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Clinical Metagenomics for Rapid Detection of Enteric Pathogens
and Characterization of the Intestinal Microbiome
Dr. Rita R. Colwell
University of Maryland, College Park
Johns Hopkins University Bloomberg School of Public Health
CosmosID Inc.
History/Cholera
Metagenomics
Microbiomes in Health and Disease
Demo
Culture - Numerical Taxonomy
Nucleic Acid (Base Composition)
Density Gradient Hybridization
Fluorescent Antibody Microscopy
Polymerase Chain Reaction (PCR)
Next Gen Sequencing
Metagenomics
1960
1965
1970
1975
1985
1996
2008
2000
A Timeline of Microbiology
First Numerical Approaches to Microbial Taxonomy
Culture - Numerical Taxonomy
Nucleic Acid (Base Composition)
Density Gradient Hybridization
Fluorescent Antibody Microscopy
Polymerase Chain Reaction
Next Gen Sequencing
Metagenomics
1960
1965
1970
1975
1985
1996
2008
2000
Culture Limitations
A curiosity –
All the bacteria
don’t grow in
laboratory culture
Solving the Mystery of the “Viable But Non-Culturable (VBNC)” Bacteria
Culture - Numerical Taxonomy
Nucleic Acid (Base Composition)
Density Gradient Hybridization
Fluorescent Antibody Microscopy
Polymerase Chain Reaction (PCR)
Next Gen Sequencing
Metagenomics
1960
1965
1970
1975
1985
1996
2008
2000
JD Oliver, Journal of Microbiology, 2005 Feb; 43 Spec No: 93-100
Over 400 papers have appeared on the VBNC phenomenon
and over 1000 papers describing the various aspects of it.
Bacteria Described to Enter The VBNC state
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.
The Copepod Vector
Copepods were found to carry approximately 10,000
to 50,000 CFU of V. cholerae per copepod
Culture - Numerical Taxonomy
Nucleic Acid (Base Composition)
Density Gradient Hybridization
Fluorescent Antibody Microscopy
Polymerase Chain Reaction (PCR)
Next Gen Sequencing
Metagenomics
1960
1965
1970
1975
1985
1996
2008
2000
10
A Simple Solution for Cholera Prevention : Sari Filtration
The move to genomics…early sixties to the present
Source: The Institute for Genomic Research
Vibrio cholerae
Sequenced and
published in 2000
Small
Chromosome
Large
Chromosome
Culture - Numerical Taxonomy
Nucleic Acid (Base Composition)
Density Gradient Hybridization
Fluorescent Antibody Microscopy
Polymerase Chain Reaction (PCR)
Next Gen Sequencing
Metagenomics
1960
1965
1970
1975
1985
1996
2008
2000
Genomic re-assortment not serotype defines epidemic clones
History/Cholera
Metagenomics
Microbiomes in Health and Disease
Demo
Role of Microbiome in Health and Wellness
Acne
Alzheimer’s Disease
Antibiotic-associated Diarrhea
Atherosclerosis & Arthritis
Asthma/Allergies
Attention Deficit Hyperactivity Disorder
Autism
Autoimmune Diseases (Multiple Sclerosis, Lupus, Rheumatoid arthritis)
Bipolar Disorder
Cancer
Chronic Fatigue / Fibromyalgia
Coeliac Disease
Chron’s Disease
Cystic Fibrosis
Dental Cavities
Depression and Anxiety
Diabetes Type 1 & 2
Epilepsy
Eczema
Irritable Bowel Syndrome
Gastric Ulcers
Malnutrition
Narcolepsy
Obesity
Parkinson’s Disease
Ulcerative Colitis
Identified Bacteria
Raw Sequence Reads
Biological specimen Community DNA
GenBookⓇ Biomarker Matching
GenBookⓇ AR/VF Library
TetR
CIPR
mecA
ctxA
Microbial
Identification &
Pathogen
Characterization
GenBookⓇ Database
How It Works
DNA Sequencing
CosmosID for Automated Metagenomics in the 21st Century
CosmosID Analyzes Microbial DNA sequences
• Growing proprietary database of 65,000
microbial genomes (bacteria, viruses, fungi and
parasites)
• In minutes, our software solution delivers
unrivaled specificity and sensitivity
• Microbial Identification at subspecies/strain level
• Relative abundance of the microbial community
• Presence of antibiotic resistance and virulence
factors
• Sequencing platform agnostic
• Can handle both short read and long read NGS
data
• Illumina, ThermoFisher, Pacific Biosciences and
Oxford Nanopore
• Commercial products (software and databases
are well maintained and continuously updated)
Infectious Disease – Rapid Evolution
§ Previously recognized pathogens
are evolving faster.
§ New, potentially dangerous
pathogens are emerging every
year.
§ Nosocomial and mixed microbial
infections are dramatically
increasing.
§ Many acute infectious diseases
have unknown or poorly known
etiology
§ Resident microflora in health and
wellness Source: Clinical Infectious Diseases 2013;57(S3):S139–70
0.0
0.0
CosmosID_filtered
CosmosID
BlastMegan_filtered
BlastMegan_filtered_liberal
LMAT
MetaPhlAn
Kraken_filtered
PhyloSift_filtered
DiamondMegan_filtered
Kraken
OneCodex
NBC
PhyloSift
OneCodex_filtered
0
20
40
60
80
100
percent
subspecies
BlastMegan_filtered
CosmosID_filtered
OneCodex_filtered
BlastMegan_filtered_liberal
DiamondMegan_filtered
CosmosID
MetaPhlAn
Kraken_filtered
LMAT
PhyloSift_filtered
CLARKS
Kraken
CLARK
NBC
OneCodex
PhyloSift
0
20
40
60
80
100
percent
species
BlastMeg
Cosmos
OneCod
BlastMegan_filter
DiamondMeg
Krak
PhyloS
B
C
CosmosID Performance
Unpublished Data:
• 34 datasets of
varying complexity
and diversity
• 12 tools
0.0
F1
0.0
F1
CosmosID_filtered
CosmosID
BlastMegan_filtered
BlastMegan_filtered_liberal
LMAT
MetaPhlAn
Kraken_filtered
PhyloSift_filtered
DiamondMegan_filtered
Kraken
OneCodex
NBC
PhyloSift
OneCodex_filtered
0
20
40
60
80
100
percent
subspecies
BlastMegan_filtered
CosmosID_filtered
OneCodex_filtered
BlastMegan_filtered_liberal
DiamondMegan_filtered
CosmosID
MetaPhlAn
Kraken_filtered
LMAT
PhyloSift_filtered
CLARKS
Kraken
CLARK
NBC
OneCodex
PhyloSift
0
20
40
60
80
100
percent
species
BlastMegan_filtered
CosmosID_filtered
OneCodex_filtered
BlastMegan_filtered_liberal
DiamondMegan_filtered
CosmosID
MetaPhlAn
Kraken_filtered
LMAT
PhyloSift_filtered
CLARKS
Kraken
CLARK
OneCodex
NBC
PhyloSift
0
20
40
60
80
100
percent
genus
F1-score
precision
recall
AUPR
B
A D
C
Collaboration with Chris Mason, Weil Cornell
Medicine
Accuracy of Relative Abundance
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BLAST−Megan
BLAST−Megan−Liberal
CLARK
CLARK−S
CosmosID−filtered
CosmosID
Diamond
Kraken−filtered
Kraken
LMAT
MetaPalette
MetaPalette−Specific
Metaphlan2
NBC
OneCodex−filtered
OneCodex
Phylosift−filtered
Phylosift
Percent Difference of Estimated to True Abundance
BioPool & NARG1 samples
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BLAST−Megan
BLAST−Megan−Liberal
CLARK
CLARK−S
CosmosID−filtered
CosmosID
Diamond
Kraken−filtered
Kraken
LMAT
MetaPalette
MetaPalette−Specific
Metaphlan2
NBC
OneCodex−filtered
OneCodex
Phylosift−filtered
Phylosift
Percent Difference of Estimated to True Abundance
HC LC samples
Synthetic Datasets Biological Datasets
Detection is one problem; abundance is much harder
Biological
Specimens
(i.e. Stool,
CSF, etc.)
Sequencing
Further analysis using CLC
• Functional
• Mapping
• Assembly
CLC
Sample to Analysis with CLC + CosmosID Plugin
CosmosID
CLC Plugin
X
Y
Z
BEST MATCH
• Microbial Identification
(subspecies & strain)
• Antibiotic Resistance
• Virulence Factors
• Relative Abundance
• Bacteria, fungi, protists,
viruses
WGS fasta or
fastq file
Curated Genome Databases
§ Most	comprehensive	and	largest	curated	databases	(>	65,000	genomes)	
§ Organized	as	phylogenetic	trees
§ Two	types	of	biomarkers:	
§ Unique	to	the	organism,	and	
§ Shared	across	the	phylogenetic	lineage	in	the	tree
Protists
CosmosID Use Cases
Some Applications:
Microbiome Research
Clinical Metagenomics
Emerging and Re-emerging Pathogen Discovery
Polymicrobial Infection Dynamics
Hospital-associated Infections
Outbreak Investigation
Food Safety
Functional Food
Human Microbiome
Home Microbiome
Subway Microbiome
Animal Microbiome
Pharmaceuticals R&D
Oil Metagenome
Environmental Screening
Cosmetics
Clinical Trial
Analyzed >30K Biological Samples
History/Cholera
Metagenomics
Microbiomes in Health and Disease:
Microbiome Analysis of Acute Diarrheal
Patients Compared with Healthy Individuals
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
Bacteria
Vibrio cholerae
Vibrio parahaemolyticus
Vibrio fluvialis
Aeromonas spp.
Campylobacter jejuni
Campylobacter coli
Shigella
Salmonella
Escherichia coli
Viruses
Rotavirus
Adenovirus
Norovirus
Sapovirus
Astrovirus
Parasites
Giardia lamblia
Cryptosporidium parvum
Entamoeba histolytica
Blastocystis hominis
Microbiome of Acute Diarrheal Patients Compared with Healthy Individuals
In collaboration with the National Institute of Cholera and
Enteric Disease (NICED), Calcutta, India
Enteric Pathogens Monitored By NICED
DIARRHEAL	PATIENTS	HEALTHY	INDIVIDUALS
A Subpopulation is Overrepresented in Diarrheal Patients Compared to Healthy Individuals
γ- Proteobacteria – Firmicutes - Bacteroidetes
N2_GY16
N2_GY31
N2_GY26
N2_GY09
N2_GY23
N2_GY29
N2_GY30
N2_GY14
N2_GY19
N3_IDH_20
N3_IDH_33
N3_IDH_38
N2_GY22
N2_GY28
N2_GY11
N2_GY12
N3_IDH_37
HMP_SRS023583
HMP_SRS043001
HMP_SRS017433
HMP_SRS019601
HMP_SRS058770
HMP_SRS064557
HMP_SRS015854
HMP_SRS017701
HMP_SRS017307
HMP_SRS015190
HMP_SRS016335
HMP_SRS022609
HMP_SRS056259
HMP_SRS019968
HMP_SRS011586
HMP_SRS013476
HMP_SRS020233
HMP_SRS019161
N3_IDH_10A
N3_IDH_2
N3_NICED_27
N2_CSN10
N3_NICED_26
N2_GY20
N2_GY13
HMP_SRS012902
N3_NICED_24
N3_IDH_40
N3_NICED_28
N3_IDH_32
N3_IDH_17
N2_CSN1
N2_CSN6
N2_CSN8
N3_NICED_30
N3_IDH_16
N3_IDH_6A
N3_IDH_18
N3_IDH_12
N2_GY17
N3_IDH_9
N3_IDH_4
N3_NICED_22
N3_NICED_25
N2_CSN9
HMP_SRS013215
N2_GY21
N2_GY25
N2_GY18
N2_CSN5
N3_IDH_7
N3_IDH_36
N2_GY27
N2_CSN3
N2_CSN2
N2_CSN7
N2_GY15
Acinetobacter
Spirochaetaceae
Sphingomonadaceae
Shigella
Flavobacteriaceae
Neisseria
Burkholderiaceae
Lactobacillus
Synergistaceae
Salmonella
Actinomycetales
Actinomycetaceae
Lactococcus lactis
Moraxellaceae
Citrobacter
Carnobacteriaceae
Micrococcaceae
Neisseriaceae
Fusobacterium
Peptoniphilaceae
Enterobacter cloacae complex
Enterobacteriales
Klebsiella
Acidaminococcaceae
Campylobacterales
Campylobacteraceae
Aeromonadaceae
Tenericutes
Bacillales Family XI. Incertae Sedis
Vibrio
Coriobacteriales
Oxalobacteraceae
Methanobacteriaceae
Peptostreptococcaceae
Burkholderiales
Erysipelotrichales
Verrucomicrobiaceae
Helicobacteraceae
Mycoplasmataceae
Campylobacter jejuni
Actinobacteria
Bacteria
Brachyspiraceae
Selenomonadales
Enterococcaceae
Bifidobacteriales
Bifidobacterium
Streptococcus
Lactobacillaceae
Leuconostocaceae
Enterobacteriaceae
Escherichia coli
Coriobacterineae
Desulfovibrionales
Fusobacteriaceae
Desulfovibrionaceae
Coriobacteriaceae
Clostridiaceae
Rikenellaceae
Clostridia
Erysipelotrichaceae
Eubacteriaceae
unclassified Clostridiales
Clostridiales
Sutterellaceae
Bacteroidales
Porphyromonadaceae
Bifidobacteriaceae
Pasteurellaceae
Streptococcaceae
Prevotellaceae
Veillonellaceae
Ruminococcaceae
Lachnospiraceae
Bacteroidaceae
Group
HC
HMP
KE
UE
FamilyLevel
Many pathogens can readily be identified from disease patients
: Known Etiology
: Unknown Etiology
UE_N2_GY31
KE_N3_IDH_5
UE_N3_IDH_40
UE_N2_GY09
UE_N3_IDH_36
UE_N2_GY22
UE_N2_GY12
KE_N3_IDH_19
UE_N2_GY23
UE_N2_GY28
UE_N2_GY26
UE_N2_GY19
UE_N3_IDH_35
UE_N2_GY17
UE_N2_GY14
KE_N3_IDH_20
UE_N3_IDH_34
UE_N3_IDH_33
UE_N2_GY20
UE_N2_GY29
UE_N3_IDH_39
UE_N2_GY11
KE_N3_IDH_3
HC_N3_NICED_23
UE_N2_GY18
UE_N2_GY13
UE_N3_IDH_31
KE_N3_IDH_7
KE_N3_IDH_9
HC_N3_NICED_26
KE_N3_IDH_17
KE_N3_IDH_16
UE_N2_GY21
UE_N2_GY30
UE_N3_IDH_37
HC_N2_CSN10
HC_N2_CSN3
UE_N2_GY15
HC_N2_CSN2
HC_N2_CSN9
KE_N3_IDH_12
HC_N3_NICED_22
KE_N3_IDH_10A
KE_N3_IDH_2
HC_N2_CSN5
UE_N2_GY25
KE_N3_IDH_18
HC_N3_NICED_25
HC_N2_CSN7
KE_N3_IDH_6A
KE_N3_IDH_4
HC_N3_NICED_27
UE_N2_GY27
UE_N3_IDH_32
UE_N3_IDH_38
UE_N2_GY24
UE_N2_GY16
KE_N3_IDH_8
KE_N3_IDH_14
KE_N3_IDH_11
HC_N3_NICED_30
HC_N3_NICED_28
HC_N3_NICED_24
HC_N2_CSN8
HC_N2_CSN1
HC_N2_CSN6
Escherichia_coli_TW11681
Escherichia_coli_str_K−12_substr_DH10B
Escherichia_coli_TW10598
Escherichia_coli_E482/B41
Escherichia_coli_MS_145−7
Escherichia_coli_NA114
Escherichia_coli_2_3916
Escherichia_coli_MS_21−1
Escherichia_coli_SMS−3−5
Escherichia_coli_XH140A
Escherichia_coli_MS_116−1
Escherichia_coli_ETEC_H10407
Escherichia_coli_MS_69−1
Escherichia_coli_MS175/116
Escherichia_coli_H252
Escherichia_coli_STEC_B2F1
Shigella_sp_D9
Escherichia_coli_SE15
Escherichia_coli_B
Escherichia_coli_MS_196−1
Escherichia_coli_3_3884/96_154/O113_H21
Escherichia_coli_55989
Escherichia_coli_O104:H4_main
Escherichia_coli_O157:H7_str_FRIK2000
Escherichia_coli_MS_115_1/2_4168/TW11681
Escherichia_coli_H736
Escherichia_coli_H494
Escherichia_coli_E22/12009/3_2608_split
Escherichia_coli_O104:H4_01/04/09−8351
Node_6642
Escherichia_coli_1827−70
Escherichia_coli_TW10722/MS145
Escherichia_coli_E22
Escherichia_coli_ATCC_8739
Escherichia_coli_TW14425
Escherichia_coli_UMN026/FVEC/042
cvmar_0012_at_1199_Escherichia_coli_GENE_yjeH
cvmar_0016_at_805_Escherichia_coli_GENE_yjeJ
cvmar_0017_at_963_Escherichia_coli_GENE_yjeK
cvmar_0019_x_at_93_Escherichia_coli_GENE_sugE
cvmar_0020_at_394_Escherichia_coli_GENE_blc
cvmar_0021_at_1117_Escherichia_coli_GENE_ampC
cvmar_0022_at_341_Escherichia_coli_GENE_frdD
cvmar_0023_at_338_Escherichia_coli_GENE_frdC
cvmar_0024_at_610_Escherichia_coli_GENE_frdB
cvmar_0025_at_1625_Escherichia_coli_GENE_frdA
cvmar_0144_at_241_Escherichia_coli_GI_21637409
cvmar_0170_at_501_Escherichia_coli_GENE_cat
cvmar_0374_s_at_486_Escherichia_coli_GENE_mrx
cvmar_0377_s_at_94_Escherichia_coli_GI_5103685
cvmar_0378_s_at_85_Escherichia_coli_GI_5103686
cvmar_0446_s_at_249_Escherichia_coli_GI_152580
cvmar_0448_s_at_403_Escherichia_coli_GI_152582
cvmar_0449_s_at_879_Escherichia_coli_GI_152583
cvmar_0450_s_at_198_Escherichia_coli_GI_152584
cvmar_0451_s_at_172_Escherichia_coli_GI_152585
cvmar_0453_s_at_740_Escherichia_coli_GI_152587
cvmar_0666_s_at_280_Escherichia_coli_GI_1648866
cvmar_0714_s_at_194_Escherichia_coli_GENE_orfF
mvir_24283_s_at_1882_Escherichia_coli_GeneID_ECC2359
mvir_24287_s_at_1457_Escherichia_coli_GeneID_ECC2363
mvir_24289_s_at_1551_Escherichia_coli_GeneID_ECC2364
mvir_24564_at_457_Escherichia_coli_GENE_cfa−I
mvir_24567_at_474_Escherichia_coli_GENE_afaE−1
mvir_24576_at_277_Escherichia_coli_GENE_draA
mvir_24614_x_at_705_Escherichia_coli_GENE_ompA
mvir_24697_at_116_Escherichia_coli_GENE_lta
mvir_24701_at_216_Escherichia_coli_GENE_sta
mvir_24711_at_1391_Escherichia_coli_GENE_pet
mvir_24721_s_at_82_Escherichia_coli_GENE_set1A
mvir_24752_at_939_Escherichia_coli_GENE_espG
mvir_43038_at_335_Escherichia_coli_GENE_agg3B
mvir_43041_at_1527_Escherichia_coli_GENE_agg3C
mvir_43044_at_495_Escherichia_coli_GENE_agg3D
mvir_43059_at_266_Escherichia_coli_GENE_aggR
mvir_43068_at_386_Escherichia_coli_GENE_cs3
mvir_43077_at_362_Escherichia_coli_GENE_cseA
mvir_43092_s_at_405_Escherichia_coli_GENE_afaE−3
mvir_43101_at_472_Escherichia_coli_GENE_draE2
mvir_43143_at_494_Escherichia_coli_GENE_aatB
mvir_43149_at_1071_Escherichia_coli_GENE_aatD
mvir_43155_at_525_Escherichia_coli_GENE_draB
mvir_43158_at_1738_Escherichia_coli_GENE_draC
mvir_43161_at_440_Escherichia_coli_GENE_draD
mvir_43164_at_168_Escherichia_coli_GENE_draP
mvir_43188_s_at_1851_Escherichia_coli_GENE_papC
mvir_43287_s_at_1880_Escherichia_coli_GENE_iutA
mvir_43338_at_202_Escherichia_coli_GENE_ltb
mvir_43350_s_at_160_Escherichia_coli_GENE_set1B
mvirdb_0213_s_at_116_Escherichia_coli_GENE_tnpR
mvirdb_0228_at_2660_Escherichia_coli_GENE_tnpA
mvirdb_0243_at_285_Escherichia_coli_GENE_tnpA
mvirdb_0247_at_93_Escherichia_coli_GENE_ycdA
mvirdb_0249_at_296_Escherichia_coli_GENE_stbB
mvirdb_0250_at_550_Escherichia_coli_GENE_stbA
mvirdb_0261_s_at_58_Escherichia_coli_GENE_yddA
mvirdb_0261_x_at_305_Escherichia_coli_GENE_yddA
mvirdb_0273_at_79_Escherichia_coli_GENE_yehA
mvirdb_0276_at_442_Escherichia_coli_GI_38606113
mvirdb_0520_s_at_258_Escherichia_coli_GENE_sugE
mvirdb_0521_at_527_Escherichia_coli_GENE_blc
mvirdb_0580_x_at_99_Escherichia_coli_GI_3334641
mvirdb_0606_s_at_103_Escherichia_coli_GENE_qacEdelta1
mvirdb_0644_at_2842_Escherichia_coli_GI_14326200
mvirdb_0835_at_2775_Escherichia_coli_GI_37983283
mvirdb_0849_at_317_Escherichia_coli_GENE_lacY
mvirdb_0856_x_at_228_Escherichia_coli_GENE_traA
org
Sample
Escherichia coli
Identify Organism Characterize for Accessory Genes
Unknown
EtiologyUnknown Etiology samples predominantly contain members of E. coli super family
Known
Etiology
Healthy
Controls
NICED PCA Bray-Curtis distance
HMP
HC
UE
KE
Treatment Group
-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 -1
-0.75
-0.5
-0.25
0
0.25
0.5
0.75
-1
-0.75
-0.5
-0.25
0
0.25
0.5
0.75
1
Microbiome of Healthy People in India Different From That of Western Europeans
Heatlhy Control
Unknown Etiology
Known Etiology
HMP
Number of Individuals with AMR genes present in 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% coverage
HMP samples had no genes present which matched at this level of coverage
Predominance of genes related to carbohydrate metabolism
Amino Acids and Derivatives
Carbohydrates
Cell Wall and Capsule
Cofactors, Vitamins,
Prosthetic Groups, Pigments
DNA Metabolism
Membrane Transport
Protein Metabolism
unclassified
Alanine, serine, and glycine
Arginine; urea cycle, polyamines
Aromatic amino acids and derivatives
Branchedunclassifiedchain amino acids
Glutamine, glutamate, aspartate, asparagine; ammonia assimilation
Histidine Metabolism
Lysine, threonine, methionine, and cysteine
Proline and 4unclassifiedhydroxyprolineunclassified_1
Aminosugars
Central carbohydrate metabolism
CO2 fixation
Diunclassified and oligosaccharides
Fermentation
Monosaccharides
Oneunclassifiedcarbon Metabolism
Organic acids
Polysaccharides
Sugar alcohols
unclassified_2
Capsular and extracellular polysacchrides
GramunclassifiedNegative cell wall components
GramunclassifiedPositive cell wall components
unclassified_3
CRISPsDNA recombination
DNA repair DNA replicationDNA uptake, competence
unclassified_4
ABC transporters
Protein and nucleoprotein secretion system, Type IV
Protein secretion system, ChaperoneunclassifiedUsher pathway (CU)
Protein secretion system, Type II
Protein secretion system, Type III
Protein secretion system, Type VI
Protein secretion system, Type VII
Protein secretion system, Type VIII (Extracellular nucleation/precipitation pathway, ENP)
Protein translocation across cytoplasmic membrane
Sugar Phosphotransferase Systems, PTS
TRAP transporters
Uniunclassified Symunclassified and Antiporters
Protein biosynthesis
Protein degradation
Protein folding
Protein processing and modification
Secretion
Selenoproteins
Arabinose Sensor and
transport moduleCell Division and Cell Cycle
Central metabolism
Clusteringunclassified
based subsystemsDormancy and Sporulation
Fatty Acids, Lipids, and Isoprenoids
Iron acquisition and metabolism
Metabolism of Aromatic Compounds
Miscellaneous
Motility and Chemotaxis
Nitrogen Metabolism
Nucleosides and Nucleotides
Phages, Prophages,
Transposable elements
Phages, Prophages, Transposable
elements, Plasmids
Phosphorus Metabolism
PhotosynthesisPotassium metabolism
Predictions based on plantunclassified
prokaryote comparative analysis
Regulation and Cell signaling
Respiration
RNA Metabolism
Secondary Metabolism
Stress Response
Sulfur Metabolism
Transcriptional regulation
Virulence
Virulence, Disease and Defense
unclassified
Alanine, serine, and glycine
Arginine; urea cycle, polyamines
Aromatic amino acids and derivatives
Branchedunclassifiedchain amino acids
Glutamine, glutamate, aspartate, asparagine; ammonia assimilation
Histidine Metabolism
Lysine, threonine, methionine, and cysteine
Proline and 4unclassifiedhydroxyprolineunclassified_1
Aminosugars
Central carbohydrate metabolism
CO2 fixation
Diunclassified and oligosaccharides
Fermentation
Monosaccharides
Oneunclassifiedcarbon Metabolism
Organic acids
Polysaccharides
Sugar alcohols
unclassified_2
Capsular and extracellular polysacchrides
GramunclassifiedNegative cell wall components
GramunclassifiedPositive cell wall components
unclassified_3
CRISPsDNA recombination
DNA repair DNA replicationDNA uptake, competence
unclassified_4
ABC transporters
Protein and nucleoprotein secretion system, Type IV
Protein secretion system, ChaperoneunclassifiedUsher pathway (CU)
Protein secretion system, Type II
Protein secretion system, Type III
Protein secretion system, Type VI
Protein secretion system, Type VII
Protein secretion system, Type VIII (Extracellular nucleation/precipitation pathway, ENP)
Protein translocation across cytoplasmic membrane
Sugar Phosphotransferase Systems, PTS
TRAP transporters
Uniunclassified Symunclassified and Antiporters
Protein biosynthesis
Protein degradation
Protein folding
Protein processing and modification
Secretion
Selenoproteins
5
10
15
Average Abundance (%)
Functional Groups
Level 1 Abundance < 5%
Functional Groups
Level 1 Abundance > 5%
Functional analysis
Qiagen Functional analysis – Reinforces the Community Composition
Beta-diversity
analysis
Permutation analysis
(significance of
clustering)
Differential
abundance analysis
Evaluation of
differentially
abundant function
HMP
Indian
healthy
HMP
Indian
healthy
Ontology (GO) Clustering based on Pfam Clustering based on Gene
Summary
• Microbial communities found in the 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
• 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.
• Multiple pathogens can readily be identified from disease patients
• Microbial community of Indian population encodes alarming rate of
antibiotic resistance genes
• Functional analysis of the Indian microbiome indicates predominance of
carbohydrate metabolism genes
• Over abundance of cyto-/hemolysis genes observed in unknown etiology
help explain diseased state
Pilot Studies Underway: NGS based (culture free) direct detection
Study Area Sample Type
Wound and surgical
Infections
Tissues, aspirates,
swabs
Infective Endocarditis cardiac valves
Broad range pathogen
detection
CSF and Biopsies
HCAP BAL specimens;
Necrotizing Fasciitis
Tissues: Muscle,
Lung, Liver
Neonatal Sepsis blood, CSF, urine
Orthopedic Infection Pure isolates
Cystic Fibrosis and UTI Stool and Urine
Study Area Sample Type
Healthcare Associated
Infections: Strain
subtyping and molecular
epidemiology
Hospital Isolates
HAI: infection control and
source tracking
Isolates and biofilms
Broad Range Pathogen
detection
Blood; Ulcer, isolates
Empyema Plural effusion
Neutropenic Infection &
Aseptic Meningitis
Blood, CSF, Throat
swab etc
Strain ID and sub-typing Clinical Isolates
Prosthetic Joint Infection Tissue, swab
Lyme Disease Blood, CSF
CosmosID is working with the top research hospitals in the United
States and Europe
Enabling End to End Microbiome Research with Great Partners
Sample Collection & Biobanking
DNA Isolation
Sequencing
High Resolution Microbial Characterization
and Identification
Functional Analysis
Sequencing Partners
Sample
Action
History/Cholera
Metagenomics
Microbiomes in Health and Disease
Demo
How CosmosID Works
Reference database
Metagenomic SampleUnique and Shared Regions Identified
Sample Matched with Database
Identification
Staphylococcus aureus subsp aureus USA300 TCH959
Propionibacterium acnes KPA171202
Enterococcus faecalis OG1RF
Thank you!
support@cosmosid.com

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