Longitudinal liver proteome profiling in dairy cows during the transition from gestation to lactation: Investigating metabolic adaptations and their interactions with fatty acids supplementation via repeated measurements ANOVA-simultaneous component analysis

Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines

The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this study was to investigate the influence of matrix stiffness on PDAC progression by analyzing the proteome of PDAC-derived extracellular vesicles (EVs). PDAC cell lines (mPDAC and KPC) were grown on synthetic supports with a stiffness close to non-tumor (NT) or tumor tissue (T), and the protein expression levels in cell-derived EVs were analyzed by a quantitative MSE label-free mass spectrometry approach. Our analysis figured out 15 differentially expressed proteins (DEPs) in mPDAC-EVs and 20 DEPs in KPC-EVs in response to matrix rigidification. Up-regulated proteins participate to the processes of metabolism, matrix remodeling, and immune response, altogether hallmarks of PDAC progression. A multimodal network analysis revealed that the majority of DEPs are strongly related to pancreatic cancer. Interestingly, among DEPs, 11 related genes (ACTB/ANXA7/C3/IGSF8/LAMC1/LGALS3/PCD6IP/SFN/TPM3/VARS/YWHAZ) for mPDAC-EVs and 9 (ACTB/ALDH2/GAPDH/HNRNPA2B/ITGA2/NEXN/PKM/RPN1/S100A6) for KPC-EVs were significantly overexpressed in tumor tissues according to gene expression profiling interaction analysis (GEPIA). Concerning the potential clinical relevance of these data, the cluster of ACTB, ITGA2, GAPDH and PKM genes displayed an adverse effect (p < 0.05) on the overall survival of PDAC patients.

Lipidomics and Transcriptome Reveal the Effects of Feeding Systems on Fatty Acids in Yak’s Meat

The differences of fatty acids in yak’s meat under graze feeding (GF) and stall feeding (SF) regimes and the regulation mechanism of the feeding system on the fatty acids content in yak ’s meat was explored in this study. First, the fatty acids in yak’s longissimus dorsi (LD) muscle were detected by gas liquid chromatography (GLC). Compared with GF yaks, the absolute content of ΣSFAs, ΣMUFAs, ΣUFAs, ΣPUFAs and Σn-6PUFAs in SF yak’s LD were higher, whereas Σn-3PUFAs was lower; the relative content of ΣMUFAs, ΣPUFAs, Σn-3PUFAs and ΣUFAs in SF yak’s LD were lower, whereas ΣSFAs was higher. The GF yak’s meat is healthier for consumers. Further, the transcriptomic and lipidomics profiles in yak’s LD were detected by mRNA-Sequencing (mRNA-Seq) and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS), respectively. The integrated transcriptomic and lipidomics analysis showed the differences in fatty acids were caused by the metabolism of fatty acids, amino acids, carbohydrates and phospholipids, and were mainly regulated by the FASN, FABP3, PLIN1, SLC16A13, FASD6 and SCD genes in the PPAR signaling pathway. Moreover, the SCD gene was the candidate gene for the high content of ΣMUFA, and FADS6 was the candidate gene for the high content of Σn-3PUFAs and the healthier ratio of Σn-6/Σn-3PUFAs in yak meat. This study provides a guidance to consumers in the choice of yak’s meat, and also established a theoretical basis for improving yak’s meat quality.

Plasma proteomics reveals crosstalk between lipid metabolism and immunity in dairy cows receiving essential fatty acids and conjugated linoleic acid

Essential fatty acids (EFA) and conjugated linoleic acids (CLA) are unsaturated fatty acids with immune-modulatory effects, yet their synergistic effect is poorly understood in dairy cows. This study aimed at identifying differentially abundant proteins (DAP) and their associated pathways in dairy cows supplied with a combination of EFA and CLA during the transition from antepartum (AP) to early postpartum (PP). Sixteen Holstein cows were abomasally infused with coconut oil as a control (CTRL) or a mixture of EFA (linseed + safflower oil) and CLA (Lutalin, BASF) (EFA + CLA) from − 63 to + 63 days relative to parturition. Label-free quantitative proteomics was performed on plasma samples collected at days − 21, + 1, + 28, and + 63. During the transition time, DAP, consisting of a cluster of apolipoproteins (APO), including APOE, APOH, and APOB, along with a cluster of immune-related proteins, were related to complement and coagulation cascades, inflammatory response, and cholesterol metabolism. In response to EFA + CLA, specific APO comprising APOC3, APOA1, APOA4, and APOC4 were increased in a time-dependent manner; they were linked to triglyceride-enriched lipoprotein metabolisms and immune function. Altogether, these results provide new insights into metabolic and immune adaptation and crosstalk between them in transition dairy cows divergent in EFA + CLA status.

Integration of Multiplied Omics, a Step Forward in Systematic Dairy Research

Due to their unique multi-gastric digestion system highly adapted for rumination, dairy livestock has complicated physiology different from monogastric animals. However, the microbiome-based mechanism of the digestion system is congenial for biology approaches. Different omics and their integration have been widely applied in the dairy sciences since the previous decade for investigating their physiology, pathology, and the development of feed and management protocols. The rumen microbiome can digest dietary components into utilizable sugars, proteins, and volatile fatty acids, contributing to the energy intake and feed efficiency of dairy animals, which has become one target of the basis for omics applications in dairy science. Rumen, liver, and mammary gland are also frequently targeted in omics because of their crucial impact on dairy animals’ energy metabolism, production performance, and health status. The application of omics has made outstanding contributions to a more profound understanding of the physiology, etiology, and optimizing the management strategy of dairy animals, while the multi-omics method could draw information of different levels and organs together, providing an unprecedented broad scope on traits of dairy animals. This article reviewed recent omics and multi-omics researches on physiology, feeding, and pathology on dairy animals and also performed the potential of multi-omics on systematic dairy research.