Plenary: Advanced Molecular Detection in Environmental ... · MO10 O139. 623-39. 1587 O12. VL426...

APHL Annual MeetingRhode Island Convention Center

June 12, 2017

Plenary:Advanced Molecular

Detection in Environmental

Matrices

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

University of Maryland, College Parkand

Johns Hopkins University Bloomberg School of Public Health

Water-related diseases

Amoebiasis

Arsenic

Diarrhoeal disease,Including cholera

Dracunuliasis (guinea worm)

Fluorosis

Giardiasis

Hepatitis A

Intestinal helminths

Malaria

Schistosomiasis

Trachoma

Typhoid

48,000,000

28-35m exposed to drinking water with elevated levels

1.5 billion

> 5000

26 million (China)

500,000

1,500,00

133,000,000

396,000,000

160,000,000

500,000,000

500,000

110,000

1,800,000

-

-

Low

-

9400

1,300,000

> 10,000

-

25,000

Cases per year Deaths per year

Background on 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.

G. Constantin de Magny

Model for the Transmission of Vibrio Cholerae from the Environment to Humans

Work begins in Bangladesh in 1975

Dan Zimble, ESRI Inc.

West Virginia UniversityCivil and Environmental Engineering

Chronology of cholera and satellites

Colwell (1996)Colwell (1996)

1996: Colwell’s coastal vibrio hypotheses

2001: Lobitz’s chlorophyll-SST

Several attempts to link satellite data with cholera

Classification of coastal and Inland cholera

Cholera and SST in the Indian Ocean

0 0.6+

R2

Six-month SST lead: R2 = 0.72

Lobitz et al., 2000, PNAS Vol. 97, No. 4 pp. 1438-1443

Vezzulli et al. Proc. Natl. Acad. Sci. USA 2016 113 (34) E5062-E5071 doi:10.1073/pnas.1609157113

Presenter

Presentation Notes

Figure 2. Change in North Atlantic sea surface temperature (degree Celsius) over the study period calculated as delta between sea surface temperature averaged over the years 2000 to 2011 and 1890 to 1958. Hot colors indicate areas of warming. Sampling areas are indicated as black dots on the map.

Vezzulli et al. Proc. Natl. Acad. Sci. USA 2016 113 (34) E5062-E5071 doi:10.1073/pnas.1609157113

Presenter

Presentation Notes

Figure 5 Multidecadal relationship between Vibrio prokaryote abundance, plankton abundance and plankton community structure in the North Sea for 1958-2011. A. Standardized (Z) Vibrio index (VAI) data (blue triangles) are superimposed to broad-scale submodel monthly time series for the phytoplankton color index (PCI, green line) and total copepod (TotCop, brown line) data for the northern and southern North Sea. Presence of human pathogenic species, V. cholerae (V.c.-yellow bacterial cells), V. parahaemolyticus (V.p.- green bacterial cell) and V. vulnificus (V.v-pink bacterial cell) is shown. Pearson correlation analysis was performed between VAI and corresponding plankton submodel data for the month of August, 1958 to 2011. B. Month by year contour plots of plankton abundance for the ten most abundant phyto- and zooplankton species in the northern and southern North Sea, according to Johns and Reid (80). PHYTOPLANKTON: Ceratium fusus (C.fusus), Ceratium furca (C.furca), Ceratium tripos (C.tripos), Ceratium lineatum (C.lin), Ceratium macroceros (C.macro), Ceratium longipes (C.long), Ceratium horridum (C.horr), Thalassiosira spp. (Thalass), Chaetoceros(Hyalochaete) spp. (Hyal), Chaetoceros(Phaeoceros) spp. (Phaeo), Rhizosolenia imbricata (R.Imb); ZOOPLANKTON: Calanus Traverse (CalTrav), Calanus I-IV (CalI-IV), Calanus finmarchicus (Cal.fin), Calanus helgolandicus (Cal.hel), Para-Pseudocalanus spp. (PPcal), Echinoderm larvae (Ech.larv), Acartia spp. (Acartia), Evadne spp. (Evadne), Oithona spp. (Oithona), Pseudocalanus adult (Pcal.ad), Podon spp. (Podon), Temora longicornis (Temora l).

Antarpreet Jutla, Elizabeth Whitcombe, Nur Hasan, Bradd Haley, Ali Akanda, Anwar Huq, Munir Alam, R. Bradley Sack and Rita Colwell. 2013. Environmental factors influencing epidemic cholera. Amer J Trop Med Hyg 89(3) 597-607

Could we have predicted the Haiti Cholera outbreak?

Recent cholera outbreak in Haiti indicated the disease remains a global threat.

Framework for developing cholera prediction models in cholera endemic (ER) and non-endemic regions (NER)

The sharp contrast in mortality rates between ER and NER exists not because we do not know how to treat cholera patients, but because of a persistent “knowledge barrier” between ER and NER.

We propose a pragmatic and adaptive framework which hypothesizes that convergence of three enabling situations - Inception, Environmental Conditions, and Transmission - are necessary for a cholera outbreak to become an epidemic.

050

100150200250300350400450

Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Sep Oct

Nov

Dec

Pre

cipi

tatio

n (m

m/m

onth

)

Average 2010

Air temperature in Haiti in 2010 and average of air temperature data for last 50 years.

Monthly rainfall in Haiti in 2010 compared with historical rainfall data.

Jutla, A.S., Whitcombe, E, Hasan, H., Haley, B., Akanda, A., Huq, A., Alam, M., Sack, B., Colwell, R.2013. Environmental factors influencing epidemic cholera. American Journal of Tropical Medicineand Hygiene, 89(3):597-607.

Epidemic cholera model

Source: The Institute for Genomic Research

Vibrio cholerae

Sequenced and published in 2000

Chromosome I (2,961,149 bp, 2,742 ORFs)

RC9 O1 Ctx+ Kenya 2740-80 O1 ElTor Env USNCTC8457 O1 ElTor 1910B33 O1 ElTor MzbMJ-1236 O1 hybrid biotype MO10 O139623-391587 O12VL426 albensisO395 O1 ClassicalAM-19226 O39 TMA21 non-O1 BrazilMAK757 O1 ElTor 1937 MZO-2 O14 MZO-3 O37 RC385 O135 Csp BayV51 O141 USV52 O37 Sudan

Chromosome II (1,072,315 bp, 1,093 ORFs)

Missing ORFs in V. cholerae strains (Reference: N16961; cutoff = 70% DNA similarity)

RC9 O1 Ctx+ Kenya 2740-80 O1 ElTor Env USNCTC8457 O1 ElTor 1910B33 O1 ElTor MzbMJ-1236 O1 hybrid biotype MO10 O139623-391587 O12VL426 albensisO395 O1 ClassicalAM-19226 O39 TMA21 non-O1 BrazilMAK757 O1 ElTor 1937 MZO-2 O14 MZO-3 O37 RC385 O135 Csp BayV51 O141 USV52 O37 Sudan

Small Chromosome Large Chromosome

Chun et al. Proc. Natl. Acad. Sci. USA 2009 106(36):15442-15447 doi:10.1073/pnas.0907787106

Presenter

Presentation Notes

Image: Circular representation of the small and large chromosomes of vibrio cholerae Caption: In 2000, the genomes of the two chromosomes possessed by V. cholerae were sequenced. The toxin genes, of which there are fifty, reside on the large chromosome. The sequencing data confirm that V. cholerae is a versatile organism, able to live in several habitat types, as well as to infect the human gastrointestinal tract. Further information: As S. Sozhamannan and others have reported, Vibrio cholerae has a gene acquisition system located on its small chromosome as well as hot spots for DNA rearrangement. Lateral transfer of genetic material is clearly occurring in this organism. The complete genome of Vibrio cholerae El Tor N16961 consists of two circular chromosomes (2,961,146 and 1,072,313 base pair) with 3,890 predicted open reading frames (2,775 and 1,115 on each chromosome respectively). The majority of recognizable genes for essential cell functions (such as DNA replication, transcription, translation, etc.) and pathogenicity (such as toxin, surface antigens, and adhesion) are located on the large chromosome. The small chromosome contains a large percentage of hypothetical genes, more genes that appear to have origins other than the Proteobacteria, a gene capture system (integron island) that suggests this may have been a mega-plasmid captured by an ancestral Vibrio species. The Vibrio cholerae genome sequence provides a starting point for understanding how a free living, environmental microorganism is also a human pathogen. Source: The Institute for Genomic Research Website: http://www.tigr.org/ NSF Funded: Yes NSF permission to use: Yes

0.00002

HC61A1

HC81A1

HC41A1HC7A1

HC80A1

HC46A1HC17A2HC22A1

HC32A1HC68A1

HCUF01HC48A1HC20A2

2010-EL17862010-EL1792HC38A1HC49A2

HC21A1HFU022010-EL1798HC40A1HC70A1

HC42A1HC57A2HC47A1

CP1038

CP1048CP1050

CIRS 101

CP1042

CP1040CP1041

MO10MJ-1236

B33CP1032

CP1033RC9

INDRE 91/1N16961

HC43A1HC23A1HC06A1

(c)7th pandemic (c)

HC-2 (b)

NCTC8457BX330286

M66-2MAK7572740-80V52O395RC27

LMA3984-412129(1)

MZO-3AM-19226

HE-25TMA21

623-391587MZO-2

HE-40HE-46HE-39

HE-48HC-44C1HC-46B1HC-43B1HC-41B1HE-45

AmazoniaTM11079-80

V51CT5369-93

RC385VL426

HE-09HE-16

0.002

(a) (b)HC-51A1

HC-02C1HC-1A2HC-2A1HC-36A1HC-50A1HC-55B2HC-55C2HC-57A1HC-59A1HC-59B1HC-60A1HC-61A2HC-78A1

HC-56A1HC-52A1

HC-55A1

0.0000005

HC-1

Haiti, 2010

Bangladesh, 2010

Zimbabwe, 2009

Bangladesh, 2002

Thailand, 2010

Zambia, 2004

Mexico, 1991Mexico, 2000

Phyl

ogen

omic

sThe Haitian V. cholerae O1 strains clustered with other 7th pandemic V. cholerae strains in a single monophyletic clade

Haitian strains branching separately from South Asian V. cholerae strains

10 Haitian strains (red) form a cluster cloud, distinct and yet, distant, from CP genomes (concurrent epidemic isolates form different parts of the world) (blue) and others (green).

Interestingly, one reference strain CP 1038 (from Zambia) genome falls into the Haitian cluster.

Principal component analysis:The three-dimensional PCA projection plots based on divergence of average nucleotide identity

Haitian Cluster Cloud

Presenter

Presentation Notes

Figure 3. The two-dimensional and three-dimensional PCA projection plots based on divergence of average nucleotide identity. The figure showed 10 Haitian strains (red) forming a cluster cloud, distinct and yet, distant, from CP genomes (blue) and others (green). The figure also illustrated that the CP genomes CP1038_11 and CP1041_14 fall into the Haitian cluster. �Results of PCA analysis (Fig. 3), based on the nucleotide divergence matrix using R (see details in SI Materials and Methods) , showed the Haitian strains forming a distinct cluster, distant from the 7th pandemic South Asian strains, V. cholerae CP1048 and CIRS101, and from other reference genomes. Interestingly, the recent (2009) Zimbabwe epidemic strain V. cholerae CP1038 clustered with the Haitian strains of V. cholerae. However, considering the limited number of reference strains available for analysis, this can be considered as preliminary but an illuminating finding.

Microbiome based Diagnostics

Microbiome Analysis for Rapid Detection of Enteric Pathogens and Characterization of the Intestinal Microbiome in Health and Disease

COSM

OSI

D G

ENIU

S® A

NAL

YSIS

SER

VICE

Microbes Extracted DNA DNA Sequencing

GENEBOOK® Library Raw Sequence ReadsGENIUS®: Probabilistic Matching

Identified BacteriaGENEBOOK® Antibiotic Resistance &

Virulence Factor Library

TetR

CIPR

mecActxA

Pathogen detection for health and wellness;

food safety and probiotics biothreat and public health

surveillance; forensic and scientific

investigation

Applications:

RESE

ARCH

& T

ESTI

NG

LAB

: SE

QU

ENCI

NG

SER

VICE

Presenter

Presentation Notes

pathogen detection for health and wellness, food safety, biothreat and public health surveillance, product safety and efficacy evaluation, and forensic and scientific investigation

CosmosID provides analysis for shotgun metagenomics

Patented Methodologies1. U.S. Patent No. 8,478,544, Issued: July 2, 2013. Direct Identification and Measurement of Relative Populations of

Microorganisms with Direct DNA Sequencing and Probabilistic Methods2. U.S. Patent No. 12/276,037, Issued Jul 8, 2014. A Method and System for Genome Identification3. U.S. Patent Application No. 13/836,139, Filed: March 15, 2013. Characterization of Biological Material in a Sample or

Isolate Using Unassembled Sequence Information, Probabilistic Methods and Trait-Specific Database Catalogs

Microbial ID using NGS Data

GenBook®: Expert-curated

genome databases

Highest performance

bioinformatics algorithms

Graphical User Interface

CosmosID Value Proposition

CosmosID: Next Generation Sequencing

Based Solution for Microbial Identification and Pathogen Characterization

Incredibly fast output – in minutes

(post sequencing)

Expert-curated proprietary genome databases (GenBook®)

High Sensitivity & High Specificity

No A priori assumptions necessary

Polymicrobialidentification from a single

test

Sub-species and Strain level identification,

including abundance

Credentials / On-going Collaborations

Client/Entity Engagement Overview

• 5 Year contract as in the in-house metagenomics solution after an in depth two year bake off

• NIST & CosmosID Metagenomics MVP Challenge v1.0

• BaseSpace Import Integration• #1 all time attended webinar through the end of 2016

• Partnering as CLC’s Metagenomics Solution

• Partnering as Thermofisher Cloud’s Metagenomics Solution

• Nominated to the White House “Cancer Moon Shot” by Vice President Joe Biden

• Working with Big and Small Pharma companies on discovery R&D, clinical trials and quality control

Diarrheal Disease Study: Infectious Disease in the Genomics Era

Diarrheal Disease Study

National Institute of Cholera and Enteric DiseaseKolkata, India

www.niced.org.ind

Total # of NICED samples: 74Indian Healthy Control (HC): 20Sick with Unknown Etiology (UE): 28Sick with Known Etiology (KE): 26Healthy Human Microbiome Project (HMP): 20

BacteriaVibrio choleraeVibrio parahaemolyticusVibrio fluvialisAeromonas spp.Campylobacter jejuniCampylobacter coliShigellaSalmonellaEscherichia coli

VirusesRotavirusAdenovirusNorovirusSapovirusAstrovirus

ParasitesGiardia lambliaCryptosporidium parvumEntamoeba histolyticaBlastocystis hominis

Enteric Pathogens Monitored By NICED(using non-metagenomic methods)

Diarrheal Disease Study

In collaboration with the National Institute of Cholera and Enteric Disease(NICED), Calcutta, India

Presenter

Presentation Notes

@ 2% Surveillance (every 50th patient) at the National Institute of Cholera and Enteric Diseases (NICED), Calcutta, India

γ- Proteobacteria – Firmicutes - Bacteroidetes

(HEALTHY)

DIA

RR

HEA

L PA

TIEN

TS

HEA

LTH

Y IN

DIV

IDU

ALS

Microbiomes of Diarrheal Subjects Compared to Healthy Subjects

Many Pathogens Readily Identified From Diseased Patients

Healthy Control

Human Microbiome Project

Diseased, Known Etiology

Diseased, Unknown Etiology

Presenter

Presentation Notes

HMP samples indicate, gut microbiome of western Europeans are compositionally similar Whereas microbiome of Indian populations significantly varied among themselves, an observation attributable to wide socio-economical and habit-habitat difference with the Indian population Healthy Indian may tolerate low level of pathogen that may indicate disease state in Western European Samples of Unknown etiology are markedly different than healthy and known etiology

Individuals with AMR genes present in their microbiome

beta.lactamase

tetracycline

sulphonamide

rifampicin

quinolone

fosfomycin

nitroimidazole

phenicol

macrolide

trimethoprim

aminoglycoside

Unknown Etiology

Known Etiology

Healthy or Asymptomatic Control

0

4.8

9.6

15

Genes which match at > 50% coverageHMP samples had no genes present which matched at this level of coverage

• Microbial communities of healthy volunteers suggest that the microbiome of healthy humans of Indian descent is markedly different than those of Western European descent.

• Indian population may tolerate low number of pathogenic microorganisms that may indicate a “disease state” for Western European descent

• Multiple pathogens can readily be identified from disease patients

• Metadata revealed that patients who exhibited profound watery diarrhea contained in their microbiome pathogens primarily of the Escherichia coli complex, namely pathogenic E. coli and Shigella species.

• The microbial community of the Indian population encodes higher rates of antibiotic resistance genes when compared to healthy HMP samples

• Functional analysis of the Indian microbiome indicates predominance of carbohydrate metabolism genes

Summary

Infectious Disease in the Genomics Era

Necrotizing fasciitis

Neighbor-joining tree using 2,514 conserved full length predicted proteins

Polymicrobial Infection: Necrotizing Fasciitis

Presenter

Presentation Notes

Late in 2014, Dr. Chopra and Dr. Colwell, founder of CosmosID, met each other in a scientific conference and discussed about the potential use of CosmosID GENIUS solution to identify and differentiate individual strains in mixed infections like this. As a result an animal experiment was designed to better understand the infection dynamics and the role of multiple strains in mixed infections, using GENIUS. Dr. Chopra and his colleagues conducted the animal experiment, by injected mixed culture of NF1-NF4 strains intra muscularly (as i.m. injection produces NF symptoms very well) All five mice injected with the mixed culture of NF-1 to -4 died by the time of muscle tissue, spleen and liver samples were collected (24 hrp.i.). They did species specific PCR which shows the presence of Aeromonas DNA in all three samples types The extracted DNA from these samples were subjected to whole genome shotgun sequencing using Illumina MiSeq at FDA, and sequenced data were analyzed by Genius software at CosmosID.

Relative distribution of four Aeromonas hydrophila strains NF1, 2, 3, and 4 into different metagenomic datasets derived from muscle, spleen and liver samples

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Mus

cle

1

Mus

cle

2

Mus

cle

4

Mus

cle

35

Sple

en 4

5

Sple

en 1

23

Live

r 1

Live

r 2

Live

r 3

Live

r 4

Live

r 5

Rel

ativ

e ab

unda

nce

of N

F st

rain

s

Aeromonas hydrophilaNF4




Strain level ID shows selective dissemination

Presenter

Presentation Notes

This analysis involved creation of a new database, where we incorporated the four NF strains into our existing curated bacterial database, which contain about 4800 bacterial genomes. Our automated process placed these four NF strains into the Aeromonas clade along with other A. hydrophila present in the database and identified unique patterns for each of the four strains (41483, 147, 47, and 63 for NF1, 2, 3, and 4 respectively). The large number of patterns unique to NF1 indicates that it's quite different than other three strains which appears to be very closely related but yet distinguishable by few dozens of unique biomarkers. We analyzed the thirteen metagenomic datasets against these newly constructed database, and the result of our analysis indicated presence of multiple strains in the muscle tissue but too our surprise both spleen and liver were occupied by only NF1. This very interesting but unexpected findings.

Strain interaction in mixed infection

Dissemination to peripheral

organs


organs


organs

• 15 Klebsiella pneumoniae carbapenemase (blaKPC)-Aeromonas sp. and Enterobacteriaceae clinical isolates were collected between 2/2012-5/2013

• These were paired with 32 sink trap biofilm samples collected from the same hospital in 3/2014.

• In addition, the 15 isolates and 9 of the sink trap biofilms were sequenced.

• Metagenomic WGS data was analyzed by CosmosID.

• To determine if the patient isolates were present in any of the biofilm samples, their genomes were assembled and added to the ~31,000 genomes already in the CosmosID bacterial database.

• The biofilm WGS metagenomes were then analyzed using this supplemented database.

• Both the sink trap biofilm samples and the patient isolates were also profiled using the CosmosID antimicrobial resistance and virulence gene databases.

Collaboration with Amy J. Mathers, UVA

Hospital Biofilms: Source Tracking

• An edge connects an isolate (in red) to a sink trap biofilm (in blue), if the isolate is present in the biofilm.

• An edge connects 2 isolates if they were both found in the same sink trap sample.

• The size of the isolate vertices represents the average abundance in the biofilm samples.

Co-occurency graph of patient isolates and sink trap biofilms based on metagenomic analysis

Patient isolate (red)Sink trap biofilm (blue)

Patient Isolates Present in Sink Trap Biofilms

• Except for 3 genes, all genes found in common between the isolates and the biofilms are plasmid-associated. • There are 2 distinct clusters of biofilms and isolates (circled).

Accessory Gene Profiling for Biofilm Samples and Patient Isolates

Plasmid AssociatedNot Plasmid Associated

Antibiotic Resistance and Virulence Genes

The Microbiome as Therapy

Pre and Post-Fecal Microbiota Transplant (FMT) Microbial Shift

Pre-FMT Post-FMT

✪ Strain associated with disease

✪

37

Protection of Microbiome from Antibiotic Induced Change

Prevented overgrowth of organisms known for secondary infection

Orange County Water District Study

The influent, secondary treated municipal wastewater of the AWPF treatment train ispurified by a three-step process: microfiltration, reverse osmosis, and 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.

Metagenomics and Public Health

SodiumHypochlorite

influent

Filter Screens

Microfiltration (MF) process

Reverse Osmosis (RO)Process

H2O2

AWPF final product water

UltravioletIrradiation System

Decarbonators

Add’n Lime

Relative abundance and diversity of parasite DNA in MF-biofilm and Q1-water. The approximate relative abundance heat map was simplified, using the GENIUS bioinformatics algorithm and curated databases. The 99 relative abundance corresponds to sequences classified as Paramecium biaurelia strain v14, Thalassiosira, and Acanthamobea polyphaga based on observed frequency of DNA sequences identified. Parasite sequences were not found in the RO-biofilms.

Acanthamobeapolyphaga Thalassiosira

Paramecium biaureliastrain v14

Q1-water

MF-biofilm

RO-biofilm

99

30

9

2

0

RO-biofilm

Adeno-associated

MF-biofilm

Q1-water

Pseudomonas

Klebsiella

Salmonella

Aeromonas

Burkholderia

Escherichia

Yersinia

Enterobacteria

Vibrio

Mycobacterium

Shigella

Stx1 Converting

Erwinia

Bacteroides

Lactococcus

Enterobacteria

Streptococcus

bacteriophage

virus

N=15

N=10N=4

N=0

Viral DNA 1709

Stx2 Converting

Roseophage

Yersinia

Escherichia

Lactococcus prophage

Phage-cdtl

Viral DNA 236

Salmonella

Enterococcus

Viral DNA 1241

Virus and bacteriophage DNA sequences comparison demonstrate the presence of bacteriophages and virus DNA in the membrane filter (MF)-biofilm and in the influent water, Q1. Note, the absence of bacteriophages and DNA viruses in the reverse osmosis (RO)-biofilm. Presence and absences of sequences (partial or complete) related to bacteriophage and viruses in MF-biofilm were compared to the Q1 water.

Comparison of virus and bacteriophage DNA sequences

A Simple, Sustainable Method for

Reducing Cholera

A Simple Solution for Cholera Prevention: Sari Filtration

Full Study

0.000.20

0.400.60

0.801.00

1.201.40

Control Sari Nylon

Test Group

Cas

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f Cho

lera

Per

100

0 Po

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tionFull Study

Control NylonSari

Test Group

Cas

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lera

Per

100

0 Po

pula

tion

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

“When one tugs at a single thing in nature, he finds it hitched to the rest of the universe.”

John Muir(1838-1914)

Collaborators and Colleagues

Anwar Huq, ProfessorUniversity of Maryland,College Park, MD

Dr. Nur HasanVice-President, Research and DevelopmentCosmosID, Inc.College Park, MD

Antarpreet Jutla, Assistant Professor, West Virginia UniversityMorgantown, WV

Dr. Seon Young Choi,

Bioinformatic Scientist, CosmosID Inc.College Park, MD

NICED:G. Balakrish NairThandavarayan Ramamurthy

University of Maryland:Shah M. RashedSeon Young ChoiAnwar Huq

CosmosID:Nur A. HasanPoorani SubramanianKelly MoffatHuai LiBrian FanelliManoj Dadlani

Orange County Water DistrictMenu Leddy

ConsultantJoseph Cotruvo

Amy J. Mathers, UVAAshok Chopra, University of Texas Medical BranchChris Grim, FDA

Genomics Team

Courtesy of GB Nair, NICED, Kolkata, India

Safe water is a global challenge

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