Species identification of adult ixodid ticks by Raman spectroscopy of their feces.

Raman spectroscopy Tick feces Tick-infested cattle

Journal

Parasites & vectors
ISSN: 1756-3305
Titre abrégé: Parasit Vectors
Pays: England
ID NLM: 101462774

Informations de publication

Date de publication:
30 Jan 2024
Historique:
received: 02 10 2023
accepted: 11 12 2023
medline: 31 1 2024
pubmed: 31 1 2024
entrez: 30 1 2024
Statut: epublish

Résumé

Ticks and tick-borne diseases pose significant challenges to cattle production, thus the species identification of ticks and knowledge on their presence, abundance, and dispersal are necessary for the development of effective control measures. The standard method of inspection for the presence of ticks is the visual and physical examination of restrained animals, but the limitations of human sight and touch can allow larval, nymphal, and unfed adult ticks to remain undetected due to their small size and site of attachment. However, Raman spectroscopy, an analytical tool widely used in agriculture and other sectors, shows promise for the identification of tick species in infested cattle. Raman spectroscopy is a non-invasive and efficient method that employs the interaction between molecules and light for the identification of the molecular constituents of specimens. Raman spectroscopy was employed to analyze the structure and composition of tick feces deposited on host skin and hair during blood-feeding. Feces of 12 species from a total of five genera and one subgenus of ixodid ticks were examined. Spectral data were subjected to partial least squares discriminant analysis, a machine-learning model. We also used Raman spectroscopy and the same analytical procedures to compare and evaluate feces of the horn fly Haematobia irritans after it fed on cattle. Five genera and one sub-genus at overall true prediction rates ranging from 92.3 to 100% were identified from the Raman spectroscopy data of the tick feces. At the species level, Dermacentor albipictus, Dermacentor andersoni and Dermacentor variabilis at overall true prediction rates of 100, 99.3 and 100%, respectively, were identified. There were distinct differences between horn fly and tick feces with respect to blood and guanine vibrational frequencies. The overall true prediction rate for the separation of tick and horn fly feces was 98%. Our findings highlight the utility of Raman spectroscopy for the reliable identification of tick species from their feces, and its potential application for the identification of ticks from infested cattle in the field.

Sections du résumé

BACKGROUND BACKGROUND
Ticks and tick-borne diseases pose significant challenges to cattle production, thus the species identification of ticks and knowledge on their presence, abundance, and dispersal are necessary for the development of effective control measures. The standard method of inspection for the presence of ticks is the visual and physical examination of restrained animals, but the limitations of human sight and touch can allow larval, nymphal, and unfed adult ticks to remain undetected due to their small size and site of attachment. However, Raman spectroscopy, an analytical tool widely used in agriculture and other sectors, shows promise for the identification of tick species in infested cattle. Raman spectroscopy is a non-invasive and efficient method that employs the interaction between molecules and light for the identification of the molecular constituents of specimens.
METHODS METHODS
Raman spectroscopy was employed to analyze the structure and composition of tick feces deposited on host skin and hair during blood-feeding. Feces of 12 species from a total of five genera and one subgenus of ixodid ticks were examined. Spectral data were subjected to partial least squares discriminant analysis, a machine-learning model. We also used Raman spectroscopy and the same analytical procedures to compare and evaluate feces of the horn fly Haematobia irritans after it fed on cattle.
RESULTS RESULTS
Five genera and one sub-genus at overall true prediction rates ranging from 92.3 to 100% were identified from the Raman spectroscopy data of the tick feces. At the species level, Dermacentor albipictus, Dermacentor andersoni and Dermacentor variabilis at overall true prediction rates of 100, 99.3 and 100%, respectively, were identified. There were distinct differences between horn fly and tick feces with respect to blood and guanine vibrational frequencies. The overall true prediction rate for the separation of tick and horn fly feces was 98%.
CONCLUSIONS CONCLUSIONS
Our findings highlight the utility of Raman spectroscopy for the reliable identification of tick species from their feces, and its potential application for the identification of ticks from infested cattle in the field.

Identifiants

pubmed: 38291487
doi: 10.1186/s13071-023-06091-7
pii: 10.1186/s13071-023-06091-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

43

Subventions

Organisme : US Department of Homeland Security
ID : 18STCBT00001
Organisme : US Department of Homeland Security
ID : 18STCBT00001
Organisme : US Department of Homeland Security
ID : 18STCBT00001
Organisme : US Department of Homeland Security
ID : 18STCBT00001
Organisme : Animal and Plant Health Inspection Service
ID : M2100259
Organisme : Animal and Plant Health Inspection Service
ID : M2100259
Organisme : Animal and Plant Health Inspection Service
ID : M2100259

Informations de copyright

© 2024. The Author(s).

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Auteurs

Tianyi Dou (T)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.

Aidan P Holman (AP)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.
Department of Entomology, Texas A&M AgriLife Research, College Station, TX, 77843, USA.

Samantha R Hays (SR)

Department of Entomology, Texas A&M AgriLife Research, College Station, TX, 77843, USA.

Taylor G Donaldson (TG)

Department of Entomology, Texas A&M AgriLife Research, College Station, TX, 77843, USA.

Nicolas Goff (N)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.

Pete D Teel (PD)

Department of Entomology, Texas A&M AgriLife Research, College Station, TX, 77843, USA. Pete.Teel@ag.tamu.edu.

Dmitry Kurouski (D)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.
Department of Biomedical Engineering, Texas A&M University, College Station, TX, 77843, USA.

Classifications MeSH