AMR dissemination in the environment Professor Liz Wellington The - - PowerPoint PPT Presentation

AMR dissemination in the environment Professor Liz Wellington

The connectivity of potential sources of antibiotic- resistant bacteria

Antibiotic resistance in the environment: soil, sediments, water bodies

Environment acts as an reservoir for antibiotic resistance genes:

• associated with antibiotic biosynthesis clusters
• in closely related non-producers
• in unrelated non-producers indigenous

soil bacteria

• in unrelated non-producers exotic bacteria =

pathogens/commensals added to soil

• Potential for selection of resistance -pollution
• HGT of resistance genes- mobilome
• Pathogens can survive in soil
• Acquire integrons/plasmids
• Act as source of antibiotic resistance

Non-producers Streptomycin Non-producers Gentamicin Non-producers Tetracycline

aac(3)-I aac(3)-II/VI aac(3)-III/IV aac(6’)-II/Ib ant(2”)-I aph(2”)-I aph3 aph6-Id ant3 adenylase aph6-Ic aph6-Ic (deg) tetA tetB tetC tetD tetE tetG tetH tetK tetL tetM tetO tetT

Producers Streptomycin

strA aphD strB1 stsC Soil Rhizosphere Manure Sewage Seawater Soil Rhizosphere Manure Sewage Seawater

Reservoirs of antibiotic resistance genes in diverse environments: survey

Prevalence

Laskaris et al., 2010. Env Micro 12, 783–796

Streptomycin biosynthetic cluster and mobility of resistance gene strA in soil Substitution rate

Substitution rate in housekeeper genes vs. streptomycin resistance strA (APH II)

The connectivity of potential sources of antibiotic- resistant bacteria

Application of sewage sludge /biosolids/ manure to land: what is the impact on antibiotic resistance in soil?

Sewage treatment and disposal

Antibiotic class General behaviour Sewage sludge River water Groundwat er Drinking water Fish Soil Crops Example compounds monitored

Chloramphenicol

impersistent/ mobile

• 

X

• 2,4-

diaminopyridines

persistent/ immobile

  X X

• 



trimethoprim

Fluoroquinolones

persistent/ immobile

  X X

• 
• ciprofloxacin, norfloxacin,
• floxacin

-lactams

impersistent mobile

• X

X X

• amoxicillin, cloxacillin,

dicloxacillin, methicillin, nafcillin, oxacillin, penicillin G, penicillin V

Macrolides

slightly persistent/ slightly mobile

  X

• azithromycin,

clarithromycin, lincomycin, roxithromycin, spyramycin, tylosin

Sulfonamides

persistent/ mobile

   X

• 



sulfamethoxazole, sulfadiazine, sulfamerazine, sulfamethazine, sulfapyridine

Tetracyclines

persistent/ immobile

• 

X X   

chlortetracycline, doxycycline, oxytetracycline, tetracycline

Occurrence of antibiotics in the natural environment, fish, crops and drinking water from published studies

A tick means that it has been monitored for and detected and a cross means that it has been monitored for and not detected. No entry means that no monitoring has been done yet (Alistair Boxall)

Schematic map of the complex class 1 integron carrying the blaCTX-M-14 gene on plasmid pAJE0508 gene on plasmid pAJE0508

Bae et al., AAC, Aug 2007, 3017-19

• 90 million tons animal faecal slurry added to UK soils per year

Gaze et al., 2011 ISME J ; Bailey-Byrne et al 2011 AEM

Class 1 integron prevalence in sewage sludge, pig slurry and following application to land

0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016

pre- application day 1 day 21 day 90 day 289

days after slurry application prevalence %

1 2 3 4 5 6 7 8 9 RB SS PS CW sample site prevalence (%)

intI1 qacE∆1 qacE qacG qacH

RB, Reed bed sediment from textile mill; SS, Fully digested sewage sludge; PS, Pig slurry; CW, Fallowed agricultural soil

+ Pig slurry intI1

Low cost AMR carriage gives selection with very low exposure Gulleberg et al., 2014 mBio

Waste water treatment plants as a reservoir for antibiotic resistance

Waste Water treatment plants

Hotspot for Horizontal Gene Transfer (HGT) as waste received from various sources Little is known about the impacts

• f effluent further downstream in

the river or the possible role of co-selection of antibiotic resistant determinants via quaternary ammonium compounds (QACs) (Gaze et al., AAC 2005, ISMEJ 2011)

P = 1 − 𝑓−𝜇

𝑗=100 𝑙

λi i!

P= probability of being colonized by a 3GC resistant coliform. λ = average number

• f 3GC coliforms consumed, which is equal to number of 3GC coliforms multipled

by the amount of water consumed (ml). i = 100, the number of coliforms needed for colonization. The volume of water consumed for > 99% probability of transient colonization of a 3GC resistant coliform at minimum levels of sediment disturbance was 12·5 ml downstream and 58 ml upstream, and under high levels of sediment disturbance, will decrease to 1·3 ml downstream and 5·8 ml upstream. Children swimming (37 ml of water consumed on average) downstream of treatment plants have a P > 99 % chance of being transiently colonized by a 3GC resistant coliform. Upstream of the WWTP, even under high levels of sediment disturbance, only swimming carried risks of colonization by 3GC resistant coliforms.

The risk of consuming 3GC resistant coliforms equal to or greater than the dose needed for colonization can be calculated using the inverse cumulative Poisson distribution

Collaboration with Wallingford CEH, meta-data available 13 sites samples every 3 months for a year: analysed for integron prevalence and 3GC resistance counts

Contribution of WWTP effluent to integron levels in a whole river system

River Thames catchment area:

In Integron pre revalence

0.5 1 1.5 2 2.5 3 3.5 Integron Prevalence / (%) Sample site

May August February

Significant difference between summer months (May and August, and Winter months November and February P = 0.004 t-test

November

Output WWTP only

Explained 49 % of variance: R2 adjusted  (0.49) P < 0.01

0.5 2.5 1.5

• 2.0

0.0

• 1.5
• 1.0
• 0.5

0.0 0.5 1.0 2.0

Actual log integron prevalence

Predicted log integron prevalence

Amos et al., 2015 ISME J

• 1.5

0.5

• 0.5
• 2.0
• 2.0
• 1.5
• 1.0
• 0.5

0.0 0.5

• 1.0

0.0

actual log integron prevalence

Predicted log integron prevalence

Explained 82. 9 % of variance : R2 adj (0.83) P < 0.01

All metadata included

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Acknowledgements

University of Birmingham Professor Peter Hawkey Claire Murray Katie Hardy Past: Present: William Gaze Greg Amos Lihong Zhang Kathy Byrn-Bailey Paris Laskaris Leo Calvo-Bado Helen Green Gemma Hill Hayley King Jennie Holden Severine Rangama Chiara Borsetto Rothamsted Research Andrew Mead CEH Wallingford Andrew Singer