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Original Articles

Enzootic situation and molecular epidemiology of Brucella in livestock from 2011 to 2015 in Qingyang, China

, , , , , , , , & show all
Pages 1-8 | Received 26 Sep 2017, Accepted 25 Feb 2018, Published online: 04 Apr 2018

Figures & data

Sample size and positive number of different animals from 2011 to 2015 years

Fig. 1 The seroprevalence of brucellosis in livestock in Qingyang from 2011 to 2015.

a The positive rates of the different counties in each year. b Differential analysis of brucellosis in different counties from 2011 to 2015. Bar, the average seroprevalence from 2011 to 2015; *Significant difference at P < 0.05. c Sample sizes and positively detected cases in the dairy cow brucellosis epidemic in Qingyang from 2011 to 2015. d Dairy cow brucellosis epidemic tendency in Qingyang from 2011 to 2015

Fig. 1 The seroprevalence of brucellosis in livestock in Qingyang from 2011 to 2015.a The positive rates of the different counties in each year. b Differential analysis of brucellosis in different counties from 2011 to 2015. Bar, the average seroprevalence from 2011 to 2015; *Significant difference at P < 0.05. c Sample sizes and positively detected cases in the dairy cow brucellosis epidemic in Qingyang from 2011 to 2015. d Dairy cow brucellosis epidemic tendency in Qingyang from 2011 to 2015
Fig. 2 The seroprevalence of brucellosis in sheep from 2011 to 2015.

a The positive rates of the different counties in each year from 2011 to 2015. b Sheep brucellosis epidemic tendency in Qingyang from 2011 to 2015. c Sheep brucellosis epidemic tendencies in different counties in Qingyang from 2011 to 2015. d Differential analysis of the seroprevalence in different counties in Qingyang. Bar, the average seroprevalence from 2011 to 2015; **Very significant difference at P < 0.01

Fig. 2 The seroprevalence of brucellosis in sheep from 2011 to 2015.a The positive rates of the different counties in each year from 2011 to 2015. b Sheep brucellosis epidemic tendency in Qingyang from 2011 to 2015. c Sheep brucellosis epidemic tendencies in different counties in Qingyang from 2011 to 2015. d Differential analysis of the seroprevalence in different counties in Qingyang. Bar, the average seroprevalence from 2011 to 2015; **Very significant difference at P < 0.01
Fig. 3 Geographic distribution of the seroprevalence of brucellosis in livestock in Qingyang, China.

Red area: seroprevalence of 2.71%; yellow area: seroprevalence between 1.50 and 1.90%; gray area: seroprevalence <1%

Fig. 3 Geographic distribution of the seroprevalence of brucellosis in livestock in Qingyang, China.Red area: seroprevalence of 2.71%; yellow area: seroprevalence between 1.50 and 1.90%; gray area: seroprevalence <1%
Fig. 4 AMOS-PCR of isolates in Qingyang.

Lane 1: 100-bp DNA ladder; 2: B. melitensis bv. 1 (16 M reference strain); 3: B. abortus 544; 4: B. suis bv. 1 (S2 vaccine); 5–14: the 10 B. melitensis isolates

Fig. 4 AMOS-PCR of isolates in Qingyang.Lane 1: 100-bp DNA ladder; 2: B. melitensis bv. 1 (16 M reference strain); 3: B. abortus 544; 4: B. suis bv. 1 (S2 vaccine); 5–14: the 10 B. melitensis isolates
Fig. 5 Dendrogram based on the MLVA-11 genotyping assay showing the relationships among the Brucella isolates.

Strain: isolate number; Origin: sample collection area; Host: host from which the strain was isolated; Year: time of isolation

Fig. 5 Dendrogram based on the MLVA-11 genotyping assay showing the relationships among the Brucella isolates.Strain: isolate number; Origin: sample collection area; Host: host from which the strain was isolated; Year: time of isolation
Fig. 6 Phylogenetic tree based on the whole genomes of nine selected B. melitensis strains.

The evolutionary history was inferred using the neighbor-joining method. The optimal tree (with branch length sum = 0.00316668) is shown. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree

Fig. 6 Phylogenetic tree based on the whole genomes of nine selected B. melitensis strains.The evolutionary history was inferred using the neighbor-joining method. The optimal tree (with branch length sum = 0.00316668) is shown. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree
Supplemental material

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