1%), Firmicutes

(1,651 of 7,028 OTUs, 23 5%), Actinobacte

1%), Firmicutes

(1,651 of 7,028 OTUs, 23.5%), Actinobacteria (874 of 7,028 OTUs, 12.4%), Bacteroidetes (466 of 7,028 OTUs, 6.6%) and Cyanobacteria (222 of 7,028 OTUs, 3.2%). Proteobacteria were still dominant in the bacterial populations after treatments. In trees receiving the antibiotic combinations KO and PS, the average OTUs over sampling time points accounted for 44.5% and 44.2%, respectively, of the treated populations, while they represented 38.9% of the control population. Proteobacteria were also dominant in the bacterial population at all sampling time points. The average signaling pathway OTUs in the antibiotic treatments accounted for 44.1%, 43.9% and 38.6% of the bacterial population in October 2010, April 2011, and October 2011, respectively. When compared to the bacterial populations in the leaves of

trees receiving the water control CHIR 99021 treatment, the Bacteroidete population decreased (Pr<0.05) by 65.3% and 51.8% in the leaves of trees receiving the KO and PS treatments, respectively (Additional file 1: Table S1). The PhyloChip data indicated a change in the community profile over the sampling time points and showed fewer unique OTUs in populations subjected to antibiotic treatments (Additional {Selleck Anti-infection Compound Library|Selleck Antiinfection Compound Library|Selleck Anti-infection Compound Library|Selleck Antiinfection Compound Library|Selleckchem Anti-infection Compound Library|Selleckchem Antiinfection Compound Library|Selleckchem Anti-infection Compound Library|Selleckchem Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|Anti-infection Compound Library|Antiinfection Compound Library|buy Anti-infection Compound Library|Anti-infection Compound Library ic50|Anti-infection Compound Library price|Anti-infection Compound Library cost|Anti-infection Compound Library solubility dmso|Anti-infection Compound Library purchase|Anti-infection Compound Library manufacturer|Anti-infection Compound Library research buy|Anti-infection Compound Library order|Anti-infection Compound Library mouse|Anti-infection Compound Library chemical structure|Anti-infection Compound Library mw|Anti-infection Compound Library molecular weight|Anti-infection Compound Library datasheet|Anti-infection Compound Library supplier|Anti-infection Compound Library in vitro|Anti-infection Compound Library cell line|Anti-infection Compound Library concentration|Anti-infection Compound Library nmr|Anti-infection Compound Library in vivo|Anti-infection Compound Library clinical trial|Anti-infection Compound Library cell assay|Anti-infection Compound Library screening|Anti-infection Compound Library high throughput|buy Antiinfection Compound Library|Antiinfection Compound Library ic50|Antiinfection Compound Library price|Antiinfection Compound Library cost|Antiinfection Compound Library solubility dmso|Antiinfection Compound Library purchase|Antiinfection Compound Library manufacturer|Antiinfection Compound Library research buy|Antiinfection Compound Library order|Antiinfection Compound Library chemical structure|Antiinfection Compound Library datasheet|Antiinfection Compound Library supplier|Antiinfection Compound Library in vitro|Antiinfection Compound Library cell line|Antiinfection Compound Library concentration|Antiinfection Compound Library clinical trial|Antiinfection Compound Library cell assay|Antiinfection Compound Library screening|Antiinfection Compound Library high throughput|Anti-infection Compound high throughput screening| file 1: Table S1; Figure 3A). The lowest number of OTUs was detected in April 2011 after the antibiotics had been applied four times (Additional file 1: Table S1). The phylum Bacteriodetes, and specifically the class Flavobacteria, significantly decreased (Pr<0.05). While the phylum Proteobacteria did not decrease, both the classes α- and β-proteobacteria did decrease significantly (Pr<0.05). OTUs within the order of Rhizobiales and the family of Rhizobiaceae were significantly decreased by the antibiotic treatments. Shannon’s and Simpson’s indices both revealed greater diversity in the water control (Figure 3B), indicating that antibiotic treatments lead to HA-1077 chemical structure lower phylum diversity. Figure 3 Bacterial richness

and diversity in phyla detected by PhyloChip™ G3 hybridization of Huanglongbing (HLB)-affected citrus. The citrus plants were treated with different antibiotic combinations, and leaf samples were collected at different times (October 2010, April 2011 and October 2011) over a year. A, Total operational taxonomic units (OTUs) in each treatment; B, Simpson’s diversity index (SDI) and Shannon-Weiner index (DIT). Each bar represents the coded relative abundance of bacteria in a single phylum. For each treatment, the Simpson’s and Shannon’s diversity statistics, which reflect both species numbers and evenness of species distribution, were plotted below the histogram. PS: 5 g/tree penicillin G potassium and 0.5 g/tree streptomycin; KO: 2 g/tree oxytetracycline and 1.0 g/tree kasugamycin; and CK: water as control.

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