1. Interactions between antibiotic resistance in soil
microbial communities and coupled elemental cycles
Michael S. Strickland, Brian Badgley, Jeb Barrett, Katharine Knowlton
Virginia Tech
@strickm27 www.stricklandresearch.net

2. McKenna (2013)
The age of antibiotic resistance

3. The burden of antibiotic resistance
•80% of U.S. antibiotic sales are for
livestock (FDA 2011, Sarmah et al 2006)
• 32.6 million lbs
•Globally, use is predicted to increase by
67% in the next 20y (Van Boeckel et al 2015)
• 40-95% of administered antibiotic is
excreted! (Toth et al 2011)
• 13-31 million lbs of antibiotics enter
the environment.
What are the consequences of antibiotic inputs on
soil microbial composition and function?

4. Antibiotic effects on soil microbes
• Bacterial community compositional shifts towards groups
indicative of resistance
• Increase in antibiotic resistance gene (ARGs) abundance
• Maintenance of antibiotic resistance may increase metabolic
demands
Schimel et al. (2007)
Focused on dairy
operations
Antibiotic

5. Examining antibiotic effects
• Nationwide observation of paired manure exposed and
reference sites.
Assessed soil parameters, bacterial community composition, ARG
abundance and activity, mass specific respiration
High input
Reference site
Google Earth (2016)
Wepking et al. (In Review)

6. Change in bacterial community composition
• Increase in relative abundance of Firmicutes and 𝛾
-Proteobacteria
• Environmental indicators of ARGs (Berendonk et al. 2015)
• 25-fold increase in Acinetobacter
CDC (2013)

7. Change in ARG abundance
• ampC was ~400% greater under high inputs
• tetO was ~3,000% greater

8. Total ARG abundance
ARG copies g soil-1

9. Implications for function
• 2-fold increase in mass specific respiration
• Back of the envelope - ~4 metric ton ha-1 y-1 increase in respired C

10. Conclusions
• Cattle inputs can markedly shift bacterial
community composition and ARG abundance
• The maintenance of antibiotic resistance may
have implications for ecosystem functions
• Can the maintenance of antibiotic resistance be
directly linked to ecosystem function?

12. Pirlimycin
Control
Cephapirin
+ No manure
S.C.A.R.E.
650 g manure m-2 month-1
562 kg manure year-1

13. S.C.A.R.E. Results
• Still analyzing 13C data
0 50 100 150 200 250 300 350 400 450 500 550 600
0
1000
2000
3000
Experiment Day
Soilrespiration(mmolsCO2m-2
d-1
)
Reference
Control
Cephapirin
Pirlimycin
Pulse-chase(May2015)
Pulse-chase(May2016)
July2015
Exp.Start(Oct2014)

14. S.C.A.R.E. Results
• Choice of antibiotic → 3.9 to 6.5 metric tons of C ha-1 y-1
difference.
C
ontrol
C
ephapirin
Pirlim
ycin
0
50
100
150
200
250
300
350
400
450
500
550
600
Antibiotic
Cumulativerespiration(molsCO2m-2
)
a
b
ab

15. Conclusions
• Cattle inputs can markedly shift bacterial
community composition and ARG abundance
• The maintenance of antibiotic resistance may
have implications for ecosystem functions
• Can the maintenance of antibiotic resistance be
directly linked to ecosystem function?
• Antibiotic treatment regimes can induce change
in soil respiration.
• Antibiotic effects can manifest rapidly and are
dependent on the type of antibiotic administered.

16. • We must also be concerned
with the effect antibiotics
have on soil microbial
communities and the
ecosystem processes that
these communities regulate.
Antibiotics and antibiotic resistance
can have ecosystem implications

17. Thank you!
Strickland Lab:
Carl Wepking
Kevan Minnick
Steve McBride
Josh Franklin
Steffany Yamada
Bethany Avera
Brian Badgley
Katharine Knowlton
Jeb Barrett
Matt Hedin
Partha Ray
Crystal Smitherman
Grant no. 2013-67019-21363
All the on-site personnel that sent soil!

18. @strickm27 www.stricklandresearch.net

19. C
ephapirin
Tetracycline
Erythrom
ycin
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
RespiratoryResponseRatio
Cows
Ref
***
***ns
Antibiotic
ARG activity

20. Microbial function
4 5 6 7
0.0
0.2
0.4
0.6
0.8
1.0
qCO2
Cows (y = 0.32x - 1.4; F1,9=11.8; P<0.01; r2=0.57)
Ref (ns)
ampC (log copies g soil-1)
0 20 40 60 80 100
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Silt + Clay (%)
qCO2
Cows (ns)
Ref (y = -0.003x + 0.59; F1,9=11.8; P<0.01; r2
=0.57

21. 0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Fungi-to-bacteria
pH
POM C:N
Mineral C:N
ampC× Input
Input
Microbial biomass C:N
Latitude
SIR
Silt+Clay
ampC
Relative parameter importance
ModelParameter
Parameter weights

22. 5 6 7 8
-0.5
0.0
0.5
1.0
1.5
2.0
ampC (log copies g dry wt soil-1)
Respiratoryresponseratio Cows
Ref
ARG activity

23. -60 -40 -20 0 20 40
-40
-20
0
20
PCoA1 (23.4%)
PCoA2(12.6%)
Cows
Ref
Input: P < 0.01
Site: P < 0.001
C
ow
s
R
ef
0
20
40
60
80
100
Manure inputRelativeabundance(%)
Sordariomycetes
Ascomycota (Other Class)
Dothideomycetes
Zygomycota (Class Incertae)
Unidentified
Pezizomycetes
Ascomycota (Unidentified Class)
Tremellomycetes
Agaricomycetes
Leotiomycetes
Eurotiomycetes
Other
A B
Fungi

24. Firmicutes
-1 0 1 2 3
-2
-1
0
1
2
3
4
5
D Firmicutes (%)
DTotalARGabundance
NY
FL
GA2
GA1
KS
MS
NH
VT
VA
WA
WV
y = 1.31x + 0.23
F1,9 = 14.61
P < 0.01
r2 = 0.62
A

25. Total ARGs

26. ermB tetO tetW ampC
C-min
Manure input
SIR biomass
Silt+Clay
Mineral C
POM C
Input × SIR
Latitude
Soil pH
Microbial C:N
Input × C-min
Input × POM C
Input × Mineral C
Input × pH
Input × Microbial C:N
Input × Silt+Clay
Input × Latitude
0
ARG
Modelparameter
Parameterweight
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
-1 0 1 2 3
-2
-1
0
1
2
3
4
5
D Firmicutes (%)
DTotalARGabundance
NY
FL
GA2
GA1
KS
MS
NH
VT
VA
WA
WV
y = 1.31x + 0.23
F1,9 = 14.61
P < 0.01
r2 = 0.62
0.0 0.5 1.0 1.5 2.0
-1
0
1
2
3
D DOC
DFirmicutes(%)
NY
FL
GA2
GA1
KS
MS
NH
VT
VA
WA
WV
y = 1.68x - 0.64
F1,9 = 16.42
P < 0.01
r2 = 0.65
A
B