrete types of epithelial cells

in mammary tissue, their data suggested a continuous spectrum of mammary epithelial cells at varying

stages of development during the lactation cycle [1]. They also concluded that a single progenitor cell type

was responsible for the generation of the epithelial cells lining mammary tissue ducts (lumina).

Implications for Breast Cancer

Epidemiologists report that breast cancer is a leading cause of cancer deaths in women especially in many Western countries [10]. It is not a single disease, as it is heterogeneous, and this challenges the

effectiveness of current therapies [11]. Many scientists suggest that breast cancer occurs when the regulatory system for controlling normal mammary epithelial cell development, growth, and hormone

responsiveness goes askew [5, 9, 12]. Thus, mammary tissue function and breast cancer development are

intimately intertwined.

Bach and colleagues also demonstrated that the first lactation cycle caused lasting changes in the mRNA profiles of epithelial cells in the mammary lumina [1]. The investigators stated that this result was

“especially interesting” as pregnancy and breastfeeding have protective effects against breast cancer [13, 14], and the mammary luminal epithelial cells were likely derived from a single type of epithelial

progenitor cell. Bach and colleagues concluded that “luminal progenitor cells maintain a memory of gestation and lactation.” They implied that a better understanding of the molecular basis of this progenitor

cell “memory” could be very informative for the discovery of new therapies for the treatment of breast

cancer [1]. The “memory” also may be an explanation for why more milk is produced after the first birth and first lactation cycle in most mammals. Importantly, the powerful single-cell mRNA profiling technique

used by Bach and colleagues [1] is also being used by other scientists to directly unravel cell hierarchies associated with the origins of human breast cancer [9, 12]. In the future, perhaps these large-scale

studies will intersect and generate additional ideas that ultimately lead to better outcomes for women with

breast cancer.

1. Bach K, Pensa S, Grzelak M, Hadfield J, Adams DJ, Marioni JC, et al. Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing. Nat Commun. 2017;8(1):2128. 2. Lee JY, Kim IH. Advancing parity is associated with high milk production at the cost of body condition and increased periparturient disorders in dairy herds. J Vet Sci. 2006;7(2):161-166. 3. Hackman NM, Schaefer EW, Beiler JS, Rose CM, Paul IM. Breastfeeding outcome comparison by parity. Breastfeed Med. 2015;10(3):156-162. 4. Sordillo LM, Nickerson SC. Morphologic changes in the bovine mammary gland during involution and lactogenesis. Am J Vet Res. 1988;49(7):1112-1120. 5. Oakes SR, Gallego-Ortega D, Ormandy CJ. The mammary cellular hierarchy and breast cancer. Cell Mol Life Sci. 2014;71(22):4301-4324. 6. Stingl J, Raouf A, Eirew P, Eaves CJ. Deciphering the mammary epithelial cell hierarchy. Cell Cycle. 2006;5(14):1519-1522. 7. Visvader JE. Keeping abreast of the mammary epithelial hierarchy and breast tumorigenesis. Genes Dev. 2009;23(22):2563-2577. 8. Perruchot MH, Arévalo-Turrubiarte M, Dufreneix F, Finot L, Lollivier V, Chanat E, et al. Mammary epithelial cell hierarchy in the dairy cow throughout lactation. Stem Cells Dev. 2016;25(19):1407-1418. 9. Valdes-Mora F, Handler K, Law AMK, Salomon R, Oakes SR, Ormandy CJ, et al. Single-cell transcriptomics in cancer immunobiology: the future of precision oncology. Front Immunol. 2018;9:2582. 10. Torre LA, Islami F, Siegel RL, Ward EM, Jemal A. Global cancer in women: burden and trends. Cancer Epidemiol Biomarkers Prev. 2017;26(4):444-457. 11. Beca F, Polyak K. Intratumor heterogeneity in breast cancer. Adv Exp Med Biol. 2016;882:169-189. 12. Valdes-Mora F, Salomon R, Gloss B, Law A, Murphy K, Roden D, et al. Single-cell RNAseq uncovers involution mimicry as an aberrant development pathway during breast cancer metastasis. bioRxiv. 2019; Jan 1:624890. 13. Opdahl S, Alsaker MD, Janszky I, Romundstad PR, Vatten LJ. Joint effects of nulliparity and other breast cancer risk factors. Br J Cancer. 2011;105(5):731-736. 14. Fortner RT, Sisti J, Chai B, Collins LC, Rosner B, Hankinson SE, et al. Parity, breastfeeding, and breast cancer risk by hormone receptor status and molecular phenotype: results from the Nurses' Health Studies. Breast Cancer Res. 2019;21(1):40.

Contributed by Dr. Ross Tellam (AM) Research Scientist Brisbane, Australia

Comprehensive Cow Milk Metabolite Database Now Online

A team of Canadian researchers combined several laboratory metabolic profiling techniques with computer text-mining software to compile the most comprehensive list of cow milk metabolites to date.

The Milk Composition Database is a publicly available, online database containing over 2,000 different metabolite entries, of which nearly half are lipid molecules.

The creation of a centralized, open access database promotes collaborative research on, and consumer awareness of, cow milk metabolites.

Some recipes are meant to be top secret—Colonel Sanders’ fried chicken; Big Mac’s special sauce; your

great aunt Ingrid’s sherry cake. But the ingredients in cow milk shouldn’t be private and confidential. The advent of targeted metabolomics approaches, which characterize large numbers of small molecules in

milk, offers the opportunity to produce a detailed and comprehensive picture of cow milk’s chemical composition. And yet, many studies employing these new techniques have not publicly reported their

findings, or report the components they have found but not their concentrations [1]. Rather than having scientists continuing to re-invent the analytical milk wheel, a team of Canadian researchers has just

published a “centralized, comprehensive, and electronically accessible database” of all detectable

metabolites in cow milk [1]. We may never know what Colonel Sanders uses to season his fried chicken

batter, but the (detectable) chemicals that make up cow milk—all 2,355 of them—are now on the record.

Filling the Database

Wouldn’t it be amazing to be able to simply pour a glass of milk into a machine and moments later have that machine spit out a piece of paper listing all of milk’s ingredients (and their relative concentrations)? Technically, such a magical machine does exist, but it only measures total macronutrients (e.g., total

protein, total fat), components that are already pretty well established for cow milk. To determine the specific types of amino acids that make up that total protein or specific fatty acids that contribute to the

total lipids requires much more complicated analytical techniques.

One of the goals of this major research undertaking was

establishing which specific techniques would yield the most detailed results. The team used four different metabolic

profiling methods: Nuclear magnetic resonance (NMR) spectroscopy; liquid chromatography high-resolution mass

spectrometry (LC–HRMS); liquid chromatography mass spectrometry (LC–MS/MS); and inductively coupled plasma

mass spectrometry (ICP–MS). Rather than lose sensitivity by trying to make one method work for all milk metabolites,

the team maximized the amount of data they were able to

retrieve by optimizing each method for a specific set of metabolites. For example, NMR is good for water-soluble

compounds that are abundant in a biological sample, whereas ICP–MS was utilized because it targets metal ions [1]. But all in, LC–HRMS was determined to be

the preferred analytical method because of its broad coverage (bonus points for not needing a large

sample, being relatively inexpensive, and being largely automated!)[1].

In addition to generating their own data, the team utilized computer-aided text mining to add in

metabolites that other researchers had previously identified [1]. Utilizing software programs developed for

the Human Metabolome Project, the team searched for publications that had particular key words of interest grouped together (for example, pulling up abstracts for all papers that have milk, dairy, bovine,

concentration, and identification). This approach identified nearly 150 papers, abstracts, or books with relevant information. Then came the tedious task of taking all of the information from these articles on

milk metabolites and entering it into the database; this required not only the time of manually inputting the information but several rounds of double-checking the details by experts in biochemistry, physiology,

and animal science [1].

Combining the data from the four different analytical methods with the results of the computer text

mining yielded 2,355 unique metabolic structures. Triglycerides made up almost half of the 2,355 metabolites, some of which were identified for the first time. The dominant ingredients were

carbohydrates (like lactose), inorganic ions (like calcium and potassium), organic acids (like citrate), and amine-containing compounds (like creatinine and choline). Consumers may be more interested in the least

abundant compounds, however. These include vitamin D3 and vitamin D2 (hence the vitamin D fortification program) and antimicrobial agents such as tetracycline and penicillin G. The latter are exogenous, present

in milk if a dairy cow was given antibiotics for infection and the milk withdrawal period was insufficient.

Their concentrations are very low (fractions of a micromole), but nevertheless, they are counted alongside

the other metabolites as part of cow milk’s chemical composition.

Accessing the Database

Dying to see the complete list of metabolites that Foroutan et al. [1] detected? You are in luck! The Milk Composition Database (MCDB) is available for dairy researchers, dairy farmers, nutritionists, milk drinkers, and all other interested parties at www.mcdb.ca. The website has a complete list of all detected

chemicals, including their structure and reference spectra. If the structures were identified via computer text mining, rather than detected and quantified directly by Foroutan et al. [1], the listing provides the

reference so you can go straight to the source to learn more.

The database started with 2,355 detectable unique metabolic structures (representing 972 metabolite

species), of which 1,285 structures (168 metabolite species), or roughly 60% of reported data, were identified by Foroutan et al. for the first time [1]. The hope is that this number will continue to grow as

analytical techniques improve. Indeed, Foroutan et al. already have plans to get back to the lab to employ a handful of different experimental methods with the hopes of adding rows to their already gigantic

spreadsheet [1].

It should be emphasized that despite this impressively high number of identified structures, the MCDB is not by any means an exhaustive list of all of the components that are in cow’s milk, just those that qualify

as metabolites. For example, the most abundant proteins in cow’s milk are not in this database, which

would have been more appropriately named the “Bovine Milk Metabolite Database.”

Nevertheless, centralized and publicly available databases like the MCDB are science research at its best, offering the chance to collaborate across laboratories, disciplines, and international borders. As milk

research moves away from quantification of macronutrients to more detailed and comprehensive methods of analysis, and as the research questions become more focused and targeted, collaborative science is the

only way forward.

1. Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS. 2019. Chemical composition of commercial cow’s milk. Journal of Agricultural and Food Chemistry 67: 4897-4914.

Contributed by Dr. Lauren Milligan Newmark Researcher, Science Writer

Antibody Type, Specificity, and Source Influence Their Survival in the Infant Gut Antibodies in human milk help protect infants from pathogens and may be particularly crucial for preterm infants.

A new study finds that antibodies in a mother’s own milk survive digestion in the infant gut better than antibodies from donor breast milk, potentially increasing their effectiveness against pathogens.

Human milk antibodies are more stable in preterm infants than in term infants, with preterm infant guts partially degrading IgA but not IgG and IgM.

Antibody survival also depends on the specificity of the antibody against different pathogens.

Maternal antibodies play an important role in protecting newborns from harmful pathogens. Antibodies

known as immunoglobulins (Igs) are transferred from the mother’s placenta into the fetus, where they

protect the infant while the infant’s immune system is still developing [1].

Human milk also contains many different Igs, such as IgA,

IgM, IgG, and secretory forms of IgA and IgM [2-4]. Consuming human milk provides additional immune

protection to infants and has been shown to reduce the risk

of infectious diseases [5].

The protective effect of maternal milk antibodies may be particularly crucial in a preterm infant, whose immune

system is relatively underdeveloped [6,7]. “Pre-term infants have an immature immune system, and it’s particularly

essential for these immunoglobulins to survive and fight against infection,” says Dr. Veronique Demers-Mathieu at

Medolac Laboratories [Boulder City, NV]. “The overall aim of my research is to improve the immunity and

growth and development of premature infants,” she says.

Demers-Mathieu was a postdoctoral researcher with Dr. David Dallas at Oregon State University, Corvallis, OR when they decided to investigate the survival of human milk antibodies in the infant gut. “In order to

have activity to bind to pathogens or toxins, the antibodies need to survive across digestion and be

intact,” says Demers-Mathieu. “Knowing what’s present in the gut is really important,” says Dallas.

Mothers of pre-term infants are often unable to provide all the milk required to feed their infants, and they

supplement their infants with human milk received from donors [8]. However, donor milk undergoes extensive processing, including pooling of milk from different mothers, multiple freeze-thaw cycles, and

pasteurization to inactivate viruses and kill bacteria [9-11]. All these steps may affect the survival and

activity of antibodies present in donor milk.

In a new study, Demers-Mathieu and Dallas found that antibodies in mother’s own milk survived digestion in the infant gut better than antibodies from donor breast milk [12]. “Total IgA, secretory IgA, total IgM

and IgG concentrations were higher in mother’s own milk than in pasteurized donor breast milk, and were higher in gastric contents when infants were fed mother’s breast milk than when infants were fed donor

breast milk,” says Demers-Mathieu.

The findings suggest that feeding infants donor milk rather than their mother’s own milk could affect their

immunity. “The higher concentration of antibodies in mother’s own breast milk than in pasteurized donor breast milk may make mother’s breast milk more effective in preventing enteric pathogen adhesion and

invasion in newborns compared with donor milk,” says Demers-Mathieu. There is some previous evidence

showing that preterm infants fed donor milk may have lower protection against pathogens [13,14].

The new study adds to our knowledge of the many different factors that influence the survival of

antibodies in the infant gut. “It’s complex, there is a lot of digestion that occurs in the stomach and

intestine, and it varies between different types of antibodies,” says Dallas.

Demers-Mathieu and Dallas previously found that preterm infants partially degrade IgA but not IgG and IgM in the stomach, and overall the stability of human milk antibodies was higher in preterm infants than

in term infants [4,15]. “This could be beneficial for assisting the preterm infants’ immature immune

system,” says Demers-Mathieu.

The researchers have also studied antibodies specific to different pathogens, and recently examined the

survival of anti-pertussis and anti-influenza A-specific antibodies [16]. “The way that flu IgA degrades

differs from the way that pertussis IgA does,” says Dallas. “The takeaway is that if you want to use an oral antibody to help prevent infection in babies, it’s really important to do this kind of work to see how much

survives and figure out how to appropriately dose the antibody,” he says.

For instance, the researchers found that anti-influenza A-specific antibodies had a higher relative abundance in mother’s milk compared with donor’s milk [16]. “This suggests that supplementation of anti-

influenza A-specific antibodies in donor milk may help reduce the risk of influenza virus infection,” says

Dallas.

Levels of human milk antibodies also vary between different mothers. “Antibodies vary widely in raw human milk between mothers, which could be due to different maternal background, nutritional and

environmental factors, as well as potential unknown factors,” says Demers-Mathieu. “The dose required of human milk antibodies to induce a significant protective effect against pathogens and their toxins remains

unknown,” she says. “Studies are needed to determine the minimum effective dose in addition to important maternal factors that may influence the concentration of antibodies in raw human milk,” says

Demers-Mathieu.

Studying the immune components of human milk could help develop new immune supplements to protect

infants from pathogens. “My long-term goal is to identify the function of human milk immune components to protect against infection and pediatric diseases in premature infants,” says Demers-Mathieu. “We would

like to develop new supplements with active immune components to add to donor milk as well as in

mother’s milk with low level of immune components.”

1. Palmeira P., Quinello C., Silveira-Lessa A.L., Zago C.A., Carneiro-Sampaio M. IgG placental transfer in healthy and pathological pregnancies. Clin Dev Immunol. 2012;2012:985646. 2. Chandra R. Immunoglobulin and protein levels in breast milk produced by mothers of preterm infants. Nutr Res. 1982;2(1):27–30. 3. Goldman A.S., Garza C., Nichols B.L., Goldblum R.M. Immunologic factors in human milk during the first year of lactation. J Pediatr. 1982 Apr;100(4):563-7. 4. Demers-Mathieu V., Underwood M.A., Beverly R.L., Nielsen S.D., Dallas D.C. Comparison of human milk immunoglobulin survival during gastric digestion between preterm and term infants. Nutrients. 2018 May 17;10(5). pii: E631. 5. Duijts L., Jaddoe V.W., Hofman A., Moll H.A. Prolonged and exclusive breastfeeding reduces the risk of infectious diseases in infancy. Pediatrics. 2010 Jul;126(1):e18-25. 6. Zemlin M., Hoersch G., Zemlin C., Pohl-Schickinger A., Hummel M., Berek C., Maier R.F., Bauer K. The postnatal maturation of the immunoglobulin heavy chain IgG repertoire in human preterm neonates is slower than in term neonates. J Immunol. 2007 Jan 15;178(2):1180-8. 7. Malek A., Sager R., Kuhn P., Nicolaides K.H., Schneider H. Evolution of maternofetal transport of immunoglobulins during human pregnancy. Am J Reprod Immunol. 1996 Nov;36(5):248-55. 8. Carroll K., Herrmann K.R. The cost of using donor human milk in the NICU to achieve exclusively human milk feeding through 32 weeks postmenstrual age. Breastfeed Med. 2013 Jun;8(3):286-90. 9. Orloff S.L., Wallingford J.C., McDougal J.S. Inactivation of human immunodeficiency virus type I in human milk: Effects of intrinsic factors in human milk and of pasteurization. J Hum Lact. 1993 Mar;9(1):13-7. 10. Hamprecht K., Maschmann J., Müller D., Dietz K., Besenthal I., Goelz R., Middeldorp J.M., Speer C.P., Jahn G. Cytomegalovirus (CMV) inactivation in breast milk: Reassessment of pasteurization and freeze-thawing. Pediatr Res. 2004 Oct;56(4):529-35. 11. Franklin J.G. A comparison of the bactericidal efficiencies of laboratory Holder and HTST methods of milk pasteurization and the keeping qualities of the processed milks. Int J Dairy Technol. 1965 Apr;18(2):115–8. 12. Demers-Mathieu V., Huston R.K., Markell A.M., McCulley E.A., Martin R.L., Spooner M., Dallas D.C. Differences in maternal immunoglobulins within mother's own breast milk and donor breast milk and across digestion in preterm infants. Nutrients. 2019 Apr 24;11(4). pii: E920. 13. Narayanan I., Murthy N.S., Prakash K., Gujral V.V. Randomised controlled trial of effect of raw and Holder pasteurised human milk and of formula supplements on incidence of neonatal infection. Lancet. 1984 Nov 17;2(8412):1111-3. 14. Schanler R.J., Lau C., Hurst N.M., Smith E.O.B. Randomized trial of donor human milk versus preterm formula as substitutes for mothers’ own milk in the feeding of extremely premature infants. Pediatrics. 2005 Aug;116(2):400-6. 15. Demers-Mathieu V., Underwood M.A., Beverly R.L., Dallas D.C. Survival of immunoglobulins from human milk to preterm infant gastric samples at 1, 2, and 3 h postprandial. Neonatology. 2018;114(3):242-50. 16. Demers-Mathieu V., Huston R.K., Markell A.M., McCulley E.A., Martin R.L., Dallas D.C. Antenatal influenza A-specific IgA, IgM, and IgG antibodies in mother’s own breast milk and donor breast milk, and gastric contents and stools from preterm infants. Nutrients. 2019;11(7): 1567-78.

Contributed by Dr. Sandeep Ravindran Freelance Science Writer Sandeepr.com

MicroRNAs May Play a Key Role in Heat Stress Responses in Mammary Glands of Lactating Cows

Heat stress in dairy cows interferes with fertility and milk production, and also lowers immunity; its effects represent a source of loss for the dairy industry.

Recently, researchers sequenced the miRNAs in heat stressed and non-heat stressed dairy cows and results suggest that miRNAs are an important regulator of the heat stress response in mammary glands.

Several of the key miRNAs for which functions are known are linked to developmental control of fat cells and stem cells in the mammary gland, which indicates a role in lactation and milk fat synthesis.

Although direct experimental evidence verifying the functions of the miRNAs in this study is yet to be obtained, these results could prove useful in developing biomarkers for the control of heat stress in cows.

The study was limited, however, in that it did not account for the differences in miRNAs that naturally occur at different stages in lactation.

A concern facing dairy farmers as the long, hot days of summer approach is the threat of heat stress in

their cows. Experienced at temperatures above 80°F, heat stress affects growth and development as well as milk composition and volume [1]. Heat stress is a major cause of low fertility in dairy cattle [2]. It also

increases susceptibility to metabolic disorders, mammary gland pathogens and mastitis. Compared with other livestock, cattle are unable to dissipate their heat load efficiently [3]. Additional heat generated by

the fermentation of food in the rumen compounds this problem. Cows’ sweating response is not highly

effective, and the animals rely on respiration to cool themselves. Because of their inefficient response, cattle accumulate a heat load during the day that must be dissipated in cooler nighttime temperatures. In

extreme weather conditions with overnight temperatures above 70°F, however, this doesn’t happen. Cattle experiencing increasing heat stress will stop feeding and become restless. They will then begin

drooling and breathing more rapidly and with increased effort. They will also begin to group together, further exacerbating the problem. If not controlled, severe cases of heat stress will result in death.

Economically, decreased milk yield and reproductive losses through hot summer months seriously affect the dairy industry. Increased occurrences of extreme weather conditions caused by ongoing global

warming will only worsen these losses.

At the cellular level, heat stress elicits a complex molecular response. Environmental stressors cause changes in the

expression—that is, the translation from DNA to protein—of various genes. These are up- or down-regulated, creating

more or less, respectively, of their corresponding proteins, and thereby changing their effect. In recent years,

microRNAs (miRNAs) have come to be recognized as important modifiers of gene expression levels related to a

wide array of biological processes [4,5]. MiRNAs are small,

noncoding RNA molecules, typically 21–25 nucleotides in length, that are widespread in the plant and animal

kingdoms. First described in 1993, they function by pairing with the messenger RNAs (mRNAs) that are the

intermediaries between DNA and protein assembly, preventing their translation into proteins. More miRNA means less of the corresponding protein. Every miRNA has one or more target genes whose expression it

affects. Changes in the levels of key miRNAs have previously been identified as part of the response to heat stress in cattle. For example, a decrease in one miRNA, called miR-181a, reduced heat stress

damage in certain blood cells of Holstein cows [6].

A recent paper by Li et al. in BMC Genomics compares the miRNA profiles of mammary glands of heat-

stressed lactating cows with those that aren’t heat stressed [7]. The goal of the research is to better our understanding of how heat stress affects milk production by identifying miRNAs that may be involved in

that process. The authors collected samples from eight mammary gland tissues of four lactating Holstein cows, first in spring, while temperatures ranged from 59°F to 68°F, and then in summer, when

temperatures sat between 86°F and 100°F. These were defined as the non-heat-stressed (NHS) and heat-stressed (HS) groups, respectively. A temperature humidity index above 72 and cows with a rectal

temperature above 102°F were considered to be indicators of heat stress.

The researchers used a technique called RNA-Seq to sequence purified miRNA samples from each group of

cows. They then compared the expression levels of individual miRNAs from cows under heat stress with the non-stressed controls. The idea here is that genes that are differently expressed between the groups

have a greater chance of being involved in the physiological processes related to heat stress. The authors used bioinformatic software to predict the target genes of miRNAs with high or varying abundance

between the two experimental groups. Because a great deal of data have been accumulated over time on the functions of various genes, by using comparative methods, researchers are able to identify target

genes and extrapolate on their functions without having to test them experimentally.

The authors looked closely at seven miRNAs that changed significantly in their abundance under heat

stress, and eight that were the most highly abundant overall. Bioinformatic methods predicted a large number of possible target genes for these miRNAs belonging to a number of broad functional groups and

chemical pathways. Several of these chemical pathways are known to play an essential role in the normal development of the mammary gland. Taken together, the results suggest that the key miRNAs identified

in this study might act as a dominant regulator during heat stress.

Though the study didn’t attempt to determine the exact functions of the miRNAs involved, several studies

have previously done so with some of the relevant miRNAs. Of these, three were found to promote the creation and/or development of fat cells, which is part of the early lactation response [8-11]. Another

contributes to the creation of mammary stem cells as well as fat cells [12]. A fifth is involved in immune function related to mastitis [13]. Overall, several of the most highly abundant miRNAs in the mammary

gland appear to be related to mammary gland structure, milk synthesis, and the lactation process.

The experimental setup used to test the cows in this study is of concern, however, because the authors, who were unavailable for comment, seem to have used the same four cows in both spring and summer,

meaning they were at different lactational stages for the two samples. Dr. Monique Rijnkels, an assistant

professor in the College of Veterinary Medicine & Biomedical Sciences at Texas A&M University, who was not involved in the study, says “It is not clear at all how long the animals had been lactating and if all

cows were lactating the same length of time at sampling,” noting that the length of time between samples

“could already be the cause of the changes observed, regardless of heat stress.”

Although this research doesn’t begin to solve the problem of heat stress in dairy cows, it has produced

some basic data to help direct future studies. The authors note that direct experimentation in vitro will be needed to confirm both the structure and functions of the miRNAs identified by this study. Eventually,

they hope these results may prove valuable for developing miRNA-based biomarkers for the control of

heat stress in cows. More speculatively, genetic engineering to adjust miRNA activity may one day help

reduce heat stress damage in dairy cows.

1. Tao S, Bubolz JW, do Amaral BC, Thompson IM, Hayen MJ, Johnson SE, Dahl GE. 2011. Effect of heat stress during the dry period on mammary gland development. J Dairy Sci. 94(12): 5976-5986. 2. Wolfenson D, Roth Z. 2019. Impact of heat stress on cow reproduction and fertility. Anim Front. 9(1): 32-38. 3. Dewell G. Heat stress in beef cattle. https://vetmed.iastate.edu/vdpam/about/production-animal-medicine/beef/bovine-disease-topics/heat-stress-beef-cattle Accessed July 25, 2019. 4. Espinoza-Lewis RA, Wang DZ. 2012. MicroRNAs in heart development. Curr Top Dev Biol. 100: 279-317. 5.Cohrt KOH. Mysterious miRNAs: An introduction to microRNAs. https://bitesizebio.com/23238/mysterious-mirnas-an-introduction-to-micrornas/ Accessed July 25, 2019. 6. Chen KL, Fu YY, Shi MY, Li HX. 2016. Down-regulation of miR-181a can reduce heat stress damage in PBMCs of Holstein cows. In Vitro Cell Dev Biol Anim. 52(8): 864-871. 7. Li Q, Yang C, Du J, Zhang B, He Y, Hu Q, Li M, Zhang Y, Wang C, Zhong J. 2018. Characterization of miRNA profiles in the mammary tissue of dairy cattle in response to heat stress. BMC Genomics 19: 975. 8. Kim YJ, Hwang SJ, Bae YC, Jung JS. 2009. Mir-21 regulates adipogenic differentiation through the modulation of TGF-beta signaling in mesenchymal stem cells derived from human adipose tissue. Stem Cells 27(12): 3093–3102. 9. Wang M, Moisa S, Khan MJ, Wang J, Bu D, Loor JJ. 2012. MicroRNA expression patterns in the bovine mammary gland are affected by stage of lactation. J Dairy Sci. 95(11): 6529–6535. 10. Yi C, Xie WD, Li F, Lv Q, He J, Wu J, Gu D, Xu N, Zhang Y. 2011. MiR-143 enhances adipogenic differentiation of 3T3-L1 cells through targeting the coding region of mouse pleiotrophin. FEBS Lett. 585(20): 3303–3309. 11. Qin L, Chen Y, Niu Y, Chen W, Wang Q, Xiao S, Li A, Xie Y, Li J, Zhao X, He Z, Mo D. 2010. A deep investigation into the adipogenesis mechanism: profile of microRNAs regulating adipogenesis by modulating the canonical Wnt/beta-catenin signaling pathway. BMC Genomics. 11: 320.

12. Elsarraj HS, Hong Y, Valdez K, Carletti M, Salah SM, Raimo M, Taverna D, Prochasson P, Bharadwaj U, Tweardy DJ, Christenson LK, Behbod F. 2013. A novel role of microRNA146b in promoting mammary alveolar progenitor cell maintenance. J Cell Sci. 126(Pt 11): 2446–2458. 13. Li R, Zhang CL, Liao XX, Chen D, Wang WQ, Zhu YH, Geng XH, Ji DJ, Mao YJ, Gong YC, Yang ZP. 2015. Transcriptome microRNA profiling of bovine mammary glands infected with Staphylococcus aureus. Int J Mol Sci. 16(3): 4997–5013.

Contributed by Erin Zimmerman Science Writer www.DrErinZimmerman.com Editorial Staff of SPLASH!® milk science update: Dr. Danielle Lemay, Executive Editor

Dr. Katie Rodger, Managing Editor Anna Petherick, Associate Editor Dr. Lauren Milligan Newmark, Associate Editor

Dr. Ross Tellam, Associate Editor Dr. Sandeep Ravindran, Associate Editor Dr. Erin Zimmerman, Contributing Editor

Prof. Peter Williamson, Associate Editor Cora Morgan, Editorial Assistant

Funding provided by California Dairy Research Foundation and the International Milk Genomics Consortium.

The views and opinions expressed in this newsletter are those of the contributing authors and editors and do not necessarily represent the views of their employers or IMGC sponsors.