The Global Infectious Diseases, Water and Health

MIT Club of Washington, DC Kenwood Country Club Bethesda, Maryland March 28, 2018

Rita R. Colwell, Ph.D., D.Sc. Distinguished University Professor

Design by: NSF/ A. Jeon Credit: Dr. James P. McVey, NOAA Major technological developments in microbial systematics and ecology over the past half century.

1960 Culture - Numerical Taxonomy

1965 Nucleic Acid (Base Composition)

Evolution of 1970 Density Gradient Hybridization Molecular Systemactics 1975 Fluorescent Antibody Microscopy

1985 Polymerase Chain Reaction (PCR)

19962000 Next Gen Sequencing

2008 Metagenomics 1960 Culture - Numerical Taxonomy

1965 Nucleic Acid (Base Composition)

1970 Density Gradient Hybridization

1975 Fluorescent Antibody Microscopy

1985 Polymerase Chain Reaction

1996 Next Gen Sequencing

2008 Metagenomics Expanding our vision to the Puerto Rico Trench 1970-1980 Building and deploying a deep sea sampler to study pressure tolerant bacteria Shipboard work Water-related diseases Cases per year Deaths per year

Amoebiasis 48,000,000 110,000 Arsenic 28-35m exposed to drinking water with elevated levels Diarrhoeal disease, 1.5 billion 1,800,000 Including cholera Dracunuliasis (guinea worm) > 5000 - Fluorosis 26 million (China) - Giardiasis 500,000 Low Hepatitis A 1,500,00 - Intestinal helminths 133,000,000 9400 Malaria 396,000,000 1,300,000 Schistosomiasis 160,000,000 > 10,000 Trachoma 500,000,000 - Typhoid 500,000 25,000

West Virginia University Civil and Environmental Engineering

1965-1975 An early contribution of marine microbiology to human health: Determination of the Vibrio cholerae life cycle Solving the mystery of the “viable but non-culturable (VBNC)” bacteria

A curiosity – all the bacteria don’t grow in laboratory culture

Now we can see them 1975 Model for the Transmission of Vibrio Cholerae from the Environment to Humans

Physical & Chemical First Responders in the Spring months Characteristics of Water (increased sunlight and • temperature warmer temperatures) • sunlight • algae and phytoplankton • rainfall blooms • pH • dissolved oxygen Followed by Zooplankton blooms • salinity & nutrients Vibrios in non-culturable state in annual cycle and on zooplankton. (Commensal or symbiotic) Fecal shedding from cholera victim transfers V. cholerae to water, food, and fomites V. Cholerae detectable in both the viable and the viable but non-culturable state in the water column in summer months Transmission of V. cholerae to humans via ingested water containing colonized copepods and free swimming V. cholerae cells. (summer months) Work begins in Bangladesh in 1975

Dan Zimble, ESRI Inc. Cholera: A Global Disease

▪ Acute water-related diarrheal disease ▪ Seventh pandemic started in 1960s ▪ Occurs in more than 50 countries affecting approximately 7 million people ▪ Bengal Delta is known as “native homeland” of cholera outbreaks ▪ Since cholera bacteria ▪ exist naturally in aquatic habitats ▪ evidence of new biotypes emerging, it is highly unlikely that cholera will be eradicated but clearly can be controlled by provision of safe drinking water. Bangladesh –The original team in 1975. Bangladesh Model of Cholera source and Transmission

G. Constantin de Magny Cholera and SST in the Indian Ocean 1985 - 2000 Six-month SST lead: R2 = 0.72

R2

0 0.6+

Lobitz et al., 2000, PNAS Vol. 97, No. 4 pp. 1438-1443 Results employing an improved predictive model

Kolkata: Significant and positive relationship between cholera and CHL(t) and Rain(t). Matlab: Significant and positive relationship between cholera and Chl(t-1).

KOLKATA MATLAB +1 mg.m-3 in CHL(t) => +32.5% in number +1 mg.m-3 in CHL(t-1) => +31.4% in of cholera cases (95% CI 8.3%-62.0%) number of cholera cases (95% CI 13.0%- +1 mm.day-1 in Rain(t) => +6.5% in number 52.7%) of cholera cases (95% CI 1.6%-11.7%)

Constantin de Magny et al., 2008, PNAS Predicted Cholera risk areas in Actual Cholera (number of cholera Haiti for December 2016 patients reported) in Haiti (December 2016)

West Virginia University Civil and Environmental Engineering © Jutla/Colwell Real-time cholera prediction for Yemen, 2017

Risk estimated on May 30th, 2017. West Virginia University Civil and Environmental Engineering © Jutla/Colwell Current Epidemic Cholera Model and satellite data source

Figure 1: Earth observations for prediction of epidemic cholera West Virginia University Civil and Environmental Engineering © Jutla/Colwell A Simple, Sustainable Method for Reducing Cholera A simple, sustainable method for preventing cholera Full Study Full Study Results 1.401.40

1.201.20 1.001.00 0.800.80 0.600.60 0.40

Population 0.40 0.200.20

0.000.00 Cases of Cholera Per 1000 1000 Per Cholera of Cases Cases of Cholera Per 1000 Population 1000 Per Cholera of Cases ControControll SariSari NylonNylon Test GroupTest Group 2007 – present www.cosmosid.com Proprietary CosmosID™ How It Works

Biological specimen Community DNA DNA Sequencing

GenBook Biomarker Matching GenBook Database Raw Sequence Reads

Identified Bacteria GenBook AR/VF Library CIPR Microbial Identification & TetR ctxA Pathogen mecA Characterization Best in Class Performance species

• Strain level accuracy • Unrivaled precision and recall • World’s Largest Curated Database • Phylogenetic • Fastest analysis

sub-species

cosmosid.com/blog-cosmosid/benchmarking-genome-biology Why Sub-species/strain-level Identification is important

E. coli Lactobacillus casei species Or a pathogen? Is it commensal? ?

Strain 1 Strain 2 O157:H7 Strain 3 Vitamin K

Vitamin B12

Colonization Barrier Effect Against Pathogens Hemorrhagic enteritis Infectious Disease in the Genomics Era

Necrotizing fasciitis Polymicrobial Infection resulting in Necrotizing Fasciitis

Neighbor-joining tree using 2,514 conserved full length predicted proteins Strain interaction in this mixed infection causing necrotizing fascitis

Dissemination Dissemination to peripheral to peripheral organs organs Microbiome Analysis of Acute Diarrheal Patients Compared with Healthy Individuals

Manuscript in preparation (2018) Diversity in the Human Microbiome

Biodiversity and functional genomics in the human microbiome Morgan et al (2013) Trends in Genetics. http://doi.org/10.1016/j.tig.2012.09.005 Diarrheal Disease Study carried out with the National Institute of Cholera and Enteric Disease, Kolkata, India

www.niced.org.ind Microbiome Analysis of Acute Diarrheal Patients Compared with Healthy Individuals

Bacteria Parasites Viruses Vibrio cholerae Giardia lamblia Rotavirus Vibrio parahaemolyticus Cryptosporidium parvum Adenovirus Vibrio fluvialis Entamoeba histolytica Norovirus Aeromonas spp. Blastocystis hominis Sapovirus Campylobacter jejuni Astrovirus Campylobacter coli Shigella Salmonella Escherichia coli Total # of NICED samples: 74 Indian Healthy Control (HC): 20 Sick with Unknown Etiology (UE): 28 Sick with Known Etiology (KE): 26 Healthy Human Microbiome Project (HMP): 20

In collaboration with the National Institute of Cholera and Enteric Disease (NICED), Calcutta, India Metagenomic results showed Overrepresentation of Subpopulation comprising enteric pathogens in Diarrheal Patients

(HEALTHY)

γ- Proteobacteria – Firmicutes - Bacteroidetes Healthy Gut Microbiome Across Countries and Cultures

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s u c B o R c p c m e 8 m o 2 P _ V e u n c m a A C _ i s r R u _ c a s s _ m _ u i m m _ r s _ c o _ _ l r u p m R n p d p o u s a e s u e i 1 s i s o e m _ p o s s u r r r e _ r u m i i s r p s 0 p p p e l t a r _ 5 r r m 4 r e i s i 7 t o o b _ _ t r _ e t p a n a e e u s _ s r m 6 i t e i t i s f c i 5 s i a D t o u n m s e u c c m m 1 o s d l i m American c v p l a l _ e a P o l s c s c m o e i s n l i _ o i o 2 r r a _ l 1 b l u c m e c o o c u d 3 r 1 u n r a n A t i i e 5 _ 3 c i b o _ S r t o e t 1 o c u n o r o r m n t e A e u i i z s v 9 n d _ e c 3 c c t s i R o c e i r s u i o l l z l u t c 9 i m r l o s u B r l a 1 e i c t a 1 c t e u 1 r o i m t l B a a e % s l r F n i e c a % s s / e % p 2 l % c _ c r a g u F 5 1 o o l 2 b A s i _ a o 1 o V _ o % e c c 1 b a A % % 1 o l d b _ 3 o 0 A R i s o C i r b r % h r 7 A 2 c m M t r o % C o 1 n A t a i o m 1 u m a ib m s e m % h p n 7 r % m e g v o 2 % E o o 1 r % i a i l o i 1 P a r r % r i % a i A e i % s % e 2 y e % C e d t r 1 m u 2 i c des o re s 1 c a 8 oi A u 2 2 i ter li s % 5 o % % A h % bac sti % B t % v 2 ic is ara pe 1 f i 2 % m in D .um tr s P s e ia R p _ o .. o n e R d r u D e .9 2 r 7 re Fa % l tie orp...cea ike % n u m s e a s .ae undef V 2 e te a P ...c .. 1 u b in 6 o Faec...rium 0 st m .. Cl.. e ip lu ll ea . se o m re s li B o . e i...e s _ te ae e o e ii c a 1 .cu a ra la re 1 R ea ae ry us o e .. % R or m oc or % .. i e u % ... A E c v c L . 1 ro c e um ae D a tia m oc re la a . m _b u 2 R ace u h _ u ci c P el c .. % 6 s s_ % in...... n sp w R S ... % to t h 1 cu B to Rum ... d % a is ex el. e 3 ep vo n oc la rq ef 2 g rm le s ..l a tr e .. oc u u u e lla ifo ra es e S r . in tia e n D M e n 07 e le S ore P a m _w s es d n fu :2 ia t c u R l e ia lo s_ G 1 ia N r % m e R R os e 1 ia f % il a A % t id e E E e 1 8 a e x id l e n _C r g 1 u e b le % tr is 1 V o p u e t ia a r r p e % or u r s _s s t. y y m 1 m ria a lo V t m a a d .. s . t C _ e a e a um l lo ri c . S o 8 in C i e r % g ri e t u i . 3 i u 2 a id 2 e te B tes t p l 0 l n l i tr i M c c C s irmicu e e t c m o in % . e s ll a o F s e s . o or iv . o . b a l . s e C s . o l. a l . to l . lu R . r C . % rc r C o L c cil t . a e a 1 a i t a a l o n B ol u c b s r s n r a e to o i u e c F c c de p i u c d c or 1 irm as f c La e s m % a i e . h s c L l . c 5 a r c . P 5% h s i . i i ut S a . o . % t a . e B i . a 1 a a r u . s e % a . i s i l a . p N e 2 n l . d d e s . r a e e s l h e . i d e e . c . i t i s u o . re e a n o o A s a F d . o c a g . t o e e m r i i f R n . 4 l e r a a i 3 c . c l r d % e r um i iella i tridi h a e . s s t t L o i b m l Aga a e le C A K t c . d t . ho m 2% l b t o a E % 1 cte E 1 c . e 2 r_ . D r b _ e a c c r a p t . c a . s li u c _ s i 1 i us % a c s r i . c n c c n o o r a e L i oc .

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m o u r 1 u R 1 o e _ _ c 6 i u M c 3 i p s m c i o % % p m c 2 a i m % i 1 n z _ c _ r 2 o b s t s o _ 2 i o i e 8 8 Tanzania n u c a e n c o y r 6 c m r o % r s s c % t e ip h 4 3 u _ o u o a t R i 1 E p 1 a a R c m e s e r s c r India 1 % P m c i u r l r p c E India u e p e o t r % _ f m t s r A o _ u _ _ S o e p e V % m c e s s ill m i 5 5 p r one 1 m d iu n a % a p e lla r _ s t _ _ is 7 n 2 o n e l 1 e m S ia % % u 1 t 1 s b _ D c e i r r 2 s c l R 1 _ p m m e o o cea S u a o ella l e 1 illon a Ve c _ l 3 t Prevo b c 3 u u t tella i e r / r c i i 5 s l c % S m c m e o i c 9 e r a n p c in d o 1 u e a t o m c B R i e s 1 s 5 r o r B e r t e u s a b u % e r F t i Selen...dales E c t _ a Prev...c a _ 1 i c l s h 3 eae s o n s c F l e i r S F e A s i c m s y u t r b / a r c E ll e 6 v s 5 n t i o o u . c r . o e L A c i c l b o . . o . r n . a 3 a re c .. . u a m V o s i r h i . % e 2 e E a s % b d .. c B u _ c r a e 2 to e 2 7 _ m C m B y a % a l . % r s e c s d 7 2 E O o F p 0 _ e i s a L s 0 2 e a 2 c p L _ :2 i % t 7 B c e L L 1 . a n s D i . l o . Negat...cutes lo .. e o u AG 9 s 8 a . t a a 3 e c C i ut n i. ri c 2% % . m c ._ o % % l 2 ia i c . c c . o o p 1 % % 4 s h t . to . n c s r 1 a i o . s R i e o _ B e % 1 i 1 R 2 m m e a t o C u l n m 1 os % u l utes . o on l . m e mi riu l a D r_ e u a Firmic . L . uc o . S a te R a bu R i .l . e .e d c u e ri R a B a . . L C .. ci ba o t s a id i l . i .l % A to s ti 1 is n 1 r d a e . ll 1% lla lo e 1 rc a % Faec.. % l e 2 % e t i e u e la A e s .rium t mo r c s iss s s % o g b ..cu O 2 ia tu r a s e 1 c . s e t i L s W t s 7 a u m c na r l r a L t 2 u i D i e o s l i . h B h R ll l i . % d . P ._ r % ib cc e o . 1 p o u i a A c i . _s a e u g t C l . a . A % a b n cea c a E tho . e . 1 er a i... . te s b . a m . % _ ac c C N . h c d u . . r e ter . s . . p 1 R .. 4 r m _re s li . . as te e o c a co F g . u a i tali h ia_ e e . . e r f % . D r c . s i h 2 eric l . e M _ m e % b h i t c r sc g . r i h E r % e 1 a 6 c % a a . 1 C s o 2 m . c a a e i s a o % le l V . b . p t i t d a ia s o . . r h i e d t L d e t V or o l i V i . t . r t c a i Co c i t c . 2 m c s e t e r p . o s r i c e oco o . 5 cc e . o a us s c l . r l 1% a r . a a r o u c m e . C i h e u l o r c 2 a re . . c e 3 mo s o e g e t % b e d a . l s s _ . r i i u t t e i e s e c d . a . e i . a p tr c h o B t 1 A Bacteria . . . t _ a s c c o s e P 2 . . o . e A l D c . S e r R _ 1% t . C a a es . Alistip a 2 mor a . p . e t i T t s s . e B a l e % _ . e 5 n us n c c . s . oc b l eptoc 5 2 . r o B t St u n 2% . i / l s c B 1 . h e c r a t o . N E c o e c c F c . B E Bacteria 1 irm . o p 2 c % A . e % a . a ic e . in r . E a u . 1% a t nte te m t . a r a a o L s g a s o e ba L . c d id c e B . t i ro c e . o r te s B . l c c . a a . i b t i e A a r e . r . r . a e m d . P e e t s . r . a o a . . 1% e P 1 . a a i s % A . S Verrucomicrobia 0.0005% o . 1 r L li a . e . ce m % i r . a s . e Verrucomicrobia 0% a ctob t c . ha i d a i . p B c i cil ic . e e r d S e . l a e us s E t e a s r a . u lo r . lm t r . . e o a e a . e e 3 p o c i m i . n . . % t e s 4 r . c e P r y 1 c t P r el . t . e r G l s e . a a E t te _e . a y % e s c o nt . c c . s 2% s e 1 P B ..ete A er 2 . s r ir. a ic o a % . Sp a . a % A . e r a o b M 2 3 e . A Spirochaetes 0.3% i r a 1 . . s o . u o e i i % undef 0.2% t . cin n occ rc c d in r 1 ilis r s et . ptoc e v t e % g o o . . Stre t t i t ra b Po e B A e a . _s e a c . _f r p l e c rphyro i 2% o . c t m c s e o . lla r A . in e r_ nada k d a c . P B i P a a a b eae i a te t o in e ro l a 2% h o e t e to te r e . um . v c . c r i c t b a a . re l d a a B m e . n R i e c n . P l A s p c ria t . ii a e undef 0.005% i a a e r t ct l . v l o e Chlamydiae 0% a m c ia l % Lactobacillus o c le a t r_ ob l 1 i e b tin a a r K Bacteria a i t e s etia ..r o au Ac b e 3 i e a irocha . b m t % r a Sp o e a a G o i l B s l e d a c n r c e r a fi e te n a K a t . i c r ii e le P . e . t b . . . B ia ia ria a b Chlamydiae 0% c . . m te n i s re r . e .tales . 1 Synergistetes 0.07% ac o i 2 mo t . o.. . u 2 b e 2 E Spir i % o E r h l e e e a r 3 o r m ctin e c la r t % d e A i _ v B m e E fi t t r p o o e nter i c o n P o s c t ob B r les n e a i r . act B a e ia e d m c eri % Ba. b i ter E h u r t c . a ace ..a e o fi ac c m e e e P . l a ae Verrucomicrobia 0.5% 3 e Sp...a d d ob o Synergistetes 0.05% % B t ia a l 1 Fusobacteria 0.3% fid s n 2 v l e t r P b ifi o % Bi i a l a e e e E a re o a r t G i B b 3 e e co c o s x o r Ba a ea 7 er c c t c.. c st t t i es a a p .de a 7 c ria % _ e e e d et s Tr...m t s cte lla ir... b ia r e o % e a te l r i p o r 3 u ob vo l a o a S o n % c r t ifid re a n e i undef 0.2% i B Fusobacteria 0.08% P e i ti . _ u a E d . c A Candidatus Saccharibacteria 0% v um c i. M c la m o teri s a A t s in l B _ ac c c e A et e _ dob h le A l ob t ifi st s % Bifi e iia ia ac o 2 s r % d e e tia r e te v r d e 3 ri i... te .. a r % i r p c _ e 1 o c c Candidatus Saccharibacteria 0% S a . e b Chlamydiae 0.004% r % o ro o h % b o c au b r Tenericutes 0% i 7 io m % d 1 i P a i e m e a or ia 3 a t 3 s m r 1 ri C ifi r n s _ m n c c . u 1 i % p . i i T a 0 o c o B . r o e 7 t 2 r e 1 % o c s B % b e e r d _ B s d i s l le o t i e r i a a ta _ 6 c m i i 4 m Tenericutes 0% ll c o... d 4 Synergistetes 0% r t e u s i a o p e e p fi m B t r S i r Cyanobacteria 0% r o o b m m o r o m e m o i B 2 r B v d o o o i e d s r e a % o r fi d r t n _ i o e r B c e e f e o a i P a e e fi f u i o d c i fi a a c m l i t e c . 1 o r t r e .. te oc B n o n d e ir % B a m r p n e a o S 1 Fusobacteria 1% 8 t Cyanobacteria 0% i i u b g u o d % fi B Clostridiales 0% c g e a l a a s 1 d _ b m u a _ one B o _ s u p % s m c B a Tre i b e v fi s t a e c e C d c u d _ d i t o r t i o B Candidatus Saccharibacteria 0% e Clostridiales 0% s 1 e c o i b u % r o e r i r e r a c r i fi m iu r i 1 m % 2 o d c e u i d o m n t e i o t 1 % % b o e t m c _ 7 r _ o m % i b 1 % a e r s c f 6 r % i a l 9 a a u t _ 7 c m o 1 Tenericutes 0.1% 3 . e a e 2 B 2 a c m c t b r t n l _ 0 T e o t c B 0 _ i c e r g 1 o o e r r r a e 2 e r r a c A i u _ s e i n a iu d s v s o D 0 B m 4 i u p l o s r m e t e l _ _ 4 p o s e Cyanobacteria 0% m a p p _ s o r _ n s s g c c 1 c o l e a e _ _ f _ u m n s _ i t s e t e s n 3 v i e a n s d e u _ _ u Clostridiales 0% i d _ d s i i _ p l o s a r o o s s e t r r u u e e _ d t e e i c m t t d s c i o c e c r a c o i n a d a r e B i t i B e f B o t c a r c Actinobacteria a Bacteroidetes - Firmicutes – Proteobacteria - c e a t i B e c B n a s Preliminary Data B What is Healthy?

PCA Analysis on app.cosmosid.com Or, is Healthy more similar than we think?

PCA Analysis on app.cosmosid.com Safe Drinking Water: Ensuring Microbial Quality in Water Manufacturing for Orange County, CA

The influent, secondary treated municipal wastewater of the AWPF treatment train is purified by a three-step process:

① microfiltration, ② reverse osmosis, and ③ ultraviolet (UV) light with hydrogen peroxide.

Initially the wastewater is screened at 4mm, Sodium hypochlorite as disinfectant is added prior to microfiltration.

Hydrogen peroxide (H2O2) is added before UV treatment.

The decarbonators remove CO2 and raise the pH; addition of lime further stabilizes the purified water. Sampling Microbial Quality at selected steps of the Water Manufacturing Process

Sodium

Hypochlorite H2O2

influent AWPF final product water

Filter lime Microfiltration (MF) Reverse Osmosis (RO) Ultraviolet Screens process process Irradiation System decarbonation Stepwise reduction of bacterial genera from MF to RO

Microfiltration (MF)

Reverse Osmosis (RO)

Relative Abundance—% Viral diversity

Genera of virus and phage DNA DNA & cDNA cDNA Q1 both

- Rhino virus branch

- Pepper mild motile virus (PMMoV) - E. coli phage - Adeno virus branch

MF_biofilm

- - Adeno virus branch PMMo - E. coli phage V

RO_biofilm

Predominately bacteriophage identified in all samples Distribution of antibiotic resistance genes (ARGs) and stepwise reduction of ARG’S in MF and RO-biofilms

(a) RO

Input water from sewage treatment plant (Q1)

Microfiltration (MF) biofilm

Reverse Osmosis (RO) - biofilm

N=141 140

120

100 N=85 Q1 80

60 Number ofARGs 40

20 N=9 MF 0 Q1-water MF-biofilm RO-biofilm Safe water is a global challenge

Courtesy of GB Nair, NICED, Kolkata, India “When one tugs at a single thing in nature, he finds it hitched to the rest of the universe.” John Muir (1838-1914) Genomics Team 2017-2020

NICED: CosmosID: G. Balakrish Nair Nur A. Hasan Thandavarayan Ramamurthy Poorani Subramanian Kelly Moffat University of Maryland: Huai Li Shah M. Rashed Brian Fanelli Seon Young Choi Manoj Dadlani Anwar Huq Orange County Water District West Virginia University Menu Leddy Antarpreet Jutla Consultant Joseph Cotruvo Amy J. Mathers, UVA Ashok Chopra, University of Texas Medical Branch Chris Grim, FDA