INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

Álam, Intikhab; Antunes, André; Kamau, Allan; Ba-Alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B.

doi:10.1371/journal.pone.0082210

Cited by 73 publications

(79 citation statements)

References 62 publications

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“…Of these 125 genome sequences collected, 76 are complete genomes and 49 are draft genomes [78] (Additional file 1: Table S4). To standardize the annotation of the 125 cyanobacterial genomes, all genome sequences were re-annotated using the INDIGO pipeline [79] to obtain consistent annotation. Based on that annotation, we derived proteomes of the considered species.…”

Section: Methodsmentioning

confidence: 99%

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

et al. 2017

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BackgroundFinding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated.ResultsHere we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis.ConclusionTo our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3389-4) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

et al. 2017

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“…To annotate the four metagenomes, we used the Automatic Annotation of Microbial Genomes (AAMG) module in DMAP (Alam et al, 2013). The AAMG includes annotation from various databases such as InterProScan (Quevillon et al, 2005), Gene…”

Section: Feature Prediction Annotation Of Function and Taxonomic Assmentioning

confidence: 99%

“…We took a different approach by aligning the predicted ORFs and rRNA from each of the replicates against the Best Global Taxonomies (Alam et al, 2013). We opted to predict the abundance by aligning the predicted ORFs and rRNA against GBT because of it"s ability to obtain insights into complex gene structure, which would not be possible to obtain from short read data.…”

Section: Feature Prediction Annotation Of Function and Taxonomic Assmentioning

confidence: 99%

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Al-Amoudi

Razali

Essack

et al. 2016

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Since the composition of soil directs the diversity of the contained microbiome and its potential to produce bioactive compounds, many studies has been focused on sediment types with unique features characteristic of extreme environments. However, not much is known about the potential of microbiomes that inhabit the highly saline and hot Red Sea lagoons. This case study explores mangrove mud and the microbial mat of sediments collected from the Rabigh harbor lagoon and Al Kharrar lagoon for antimicrobial bioprospecting. Rabigh harbor lagoon appears the better location, and the best sediment type for this purpose is mangrove mud. On the other hand, Al Kharrar lagoon displayed increased anaerobic hydrocarbon degradation and an abundance of bacterial DNA associated with antibiotic resistance. Moreover, our findings show an identical shift in phyla associated with historic hydrocarbon contamination exposure reported in previous studies (that is, enrichment of Gamma- and Delta-proteobacteria), but we also report that bacterial DNA sequences associated with antibiotic synthesis enzymes are derived from Gamma-, Delta- and Alpha-proteobacteria. This suggests that selection pressure associated with hydrocarbon contamination tend to enrich the bacterial classes DNA associated with antibiotic synthesis enzymes. Although Actinobacteria tends to be the common target for research when it comes to antimicrobial bioprospecting, our study suggests that Firmicutes (Bacilli and Clostridia), Bacteroidetes, Cyanobacteria, and Proteobacteria should be antimicrobial bioprospecting targets as well. To the best of our knowledge, this is the first metagenomic study that analyzed the microbiomes in Red Sea lagoons for antimicrobial bioprospecting.

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“…Genome annotation was carried out with the Indigo pipeline (12) with the exception of open reading frame (ORF) prediction by FragGeneScan (13). The annotation of H. elongata strain K4 resulted in 2,354 ORFs, 5 rRNAs, 59 tRNAs, and 39 ncRNAs.…”

Section: Genome Announcementmentioning

confidence: 99%

Draft Genome Sequence of Halomonas elongata Strain K4, an Endophytic Growth-Promoting Bacterium Enhancing Salinity Tolerance In Planta

et al. 2016

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INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

Cited by 73 publications

References 62 publications

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Draft Genome Sequence of Halomonas elongata Strain K4, an Endophytic Growth-Promoting Bacterium Enhancing Salinity Tolerance In Planta

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