Interactions between antibiotic resistance, soil microbial communities, and coupled elemental cycles

4 5 6 7 8

ampC (log copies g dry wt soil-1)

HighLow

y = 0.31x - 1.48F1,20 = 14.25P < 0.01r2 = 0.42

2 4 6 8 100.0

0.2

0.4

0.6

0.8

1.0

tetO (log copies g dry wt soil-1)

Rm

ass

(CO

2-C

(mg µ

g m

icro

bial

bio

mas

s-1 )

)

y = 0.14x - 0.57F1,20 = 15.33P < 0.001r2 = 0.43

4 5 6 7 8

ampC (log copies g dry wt soil-1)

HighLow

y = 0.31x - 1.48F1,20 = 14.25P < 0.01r2 = 0.42

HighLow

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Inputs

Rm

ass

(CO

2-C

(mg µ

g m

icro

bial

bio

mas

s-1))

*

-3 -2 -1 0 1 2-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

NMDS1

NMDS2

HighLow

Stress = 0.11

Michael S. Strickland1, Katharine F. Knowlton2, Brian Badgley3, John E. Barrett1, Carl Wepking1, Kevan Minick1 1Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061. 2Department of Dairy Science, Virginia Tech, Blacksburg, VA 24061. 3Department of Crop & Soil Environmental Sciences, Virginia Tech, Blacksburg, VA 24061.

1. Antibiotic effects at a regional scale: Figure 1. Soils were sourced from 11 dairy farms across the United States under either high or low inputs of cattle inputs. An array of soil and microbial community characteristics were determined including antibiotic resistant gene (ARG) abundance, fungal and bacterial community composition, and mass specific respiration (Rmass).

a b

*

Figure 2. The a) abundance of antibiotic resistant genes and b) mass specific respiration under high and low inputs of cattle manure. Under high manure inputs, the antibiotic resistant genes, ampC and tetO were greater as was mass specific respiration.

Figure 3. Mass specific respiration was positively related to the abundance of both tetO and ampC. This relationship may indicate that the maintenance of ARGs leads to less efficient carbon cycling by the microbial community.

Figure 4. Bacterial (shown) and fungal community composition differed between high and low inputs. Notably for the bacterial community this was mainly due to a ~48% and ~38% increase in Firmicutes and γ-Proteobacteria, respectively. Notably, both groups are indicators of possible human pathogen concern.

2. Effects of antibiotics on carbon and nutrient cycling: Figure 5. Established the S.C.A.R.E. (Soil Carbon Antibiotic Resistance Experiment) sites in July 2014. This included 4 treatments (n=6): no manure control, control manure, Cephapirin manure, and Pirlimycin manure.

Figure 6. Manure is amended monthly by hand at a rate equivalent to high cattle stocking densities. Additionally, soil respiration is monitored monthly.

a b

c

Figure 7. In May 2015, we conducted the first of three short-term 13C and 15N pulse-chase experiments at the S.C.A.R.E. site. a) Chambers used to pulse plots with 13CO2, b) sub-plots were harvested 1, 2, and 7 days after harvesting, c) one of the sub-plots harvested to 10cm depth.

Figure 8. Treatment effects on microbial biomass.

Figure 9. Treatment effects on mineralizable C.

Acknowledgements. We thank all of the individuals that sampled and shipped soil for this project. We also thank Matt Hedin, Josh Franklin, Steven McBride, Kevin Eliason, and Steffany Yamada for field assistance. This project was supported by Agriculture and Food Research Competitive Grant no. 2013-67019-21363 from the USDA National Institute of Food and Agriculture. .

Figure 10. Results from catabolic response profiling. A significant treatment effect was noted (P <0.01).