A. Resistance, “Tackling a Crisis for the Health and Wealth of Nations,” Rev. Antimicrob. Resist., 2014.
Toner E, Adalja A, Gronvall GK, Cicero A, Inglesby TV. Antimicrobial resistance is a global health emergency. Heal Secur. 2015;13(3):153–5.
Article
Google Scholar
Genilloud O. The re-emerging role of microbial natural products in antibiotic discovery. Antonie Van Leeuwenhoek. 2014;106(1):173–88.
Article
CAS
Google Scholar
Hutchings MI, Truman AW, Wilkinson B. Antibiotics: past, present and future. Curr Opin Microbiol. 2019;51:72–80.
Article
CAS
Google Scholar
Katz L, Baltz RH. Natural product discovery: past, present, and future. J Ind Microbiol Biotechnol. 2016;43(2–3):155–76.
Article
CAS
Google Scholar
R. D. Firn and C. G. Jones, “An explanation of secondary product ‘redundancy,’” in Phytochemical diversity and redundancy in ecological interactions, Springer, 1996, pp. 295–312.
Galanie S, Entwistle D, Lalonde J. Engineering biosynthetic enzymes for industrial natural product synthesis. Nat Prod Rep. 2020;37(8):1122–43.
Article
CAS
Google Scholar
K. Alam, J. Hao, Y. Zhang, and A. Li, “Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways,” Biotechnol. Adv., p. 107759, 2021.
C. L. Schoch et al., “NCBI Taxonomy: a comprehensive update on curation, resources and tools,” Database, vol. 2020, 2020.
Depoorter E, Bull MJ, Peeters C, Coenye T, Vandamme P, Mahenthiralingam E. Burkholderia: an update on taxonomy and biotechnological potential as antibiotic producers. Appl Microbiol Biotechnol. 2016;100(12):5215–29.
Article
CAS
Google Scholar
Kunakom S, Eustáquio AS. Burkholderia as a source of natural products. J Nat Prod. 2019;82(7):2018–37.
Article
CAS
Google Scholar
Alam K, et al. In silico genome mining of potential novel biosynthetic gene clusters for drug discovery from Burkholderia bacteria. Comput Biol Med. 2022;140: 105046.
Article
CAS
Google Scholar
Liu X, Cheng Y-Q. Genome-guided discovery of diverse natural products from Burkholderia sp. J Ind Microbiol Biotechnol. 2014;41(2):275–84.
Article
CAS
Google Scholar
Hwang S, et al. Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome. Nucleic Acids Res. 2019;47(12):6114–29.
Article
CAS
Google Scholar
Li Y, Zhang C, Liu C, Ju J, Ma J. Genome sequencing of Streptomyces atratus SCSIOZH16 and activation production of nocardamine via metabolic engineering. Front Microbiol. 2018;9:1269.
Article
Google Scholar
E. W. Myers et al., “A whole-genome assembly of Drosophila,” Science (80-. )., vol. 287, no. 5461, pp. 2196–2204, 2000.
J. C. Venter et al., “The sequence of the human genome,” Science (80-. )., vol. 291, no. 5507, pp. 1304–1351, 2001.
Istrail S, et al. Whole-genome shotgun assembly and comparison of human genome assemblies. Proc Natl Acad Sci. 2004;101(7):1916–21.
Article
CAS
Google Scholar
Levy S, et al. The diploid genome sequence of an individual human. PLoS Biol. 2007;5(10): e254.
Article
Google Scholar
Goldberg SMD, et al. A Sanger/pyrosequencing hybrid approach for the generation of high-quality draft assemblies of marine microbial genomes. Proc Natl Acad Sci. 2006;103(30):11240–5.
Article
CAS
Google Scholar
Berlin K, Koren S, Chin C-S, Drake JP, Landolin JM, Phillippy AM. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat Biotechnol. 2015;33(6):623–30.
Article
CAS
Google Scholar
Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics. 2007;23(6):673–9.
Article
CAS
Google Scholar
Stanke M, Schöffmann O, Morgenstern B, Waack S. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics. 2006;7(1):1–11.
Article
Google Scholar
Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25(5):955–64.
Article
CAS
Google Scholar
G. O. Consortium, “The Gene Ontology (GO) database and informatics resource,” Nucleic Acids Res., vol. 32, no. suppl_1, pp. D258–D261, 2004.
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30.
Article
CAS
Google Scholar
Meier-Kolthoff JP, Göker M. TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat Commun. 2019;10(1):1–10.
Article
CAS
Google Scholar
Yoon S-H, et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol. 2017;67(5):1613.
Article
CAS
Google Scholar
Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol. 1981;17(6):368–76.
Article
CAS
Google Scholar
Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35(6):1547.
Article
CAS
Google Scholar
Ha S-M, et al. Application of the whole genome-based bacterial identification system, TrueBac ID, using clinical isolates that were not identified with three matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) systems. Ann Lab Med. 2019;39(6):530–6.
Article
CAS
Google Scholar
Camacho C, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10(1):1–9.
Article
Google Scholar
Lee I, Kim YO, Park S-C, Chun J. OrthoANI: an improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol Microbiol. 2016;66(2):1100–3.
Article
CAS
Google Scholar
L. M. Rodriguez-R and K. T. Konstantinidis, “The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes,” PeerJ Preprints, 2016.
Yoon S-H, Ha S-M, Lim J, Kwon S, Chun J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek. 2017;110(10):1281–6.
Article
CAS
Google Scholar
K. Blin et al., “antiSMASH 6.0: improving cluster detection and comparison capabilities,” Nucleic Acids Res., p. 1, 2021.
Machado H, Sonnenschein EC, Melchiorsen J, Gram L. Genome mining reveals unlocked bioactive potential of marine Gram-negative bacteria. BMC Genomics. 2015;16(1):1–12.
Article
CAS
Google Scholar
Churchill GA. Stochastic models for heterogeneous DNA sequences. Bull Math Biol. 1989;51(1):79–94.
Article
CAS
Google Scholar
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.
Article
CAS
Google Scholar
Finn RD, et al. Pfam: the protein families database. Nucleic Acids Res. 2014;42(D1):D222–30.
Article
CAS
Google Scholar
D. A. Benson et al., “GenBank Nucleic Acids Res 41 (D1),” D36–D42, 2013.
U. Consortium. UniProt: a hub for protein information. Nucleic Acids Res. 2015;43(D1):D204–12.
Article
Google Scholar
R. Hammami, A. Zouhir, C. Le Lay, J. Ben Hamida, and I. Fliss, “BACTIBASE second release: a database and tool platform for bacteriocin characterization,” Bmc Microbiol., vol. 10, no. 1, pp. 1–5, 2010.
Waghu FH, Barai RS, Gurung P, Idicula-Thomas S. CAMPR3: a database on sequences, structures and signatures of antimicrobial peptides. Nucleic Acids Res. 2016;44(D1):D1094–7.
Article
CAS
Google Scholar
Medema MH, et al. Minimum information about a biosynthetic gene cluster. Nat Chem Biol. 2015;11(9):625–31.
Article
CAS
Google Scholar
Ziemert N, Podell S, Penn K, Badger JH, Allen E, Jensen PR. The natural product domain seeker NaPDoS: a phylogeny based bioinformatic tool to classify secondary metabolite gene diversity. PLoS ONE. 2012;7(3): e34064.
Article
CAS
Google Scholar
J. R. Grant and P. Stothard, “The CGView Server: a comparative genomics tool for circular genomes,” Nucleic Acids Res., vol. 36, no. suppl_2, pp. W181–W184, 2008.
van Heel AJ, de Jong A, Song C, Viel JH, Kok J, Kuipers OP. BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins. Nucleic Acids Res. 2018;46(W1):W278–81.
Article
Google Scholar
Skinnider MA, et al. Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences. Nat Commun. 2020;11(1):1–9. https://doi.org/10.1038/s41467-020-19986-1.
Article
CAS
Google Scholar
Liu J, et al. Rational construction of genome-reduced Burkholderiales chassis facilitates efficient heterologous production of natural products from proteobacteria. Nat Commun. 2021;12(1):1–16.
Google Scholar
W.-H. Liu et al., “Indole-3-acetic acid in Burkholderia pyrrocinia JK-SH007: Enzymatic identification of the indole-3-acetamide synthesis pathway,” Front. Microbiol., p. 2559, 2019.
Alisi C, et al. Metabolic profiling of Burkholderia cenocepacia, Burkholderia ambifaria, and Burkholderia pyrrocinia isolates from maize rhizosphere. Microb Ecol. 2005;50(3):385–95.
Article
CAS
Google Scholar
Sfeir MM. Burkholderia cepacia complex infections: more complex than the bacterium name suggest. J Infect. 2018;77(3):166–70.
Article
Google Scholar
Winter JM, Behnken S, Hertweck C. Genomics-inspired discovery of natural products. Curr Opin Chem Biol. 2011;15(1):22–31.
Article
CAS
Google Scholar