Using 16S rRNA gene as marker to detect unknown bacteria in microbial communities

BMC Bioinformatics

Volumn 18, Issue , 2017, Pages

  Tran, Quang ^a   Pham, Diem Trang ^a   Phan, Vinhthuy ^a  

^a University of Memphis   (United States)

Author keywords

Bacteria detection; Metagenomics; NGS analysis

Indexed keywords

BACTERIA; MICROORGANISMS; RNA;

BACTERIA DETECTION; COMPUTATIONAL COSTS; ENVIRONMENTAL SAMPLE; METAGENOMICS; MICROBIAL COMMUNITIES; NEXT-GENERATION SEQUENCING; NGS ANALYSIS; ROBUST PREDICTIONS;

GENES;

RNA 16S;

ALGORITHM; BACTERIAL GENOME; BACTERIUM; DNA SEQUENCE; GENETIC MARKER; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; ISOLATION AND PURIFICATION; METAGENOME; MICROFLORA; PROCEDURES;

ALGORITHMS; BACTERIA; GENETIC MARKERS; GENOME, BACTERIAL; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; METAGENOME; MICROBIOTA; RNA, RIBOSOMAL, 16S; SEQUENCE ANALYSIS, DNA;

EID: 85039708495     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-017-1901-8     Document Type: Article

References (22)

1. Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, Paczian T, Rodriguez A, Stevens R, Wilke A, et al.The metagenomics rast server-a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics. 2008; 9(1):386.
2. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nature methods. 2012; 9(8):811-4.
3. Brady A, Salzberg SL. Phymm and phymmbl: metagenomic phylogenetic classification with interpolated markov models. Nature Methods. 2009; 6(9):673-6.
4. Lindner MS, Renard BY. Metagenomic abundance estimation and diagnostic testing on species level. Nucleic Acids Res. 2013; 41(1):10-10.
5. Meinicke P, Aßhauer KP, Lingner T. Mixture models for analysis of the taxonomic composition of metagenomes. Bioinformatics. 2011; 27(12):1618-24.
6. Nalbantoglu OU, Way SF, Hinrichs SH, Sayood K. Raiphy: phylogenetic classification of metagenomics samples using iterative refinement of relative abundance index profiles. BMC Bioinformatics. 2011; 12(1):41.
7. Ounit R, Wanamaker S, Close TJ, Lonardi S. Clark: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers. BMC Genomics. 2015; 16(1):236.
8. Lindner MS, Renard BY. Metagenomic profiling of known and unknown microbes with microbegps. PloS ONE. 2015; 10(2):0117711.
9. Muyzer G, De Waal EC, Uitterlinden AG. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16s rrna. Appl Environ Microbiol. 1993; 59(3):695-700.
10. Stackebrandt E, Goebel B. Taxonomic note: a place for dna-dna reassociation and 16s rrna sequence analysis in the present species definition in bacteriology. Int J Syst Evol Microbiol. 1994; 44(4):846-9.
11. Langille MG, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Thurber RL, Knight R, Beiko RG. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnol. 2013; 31(9):814-21.
12. Langmead B, Salzberg SL. Fast gapped-read alignment with bowtie 2. Nat Methods. 2012; 9(4):357-9.
13. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010; 26(5):589-95.
14. Liu CM, Wong T, Wu E, Luo R, Yiu SM, Li Y, Wang B, Yu C, Chu X, Zhao K, et al.Soap3: ultra-fast gpu-based parallel alignment tool for short reads. Bioinformatics. 2012; 28(6):878-9.
15. Vo NS, Tran Q, Niraula N, Phan V. Randal: a randomized approach to aligning dna sequences to reference genomes. BMC Genomics. 2014; 15(5):2.
16. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, et al.The sequence alignment/map format and samtools. Bioinformatics. 2009; 25(16):2078-9.
17. Galler BA, Fisher MJ. An improved equivalence algorithm. Commun ACM. 1964; 7(5):301-3.
18. Lee VE, Ruan N, Jin R, Aggarwal C In: Aggarwal CC, Wang H, editors. A Survey of Algorithms for Dense Subgraph Discovery. Boston: Springer: 2010. p. 303-36.
19. Vinh NX, Epps J, Bailey J. Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance. J Mach Learn Res. 2010; 11(Oct):2837-54.
20. Hubert L, Arabie P. Comparing partitions. J Classif. 1985; 2(1):193-218.
21. Rosenberg A, Hirschberg J. V-measure: A conditional entropy-based external cluster evaluation measure. In: EMNLP-CoNLL: 2007. p. 410-20.
22. Angly FE, Willner D, Rohwer F, Hugenholtz P, Tyson GW. Grinder: a versatile amplicon and shotgun sequence simulator. Nucleic Acids Res. 2012; 40(12):e94. doi: 10.1093/nar/gks251.