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Perez-Hernandez G, Ellett MD, Banda LJ, Dougherty D, Parsons CLM, Lengi AJ, Daniels KM, Corl BA. Cyclical heat stress during lactation influences the microstructure of the bovine mammary gland. J Dairy Sci 2024:S0022-0302(24)00866-X. [PMID: 38825136 DOI: 10.3168/jds.2024-24809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/19/2024] [Indexed: 06/04/2024]
Abstract
This study aimed to evaluate the impact of heat stress on mammary epithelial cell (MEC) losses into milk, secretory mammary tissue structure, and mammary epithelial cell activity. Sixteen multiparous Holstein cows (632 ± 12 kg BW) approximately 100 d in milk housed in climate-controlled rooms were paired by body weight and randomly allocated to one of 2 treatments, heat stress (HS) or pair feeding thermoneutral (PFTN) using 2 cohorts. Each cohort was subjected to 2 periods of 4 d each. In period 1, both treatments had ad libitum access to a common total mixed ration and were exposed to a controlled daily temperature-humidity index (THI) of 64. In period 2, HS cows were exposed to controlled cyclical heat stress (THI: 74 to 80), while PFTN cows remained at 64 THI and daily dry matter intake was matched to HS. Cows were milked twice daily, and milk yield was recorded at each milking. Individual milk samples on the last day of each period were used to quantify MEC losses by flow cytometry using butyrophilin as a cell surface marker. On the final day of period 2, individual bovine mammary tissue samples were obtained for histomorphology analysis, assessment of protein abundance, and evaluation of gene expression of targets associated with cellular capacity for milk and milk component synthesis, heat response, cellular proliferation, and autophagy. Statistical analysis was performed using the GLIMMIX procedure of SAS. Milk yield was reduced by 4.3 kg by HS (n = 7) compared with PFTN (n = 8). Independent of treatment, MEC in milk averaged 174 cells/mL (2.9% of total cells). There was no difference between HS vs. PFTN cows for MEC shed or concentration in milk. Alveolar area was reduced 25% by HS, and HS had 4.1 more alveoli than PFTN. Total number of nucleated MEC per area were greater in HS (389 ± 1.05) compared with PFTN (321 ± 1.05); however, cell number per alveolus was similar between groups (25 ± 1.5 vs. 26 ± 1.4). There were no differences in relative fold expression for GLUT1, GLUT8, CSN2, CSN3, LALBA, FASN, HSPA5, and HSPA8 in HS compared with PFTN. Immunoblotting analyses showed a decrease abundance for phosphorylated STAT5 and S6K1, and an increase in LC3 II in HS compared with PFTN. These results suggest that even if milk yield differences and histological changes occur in the bovine mammary gland after 4 d of heat exposure, MEC loss into milk, nucleated MEC number per alveolus, and gene expression of nutrient transport, milk component synthesis, and heat stress related targets are unaffected. In contrast, the abundance of proteins related to protein synthesis and cell survival decreased significantly, while an upregulation of proteins associated with autophagy in HS compared with PFTN.
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Affiliation(s)
| | - M D Ellett
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061
| | - L J Banda
- Animal Science Department, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - D Dougherty
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061
| | - C L M Parsons
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061
| | - A J Lengi
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061
| | - K M Daniels
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061
| | - B A Corl
- School of Animal Sciences, Virginia Tech, Blacksburg, VA 24061.
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Nyquist SK, Gao P, Haining TKJ, Retchin MR, Golan Y, Drake RS, Kolb K, Mead BE, Ahituv N, Martinez ME, Shalek AK, Berger B, Goods BA. Cellular and transcriptional diversity over the course of human lactation. Proc Natl Acad Sci U S A 2022; 119:e2121720119. [PMID: 35377806 PMCID: PMC9169737 DOI: 10.1073/pnas.2121720119] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/14/2022] [Indexed: 12/04/2022] Open
Abstract
Human breast milk (hBM) is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We generated and analyzed single-cell RNA-sequencing (scRNA-seq) data to characterize the transcriptomes of cells from hBM across lactational time from 3 to 632 d postpartum in 15 donors. We found that the majority of cells in hBM are lactocytes, a specialized epithelial subset, and that cell-type frequencies shift over the course of lactation, yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone-, growth factor-, and milk production-related pathways. Generalized additive models suggest that one subcluster, LC1 epithelial cells, increases as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several subclusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal–infant dyad metadata, and our quantification of alterations at the gene and pathway levels provide a detailed longitudinal picture of hBM cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.
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Affiliation(s)
- Sarah K. Nyquist
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Program in Computational and Systems Biology, Massachusetts Institute of Technology; Cambridge, MA 02139
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
- Computer Science and Artificial Intelligence Laboratory, Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Patricia Gao
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Tessa K. J. Haining
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Michael R. Retchin
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Yarden Golan
- Department of Bioengineering and Therapeutic Sciences, Institute for Human Genetics, University of California, San Francisco, CA 94143
| | - Riley S. Drake
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139
| | - Kellie Kolb
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Benjamin E. Mead
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, Institute for Human Genetics, University of California, San Francisco, CA 94143
| | | | - Alex K. Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Program in Computational and Systems Biology, Massachusetts Institute of Technology; Cambridge, MA 02139
- Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Division of Health Science & Technology, Harvard Medical School, Boston, MA 02115
- Department of Immunology, Massachusetts General Hospital, Boston, MA 02114
| | - Bonnie Berger
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Computer Science and Artificial Intelligence Laboratory, Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Brittany A. Goods
- Thayer School of Engineering, Program in Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755
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van Amerongen R, Kordon EC, Koledova Z. Connecting the Dots: Mammary Gland and Breast Cancer at Single Cell Resolution. J Mammary Gland Biol Neoplasia 2021; 26:1-2. [PMID: 34125362 DOI: 10.1007/s10911-021-09492-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 05/26/2021] [Indexed: 02/08/2023] Open
Affiliation(s)
- Renée van Amerongen
- Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Edith C Kordon
- Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
- Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Zuzana Koledova
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
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