A longitudinal quantitative real-time PCR (qPCR) study of 45 lipogenic genes in Holstein mammary tissue (Bionaz & Loor, 2008) produced a network model in which PPARG, PPARGC1A and INSIG1, rather than SREBF1 alone, appear to coordinate milk fat synthesis during lactation, and in which transcript abundances correlate only weakly with milk fatty-acid phenotypes. The unresolved problem is to convert this mRNA-level model into a mechanistic and quantitatively predictive account: determine whether the large lactation-cycle changes in transcript abundance (INSIG1, SCD, ABCG2, FABP3, LPIN1 and others) translate into corresponding changes in protein abundance, localization, post-translational modification and catalytic activity; establish the causal structure of the proposed PPARG–PPARGC1A–INSIG1–SREBF module; identify the physiologically important milk cargo of the strongly induced ABCG2 transporter beyond riboflavin; and partition control of lipogenic fluxes between transcriptional and post-transcriptional regulation so that quantitative flux and substrate-pool measurements close the gap between transcriptomics and milk lipid composition. Later literature has delivered pharmacological and knockdown evidence for parts of the transcription-factor module (mostly in goat, buffalo or bovine cell culture) and additional endogenous ABCG2 substrates, but no systematic protein/activity map across lactation, no direct demonstration that PPARG transcriptionally controls INSIG1 in bovine mammary epithelium, no abundant ABCG2 milk cargo, and no quantitative transcript-to-flux control model exists.

Background

Milk fat (triacylglycerol, TAG) is synthesized in the secretory epithelial cells of the mammary gland from fatty acids (FA) taken up from blood (via lipoprotein lipase, LPL, and the FA transporter CD36) and from FA made de novo (acetyl-CoA carboxylase ACACA, fatty-acid synthase FASN) or desaturated (stearoyl-CoA desaturase, SCD), shuttled inside the cell (FABP3, a cytosolic fatty-acid-binding protein), then assembled into TAG by the glycerolipid-assembly enzymes (GPAM, AGPAT6, LPIN1, DGAT1) and secreted in milk fat globules. Bionaz and Loor (2008) measured the abundance of 45 lipogenic transcripts in bovine mammary tissue at seven time points, from late pregnancy (15 days before parturition) through late lactation (240 days after parturition). Three findings defined the open questions addressed here. First, the study challenged the prevailing view that the membrane-bound transcription factor SREBP1 (gene SREBF1), the canonical lipogenic regulator, is the central controller in bovine mammary tissue, and instead proposed a module in which PPARG (peroxisome proliferator-activated receptor gamma, a nuclear receptor and known adipocyte lipogenic regulator), its coactivator PPARGC1A (PGC-1alpha), and INSIG1 (insulin-induced gene 1, an endoplasmic-reticulum anchor protein that retains the SREBP–SCAP complex — SCAP being the escort protein that carries SREBPs from the endoplasmic reticulum to the Golgi for activation — and thereby inhibits SREBP activation) jointly control SREBF expression and downstream lipogenic genes; the authors stated that the specific roles of INSIG1 and PPARG during lactation 'need to be determined' by further functional studies. Second, the transcript of ABCG2 (an ATP-binding cassette efflux transporter expressed on the apical membrane of mammary alveoli) rose ~30-fold during lactation to ~9% of all transcripts measured, yet the only demonstrated milk cargo at the time was riboflavin (vitamin B2; demonstrated in Abcg2-knockout mice by van Herwaarden et al. 2007), a quantitatively marginal nutrient — making the transporter's physiological role in milk secretion an open puzzle (a missense variant, Y581S, was known to affect milk yield and composition). Third, transcript patterns correlated only weakly with milk FA composition and desaturase indices (milk fatty-acid product-to-substrate ratios used as proxies for apparent SCD activity), and protein activity is regulated at post-translational levels (e.g. ACACA), so transcript abundance alone cannot predict pathway flux. Pre-existing mechanistic context includes the demonstration that the PPARG agonist rosiglitazone induces Insig-1 in rodent adipose tissue (Kast-Woelbern et al. 2004), supporting the plausibility of the proposed module. Subsequent work built cell-culture tools (primary bovine, goat and buffalo mammary epithelial cells, and MAC-T, an immortalized bovine mammary epithelial cell line) and produced partial answers.

Problem Statement

Determine how the lipogenic network identified at the mRNA level in bovine mammary tissue during the lactation cycle operates mechanistically, by answering, for the lactating bovine mammary gland: (1) do the large lactation-cycle changes in transcript abundance of the core lipogenic genes (including INSIG1, SCD, ABCG2, FABP3, LPIN1, ACACA) translate into corresponding changes in protein abundance, subcellular localization, post-translational modification and catalytic activity, or is protein-level regulation largely uncoupled from transcript abundance? (2) what is the causal structure and directionality of the proposed PPARG-PPARGC1A-INSIG1-SREBF module — in particular, does PPARG activity directly regulate INSIG1, and does this in turn modulate SREBP processing and downstream lipogenic gene induction? (3) which milk components besides riboflavin are actively exported by ABCG2 in the lactating gland, and what is the physiologically important cargo that accounts for its marked induction and its effect on milk composition? and (4) what is the relative contribution of transcriptional versus post-transcriptional/post-translational regulation and of substrate/flux-level constraints (e.g. uptake selectivity of blood very-low-density-lipoprotein TAG, compartmental substrate pools) in determining milk fatty-acid output — i.e. what quantitative measurements of protein activity and metabolic flux are needed to make the transcript-level network predict milk lipid composition? The four parts are jointly posed as one integrated mechanism rather than independent alternatives.

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