Abstract: Foals that develop pulmonary ultrasonographic lesions on Rhodococcus equi (R. equi) endemic farms are treated with antibiotics because those at risk of developing clinical pneumonia (~20%) cannot be recognised early. Candidate biomarkers identified using metabolomics may aid targeted treatment strategies against R. equi. Objective: (1) To describe how foal ageing affects their plasma metabolome (birth to 8 weeks) and (2) to establish the effects that experimental infection with Rhodococcus equi (R. equi) has on foal metabolome. Methods: Experimental study. Methods: Nine healthy newborn foals were experimentally infected with R. equi as described in a previous study. Foals were treated with oral antibiotics if they developed clinical pneumonia (n = 4, clinical group) or remained untreated if they showed no signs of disease (n = 5, subclinical group). A group of unchallenged foals (n = 4) was also included in the study. By the end of the study period (8 weeks), all foals were free of disease. This status was confirmed with transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography. Plasma metabolomics was determined by GC-MS weekly for the study duration (8 weeks). Results: Foals' plasma metabolome was altered by ageing (birth to 8 weeks) and experimental infection with R. equi as demonstrated using multivariate statistical analysis. The intensities of 25 and 28 metabolites were altered by ageing and infection (p < 0.05) respectively. Furthermore, 20 metabolites changed by more than 2-fold between clinical and subclinical groups. Conclusions: The number of foals is limited. Foals were experimentally infected with R. equi. Conclusions: Ageing and R. equi infection induced changes in the plasma metabolome of foals. These results provide an initial description of foal's plasma metabolome and serve as background for future identification of R. equi pneumonia biomarkers. Unassigned: Les poulains qui développent des lésions pulmonaires échographiques dans les fermes d'élevage où Rhodococcus equi (R. equi) est endémique sont traités avec antibiotiques car ceux à risque de développer des lésions cliniques (~20%) ne peuvent être identifiés précocement. Certains biomarqueurs identifiés par le biais de la métabolomique pourraient aider à orienter les stratégies de traitement pour R. equi. Objective: (1) Décrire les changements de métabolome plasmatique qui surviennent chez les poulains en lien avec l'âge (naissance jusqu'à 8 semaines d'âge) et (2) Établir les effets d'une infection expérimentale à Rhodococcus Equi sur le métabolome des poulains. TYPE D'ÉTUDE: Étude expérimentale. MÉTHODES: Neufs poulains nouveaux-nés en santé ont été infectés de façon expérimentale par R. equi tel que décrit précédemment. Ils ont été traités avec des antibiotiques s'ils ont développé une pneumonie clinique (n = 4, groupe clinique) ou ont simplement été suivi dans le temps s'ils n'ont pas montré de signes de la maladie (n = 5, groupe sous-clinique). Un groupe de poulains sains (n = 4) était aussi inclus dans l'étude. À la fin de l'étude (8 semaines), tous les poulains étaient sains tel que confirmé par l'évaluation et la culture de leur fluide de lavage transtrachéal de même qu'à l'échographie thoracique. Les métabolomiques plasmastiques ont été déterminées par GC-MS de façon hebdomadaire pour la durée de l'étude (8 semaines). RÉSULTATS: À la fois l'âge et l'infection expérimentale ont altéré le métabolome plasmatique des poulains tel que démontré par l'analyse statistique multivariée. L'âge a altéré l'intensité de 25 métabolites et l'infection a modifié l'intensité de 28 métabolites (p < 0.05). De plus, 20 métabolites ont changé de plus de 2 fois leur valeur initiale, entre les groupes cliniques et sous-cliniques. Unassigned: Le nombre de poulains reste limité. Les poulains ont été infecté par R. equi de façon expérimentale. Conclusions: Le vieillissement et l'infection par R. equi induisent des changements dans le métabolome plasmatique des poulains. Ces résultats représentent une description initiale du métabolome plasmatique chez le poulain et peuvent servir de base pour l'identification future de biomarqueurs pour la détection de pneumonie à Rhodococcus equi.
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.
This research investigates the effects of aging and Rhodococcus equi infection on the plasma metabolome of foals. The study reveals changes in plasma metabolites due to both factors, with significant differences identified between foals exhibiting signs of pneumonia and those that were not symptomatic.
Research Objective and Methods
The research had two main objectives. Firstly, the researchers aimed to understand the changes in the plasma metabolome of foals as they age, from birth to eight weeks. Secondly, they sought to study the impact of an experimental Rhodococcus equi infection on the foals’ metabolome.
The research was experimental in nature and involved nine newborn healthy foals.
Each foal was intentionally infected with Rhodococcus equi as per methods detailed in a previous study.
If a foal developed clinical pneumonia, treatment with antibiotics was initiated (four foals fell into this clinical group). If a foal did not show signs of the disease, it was left untreated (five foals were in this subclinical group). A separate group of unchallenged foals was also included for study (this group consisted of four foals).
The foals were observed until they were eight weeks old. At this point, all foals were confirmed to be free of disease through a transtracheal wash fluid evaluation, culture, and thoracic ultrasonography.
The plasma metabolome of each foal was studied using Gas Chromatography-Mass Spectrometry (GC-MS) on a weekly basis for the duration of the study.
Research Results
Aging (birth to 8 weeks) and experimental Rhodococcus equi infection resulted in alterations in the foals’ plasma metabolome. This was determined through multivariate statistical analysis of the GC-MS results.
25 metabolites were identified with alterations linked to the aging process, and 28 metabolites had alterations associated with the infection. These alterations were significant (p < 0.05).
A clear differentiation was shown between the clinical and subclinical groups. In fact, 20 metabolites demonstrated more than a two-fold change between these two groups.
Conclusions and Limitations
The study concluded that both aging and Rhodococcus equi infection contribute to significant changes in the plasma metabolome of foals. The observed differences between clinical and subclinical groups suggest potential biomarkers for pneumonia.
However, the research was limited by the number of foals involved in the study and by the use of experimental infection. More work, with larger sample sizes and natural infections, is needed to validate these observations and further understand the potential of metabolomic analysis as a tool for Rhodococcus equi pneumonia identification.
Cite This Article
APA
Sanclemente JL, Rivera-Velez SM, Horohov DW, Dasgupta N, Sanz MG.
(2022).
Plasma metabolome of healthy and Rhodococcus equi-infected foals over time.
Equine Vet J, 55(5), 831-842.
https://doi.org/10.1111/evj.13894
Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA.
Rivera-Velez, Sol M
Molecular Determinants Core, Johns Hopkins All Children's Hospital, St Petersburg, Florida, USA.
Horohov, David W
Maxwell H. Gluck Equine Research Center, Department of Veterinary Clinical Sciences, University of Kentucky, Lexington, Kentucky, USA.
Dasgupta, Nairanjana
Department of Mathematics and Statistics, College of Arts and Sciences, Washington State University, Pullman, Washington, USA.
Sanz, Macarena G
Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA.
MeSH Terms
Animals
Horses
Rhodococcus equi
Actinomycetales Infections / veterinary
Horse Diseases / epidemiology
Pneumonia / veterinary
Metabolome
Anti-Bacterial Agents
Grant Funding
CVM Intramural Research Fund, WSU
References
This article includes 67 references
Cohen ND, Chaffin MK, Martens RJ. Control and prevention of pneumonia in foals caused by Rhodococcus equi. Compend Contin Educ Pract Vet 2000;22:1062-70.
Boyen F, Pasmans F, Haesebrouck F. Short communications: acquired antimicrobial resistance in equine Rhodococcus equi isolates. Vet Rec 2011;168(4):101a.
Rivera-Velez SM, Broughton-Neiswanger LE, Suarez MA, Slovak JE, Hwang JK, Navas J. Understanding the effect of repeated administration of meloxicam on feline renal cortex and medulla: a lipidomics and metabolomics approach. J Vet Pharmacol Ther 2019;42(4):476-86.
Fanos V, Iacovidou N, Puddu M, Ottonello G, Noto A, Atzori L. Metabolomics in neonatal life. Early Hum Dev 2013;89(Suppl 1):S7-10.
Silva CAM, Graham B, Webb K, Ashton LV, Harton M, Luetkemeyer AF. A pilot metabolomics study of tuberculosis immune reconstitution inflammatory syndrome. Int J Infect Dis 2019;84:30-8.
du Preez I, Luies L, Loots DT. The application of metabolomics toward pulmonary tuberculosis research. Tuberculosis (Edinb) 2019;115:126-39.
Rahman MT, Herron LL, Kapur V, Meijer WG, Byrne BA, Ren J. Partial genome sequencing of Rhodococcus equi ATCC 33701. Vet Microbiol 2003;94(2):143-58.
Frediani JK, Jones DP, Tukvadze N, Uppal K, Sanikidze E, Kipiani M. Plasma metabolomics in human pulmonary tuberculosis disease: a pilot study. PLoS One 2014;9(10):e108854.
Weiner J 3rd, Parida SK, Maertzdorf J, Black GF, Repsiliber D, Telaar A. Biomarkers of inflammation, immunosuppression and stress with active disease are revealed by metabolomic profiling of tuberculosis patients. PLoS One 2012;7(7):e40221.
Zhou A, Ni J, Xu Z, Wang Y, Lu S, Sha W. Application of (1)h NMR spectroscopy-based metabolomics to sera of tuberculosis patients. J Proteome Res 2013;12(10):4642-9.
Fiehn O, Kind T. Metabolite profiling in blood plasma. Methods Mol Biol 2007;358:3-17.
Sumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA. Proposed minimum reporting standards for chemical analysis: chemical analysis working group (CAWG) metabolomics standards initiative (MSI). Metabolomics 2007;3:211-21.
Fiehn O, Wohlgemuth G, Scholz M. Setup and annotation of metabolomic experiments by integrating biological and mass spectrometric metadata. Lect Notes Bioinformatics (Subseries Lect Notes Comput Sci) 2005;3615:224-39.
Wishart DS, Guo A, Oler E, Wang F, Anjum A, Peters H. HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Res 2022;50:D622-D631.
Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res 2021;49:D545-D551.
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res 2021;49:D1388-D1395.
The Metabolomics Workbench National Metabolomics Data Repository. https://www.metabolomicsworkbench.org/.
ChemSpider - Royal Society of Chemistry. Home Page. http://www.chemspider.com/.
Bjerrum JT, Nielsen OH, Wang YL, Olsen J. Technology insight: metabonomics in gastroenterology - basic principles and potential clinical applications. Nat Clin Pract Gastroenterol Hepatol 2008;5:332-43.
Rivera-Velez SM, Broughton-Neiswanger LE, Suarez M, Piñeyro P, Navas J, Chen S. Repeated administration of the NSAID meloxicam alters the plasma and urine lipidome. Sci Rep 2019;9:1-11.
Chong J, Wishart DS, Xia J. Using MetaboAnalyst 4.0 for comprehensive and integrative metabolomics data analysis. Curr Protoc Bioinformatics 2019;68:1-128.
Queiroz A, Pinto IFD, Lima M, Giovanetti M, Goes de Jesus J, Xavier J. Lipidomic analysis reveals serum alteration of plasmalogens in patients infected with ZIKA virus. Front Microbiol 2019;10:1-10.
Rosa F, Matazel KS, Elolimy AA, Adams SH, Bowlin A, Williams KD. Human milk-fed piglets have a distinct small intestine and circulatory metabolome profile relative to that of milk formula-fed piglets. mSystems 2021;6(1):e01376-20.
Potočnik K, Cantner V, Kuterovac K, Cividini A. Mare's milk: composition and protein fraction in comparison with different milk species. Mljekarstvo 2011;61:107-13.
Scalabre A, Jobard E, Demede D, Gaillard S, Pontoizeau C, Mouriquand P. Evolution of newborns' urinary metabolomic profiles according to age and growth. J Proteome Res 2017;16(10):3732-40.
Salamon RV, Salamon S, Csapó-Kiss Z, Csapó J. Composition of mare's colostrum and milk I. Fat content, fatty acid composition and vitamin contents. Acta Univ Sapientiae Alimentaria 2009;2:119-31.
Csapó J, Stefler J, Martin TG, Makray S, Csapó-Kiss Z. Composition of mares' colostrum and milk. Fat content, fatty acid composition and vitamin content. Int Dairy J 1995;5:393-402.
Dessi A, Murgia A, Agostino R, Pattumelli MG, Schirru A, Scano P. Exploring the role of different neonatal nutrition regimens during the first week of life by urinary GC-MS metabolomics. Int J Mol Sci 2016;17(2):265.
Thomas B, Gruca LL, Bennett C, Parimi PS, Hanson RW, Kalhan SC. Metabolism of methionine in the newborn infant: response to the parenteral and enteral administration of nutrients. Pediatr Res 2008;64(4):381-6.
Stadtman ER, Van Remmen H, Richardson A, Wehr NB, Levine RL. Methionine oxidation and aging. Biochim Biophys Acta 2005;1703(2):135-40.
Liu S, He L, Yao K. The antioxidative function of alpha-ketoglutarate and its applications. Biomed Res Int 2018;2018:3408467.
Khoo KH, Suzuki R, Dell A, Morris HR, McNeil MR, Brennan PJ. Chemistry of the lyxose-containing mycobacteriophage receptors of Mycobacterium phlei/Mycobacterium smegmatis. Biochemistry 1996;35(36):11812-9.
Pieszka M, Luszczynski J, Zamachowska M, Dlugosz B, Hedrzak M. Is mare milk and appropriate food for people? - A review. Ann Anim Sci 2016;16(1):33-51.
Dempsey DA, Klessig DF. How does the multifaceted plant hormone salicylic acid combat disease in plants and are similar mechanisms utilized in humans?. BMC Biol 2017;15(1):23.
Hooftman A, O'Neill LAJ. The immunomodulatory potential of the metabolite itaconate. Trends Immunol 2019;40(8):687-98.
Sorgdrager FJH, Naude PJW, Kema IP, Nollen EA, Deyn PP. Tryptophan metabolism in inflammaging: from biomarker to therapeutic target. Front Immunol 2019;10:2565.
Fernandez-Garcia M, Rey-Stolle F, Boccard J, Reddy VP, Garcia A, Cumming BM. Comprehensive examination of the mouse lung metabolome following mycobacterium tuberculosis infection using a multiplatform mass spectrometry approach. J Proteome Res 2020;19(5):2053-70.
Meier MA, Ottiger M, Vogeli A, Steuer C, Bernasconi L, Thomann R. Activation of the tryptophan/serotonin pathway is associated with severity and predicts outcomes in pneumonia: results of a long-term cohort study. Clin Chem Lab Med 2017;55(7):1060-9.
Weinstock DM, Brown AE. Rhodococcus equi: an emerging pathogen. Clin Infect Dis 2002;34(10):1379-85.
Zhou B, Lou B, Liu J, She J. Serum metabolite profiles as potential biochemical markers in young adults with community-acquired pneumonia cured by moxifloxacin therapy. Sci Rep 2020;10(1):4436.
Ivanov AV, Bartosch B, Isaguliants MG. Oxidative stress in infection and consequent disease. Oxid Med Cell Longev 2017;2017:3496043.
Sato F, Hasegawa T. Changes in serum concentration of uric acid and allantoin due to exhaustive treadmill exercise. J Equine Sci 1999;10(2):45-8.
Dadmarz M, vd Burg C, Milakofsky L, Hofford JM, Vogel WH. Effects of stress on amino acids and related compounds in various tissues of fasted rats. Life Sci 1998;63(16):1485-91.
Inoue S, Ikeda H. Differences in plasma amino acid levels in patients with and without bacterial infection during the early stage of acute exacerbation of COPD. Int J Chron Obstruct Pulmon Dis 2019;14:575-83.
Ogle CK, Ogle JD, Mao JX, Simon J, Noel JG, Li BG. Effect of glutamine on phagocytosis and bacterial killing by normal and pediatric burn patient neutrophils. JPEN J Parenter Enteral Nutr 1994;18(2):128-33.
Kim H. Glutamine as an immunonutrient. Yonsei Med J 2011;52(6):892-7.
Wu N, Yang M, Gaur U, Xu H, Yao Y, Li D. Alpha-ketoglutarate: physiological functions and applications. Biomol Ther (Seoul) 2016;24(1):1-8.
Ikeda H. Plasma amino acid in patients with bacterial pneumonia. In: B57. Clinical studies in lung infections: risk factors and biomarkers, American Thoracic Society. 2019;199:A3679-A3679.
Banoei MM, Vogel HJ, Weljie AM, Kumar A, Yende S, Angus DC. Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia. Crit Care 2017;21(1):97.
Ibarra R, Dazard JE, Sandlers Y, Rehman F, Abbas R, Kombu R. Metabolomic analysis of liver tissue from the VX2 rabbit model of secondary liver tumors. HPB Surg 2014;2014:310372.
Steenbergen R, Oti M, Ter Horst R, Tat W, Neufeldt C, Belovodskiy A. Establishing normal metabolism and differentiation in hepatocellular carcinoma cells by culturing in adult human serum. Sci Rep 2018;8(1):11685.
McReynolds CB, Cortes-Puch I, Ravindran R, Khan IH, Hammock BG, Shih P-AB. Plasma linoleate diols are potential biomarkers for severe COVID-19 infections. Front Physiol 2021;12:663869.
Laiakis EC, Morris GA, Fornace AJ, Howie SR. Metabolomic analysis in severe childhood pneumonia in The Gambia, West Africa: findings from a pilot study. PLoS One 2010;5(9):e12655.