Development and Validation of a Transcriptomics-based Index to Assess Metabolic and Physiological Functions in the Blood of Pigs

Assessment of efficiency in pigs typically involves performance metrics, carcass evaluation and selected biomarkers, but lacks a standardized functional evaluation method. A novel approach was developed using blood transcriptomics to assess metabolic efficiency as it relates to FCR. This method quantified mRNA via poly-A selection (>20 M reads/sample) targeting 6,000 genes in 200 pathways grouped into six metabolic functions: energy and mitochondrial function, anabolism and nutrient utilisation, tissue turnover and repair, immune cost, oxidative balance and detoxification and neuroendocrine & gut-brain signalling. A topology-based pathway activation algorithm (BIOFRACTAL, Portugal) analyzed signatures of significantly activated pathways in treatments relative to their respective controls. Significance was evaluated at adjP < 0.05. A standardized Metabolic Efficiency Index (MEI; Metabolic Efficacy Index, BIOFRACTAL, Portugal) was calculated using a similarity score comparing treatment signatures with a benchmark of acute systemic infection via LPS challenge, where 100% matched severe systemic challenge and +100% indicated the opposite profile. The MEI was validated with three datasets: 1) blood samples from LPS challenge pigs versus non-challenge controls 2-, 6- and 24-hours post-infection (n = 32), 2) blood samples from Salmonella challenged versus non-challenged controls at 2 and 7 days post-infection (n = 12), and 3) blood samples from sick versus healthy finisher pigs and grower versus finisher pigs (n = 64). In dataset 1, the MEI value for challenged pigs was -84% (adjP < 0.05) at 6 hours post-infection with all 6 functions being negatively impacted ranging from -71 to -93% with nutrient metabolism and gut-brain signalling being most severely impacted vs. controls (-92 and -93%, respectively). Dataset 2 showed a MEI of -71% (adjP < 0.05) in pig blood at 2 DPI however at 7 DPI the MEI was back up to -50% which was driven by improvements in immune cost and neuroendocrine and gut-brain signalling functions. Dataset 3 indicated a -61% MEI (adjP < 0.05) for sick versus healthy commercially raised late growing pigs with oxidative balance and detoxification (-89%) and anabolism and nutrient utilisation (-69%) driving this negative response. In contrast, the comparison of healthy finishers to healthy grower showed a MEI of + 17% (adjP < 0.05) highlighting changes in anabolism and nutrient utilisation (+79%) and tissue turnover and repair (+38%). This transcriptomics-based method effectively quantified changes in six key metabolic and physiological functions, offering a functional index for both detrimental and beneficial impacts in independent datasets.