Through this proposal, we will develop new computational tools for reconstructing nearly- complete microbial genomes from complex mixtures, as well as their strain structure. We will build upon our initial successes in developing metagenomic assembly algorithms capable of characterizing strain variants (7, 8), as well as upon our experience in using co-abundance across samples to link/bin together genes originating from the same organism (9). In addition, we will develop algorithms able to use information generated by emerging technologies, such as chromosome conformation information generated by Hi-C (10-12), or information about DNA modifications as generated by new nanopore sequencing devices(13, 14).

Public Health Relevance

Metagenomics studies are starting to elucidate the roles microbes play in human health and disease. This proposal will enhance future metagenomic studies by providing full featured, efficient, and robust algorithms and tools for reconstructing the genomes and metagenomes from high-throughput sequencing data.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
2R01AI100947-05A1
Application #
9842071
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Brown, Liliana L
Project Start
2013-03-21
Project End
2023-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
5
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Maryland College Park
Department
Biostatistics & Other Math Sci
Type
Earth Sciences/Resources
DUNS #
790934285
City
College Park
State
MD
Country
United States
Zip Code
20742
Ghurye, Jay; Pop, Mihai; Koren, Sergey et al. (2017) Scaffolding of long read assemblies using long range contact information. BMC Genomics 18:527
Olson, Nathan D; Treangen, Todd J; Hill, Christopher M et al. (2017) Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes. Brief Bioinform :
Sczyrba, Alexander; Hofmann, Peter; Belmann, Peter et al. (2017) Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software. Nat Methods 14:1063-1071
Pop, Mihai; Paulson, Joseph N; Chakraborty, Subhra et al. (2016) Individual-specific changes in the human gut microbiota after challenge with enterotoxigenic Escherichia coli and subsequent ciprofloxacin treatment. BMC Genomics 17:440
Rashid, Mahamud-Ur; Almeida, Mathieu; Azman, Andrew S et al. (2016) Comparison of inferred relatedness based on multilocus variable-number tandem-repeat analysis and whole genome sequencing of Vibrio cholerae O1. FEMS Microbiol Lett 363:
Morris, Alison; Paulson, Joseph N; Talukder, Hisham et al. (2016) Longitudinal analysis of the lung microbiota of cynomolgous macaques during long-term SHIV infection. Microbiome 4:38
Mendelowitz, Lee M; Schwartz, David C; Pop, Mihai (2016) Maligner: a fast ordered restriction map aligner. Bioinformatics 32:1016-22
Almeida, Mathieu; Pop, Mihai; Le Chatelier, Emmanuelle et al. (2016) Capturing the most wanted taxa through cross-sample correlations. ISME J 10:2459-67
Simpson, Jared T; Pop, Mihai (2015) The Theory and Practice of Genome Sequence Assembly. Annu Rev Genomics Hum Genet 16:153-72
Pop, Mihai; Salzberg, Steven L (2015) Use and mis-use of supplementary material in science publications. BMC Bioinformatics 16:237

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