Meta-analysis of bovine respiratory microbiota: link between respiratory microbiota and bovine respiratory health

被引:13
作者
Zeineldin, Mohamed [1 ,2 ]
Elolimy, Ahmed A. [3 ,4 ,5 ]
Barakat, Radwa [6 ]
机构
[1] Univ Illinois, Carl R Woese Inst Genom Biol, 3113 IGB,1206 W Gregory Dr, Urbana, IL 61802 USA
[2] Benha Univ, Coll Vet Med, Dept Anim Med, Al Qalyubia 13511, Egypt
[3] Univ Arkansas Med Sci, Dept Pediat, Little Rock, AR 72002 USA
[4] Arkansas Childrens Nutr Ctr, Little Rock, AR 72002 USA
[5] Natl Res Ctr, Dept Anim Prod, Giza 12622, Egypt
[6] Univ Illinois, Dept Comparat Biosci, Urbana, IL 61802 USA
关键词
bovine; meta-analysis; microbiota; respiratory; sequencing; NASOPHARYNGEAL MICROBIOTA; FEEDLOT CATTLE; MANNHEIMIA-HAEMOLYTICA; DAIRY CALVES; RISK-FACTORS; BEEF-CATTLE; DISEASE; PATHOGENS; ASSOCIATIONS; PREVALENCE;
D O I
10.1093/femsec/fiaa127
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Bovine respiratory microbiota plays a significant role in bovine respiratory health. We conducted a meta-analysis using publicly available 16S rRNA gene datasets from the respiratory tract to characterize respiratory microbiota in feedlot cattle. Our aims were to determine the factors that influence microbiota development and to assess the differences in microbiota composition and diversity between healthy calves and those that developed bovine respiratory disease (BRD). Our results showed that the overall composition and diversity of respiratory microbiota in cattle were significantly affected by study design, 16S rRNA hypervariable region sequenced, health status, time since arrival to the feedlot, sampling sites in the respiratory tract and antibiotic treatment. Assessment of diversity indices showed a statistically significant difference between the BRD-affected cattle and healthy control calves. Using multivariate network analysis and Spearman's correlation analyses, we further distinguished the taxa that were commonly associated with BRD when the day of arrival to the feedlot was added to the model. The probability of being identified as BRD was significantly correlated with days 7, 12 and 14 following the calf's arrival to the feedlot. These findings could help in proposing strategies to further evaluate the link between respiratory microbiota and bovine respiratory health.
引用
收藏
页数:16
相关论文
共 66 条
[1]   The microbiome at the pulmonary alveolar niche and its role in Mycobacterium tuberculosis infection [J].
Adami, Alexander J. ;
Cervantes, Jorge L. .
TUBERCULOSIS, 2015, 95 (06) :651-658
[2]   Characterization of the nasopharyngeal microbiota in health and during rhinovirus challenge [J].
Allen, E. Kaitlynn ;
Koeppel, Alex F. ;
Hendley, J. Owen ;
Turner, Stephen D. ;
Winther, Birgit ;
Sale, Michele M. .
MICROBIOME, 2014, 2
[3]   The clinical syndrome of BRD: what it is and what it is not [J].
Apley, Michael .
ANIMAL HEALTH RESEARCH REVIEWS, 2014, 15 (02) :135-137
[4]   Analysis of the Upper Respiratory Tract Microbiotas as the Source of the Lung and Gastric Microbiotas in Healthy Individuals [J].
Bassis, Christine M. ;
Erb-Downward, John R. ;
Dickson, Robert P. ;
Freeman, Christine M. ;
Schmidt, Thomas M. ;
Young, Vincent B. ;
Beck, James M. ;
Curtis, Jeffrey L. ;
Huffnagle, Gary B. .
MBIO, 2015, 6 (02)
[5]   Isolation and identification of Caviibacter abscessus from cervical abscesses in a series of pet guinea pigs (Cavia porcellus) [J].
Bemis, David A. ;
Johnson, Brian H. ;
Bryant, Mary Jean ;
Jones, Rebekah D. ;
McCleery, Brynn V. ;
Greenacre, Cheryl B. ;
Perreten, Vincent ;
Kania, Stephen A. .
JOURNAL OF VETERINARY DIAGNOSTIC INVESTIGATION, 2016, 28 (06) :763-769
[6]  
Bokulich NA, 2013, NAT METHODS, V10, P57, DOI [10.1038/nmeth.2276, 10.1038/NMETH.2276]
[7]   Upper and lower respiratory tract microbiota in horses: bacterial communities associated with health and mild asthma (inflammatory airway disease) and effects of dexamethasone [J].
Bond, Stephanie L. ;
Timsit, Edouard ;
Workentine, Matthew ;
Alexander, Trevor ;
Leguillette, Renaud .
BMC MICROBIOLOGY, 2017, 17
[8]   The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies [J].
Brooks, J. Paul ;
Edwards, David J. ;
Harwich, Michael D., Jr. ;
Rivera, Maria C. ;
Fettweis, Jennifer M. ;
Serrano, Myrna G. ;
Reris, Robert A. ;
Sheth, Nihar U. ;
Huang, Bernice ;
Girerd, Philippe ;
Strauss, Jerome F., III ;
Jefferson, Kimberly K. ;
Buck, Gregory A. .
BMC MICROBIOLOGY, 2015, 15
[9]   QIIME allows analysis of high-throughput community sequencing data [J].
Caporaso, J. Gregory ;
Kuczynski, Justin ;
Stombaugh, Jesse ;
Bittinger, Kyle ;
Bushman, Frederic D. ;
Costello, Elizabeth K. ;
Fierer, Noah ;
Pena, Antonio Gonzalez ;
Goodrich, Julia K. ;
Gordon, Jeffrey I. ;
Huttley, Gavin A. ;
Kelley, Scott T. ;
Knights, Dan ;
Koenig, Jeremy E. ;
Ley, Ruth E. ;
Lozupone, Catherine A. ;
McDonald, Daniel ;
Muegge, Brian D. ;
Pirrung, Meg ;
Reeder, Jens ;
Sevinsky, Joel R. ;
Tumbaugh, Peter J. ;
Walters, William A. ;
Widmann, Jeremy ;
Yatsunenko, Tanya ;
Zaneveld, Jesse ;
Knight, Rob .
NATURE METHODS, 2010, 7 (05) :335-336
[10]   Associations between weather conditions during the first 45 days after feedlot arrival and daily respiratory disease risks in autumn-placed feeder cattle in the United States [J].
Cernicchiaro, N. ;
Renter, D. G. ;
White, B. J. ;
Babcock, A. H. ;
Fox, J. T. .
JOURNAL OF ANIMAL SCIENCE, 2012, 90 (04) :1328-U329