Pathogen, indicator, & antibiotic resistant bacteria influenced by waste

residual land application

J. P. Brooks, M. R. McLaughlin, J.R. Read, & A. AdeliUSDA-ARS, Mississippi State, MS

Genetics and Precision Agriculture Unit

Organic Matter & It’s Importance to Crop Production Sustainability

2015 is the International Year of Soils◦ Nearly 1/3 of soil are degrading

Decreased organic matter

Desertification

Changes in biodiversity/cycles

◦ Implications of organic matter losses

Recognized soil quality loss

Failed productivity, efficiency, runoff, etc.

D. Wall & J. Six, Science 2015

Components of Soil

Typical soil biological activity in two soil zones◦ Rhizosphere – Hiltner (1904) defined as portion of soil where

microorganism-mediated processes are under the influence of the root system

◦ Vadose – Limited soil biological activity, but more work currently focused on this area

Mineral Fraction(95-99% by weight)

Organic Fraction(1-5% by weight)

Biological Fraction(≃ 0.05% by volume)

Sand Organic debris Virus

Silt Colloidal organic matter Bacteria

Clay Fungi

Protozoa

Soil Biology – The Master of the Universe

Soil biology controls all aspects of soil health…◦ All aspects of plant health…

◦ All aspects of animal health…

◦ All aspects of human health…

Sources: Texas A&M, Plantdesigns.com, earthobservatory.nasa.gov

Replacing Organic Matter

Broiler litter application

Biosolids application

Swine effluent applicationBiosolids applicationCover crop

“Organic” Waste Residuals

Municipal Waste Residuals◦ Biosolids, compost, sludge, etc.

◦ Two classes – Class A & B

◦ Potential for pathogens/metals/organics

◦ Treated to reduce pathogens EPA mandated – part 503

Anecdotally – pathogen/metal levels are dropping with advances in treatment

◦ Provides nutrients, some moisture, and organic matter

◦ Long-term usage across US

CAFO Waste Residuals◦ Manure – compost, litter, effluent,

pasture (cow pats), etc.

◦ Potential for pathogens and metals

◦ Not treated – typically Storage, anaerobic digestion

No mandated laws or regulatory control defining treatment

Some suggestions for 90-120 d holding period

◦ Provides nutrients, some moisture, and organic matter

◦ Long-term usage across US

Municipal Biosolids - Two Classes

There are no comparable treatment regulations, only recommendations (USDA-AMS), for CAFO manure.

EPA established Classes◦ Based on technical detection limits

Class A◦ <1000 MPN g-1 Fecal Coliform◦ <3 MPN 4 g-1 Salmonella◦ <1 Ova 4 g-1 Helminth Ova (Ascaris)◦ <1 MPN 4 g-1 Enteric Virus

Class B◦ <2 000 000 MPN g-1 Fecal Coliform

Pathogen & Antibiotic Resistance Potential

Class B Biosolids◦ Fecal/oral pathogens & any

excreeted human path◦ Antibiotic resistant bacteria/geneTable 1: Pathogen Examples

Litter, swine effluent, cow manure◦ Zoonotic fecal/oral pathogens◦ Antibiotic resistant bacteria/geneTable 2: Pathogen Examples

Pathogen ~ Level (Path/g)

Reference

Campylobacter 1-10 Betaieb, 1990; Jones, 1990; Pepper, 2010

Listeria 1-50 Garrec, 2003

Salmonella 5-200 Pepper, 2010; Gerba, 2008

Adenovirus 1-500 Viau, 2009; Pepper, 2010

Enterovirus 1-200 Soares, 1994; Guzman, 2007; Pepper, 2010

Norovirus 1,000-5,000* Wong, 2010

Parasites 1-10 Guzman, 2007

Pathogen ~ Level (Path/g)

Reference

Campylobacter 10-10,000 Hutchison, 2005; Chinivasagam, 2004;

McLaughlin, 2009;

Listeria 1-5,000 Hutchison, 2005; Chinivasagam, 2004;

McLaughlin, 2009;

Salmonella 1-10,000 Hutchison, 2005; Chinivasagam, 2004;

McLaughlin, 2009;

E. coli O157:H7 1-5,000 Berry, 2005; Hutchison, 2005

Parasites 1-500 Heitman, 2002;Hutchison, 2005; Atwill,

2006

Need for the Study

Current research lacks true comparisons between manures & between manures/biosolids, no comparisons of risk

◦ No comparisons from a pathogen standpoint or ecological/agronomic

◦ Research by Brooks, Pepper, Viau, Peccia, Gerba, Sorber, Hutchison, McLaughlin, etc. have focused on one waste

◦ Purpose of this study, to facilitate a comparison at field and bench scales Multiple year, multiple studies at bench and small plot scale Focus – Pathogens, Indicators, Antibiotic Resistance, Ecology, Plant,

Nutrients

Approach

Experimental Design◦ Small-plot scale study, 2011-

2014

Random, complete block design on forage plots

5 treatment – 4 replicates Rates: BS-8 Mg/ha; PL-5

Mg/ha; ES-2.54 ha-cm; EI-2.54 ha-cm◦ ES and EI – effluent surface

and incorporated, respectively

Plot layout on Prestage Farm 1, Crawford, MS. Note two utility poles (X) and one irrigation riser (I).

Plots are 5x10m with 5m borders between plots in each row of ten and 10m alleys between each of three rows (top/north/row-3 ten plots are unused).

Treatments: 1=Municipal Biosolids (BS), 2=Poultry Litter (PL), 3=Effluent Incorporated (EI), 4=Effluent Surface-applied (ES), and 5=Control (CO). 5 treatments x 4 replications (Blocks) = 20 plots

X

1=Biosolids

2=Poultry Litter

3=Effluent Inc

4=Effluent Sur

5=Control

Treatments

Row 3

Point of Origin

Row 2

Row 1

Gravel Road to Farm 2

Approach

Microbial Assays◦ 5 random soil cores (0-10 cm) were collected & homogenized

Targeted samples to locations where residuals were located

◦ Moisture content and 10 g aliquot, stomaching/95 ml saline, serial 10 fold dilutions, ~10 g frozen

◦ Heterotrophic plate count (HPC), Gram + (GPB), Gram – (GNB), Clostridium perfringens (Cp)

◦ E. coli, Listeria, Salmonella, & Campylobacter - Presence absence in 10 g soil/95 ml enrichment medium

Approach

Microbial Assays◦ Quantitative PCR (qPCR) - 16S rRNA, Class I Integron (intI); Tetracycline, Penicillin, Macrolide, Methicillin – resistance genes

◦ Kirby-Bauer disc diffusion – LVX, N, K, GM, CF, CFP, CIP, TE, IPM, AM, PB, AN – E. coli, C. perfringens, Staphylococci, Salmonella

◦ Statistics – One way ANOVA, chi-square, Mixed Models

Results

Year 1 – HPC levels remained unchanged despite treatment

16S rRNA demonstrated similar trends

HPC level increases in most treatments, regardless of treatments◦ Due to increases in soil moisture

◦ BG moisture increased from ~16% to 20% to 40% (following rain event) (Year 2 was exception)

Time (week)

-4 -2 0 2 4 6 8 10 12 14 16

Lo

g10

- C

FU

/g

7.0

7.5

8.0

8.5

9.0

9.5

10.0

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 1 – HPC by time

Treatment

CO BS EI ES PL

Lo

g10

GU

/g

10.5

11.0

11.5

12.0

12.5

13.0

13.5 Year 1 – 16S rRNA

Time (week)

0 2 4 6 8 10

Lo

g10

CF

U/g

7.2

7.4

7.6

7.8

8.0

8.2

8.4

8.6

8.8

9.0

9.2

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 2 – HPC by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

8.6

8.8

9.0

9.2

9.4

9.6

9.8

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 3 – HPC by time

Time (week)

-4 -2 0 2 4 6 8 10 12 14 16

Log10 C

FU

/g

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

Col 16 vs Col 18

Col 16 vs Col 17

Col 16 vs Col 19

Col 16 vs Col 20

Col 16 vs Col 21

Results

Gram positive bacteria (GPB)◦ PL was most significant

◦ GPB were more consistent and didn’t show extremes

Gram negative bacteria (GNB)◦ PL was most significant

◦ GNB were more subject to zymogenous behavior

◦ All treatments increased by 1 log

Year 1 – GNB by time

Year 2 – GNB by time Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 2 – GPB by time

Time (week)

-4 -2 0 2 4 6 8 10 12 14 16

Log10 C

FU

/g

4.5

5.0

5.5

6.0

6.5

7.0

7.5

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 1 – GPB by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

4.5

5.0

5.5

6.0

6.5

7.0

7.5

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 3 – GPB by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

3

4

5

6

7

8

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 2 – GNB by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

-2

0

2

4

6

8

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 3 – GNB by time

Results

Time (week)

-4 -2 0 2 4 6 8 10 12 14 16

Log10 C

FU

/g

-1

0

1

2

3

4

5

Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 1 – Cp by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

-1

0

1

2

3

4

5Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 2 – Cp by time

Time (week)

0 2 4 6 8 10

Log10 C

FU

/g

0

1

2

3

4

5 Time (w) vs CO

Time (w) vs BS

Time (w) vs EI

Time (w) vs ES

Time (w) vs PL

Year 3 – Cp by time

Clostridium perfringens(Cp)◦ BS, ES, EI, PL – increased

soil Cp levels by 2 log10

◦ Cp is sometimes transient in poultry (year 2)

◦ Presence in CO suggests feral animals

Results

Treatment effect -GPB, Cp and intI◦ PL, BS were most

significant treatments

◦ ES and EI treatments were significant at early time points for Cp

Treatment

CO BS EI ES PL

Log10 C

FU

/g

4.5

5.0

5.5

6.0

6.5

7.0 Year 1, week 2 GPB by treatment

A

BB

B

B

Treatment

CO BS EI ES PL

Lo

g10

CF

U/g

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0 Year 1, week 2 Cp by treatment

C

B

A A

B

Treatment

CO BS EI ES PL

Log10 C

FU

/g

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5Year 2, week 0 GPB by treatment

B BB

A

C

Treatment

CO BS EI ES PL

Log10 C

FU

/g

0

1

2

3

4

5

Year 2, week 0 Cp by treatment

A

B

CC

B

Results

Treatment effect◦ intI levels, cyclical or

sustainable? Integron I gene

appeared to increase by year until year 3

intI decrease in year 3, due to increased temperature?

Increase from 5 to 8 log10◦ Suggests antibiotic

resistance can become sustainable provided application continues.

Treatment

CO BS EI ES PL

Log10 G

U/g

5.52

5.54

5.56

5.58

5.60

5.62 Year 1, week 2 intI by treatment

A

A

AA

A

Treatment

CO BS EI ES PL

Log10 G

U/g

6.5

7.0

7.5

8.0

8.5

9.0

9.5 Year 2, week 8 intI by treatment

BBB

B

A

Treatment

CO BS EI ES PL

Log10 G

U/g

6.5

7.0

7.5

8.0

8.5

9.0

9.5

Year 2, week 0 intI by treatment

C

BCA

B

C

Results

Overall, true pathogen levels were low for all wastes.

E. coli isolates were dependent on residual waste type

◦ All 3 years – more frequently present in BS, EI, and ES applied plots.

◦ Influence of feral animals was also likely as CO samples were also positive

Salmonella isolates were only dependent on waste in yr 3.

◦ BS applied plots were more likely positive

No Campylobacter spp. detected in soil, wastes were positive, but numbers were below 100/g.

Results

Kirby – Bauer Disc Diff.◦ E. coli isolates (n=120) – all

considered, regardless of treatment 47.5% resistant to 1 class 47.5% resistant to 2 or 3 classes 3% resistant to >4 classes <2% susceptible to all

◦ Nearly all resistant to cephalothinor tetracycline Ceph – intrinsic res. in many

Enterobactericae, though many E. coli are susc.

◦ Only 3 isolates resistant to quinolone antibiotics

◦ No imipenem resistance

Antibiograms – E. coli isolates31 19 19 23 14 30 35 0 32 18 14 22

26 19 21 22 20 24 28 23 24 10 14 22

30 20 21 22 12 28 33 0 29 21 14 22

35 23 24 24 13 26 38 23 36 24 15 25

31 20 20 23 13 28 34 21 31 18 13 21

28 21 21 22 20 25 22 23 25 0 14 21

32 13 0 22 13 28 33 0 28 18 14 23

28 19 19 22 16 26 31 0 23 0 14 22

0 20 9 0 14 25 0 0 28 0 15 18

31 19 18 21 14 27 31 21 30 17 14 20

30 20 20 21 #VALUE! 27 33 22 29 19 13 21

28 19 20 22 #VALUE! 26 30 0 25 19 14 22

32 19 20 22 #VALUE! 27 32 0 31 18 20 22

33 22 21 22 12 26 36 0 28 0 15 23

34 19 20 21 #VALUE! 27 35 0 30 19 13 22

27 20 21 22 18 24 28 21 #VALUE! 18 14 23

31 20 21 10 11 28 #VALUE! 0 31 17 14 23

30 18 20 22 16 28 33 22 29 20 14 22

29 19 19 21 0 18 30 26 28 15 14 22

31 21 22 24 13 29 34 0 29 18 14 23

29 23 21 21 21 29 29 12 28 22 15 21

32 20 21 23 12 22 34 24 30 19 14 23

32 20 21 22 15 28 32 24 32 19 15 22

31 20 20 21 14 28 25 0 32 19 15 21

28 20 20 21 17 28 33 0 28 19 14 21

33 22 21 22 14 29 33 0 33 19 15 22

32 19 21 22 15 30 34 24 31 19 14 22

32 19 22 22 14 28 35 0 29 21 15 22

33 20 21 20 14 30 35 0 33 20 14 22

33 20 20 21 14 27 36 22 25 18 14 21

37 20 21 21 15 27 40 23 31 20 14 22

36 22 20 0 10 14 37 0 34 0 15 24

37 21 21 25 14 29 41 26 36 22 15 25

30 20 15 23 14 30 34 0 35 22 16 22

32 22 23 24 13 32 36 25 34 20 15 23

34 20 23 23 15 32 36 0 31 21 15 23

34 21 21 23 12 31 37 22 29 21 15 22

36 22 22 24 12 30 41 23 32 20 16 23

36 20 23 23 16 31 38 0 30 24 16 23

33 22 23 24 15 29 39 25 33 20 15 23

33 21 22 22 14 29 40 24 33 20 15 24

32 20 20 22 13 30 34 0 33 20 15 23

33 20 21 22 12 19 33 0 32 0 14 23

39 13 0 23 19 29 39 0 30 20 15 23

34 20 22 23 14 33 36 24 32 19 15 23

35 22 22 24 14 29 38 0 33 20 14 25

36 19 21 22 14 29 37 0 35 20 16 22

0 19 21 21 12 24 0 25 35 0 15 22

32 20 20 22 18 32 36 0 33 21 16 22

27 22 23 24 13 29 35 24 33 19 16 24

12 10 0 24 14 28 11 0 34 0 16 23

33 19 20 23 13 30 34 0 34 20 14 21

35 20 22 16 13 25 41 0 35 0 16 23

35 20 20 22 15 26 38 22 30 19 14 20

33 22 22 24 14 28 35 24 33 21 15 23

34 20 21 22 14 29 38 24 34 19 14 23

32 20 22 23 13 29 35 24 30 19 14 22

34 19 21 21 13 30 37 23 31 21 14 21

35 20 21 22 14 27 37 24 29 20 16 23

36 22 21 22 15 29 37 24 31 20 14 23

32 20 21 22 13 28 37 0 28 19 15 22

33 21 23 23 14 28 37 23 32 21 15 22

34 20 22 21 13 28 38 9 33 20 15 21

34 10 0 21 14 25 35 0 31 0 15 21

34 20 22 22 14 33 38 23 36 19 15 22

Cephalothin

Tetracycline

Imipenem

Discussion

Treatments exhibited short-term effects, 0-14 weeks◦ Higher organic matter equated to longer term effects.◦ Other studies have suggested that treatment-based pathogen survival

doesn’t extend beyond these time periods (McLaughlin et al.)

Pathogen levels were low in soil◦ Numbers in waste residuals were low, difficult to find the “lone

gunman”◦ CO numbers suggested feral wild life

Antibiotic resistance suggested no treatment bias, for E. coli◦ Cyclical nature of ARGs suggests intrinsic resistance

Preliminary Conclusions

Risk assessments need to be targeted with correct assumptions

Overall pathogen levels were low in waste residuals indicating risks most likely low when comparing directly

Antibiotic resistance, though results still forthcoming, demonstrated sustainability through repeated applications.◦ Though, intrinsic presence of many ARGs may account for variability, as CO increased

◦ Increased temperatures reduced class I integron gene presence

Questions & Contact Information

John P. Brooks◦ USDA-ARS – Mississippi State University

◦ 810 HWY 12 E., Mississippi State, MS 39762

◦ Email: john.brooks@ars.usda.gov

◦ Phone: 662-320-7411

Mention of trade names, commercial products, or organizationsdoes not imply endorsement by the U.S. Government.

Discussion

Treatments exhibited short-term effects, 0-14 weeks◦ PL and BS exhibited strong effects even beyond 8 weeks, most likely

due to high organic matter.

◦ ES and EI were limited to less than 8 weeks.

Other studies have suggested that treatment-based pathogen survival doesn’t extend beyond these time periods (McLaughlin et al.)

True pathogens were limited in presence◦ Numbers in waste residuals were low

CO numbers suggested feral wild life Antibiotic resistance suggested no treatment bias, for E. coli