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Microbial taxa in dust and excreta associated with the productive performance of commercial meat chicken flocks.
Bindari, Yugal Raj; Moore, Robert J; Van, Thi Thu Hao; Walkden-Brown, Stephen W; Gerber, Priscilla F.
Affiliation
  • Bindari YR; Animal Science, School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
  • Moore RJ; School of Science, RMIT University, Bundoora West Campus, Plenty Rd, Bundoora, VIC, 3083, Australia.
  • Van TTH; School of Science, RMIT University, Bundoora West Campus, Plenty Rd, Bundoora, VIC, 3083, Australia.
  • Walkden-Brown SW; Animal Science, School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
  • Gerber PF; Animal Science, School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia. pgerber2@une.edu.au.
Anim Microbiome ; 3(1): 66, 2021 Oct 02.
Article in En | MEDLINE | ID: mdl-34600571
ABSTRACT

BACKGROUND:

A major focus of research on the gut microbiota of poultry has been to define signatures of a healthy gut and identify microbiota components that correlate with feed conversion. However, there is a high variation in individual gut microbiota profiles and their association with performance. Population level samples such as dust and pooled excreta could be useful to investigate bacterial signatures associated with productivity at the flock-level. This study was designed to investigate the bacterial signatures of high and low-performing commercial meat chicken farms in dust and pooled excreta samples. Poultry house dust and fresh pooled excreta were collected at days 7, 14, 21, 28 and 35 of age from 8 farms of two Australian integrator companies and 389 samples assessed by 16S ribosomal RNA gene amplicon sequencing. The farms were ranked as low (n = 4) or high performers (n = 4) based on feed conversion rate corrected by body weight.

RESULTS:

Permutational analysis of variance based on Bray-Curtis dissimilarities using abundance data for bacterial community structure results showed that company explained the highest variation in the bacterial community structure in excreta (R2 = 0.21, p = 0.001) while age explained the highest variation in the bacterial community structure in dust (R2 = 0.13, p = 0.001). Farm performance explained the least variation in the bacterial community structure in both dust (R2 = 0.03, p = 0.001) and excreta (R2 = 0.01, p = 0.001) samples. However, specific bacterial taxa were found to be associated with high and low performance in both dust and excreta. The bacteria taxa associated with high-performing farms in dust or excreta found in this study were Enterococcus and Candidatus Arthromitus whereas bacterial taxa associated with low-performing farms included Nocardia, Lapillococcus, Brachybacterium, Ruania, Dietzia, Brevibacterium, Jeotgalicoccus, Corynebacterium and Aerococcus.

CONCLUSIONS:

Dust and excreta could be useful for investigating bacterial signatures associated with high and low performance in commercial poultry farms. Further studies on a larger number of farms are needed to determine if the bacterial signatures found in this study are reproducible.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Incidence_studies / Risk_factors_studies Language: En Journal: Anim Microbiome Year: 2021 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Incidence_studies / Risk_factors_studies Language: En Journal: Anim Microbiome Year: 2021 Document type: Article Affiliation country: Australia