Whole-Genome Sequencing for Surveillance of AMR in

Foodborne Bacterial PathogensErrol Strain

Senior Advisor for Science InformaticsNational Antimicrobial Resistance Monitoring System (NARMS)

FDA Center for Veterinary Medicine

CASSS Meeting 2/20/2022

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DisclaimerThe views expressed in this presentation are the thoughts and opinions of the author and do not represent the views or policies of the FDA. Center for Veterinary Medicine

• Office of Research, Laurel MD• Changes in the antimicrobial

susceptibility of enteric (intestinal) bacteria – food, animals, humans

• Track & limit spread of resistance

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Overview1. What is NARMS2. Whole-Genome Sequencing (WGS) and

Food Safety3. Genotype = Phenotype4. NCBI Pathogen Detection

1. What is NARMS?

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The Review on Antimicrobial Resistance Chaired by Jim

O’Neill December 2014

Global Burden of rise in

Antimicrobial Resistance

(AMR) – 2.5-3% reduction in

GDP by 2050

FDA\NARMS – Monitor burden of

resistance from food animals

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• NARMS is a collaborative program of state and local public health departments and universities, the FDA, the Centers for Disease Control and Prevention (CDC), and the U.S. Department of Agriculture (USDA).

• This national public health surveillance system tracks changes in the antimicrobial susceptibility of enteric (intestinal) bacteria found in ill people (CDC), retail meats (FDA), and food animals (USDA) in the United States.

• The NARMS program helps promote and protect public health by providing information about emerging bacterial resistance, how resistant infections differ from susceptible infections, and the impact of interventions designed to limit the spread of resistance.

• NARMS data are used by FDA to make regulatory decisions designed to preserve the effectiveness of antibiotics for humans and animals.

Random stratified sampling in 21 States

ORA Imported Foods

Random cecal samplingof national production

at slaughter

Eastern FSIS Laboratory

Animal PopulationRetail Meats

21 States Labs

Human Population

Physician Visit

Local Lab

State Lab

Campylobacter

Salmonella

Enterococcus

E. coli

HACCP isolates

FSIS

Data Integration

Integrated Report

(E. coli O157:H7, S. Typhi, Shigella, Vibrio)

Integrated Surveillance of Antimicrobial Resistance in Foodborne Bacteria:1996

ChickenTurkeyPorkBeef

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• Cover all 4 U.S census regions: W,

MW, NE and S;• Collect samples in

area that represent 22.67% of the US

population;• Test samples from

states that encompass 58.44%

of the U.S population;

State Public Health Departments and Universities2002 CT, GA, MD, MN, TN, OR 2003 CT, GA, MD, MN, TN, OR, NY, CA 2004 CT, GA, MD, MN, TN, OR, NY, CA, CO, NM2008 CT, GA, MD, MN, TN, OR, NY, CA, CO, NM, PA2012 CT, GA, MD, MN, TN, OR, NY, CA, CO, NM, PA, WA, LA, MO,2017 CT, GA, MD, MN, TN, OR, NY, CA, CO, NM, PA, WA, LA, MO, IA, SC, KS, ND/SD, TX/OK, NC2020 CT, GA, MD, MN, TN, OR, NY, CA, CO, NM, PA, WA, LA, MO, IA, SC, KS, ND/SD, TX/OK, OH, HI

Retail Meat Sampling

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NARMS Panels (2018)

Salmonella Campylobacter E. coli EnterococcusAmoxicillin-Clavulanic Acid X XAmpicillin X XAzithromycin X X XCefoxitin X XCeftiofur X XCeftriaxone X XChloramphenicol X X X XCiprofloxacin X X X XClindamycin XDaptomycin XErythomycin X XFlavovmycin XFlorenicol XGentamicin X X X XKanamycin XLincomycin XLinezolid XMeropenem X X XNalidixic Acid X X XNitrofurantoin XPenicillin XStreptomycin X X XSulfamethoxazole-Sufisoxazole X XTelithromycin XTetratracycline X X X XTigecycline XTrimethoprim-Sulfamethoxazole X XTylosin XVancomycin X

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Veterinary Laboratory Investigation and

Response Network (Vet-LIRN)

• 2017-2018 pilot to evaluate the feasibility of using Vet-LIRN

veterinary diagnostic laboratories to monitor the

antimicrobial susceptibility of three veterinary pathogens:

Escherichia coli and Staphylococcus pseudintermedius in dogs

and Salmonella enterica in any host. Approximately 5,000

isolates from clinically sick animals were collected and tested

• Twenty Vet-LIRN Source diagnostic laboratories collected

isolates and tested the susceptibility using Clinical and

Laboratory Standards Institute (CLSI) methods. Additional

information about the pathogen (the organ it came from, the

animal species, which part of the country) was reported.

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Pettengill JB, et al. Distribution of antimicrobial resistance genes across Salmonella enterica isolates from animal and non-animal foods. Submitted.

2. WGS and Food Safety

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Why Develop a WGS based Network?

Tracking and Tracing of food pathogens• Insufficient resolution of current tools

-matching clinical to environmental-improve the environmental database

• Faster identification of the food involved in the outbreak

• Limited number of investigators vs. facilities and import lines

• Global travel• Global food supply

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Farm/Supplier Processing Facility/ Distributor

Food/Feed Patient

Laboratory

WGS and Food Safety

Microbiology Laboratory Workflow

GenomeTrakr Labs& Collaborators

Salmonella

Listeria

E.coli and Shigella, Campylobacter jejuni, Klebsiella pneumoniae, Mycobacterium tuberculosis, Acinetobacter baumannii, Neisseria, Pseudomonas aeruginosa, Enterobacter, Clostridioides difficile, Vibrio parahaemolyticus, Vibrio cholerae, Legionella pneumophila, Cronobacter, Serratia marcescens, Staphylococcus pseudintermedius, Klebsiella oxytoca, Citrobacter freundii, Vibrio vulnificus, Clostridium botulinum, Clostridium perfringens, Providencia alcalifaciens, Elizabethkingia anopheles, Morganella morganii, Photobacterium damselae, Corynebacterium striatum, Kluyvera intermedia

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> 300K Foodborne Pathogens

3. Genotype = Phenotype

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Genotype-Phenotype Correlation

Isolate N33849PS

Phenotypic susceptibility

NAL FIS CHL TET STR

Sequencing/genotyping GyrA (S83L) sul2 floR tetA strA/strB

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Predicting Resistance from the Genome

Bacterium Gen/Phe correlation Reference

99.70% Zankari et al., 2013, J Antimicrob Chemother

99.00% McDermott et al., 2016, Antimicrob Agents Chemother

97.10% Stoesser et al., 2013, J Antimicrob Chemother

98.50% Tyson et al 2015., J Antimicrob Chemother

Campylobacter spp. 99.20% Zhao et al 2015., J Antimicrob Chemother

Staphylococcus aureus 98.80% Gordon et al 2014., J Antimicrob Chemother

Pneumococcus 98.00% Metcalf et al 2016, Clin Microbiol Infect

Enterobacteriaceae (B-lacs) 100.00% Shelburne et al, 2017 Clin Infect Dis

95.30% Phelan et al 2016. Genome Med

92.30% Walker et al 2015. Lancet Infect Dis

Salmonella enterica

Escherichia coli

Mycobacterium

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Resistance Genes

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Resistance Gene Antimicrobial Class Resistance Phenotypeaac(3)-Id, aac(3)-IId, aac(3)-IV, aac(3)-VI Aminoglycosides GentamicinaadB Aminoglycosides Gentamicin, Kanamycinaph(3')-la, aph(3')-II Aminoglycosides Kanamycinaph(4)-la Aminoglycosides Hygromycin BaadA, 1, 2, 5, 7, 12, 13, 24, aac(6')-lb, aph(6)-lc, aph(3')-

lb (strA), aph(6)-Id (strB)

Aminoglycosides Streptomycin

blaCMY-2, blaCTX-M-1, blaCTX-M-14b, blaSHV-2a, blaFOX-6 β-lactams Amoxicillin-clavulanic acid, Ampicillin, Ceftriaxone, Cefoxitin,Ceftiofur

blaCARB-2, blaHERA-3, blaLAP-1, blaOXA2, blaTEM-1 β-lactams Ampicillin

ble, blmS Bleomycinsul1, 2, 3 Folate Pathway Inhibitors Sulfisoxazoledfr5, 7, dfrA1,8, 12, 14, 15, 17. Folate Pathway Inhibitors Trimethoprim-SulfamethoxazolemphA Macrolides Azithromycinmel, mphB, mphE Macrolides ErythromycincatA1, cmlA, floR Phenicols Chloramphenicol

oqxA, oqxB

Phenicols,Olaquindox, Quinolones Olaquindox

qacH QAC Disinfectants, ethidium bromideqnrA, qnrB19, qnrS Quinolones Reduced susceptibility to NAL, CIPtetA, B, C, D, G, M, O, X Tetracyclines TetracyclinelinB Lincosamides Lincomycin

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Correlation between Antimicrobial Resistance Phenotype and Genotype in Salmonella (n=640)

ANTIBIOTICPhenotype: Resistant Phenotype: Susceptible

Genotype: resistant

Genotype: susceptible

Genotype: resistant

Genotype: susceptible

Sensitivity Specificity

GENTAMICIN 99 6 5 530 94.3% 99.1%STREPTOMYCIN 257 3 35 345 98.8% 90.8%AMOXY/CLAV 114 2 0 524 98.3% 100.0%CEFOXITIN 93 2 21 524 97.9% 96.1%CEFTIOFUR 113 0 4 523 100.0% 99.2%CEFTRAXONE 116 0 1 523 100.0% 99.8%AMPICILLIN 241 1 1 397 99.6% 99.7%SULFA 244 1 0 395 99.6% 100.0%TRM/SULFA 19 3 0 618 86.4% 100.0%AZTREONAM 1 0 0 639 100.0% 100.0%CHLORAMPHENICOL 44 0 1 595 100.0% 99.8%CIPROFLOXACIN 4 0 0 636 100.0% 100.0%NALIDIXIC ACID 13 2 0 625 86.7% 100.0%TETRACYCLINE 349 0 0 291 100.0% 100.0%

Totals 1707 20 68 7164 98.8% 99.1%

A total of 65 unique resistance genes, plus two housekeeping genes mutations were identified;

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• Used 5,278 NARMS isolates with phenotype/genotype data

• Susceptibility to 16 antibiotics

• The MIC prediction models have average accuracies between 95-96% within ± 1 two-fold dilution factor.

• The models are capable of predicting susceptible and

resistant MICs with no a priori information about the underlying gene content of the genomes.

• By using diverse genomes for training sets, MIC prediction models with accuracies >90% can be

generated with fewer than 500 genomes.

Using AI to Predict MICs in Salmonella

Nguyen, M. et al. Using machine learning to predict antimicrobial MICs and associated genomic features for nontyphoidal Salmonella.

J. Clin Microbiol. Volume 57(2), Jan 30., 2019 .

4. NCBI Pathogen Detection

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Monitoring the Resistome: In nucleum veritatis

• WGS is replacing many long-standing laboratory methods

• Involves a single analytical workflow providing a common data set at lower costs

• Provides the highest practical resolution of individuating structural traits in an organism

• Theoretically, any phenotype can be inferred from the genotype

• Major impact on microbiology, epidemiology and public health surveillance

• Level of detail results in a stronger scientific foundation for risk analysis and regulatory decision making

Last accessed Feb 15, 2020

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Pathogen: environmental/food/other sample from Listeria monocytogenes BioSample: SAMN02709234;Sample name: FDA00007620Organism Listeria monocytogenescellular organisms; Bacteria; Firmicutes; Bacilli;Bacillales; Listeriaceae; ListeriaPathogen: environmental/food/other; v.1.0strain FDA00007620host disease missinglatitude and longitude missingcollection date 3/26/2012isolate CFSAN003790geographic location Italyisolation source moliterno al tartufo

cheesecollected by FDAPFGE_SecondaryEnzyme_pattern GX6A12.0280PFGE_PrimaryEnzyme_pattern GX6A16.0085SubmissionFDA, Justin Payne; 2014-03-27ID: 2709234

Pathogen: clinical or host-associated samplefrom Salmonella enterica

BioSample: SAMN02927343; Sample name:/2013K-0563Organism Salmonella entericacellular organisms; Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales; Enterobacteriaceae; SalmonellaPathogen: clinical or host-associated; version 1.0strain 2013K-0563collected by CDCcollection date Missinggeographic location USAhost Missinghost disease Missingisolation source Missinglatitude and longitude Missing

SubmissionPulsenet, Eija Trees; 2014-07-18ID: 2927343

Food/environmental Submission Clinical Submission

Metadata

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Standard Antibiogram

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NCBI Pathogen Detection

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NCBI Pathogen Detection & AMRFinderPlus

Clinical isolate within 3 nucleotide changes of food/environmental isolate AMR genotype

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AST Phenotypes and AMR Genotypes

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Recap• NCBI Pathogen Detection and AMRFinder Plus– https://www.ncbi.nlm.nih.gov/pathogens/

• FDA NARMS and Vet-LIRN– Retail Meats/Seafood and Companion Animals

• Public Data Sharing– Anyone can submit to NCBI SRA and Pathogen

Detection– Need for more AST data, only ~2% of Salmonella

Acknowledgements

• FDA• Center for Veterinary Medicine• Center for Food Safety and Applied Nutrition• Office of Regulatory Affairs

• National Institutes of Health• National Center for Biotechnology Information

• State Health and University Labs• Alaska• Arizona• California• Florida• Hawaii• Maryland• Minnesota• New Mexico• New York• South Dakota• Texas• Virginia• Washington

• USDA/FSIS and ARS

• CDC• Enteric Diseases Laboratory

• INEI-ANLIS “Carolos Malbran Institute,” Argentina

• Centre for Food Safety, University College Dublin, Ireland and Irish FSA

• Melbourne (FSA). Australia

• Public Health England, UK

• Institute for Food Safety and Health (IFSH)

• WHO and FAO

• Illumina

• Pac Bio

• Other independent collaborators

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Questions/Discussion