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In-depth immunophenotyping reveals significant alteration of lymphocytes in buffalo with brucellosis.

Francesco GrandoniFederica SignorelliAlessandra MartuccielloFrancesco NapolitanoImmacolata De DonatoAnna DonniacuoGabriele Di VuoloGiovanna De MatteisGenny Del ZottoWilliam C DavisEsterina De Carlo
Published in: Cytometry. Part A : the journal of the International Society for Analytical Cytology (2023)
Water buffalo (Bubalus bubalis) has a prominent position in the livestock industry worldwide but still suffers from limited knowledge on the mechanisms regulating the immune against infections, including brucellosis (BRC), one of the most significant neglected zoonotic diseases of livestock. Seventy-three buffalo were recruited for the study. Thirty-five were naturally infected with Brucella spp. The aims of the study were to (i) verify the cross-reactivity of 16 monoclonal antibodies (mAbs) developed against human, bovine, and ovine antigens; (ii) evaluate lymphocyte subset alterations in BRC positive buffalo; (iii) evaluate the use of the canonical discriminant analysis (CDA), with flow cytometric data, to discriminate BRC positive from negative animals. A new set of eight mAbs (anti CD3e, CD16, CD18, CD45R0, CD79a; CD172a) were shown to cross-react with water buffalo orthologous molecules. BRC positive animals presented a significant (p < 0.0001) decrease in the percentage of PBMC (29.5 vs. 40.3), total, T and B lymphocytes (23.0 vs. 35.5, 19.2 vs. 28.9, 2.6 vs. 5.7, respectively). In contrast, they showed an increase in percentage of granulocytes (65.2 vs. 55.1; p < 0.0001) and B lymphocytes CD21 neg (22.9 vs. 16.1; p = 0.0067), a higher T/B lymphocyte ratio (10.3 vs. 6.4; p = 0.0011) and CD3 + /CD21 + (14.7 vs. 8.3; p = 0.0005) ratio. The CDA, applied to 33 different flow cytometric traits, allowed the discrimination of all BRC positive from negative buffalo. Although this is a preliminary study, our results show that flow cytometry can be used in a wide range of applications in livestock diseases, including in support of uncertain BRC diagnoses.
Keyphrases
  • peripheral blood
  • flow cytometry
  • nk cells
  • healthcare
  • endothelial cells
  • magnetic resonance
  • computed tomography
  • gene expression
  • immune response
  • machine learning
  • dna methylation
  • genome wide
  • big data