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Md. Emran Hossain,
- Professor, Department of Animal Science and Nutrition, Chattogram Veterinary and Animal Sciences University, Khulshi, Chattogram-4225, Bangladesh, , Bangladesh
Abstract
Feed efficiency in poultry emerges from complex interactions among nutrient absorption, metabolic transformation, cellular energy expenditure, and productive tissue accretion. However, conventional whole-organ and bulk-tissue approaches inadequately capture the cellular heterogeneity underlying nutrient utilization and metabolic efficiency. This review proposes a cell-resolved framework integrating single-cell multi-omics, spatial metabolomics, and stable-isotope nutrient-flux mapping to elucidate hidden metabolic specialization across intestinal, hepatic, and skeletal-muscle cell populations. Particular emphasis is placed on intestinal epithelial nutrient acquisition, hepatic substrate repartitioning, and skeletal-muscle anabolic metabolism as interconnected determinants of feed conversion efficiency. We introduce three complementary conceptual frameworks: the Cellular Metabolic Specialization Hypothesis, which attributes nutrient-use heterogeneity to distinct cellular metabolic programs; the Interorgan Metabolic Synchronization Hypothesis, which links coordinated substrate exchange with productive nutrient allocation; and the Cellular Metabolic Bottleneck Hypothesis, which identifies metabolically constrained cellular populations as potential determinants of systemic inefficiency. Emerging technologies, including single-cell transcriptomics, spatially resolved metabolite imaging, isotope tracing, and constraint-based metabolic modeling, are critically evaluated for their capacity to reconstruct cellular nutrient trajectories and distinguish metabolic associations from causal mechanisms. Furthermore, opportunities for integrating cell-specific metabolic signatures with precision nutrition, artificial intelligence, and computational digital twins are explored. Critical challenges involving cellular annotation, spatial resolution, flux quantification, experimental validation, and commercial translation are addressed. Ultimately, establishing a quantitative cellular architecture of feed efficiency could transform poultry nutritional research by identifying actionable metabolic vulnerabilities, improving nutrient-partitioning precision, and supporting sustainable growth without compromising physiological resilience, animal welfare, or meat quality under diverse commercial production conditions.
Keywords: Feed efficiency; Cellular metabolic specialization; Single-cell multi-omics; Spatial metabolomics; Nutrient-flux mapping.
References
[1] H. A. K. Al-Jaf and S. A. Rashid, “Synergistic effects of zinc oxide and selenium nanoparticles in drinking water on broiler chicken growth, antioxidant, and immunity responses,” Vet. Anim. Sci., vol. 30, p. 100528, Feb. 2025, doi: 10.1016/j.vas.2025.100528.
[2] O. Kolawole, A. Graham, C. Donaldson, B. Owens, and …, “Low doses of mycotoxin mixtures below EU regulatory limits can negatively affect the performance of broiler chickens: A longitudinal study,” 2020, mdpi.com. [Online]. Available: https://www.mdpi.com/2072-6651/12/7/433
[3] R. Opazo, C. Salinas, and A. Villasante, “Formulation strategies of probiotics in broilers: systematic review and meta-analysis of their effects on production performance,” Front. Anim. Sci., vol. 6, no. September, pp. 1–18, 2025, doi: 10.3389/fanim.2025.1679614.
[4] M. E. Hossain, K. Adhikary, P. Bhowmik, N. Akter, S. Islam, and M. A. Hoque, “Synergistic interplay of Azadirachta indica and Curcuma longa improves feed efficiency and ω-6 fatty acid content in the breast muscle of broiler chicken,” Vet. Anim. Sci., vol. 29, p. 100489, 2025, doi: https://doi.org/10.1016/j.vas.2025.100489. [5] K. Dev et al., “Dietary synbiotic supplementation improves the growth performance, body antioxidant pool, serum biochemistry, meat quality, and lipid oxidative stability in broiler chickens,” 2020. doi: 10.1016/j.aninu.2020.03.002.
[6] M. V. Teixeira Netto, A. Massuquetto, E. L. Krabbe, D. Surek, S. G. Oliveira, and A. Maiorka, “Effect of Conditioning Temperature on Pellet Quality, Diet Digestibility, and Broiler Performance,” J. Appl. Poult. Res., vol. 28, no. 4, pp. 963–973, 2019, doi: 10.3382/japr/pfz056.
[7] W. P. Lokapirnasari et al., “Supplementation of synbiotic content of moringa oleifera extract and lactobacillus to improve growth performance in starter phase diet of broiler chicken,” Trop. J. Nat. Prod. Res., vol. 4, no. 12, pp. 1096–1100, 2020, doi: 10.26538/tjnpr/v4i12.11.
[8] C. W. Tallentire, I. Leinonen, and I. Kyriazakis, “Breeding for efficiency in the broiler chicken: A review,” Agron. Sustain. Dev., vol. 36, no. 4, p. 66, Nov. 2016, doi: 10.1007/s13593-016-0398-2.
[9] R. Mohammadalipour, H. R. Rahmani, R. Jahanian, A. Riasi, M. Mohammadalipour, and N. Nili, “Effect of early feed restriction on physiological responses, performance and ascites incidence in broiler chickens raised in normal or cold environment,” Animal, vol. 11, no. 2, pp. 219–226, 2017, doi: 10.1017/S1751731116001555. [10] S. Wei et al., “Multiomics insights into the female reproductive aging,” 2024, Elsevier. doi: 10.1016/j.arr.2024.102245.
[11] R. Saif and A. Iftikhar, “Bioinformatics: Multiomics Applications in Food Science,” 2022, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Ali- Iftikhar-8/publication/360545445_Bioinformatics_Multi- Omics_Applications_in_Food_Science/links/6631de1008aa54017acfc742/Bioinformat ics-Multi-Omics-Applications-in-Food-Science.pdf
[12] R. K. Choudhary et al., “Animal Wellness: The Power of Multiomics and Integrative Strategies: Multiomics in Improving Animal Health,” Vet. Med. Int., vol. 2024, no. 1, 2024, doi: 10.1155/2024/4125118.
[13] R. K. Choudhary, S. K. BV, and …, “Animal wellness: the power of multiomics and integrative strategies: multiomics in improving animal health,” Vet. Med. …, 2024, doi: 10.1155/2024/4125118.
[14] S. Yang, J. Zheng, H. Mao, P. Vinitchaikul, D. Wu, and J. Chai, “Multiomics of yaks reveals significant contribution of microbiome into host metabolism,” 2024, nature.com. doi: 10.1038/s41522-024-00609-2.
[15] A. Papanikolaou et al., “Plasma metabolomics reveals distinct responses to acute and chronic heat stress in broilers,” Poult. Sci., vol. 105, no. 7, p. 106876, 2026, doi: https://doi.org/10.1016/j.psj.2026.106876.
[16] M. E. A. El-Hack, A. A. Allam, A. K. Aldhalmi, and …, “Integrating metabolomics for precision nutrition in poultry: optimizing growth, feed efficiency, and health,” Front. Vet. …, 2025, doi: 10.3389/fvets.2025.1594749.
[17] E. Biagi et al., “Effects of Vitamin B2 Supplementation in Broilers Microbiota and Metabolome,” Microorganisms, vol. 8, no. 8, p. 1134, Feb. 2020, doi: 10.3390/microorganisms8081134.
[18] M. A. H. Shahid, R. Jha, and B. Mishra, “Changes in the gut microbiome, metabolic pathways, and intestinal gene expression during the peak, mid, and decline egg production phases in laying hens,” Poult. Sci., vol. 105, no. 3, p. 106372, 2026, doi: 10.1016/j.psj.2026.106372.
[19] L. A. Rubio, “Possibilities of early life programming in broiler chickens via intestinal microbiota modulation,” 2019, Elsevier. doi: 10.3382/ps/pey416.
[20] M. E. Hossain and N. B. Amin, “Proliferation dynamics of enterocytes: Implications for intestinal barrier function, performance, health, and welfare in broiler chickens,” Poult. Sci., vol. 105, no. 9, p. 107128, 2026, doi: https://doi.org/10.1016/j.psj.2026.107128.
[21] J. Vélez et al., “First metabolic insights into ex vivo cryptosporidium parvum-infected bovine small intestinal explants studied under physioxic conditions,” 2021, mdpi.com. doi: 10.3390/biology10100963.
[22] R. A. Leng, “The rumen-a fermentation vat or a series of organized structured microbial consortia: Implications for the mitigation of enteric methane production by feed additives,” 2011, lrrd.cipav.org.co. [Online]. Available: https://lrrd.cipav.org.co/lrrd23/12/leng23258.htm
[23] J. Gao et al., “Impact of the gut microbiota on intestinal immunity mediated by tryptophan metabolism,” 2018, frontiersin.org. doi: 10.3389/fcimb.2018.00013.
[24] G. Esposito, P. C. Irons, E. C. Webb, and A. Chapwanya, “Interactions between negative energy balance, metabolic diseases, uterine health and immune response in transition dairy cows,” Anim. Reprod. Sci., vol. 144, no. 3–4, pp. 60–71, 2014, doi: 10.1016/j.anireprosci.2013.11.007.
[25] W. F. A. Marei, J. De Bie, I. Xhonneux, S. Andries, J. H. Britt, and J. L. M. R. Leroy, “Metabolic and antioxidant status during transition is associated with changes in the granulosa cell transcriptome in the preovulatory follicle in high-producing dairy cows at the time of breeding,” 2022, Elsevier. doi: 10.3168/jds.2022-21928.
[26] L. Gu, H. Liu, X. Gu, C. Boots, K. H. Moley, and Q. Wang, “Metabolic control of oocyte development: Linking maternal nutrition and reproductive outcomes,” Cell. Mol. Life Sci., vol. 72, no. 2, pp. 251–271, 2015, doi: 10.1007/s00018-014-1739-4.
[27] R. Jastrząb, D. Graczyk, and P. Siedlecki, “Molecular and cellular mechanisms influenced by postbiotics,” 2021, mdpi.com. [Online]. Available: https://www.mdpi.com/1422-0067/22/24/13475
[28] U. Bernabucci, N. Lacetera, L. H. Baumgard, R. P. Rhoads, and …, “Metabolic and hormonal acclimation to heat stress in domesticated ruminants,” Animal, 2010, [Online]. Available: https://www.cambridge.org/core/journals/animal/article/metabolic-and-hormonal- acclimation-to-heat-stress-in-domesticated- ruminants/C19BE92A63F33A0B8CD56ED7501C645E
[29] Z. Xie, S. Cheng, X. Gong, and X. Ma, “Applications of stable isotopes in lipid metabolic tracing and lipidomics analysis,” TrAC – Trends Anal. Chem., vol. 196, p. 118629, 2026, doi: 10.1016/j.trac.2025.118629.
[30] I. Sokra, S. Somaly, H. M.-J. of A. and Technology, and undefined 2026, “CRISPR–Cas9–Based genome editing in microbial biotechnology: Advances in metabolic engineering, fermentation systems, and industrial applications,” researchgate.net, vol. 2, no. 1, pp. 379–387, 2026, doi: 10.1007/978-981-95-6970- 0_20.
[31] A. Hubert et al., “Detection of quantitative trait loci and genetic correlations of lipid reserves and production traits in aging laying hens,” Poult. Sci., vol. 105, no. 8, 2026, doi: 10.1016/j.psj.2026.106963.
[32] T. Zenda et al., “Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value,” Front. Plant Sci., vol. 12, Dec. 2021, doi: 10.3389/fpls.2021.774994.
[33] J. Cavanaugh, J. Oswari, and S. S. Margulies, “Role of stretch on tight junction structure in alveolar epithelial cells,” Am. J. Respir. Cell Mol. Biol., vol. 25, no. 5, pp. 584–591, 2001, doi: 10.1165/ajrcmb.25.5.4486.
[34] M. Kerschnitzki, T. Zander, P. Zaslansky, P. Fratzl, R. Shahar, and W. Wagermaier, “Rapid alterations of avian medullary bone material during the daily egg-laying cycle,” Bone, vol. 69, pp. 109–117, 2014, doi: 10.1016/j.bone.2014.08.019.
[35] H. Ba et al., Single-cell multi-omics reveals unique regulatory mechanisms that sustains unprecedented elongation rate of bone structure, the deer antler. researchsquare.com, 2025. [Online]. Available: https://www.researchsquare.com/article/rs-6919532/latest
[36] Y. Nam et al., “Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine,” Annu. Rev. Biomed. Data Sci., vol. 7, no. 1, pp. 225–250, Aug. 2024, doi: 10.1146/annurev- biodatasci-102523-103801.
[37] Y. Lu et al., “Innovative Insights into Single-Cell Technologies and Multi-Omics Integration in Livestock and Poultry,” Int. J. Mol. Sci., vol. 25, no. 23, pp. 1–19, 2024, doi: 10.3390/ijms252312940.
[38] W. Zheng, J. Zhang, J. Huang, B. Han, Y. Liu, and D. Sun, “A pilot multi-omics study reveals genetic mechanisms regulating milk component traits in dairy cattle,” Commun. Biol., vol. 8, no. 1, p. 1150, 2025, doi: 10.1038/s42003-025-08615-6.
[39] J. Cao, X. Zhou, J. Liu, D. Liu, and G. Liu, “Single-Cell Multi-Omics Sequencing Technologies and Their Applications in Livestock and Poultry Research,” J. Agric. Food Chem., vol. 73, no. 51, pp. 32508–32520, Dec. 2025, doi: 10.1021/acs.jafc.5c13040.
[40] H. J. Chen et al., “Integrated metabolic-transcriptomic network identifies immunometabolic modulations in human macrophages,” Cell Rep., vol. 43, no. 9, 2024, doi: 10.1016/j.celrep.2024.114741.
[41] M. Naeem and A. Fatima, “Nutrigenomics and Epigenetic Regulation in Poultry: DNA-Based Mechanisms Linking Diet to Performance and Health,” DNA, vol. 5, no. 4, p. 60, 2025, doi: 10.3390/dna5040060.
[42] L. Kappari, J. R. Dasireddy, T. J. Applegate, R. K. Selvaraj, and R. Shanmugasundaram, “MicroRNAs: exploring their role in farm animal disease and mycotoxin challenges,” Front. Vet. Sci., vol. 11, no. May, 2024, doi: 10.3389/fvets.2024.1372961.
[43] M. B. Wheeler, E. Monaco, M. Bionaz, and T. Tanaka, “The role of existing and emerging biotechnologies for livestock production: Toward holism,” Acta Sci. Vet., vol. 38, no. SUPPL. 2, 2010, Accessed: Mar. 26, 2026. [Online]. Available: https://www.academia.edu/download/3578538/08_sbte_wheeler.pdf
[44] E. B. Isik et al., “Multimodal spatial omics: From data acquisition to computational integration,” Patterns, 2026. [45] P. A. Leggieri et al., “Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes,” Annu. Rev. Biomed. Eng., vol. 23, no. 1, pp. 169–201, 2021, doi: 10.1146/annurev-bioeng-082120-022836.
[46] M. Naeem, “Functional genomics and proteomics in broiler chickens: an integrative framework for growth, immune competence, and stress adaptation,” J. Basic Appl. Zool., vol. 87, no. 1, p. 23, 2026, doi: 10.1186/s41936-026-00562-w.
[47] G. B. Mekonnen, “Integrative multi-omics and predictive precision systems for poultry meat and egg quality: Mechanisms, applications, and commercial challenges,” Poult. Sci., vol. 105, no. 10, p. 107378, 2026, doi: 10.1016/j.psj.2026.107378.
[48] K. P. Uvarajan, “Omics-Driven Insights into Nutrigenomics and Growth Optimization in Aquatic Species,” 2024, aasrresearch.com. [Online]. Available: https://www.aasrresearch.com/index.php/NJSFAI/article/download/307/329
[49] M. E. Hossain and N. B. Amin, “How Close are Modern Broilers to Their Physiological Ceiling? Have Genetic, Nutritional, and Precision Technologies Reached Biological Limits? A Systems Biology Perspective through Physiological Ceiling Theory,” Poult. Sci., p. 107849, 2026, doi: https://doi.org/10.1016/j.psj.2026.107849.
[50] M. Kussmann, F. Raymond, and M. Affolter, “OMICS-driven biomarker discovery in nutrition and health,” J. Biotechnol., 2006, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0168165606001775
[51] A. Salahi and W. A. A. El-Ghany, “Gut microbial signatures in poultry under low- protein diets and lysine restriction: implications for precision nutrition,” Vet. Anim. Sci., vol. 34, no. August, p. 100848, 2026, doi: https://doi.org/10.1016/j.vas.2026.100848.
[52] R. K. Tekade, N. Soni, S. Neetu, and …, “Omics-Driven Novel Technologies in Food and Nutrition Research,” Nutr. …, 2017, doi: 10.1201/9781315153711-2.
[53] O. E. Ojo and S. Kreuzer-Redmer, “MicroRNAs in Ruminants and Their Potential Role in Nutrition and Physiology,” Vet. Sci., vol. 10, no. 1, 2023, doi: 10.3390/vetsci10010057.
[54] B. L. Fan, L. H. Chen, L. L. Chen, and H. Guo, “Integrative Multi-Omics Approaches for Identifying and Characterizing Biological Elements in Crop Traits: Current Progress and Future Prospects,” Int. J. Mol. Sci., vol. 26, no. 4, 2025, doi: 10.3390/ijms26041466.
[55] C. Zhang et al., “Multi-omics reveals that the host-microbiome metabolism crosstalk of differential rumen bacterial enterotypes can regulate the milk protein synthesis of dairy cows,” J. Anim. Sci. Biotechnol., vol. 14, no. 1, p. 63, 2023, doi: 10.1186/s40104-023-00862-z.
[56] Y. Xie et al., “Integrative multi‑omics analysis of lipid metabolism during the growth and development of Qiandongnan Xiaoxiang chickens based on the gut‑muscle axis,” Poult. Sci., vol. 105, no. 8, p. 107001, 2026, doi: 10.1016/j.psj.2026.107001.
[57] Z. Xiong, L. Li, K. Ouyang, M. Qu, and Q. Qiu, “Deciphering Heat Stress Mechanisms and Developing Mitigation Strategies in Dairy Cattle: A Multi-Omics Perspective,” Agric., vol. 15, no. 14, 2025, doi: 10.3390/agriculture15141477.
[58] Z. Liu et al., “Multi-omics analysis reveals the mechanism of rosemary extract supplementation in increasing milk production in Sanhe dairy cows via the ‘rumen- serum-milk’ metabolic pathway,” Anim. Nutr., vol. 23, pp. 396–414, 2025, doi: 10.1016/j.aninu.2025.04.017.
[59] Z. Wang et al., “Multi-omics evaluation of feeding strategies on yak meat quality: insights from eDNA, metagenomics, and metabolomics,” Food Biosci., vol. 69, 2025, doi: 10.1016/j.fbio.2025.106909.
[60] S. Yadav, P. Y. Teng, J. Choi, A. K. Singh, and W. K. Kim, “Nutrient profile and effects of carinata meal as alternative feed ingredient on broiler performance, tight junction gene expression and intestinal morphology,” 2022, Elsevier. doi: 10.1016/j.psj.2021.101411.
[61] A. L. Unger et al., “Harnessing the Magic of the Dairy Matrix for Next-Level Health Solutions: A Summary of a Symposium Presented at Nutrition 2022,” 2023, Elsevier. doi: 10.1016/j.cdnut.2023.100105.
[62] C. Losacco, G. Pugliese, L. Forte, V. Tufarelli, A. Maggiolino, and P. De Palo, “Digital Transition as a Driver for Sustainable Tailor-Made Farm Management: An Up-to-Date Overview on Precision Livestock Farming,” Agric., vol. 15, no. 13, 2025, doi: 10.3390/agriculture15131383.
[63] F. H. Chilton, R. Dutta, L. M. Reynolds, S. Sergeant, and …, “Precision nutrition and omega-3 polyunsaturated fatty acids: A case for personalized supplementation approaches for the prevention and management of …,” 2017, mdpi.com. [Online]. Available: https://www.mdpi.com/2072-6643/9/11/1165
[64] U. E. Obianwuna et al., “Phytobiotics in poultry: revolutionizing broiler chicken nutrition with plant-derived gut health enhancers,” J. Anim. Sci. Biotechnol., vol. 15, no. 1, p. 169, Feb. 2024, doi: 10.1186/s40104-024-01101-9.
[65] A. F. Moss, P. V. Chrystal, D. J. Cadogan, S. J. Wilkinson, T. M. Crowley, and M. Choct, “Precision feeding and precision nutrition: A paradigm shift in broiler feed formulation?,” Anim. Biosci., vol. 34, no. 3, pp. 354–362, 2021, doi: 10.5713/ab.21.0034.
[66] R. N. Zadoks et al., “Nutritional, microbial and environmental perspectives in sustainable broiler production,” Nutr. Res. Rev., vol. 39, p. e27, 2026, doi: DOI: 10.1017/S0954422426100481.
[67] A. Nawab et al., “Evaluation of Precision Feeding to Enhance Broiler Growth Performance,” Animals, vol. 15, no. 16, p. 2433, Feb. 2025, doi: 10.3390/ani15162433.
[68] U. E. Obianwuna, “Phytobiotics in poultry: revolutionizing broiler chicken nutrition with plant-derived gut health enhancers,” 2024, [Online]. Available: http://files/2114/Obianwuna
International Journal of Cell Biology and Cellular Functions
| Volume | 04 | |
| 02 | ||
| Received | 09/10/2026 | |
| Accepted | 13/10/2026 | |
| Published | 23/10/2026 | |
| Publication Time | 14 Days |