Predicted Resistance at CDC

Transcription

1 National Center for Emerging and Zoonotic Infectious Diseases Predicted Resistance at CDC Ian Plumb, MBBS MSc Medical Epidemiologist, NARMS Team, EDEB, DFWED PulseNet & OutbreakNet Regional Meeting, East Coast Tampa, Florida January 15, 2019

2 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

3 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

4 ANTIBIOTICS ANTIMICROBIAL SUSCEPTIBILITY TESTING: METHODS ANTIBIOTIC DILUTIONS (Broth microdilution method) MEAN INHIBITORY CONCENTRATION (e.g., using CLSI criteria for Salmonella and ciprofloxacin) (µg/ml) Intermediate Resistant Decreased susceptibility

5 ANTIMICROBIAL RESISTANCE WORKFLOW Sick patient Blood, stool or other specimen Public health laboratory Sampling for CDC NARMS Outbreak isolate requests All Salmonella Typhi, Vibrio 1 in 20 non-typhoidal Salmonella, Shigella, and E. coli O157 H7 Selected Campylobacter NARMS susceptibility testing Predicted Resistance Sequencing Resistance genes & mutations

6 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

7 ANTIBIOTIC RESISTANCE DETERMINANTS Acquisition Mutation Gene(s) from plasmid, bacteriophage, or free DNA Selection Antibiotic use Expansion In animal reservoirs In human infections EMERGING STRAIN CHROMOSOME PLASMID BACTERIUM

8 RESISTANCE DETERMINANTS IN SALMONELLA Drug Ampicillin Ceftriaxone Ciprofloxacin Example of resistance determinants blatem-1b blacmy-2, blactx-m-65 qnrb19, gyra*, parc* Azithromycin mph(a), erm(b) Gentamicin aac(3)-iva, aph (2 ) Sulfisoxazole sul2 Tetracycline tet(b) Chloramphenicol catb, flor, cmla1 Caveats: variation by pathogen; challenging nomenclature; dependent on gene calls References: Frye (2013) PMID ; ResFinder; PointFinder, CARD database *Mutation

9 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

10 Antimicrob Agents Chemother 60: J Antimicrob Chemother 2015; 70: Appl Environ Microbiol 82:

11 RELIABILITY OF PREDICTED RESISTANCE GENE OR MUTATION EXPRESSION ❺ DECREASED SUSCEPTIBILITY ❶ ❸ ❻ RESISTANCE ❷DETERMINANT DETECTED PREDICTED RESISTANCE ❹ Genes detected Predicted AST aada1 sul1 aac(3)-via SSuGen SSuGen aada1 sul1 aac(6')ib-cr aac(3)-vssucip(i/r)gen SSuGen aada1 sul1 tet(a) aac(3)-via SSuTGen SSuTGen aada1 sul1 tet(c) aac(3)-via SSuTGen SSuTGen aada1 tet(a) aac(3)-via dfra15 STGen STGenCot aada12 aada2 blatem-1b dfra1assutcip(i/r)cotlintmassutcipcot CONFIRMED RESISTANCE Genes detected Predicted AST aada1 sul1 aac(3)-via SSuGen SSuGen aada1 sul1 aac(6')ib-cr aac(3)-vssucip(i/r)gen SSuGen aada1 sul1 tet(a) aac(3)-via SSuTGen SSuTGen aada1 sul1 tet(c) aac(3)-via SSuTGen SSuTGen aada1 tet(a) aac(3)-via dfra15 STGen STGenCot aada12 aada2 blatem-1b dfra1assutcip(i/r)cotlintmassutcipcot ❶ Gene or plasmid lost ❷ Detection problem ❸ Novel gene or mutation REASONS FOR DISCORDANCE ❹ Inconsistent mechanism ❺ gene expression ❻ MIC shift below cut-off

12 NARMS CDC NON-TYPHOIDAL SALMONELLA (2015) Antibiotic No. (%) resistant* by phenotypic testing Predicted resistance sensitivity (%) Ampicillin 238 (10.1%) 99.6% 99.8% Ceftriaxone 56 (2.4%) 100.0% 100.0% Ciprofloxacin 101 (4.3%) 90.1% 99.9% Gentamicin 36 (1.5%) 94.4% 99.7% Sulfisoxazole 237 (10.0%) 96.2% 99.9% Chloramphenicol 76 (3.2%) 97.4% 100.0% Tetracycline 273 (11.5%) 98.2% 99.5% Predicted resistance specificity (%) *See NARMS website for definitions. Includes intermediate susceptibility to ciprofloxacin.

13 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

14 Number of isolates (Salm/Shig/Eco) CDC NATIONAL ANTIMICROBIAL RESISTANCE SURVEILLANCE TEAM % 50% % 14% Total WGS Projected WGS %WGS at PHLs 0

15 PREDICTED RESISTANCE WORKFLOW MYSEQ COMPUTATIONAL CLUSTER (CDC) Updates to blast tools (Center for Genomic Epidemiology) ANTIMICROBIAL RESISTANCE SURVEILLANCE TEAM (CDC) Screen with blast tools (ResFinder, PointFinder, PlasmidFinder) QC (90% identity, 60% coverage) Resistance genes and mutations Predicted resistance

16 BIONUMERICS WORKFLOW Experiment numbers 1 - Antibiotic class 8 - Plasmid type 13 - Resistance determinants

17 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

18 VALUE OF SEQUENCING AND PREDICTED RESISTANCE RESISTANCE DETERMINANTS Detect new strains Detect emerging strains Identify sources

19 Antibiotic Resistance Island - A Novel trimethoprim resistance gene dfra34 dfra5_1_x12868 * dfra30_1_am dfra14_1_dq * dfra25_1_dq * dfra27_1_fj459817* dfra28_2_fm dfra16_1_af077008* dfra1_1_x00926 * dfra15_1_hm * dfra15b_1_aj * dfra29_1_am * dfra7_1_aj * dfra17_1_fj * dfra32_1_gu * dfra6_1_z86002 dfra31_1_ab dfra12_1_ab * dfra13_1_z50802 dfra21_1_am * dfra12-group dfra22_1_hm dfra33_1_fm dfra3_1_j03306 * dfra26_1_am dfra20_1_aj dfra8_1_u10186 * dfra9_1_x57730 dfra24_1_aj dfra34 dfra34 * dfra3b_1_ay dfra10_1_l06418 * dfra18_1_aj * dfra23_1_aj * dfra1-group

20 Tracking of mcr-1 ( ) and mcr-3 ( ) in the U.S.

21 Initial investigation: Salmonella Heidelberg linked to dairy bull calves Wisconsin Dairy calf ill with scours Salmonella Heidelberg was isolated from the environment at a livestock market WGS showed human, bovine, and livestock market isolates were highly related

22 VALUE OF SEQUENCING AND PREDICTED RESISTANCE RESISTANCE DETERMINANTS Genes detected Predicted AST aada1 sul1 aac(3)-via SSuGen SSuGen aada1 sul1 aac(6')ib-cr aac(3)-vssucip(i/r)gen SSuGen aada1 sul1 tet(a) aac(3)-via SSuTGen SSuTGen aada1 sul1 tet(c) aac(3)-via SSuTGen SSuTGen aada1 tet(a) aac(3)-via dfra15 STGen STGenCot aada12 aada2 blatem-1b dfra1assutcip(i/r)cotlintmassutcipcot PREDICTED RESISTANCE Detect new strains Detect emerging strains Identify sources Faster and more complete data for outbreaks Historical comparison Clinical implications

23 Impact of AMD: Campylobacter jejuni linked to puppies Resistance pattern identified almost one month earlier than AST results were available Isolate sequences available for screening (n = 2) Outbreak identified Screening results available Isolates arrive at CDC for AST (n = 8) AST results available August September

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25 Questions: What is predicted resistance? What are resistance determinants? How accurately can we predict resistance? How is predicted resistance changing workflows? What s the value of predicted resistance? Where can I see predicted resistance information?

26 FINDING PREDICTED RESISTANCE NARMS

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30 FINDING PREDICTED RESISTANCE NARMS SEDRIC

31 FINDING PREDICTED RESISTANCE NARMS SEDRIC NCBI

32 FINDING PREDICTED RESISTANCE NARMS SEDRIC NCBI BIONUMERICS

33 Summary Detection of resistance determinants and predicting resistance are increasingly valuable tools The impact of predicted resistance depends on reliable detection of resistance determinants and correlation with susceptibility tests Please contact with any queries

34 ACKNOWLEDGEMENTS CDC NARMS National Antimicrobial Resistance Monitoring System, Enteric Diseases Epidemiology Branch National Antimicrobial Resistance Surveillance Team Enteric Diseases Laboratory Branch Cindy Friedman (Team Lead) Surveillance Unit Jean Whichard (Team Lead) Applied Research Unit Louise Francois Watkins Ian Plumb Felicita Medalla Beth Karp Christy Bennett Porscha Bumpus- White Hayat Caidi (Unit Lead) Andre McCullough Kaitlin Tagg Jason P. Folster (Unit Lead) Jessica Chen Zachary Schneider Meseret Birhane Jared Reynolds Lauren Ahart Michelle Sanders Elizabeth Meservey Jacob Wilson Hattie Webb Justin Kim

35 For more information, contact CDC CDC-INFO ( ) TTY: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.