TY - JOUR

T1 - Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient

AU - Нурк, Сергей Юрьевич

AU - Fang, Xin

AU - Monk, Jonathan M

AU - Akseshina, Margarita

AU - Zhu, Qiyun

AU - Gemmell, Christopher

AU - Gianetto-Hill, Connor

AU - Leung, Nelly

AU - Szubin, Richard

AU - Sanders, Jon

AU - Beck, Paul L

AU - Li, Weizhong

AU - Sandborn, William J

AU - Gray-Owen, Scott D

AU - Knight, Rob

AU - Allen-Vercoe, Emma

AU - Palsson, Bernhard O

AU - Smarr, Larry

PY - 2018/10/30

Y1 - 2018/10/30

N2 - Dysbiosis of the gut microbiome, including elevated abundance of putative leading bacterial triggers such as E. coli in inflammatory bowel disease (IBD) patients, is of great interest. To date, most E. coli studies in IBD patients are focused on clinical isolates, overlooking their relative abundances and turnover over time. Metagenomics-based studies, on the other hand, are less focused on strain-level investigations. Here, using recently developed bioinformatic tools, we analyzed the abundance and properties of specific E. coli strains in a Crohns disease (CD) patient longitudinally, while also considering the composition of the entire community over time. In this report, we conducted a pilot study on metagenomic-based, strain-level analysis of a time-series of E. coli strains in a left-sided CD patient, who exhibited sustained levels of E. coli greater than 100X healthy controls. We: (1) mapped out the composition of the gut microbiome over time, particularly the presence of E. coli strains, and found that the abundance and dominance of specific E. coli strains in the community varied over time; (2) performed strain-level de novo assemblies of seven dominant E. coli strains, and illustrated disparity between these strains in both phylogenetic origin and genomic content; (3) observed that strain ST1 (recovered during peak inflammation) is highly similar to known pathogenic AIEC strains NC101 and LF82 in both virulence factors and metabolic functions, while other strains (ST2-ST7) that were collected during more stable states displayed diverse characteristics; (4) isolated, sequenced, experimentally characterized ST1, and confirmed the accuracy of the de novo assembly; and (5) assessed growth capability of ST1 with a newly reconstructed genome-scale metabolic model of the strain, and showed its potential to use substrates found abundantly in the human gut to outcompete other microbes. In conclusion, inflammation status (assessed by the blood C-reactive protein and stool calprotectin) is likely correlated with the abundance of a subgroup of E. coli strains with specific traits. Therefore, strain-level time-series analysis of dominant E. coli strains in a CD patient is highly informative, and motivates a study of a larger cohort of IBD patients.

AB - Dysbiosis of the gut microbiome, including elevated abundance of putative leading bacterial triggers such as E. coli in inflammatory bowel disease (IBD) patients, is of great interest. To date, most E. coli studies in IBD patients are focused on clinical isolates, overlooking their relative abundances and turnover over time. Metagenomics-based studies, on the other hand, are less focused on strain-level investigations. Here, using recently developed bioinformatic tools, we analyzed the abundance and properties of specific E. coli strains in a Crohns disease (CD) patient longitudinally, while also considering the composition of the entire community over time. In this report, we conducted a pilot study on metagenomic-based, strain-level analysis of a time-series of E. coli strains in a left-sided CD patient, who exhibited sustained levels of E. coli greater than 100X healthy controls. We: (1) mapped out the composition of the gut microbiome over time, particularly the presence of E. coli strains, and found that the abundance and dominance of specific E. coli strains in the community varied over time; (2) performed strain-level de novo assemblies of seven dominant E. coli strains, and illustrated disparity between these strains in both phylogenetic origin and genomic content; (3) observed that strain ST1 (recovered during peak inflammation) is highly similar to known pathogenic AIEC strains NC101 and LF82 in both virulence factors and metabolic functions, while other strains (ST2-ST7) that were collected during more stable states displayed diverse characteristics; (4) isolated, sequenced, experimentally characterized ST1, and confirmed the accuracy of the de novo assembly; and (5) assessed growth capability of ST1 with a newly reconstructed genome-scale metabolic model of the strain, and showed its potential to use substrates found abundantly in the human gut to outcompete other microbes. In conclusion, inflammation status (assessed by the blood C-reactive protein and stool calprotectin) is likely correlated with the abundance of a subgroup of E. coli strains with specific traits. Therefore, strain-level time-series analysis of dominant E. coli strains in a CD patient is highly informative, and motivates a study of a larger cohort of IBD patients.

KW - CELLULOSE

KW - COLONIZATION

KW - DEOXYRIBOSE

KW - Escherichia coli

KW - GENETIC DIVERSITY

KW - GENOMES

KW - GUT MICROBIOTA

KW - INFLAMMATORY-BOWEL-DISEASE

KW - KNOWLEDGEBASE

KW - PROTEIN

KW - RECONSTRUCTIONS

KW - de novo assembly

KW - gut microbiome

KW - inflammatory bowel disease

KW - metagenomics

UR - https://www.frontiersin.org/article/10.3389/fmicb.2018.02559/full

UR - http://www.mendeley.com/research/metagenomicsbased-strainlevel-analysis-escherichia-coli-timeseries-microbiome-samples-crohns-disease

U2 - 10.3389/fmicb.2018.02559

DO - 10.3389/fmicb.2018.02559

M3 - Article

C2 - 30425690

VL - 9

SP - 2559

JO - Frontiers in Microbiology

JF - Frontiers in Microbiology

SN - 1664-302X

M1 - 2559

ER -