Super Bugs Prediction | Detection | Control Mark Tamplin Centre of - PowerPoint PPT Presentation

Super Bugs Prediction | Detection | Control Mark Tamplin Centre of Food Safety & Innovation

Outline Outline Super bugs o Drivers o Forecasting and detection o Management

Emerging Infectious Disease Outline “One that has appeared in the population for the first time, or that may have existed previously but is rapidly increasing in incidence or geographical range .” World Health Organization

Emerging Infectious Disease Outline “ Infectious diseases whose incidence in humans has increased in the past 2 decades or threatens to increase in the near future, have been defined as "emerging." ” US Centers for Disease Control and Prevention

Some major factors that underlie Outline disease emergence and reemergence Morens DM, Fauci AS (2013) Emerging Infectious Diseases: Threats to Human Health and Global Stability. PLoS Pathog 9(7): e1003467. doi:10.1371/journal.ppat.1003467

Super bugs Hazards • Antibiotic resistance o multiple antibiotic resistance • Virulence factors o acquisition of single/multiple genes • Mutations o increase virulence or change host range

One Health NCAS, 2016 Queenan et al., 2016 Intern. J. Antimicrob. Agents Robinson et al., 2016 Trans R Soc Trop Med Hyg Singh, P. 2017 BJM

Antimicrobial Resistance

Antibiotics Hazards Used to Treat, Control and Prevent Microbial Disease Fungi Parasites Viruses Bacteria

Natural role of antibiotics Hazards • Provides a competitive advantage for microbial growth in environmental niches. • Reduces competition in a space, leading to a selective advantage for reproduction.

Natural vs anthropogenic Significant correlation • tet W - phosphorus buffering index • ermB - ammonia, chloride and potassium base saturation • tet W and bla TEM - organic matter, magnesium base saturation

Sources of antibiotics Hazards

Emergence of resistance Hazards • Late 1940s: penicillin-resistant Staphylococcus aureus • 1940-1950: chloramphenicol, tetracycline and erythromycin resistance • Late 1970’s: methicillin -resistant S. aureus (MRSA) • 1997: vancomycin-resistant enterococci (VRE) • 2002: vancomycin-resistant S. aureus • Multiple drug-resistant Pseudomonas aeruginosa

Antibiotic applications in agri/aqua-culture Hazards Antimicrobial class Animal Disease Disease Growth Plant Human Species Treat. Prev. Prom. Use Use Aminoglycosides b,g,p,s,w x x x x Beta-lactams b,d,f,p,s,w x x x x Chloramphenicol b Fluoroquinolones b x x Glycopeptides x Ionophores b,f,g,p,r,s x x x x Macrolides b,p,w x x x x Polypeptides f,p,w x x x x Sulfonamides b,d,f,p,w, fish x x x Tetracyclines b,d,f,bees, p,s,w,fish, lobster x x x x x b=beef cattle, g=goats, p=poultry, s=sheep, w=swine, f=fowl, d=dairy cattle

Impact of antibiotic resistance Hazards • 2,000,000 infections • 23,000 deaths • $20 billion direct medial costs • $35 billion indirect costs CDC, 2013

Impact of antibiotic resistance Hazards O’Neill, 2016

Mechanisms of antibiotic resistance Hazards • Cell wall (e.g. gram+ versus gram-) • Efflux mechanisms (pumps) • Degradative enzymes (e.g. beta-lactamases) • Mutations in DNA or RNA (10 -6 to 10 -9 ) o Alteration of receptors o Membrane permeability changes • Genetic transfer

Plasmids Hazards Extrachromosomal genetic material Plasmids

Transposons Hazards Extrachromosomal genetic material (e.g. bacteriophage-mediated) Transposons

Drivers of Super Bugs • Host • Population densities • Environment

Categories of persons at risk to serious foodborne disease: • fetus and infants • people with chronic diseases • elderly • immuno-compromised • reduced host defences

Susceptibility Consumers are also changing Much like how we affect the environment, we also influence our susceptibility. Increasingly, more people have: • chronic disease • compromised host defenses These issues will impact control strategies.

Population growth (i.e. density) Mega shock: World population growth Year 1978 2006 2050 Africa 456 932 2191 Asia 2538 3989 5142 Europe 686 732 719 Latin America 1 346 563 750 North America 249 332 446 Oceania 22 34 55 (Australia) (14.3) (20.7) (31.7) World 4300 6583 9306 millions UN DEMOBASE Extract 2011 1 Includes The Caribbean

Higher densities • Higher densities of contaminants = greater probability of genetic transfer (people, agriculture, aquaculture) • Water (and air) treatment will become increasingly important.

Climate Change

Toxic Algal Blooms - oysters - lobsters - mussels

Modelling pathogens as a function Vibrio disease of environmental parameters 100000 10000 V. parahaemolyticus density 1000 in oyster (Vp/g) 100 10 1 0.1 0.01 -5 0 5 10 15 20 25 30 35 Water temperature (  C) Regression fit of log 10 V. parahaemolyticus (Vp) densities in oysters versus water temperature (DePaola et al ., 1990). Mean log 10 Vp/g or median Vp/g (solid line) and 95% confidence limits (dashed lines). FDA V. parahaemolyticus Risk Assessment 2005

New pathogenic strains • Example – Vibrio parahaemolyticus o O3:K6 strain emerged in India in 1996 o Arrival of the Asian O3:K6 serotype in Chile was facilitated by warm equatorial water displaced from Asia to Americas by two El Niño episodes. • Example - Vibrio cholerae o O1 strain emerged in USA Gulf of Mexico in 1980 o O1 strain emerged in Peru in 1991 o O139 emerged in India in 1992

Forecasting and detecting Super Bugs

Foodborne Illness Surveillance

Whole Genome Sequencing

But can we detect them all? • Creutzfeldt Jakob disease • Scrapie • Mad Cow Disease - bovine spongiform encephalopathy

Real-time monitoring o Identifying markers (indicators) and the use of models will become increasingly important. o Real-time monitoring of microbial communities.

Log Vp/g=-2.05+ 0.097*temp water +0.2*sal-0.0055*SAL 2 √growth rate = 0.0303 x (temp-13.37)

Managing Super Bugs

One Health UC Davis, https://www.ucdavis.edu/one-health/collaborations/

Water temperature V. vulnificus baseline levels Figure 5: Figure 6: 90W 89W 88W 87W 90W 89W 88W 87W 30.7N Alabama Florida 30.7N Sep. 18, 2004 Sep. 18, 2004 Alabama Florida Mississippi SST V Vulnificus (baseline) Mississippi log of mean Vv/g at harvest 30.3N 30.3N 29.9N 29.9N Louisiana Louisiana 29.5N 29.5N 29.1N 29.1N Celsius 3.5 3.6 3.7 3.8 3.9 4.0 25 26 27 28 29 30 90W 89W 88W 87W 90W 89W 88W 87W 30.7N 30.7N Alabama Florida Sep. 18, 2004 Sep. 18, 2004 Alabama Florida V Vulnificus (baseline) Mississippi V Vulnificus (scenario 1) Mississippi log of mean Vv/g log of mean Vv/g at consumption at consumption 30.3N 30.3N 29.9N 29.9N Louisiana Louisiana 29.5N 29.5N 29.1N 29.1N 3.5 3.7 3.9 4.1 4.3 4.5 4.0 4.2 4.4 4.6 4.8 5.0 Figure 7: V. vulnificus levels at time of consumption Figure 8: Log mean risk at consumption FAO/WHO Working Group 5 Risk Management Exercise 2006

NextGen Antimicrobials • Bacteriophage • Bacteriocins • Quorum factors • Probiotics/prebiotics

Bacteriophage

Bacteriocins Bacteriocins

Quorum factors Quorum Sensing Blocking pathogen signalling

Probiotics and Prebiotics

Managing microbial communities Manipulating microbial communities Manipulating species to displace pathogens, prevent disease and improve health.

PREDICT Manipulating microbial communities http://www.vetmed.ucdavis.edu/ohi/predict/

Thank you!