An image analysis-aided method for redundancy reduction in differentiation of identical Actinobacterial strains.

AIM: To simplify the recognition of Actinobacteria, at different stages of the growth phase, from a mixed culture to facilitate the isolation of novel strains of these bacteria for drug discovery purposes. MATERIALS & METHODS: A method was developed based on Gabor transform, and machine learning using k-Nearest Neighbors and Naive Bayes classifier, Logitboost, Bagging and Random Forest to automatically categorize the colonies. RESULTS: A signature pattern was inferred by the model, making the differentiation of identical strains possible. Additionally, higher performance, compared with other classification methods was achieved. CONCLUSION: This automated approach can contribute to the acceleration of the drug discovery process while it simultaneously can diminish the loss of budget due to the redundancy occurred by the inexperienced researchers.

Hydrocarbon degraders establish at the costs of microbial richness, abundance and keystone taxa after crude oil contamination in permafrost environments.

Oil spills from pipeline ruptures are a major source of terrestrial petroleum pollution in cold regions. However, our knowledge of the bacterial response to crude oil contamination in cold regions remains to be further expanded, especially in terms of community shifts and potential development of hydrocarbon degraders. In this study we investigated changes of microbial diversity, population size and keystone taxa in permafrost soils at four different sites along the China-Russia crude oil pipeline prior to and after perturbation with crude oil. We found that crude oil caused a decrease of cell numbers together with a reduction of the species richness and shifts in the dominant phylotypes, while bacterial community diversity was highly site-specific after exposure to crude oil, reflecting different environmental conditions. Keystone taxa that strongly co-occurred were found to form networks based on trophic interactions, that is co-metabolism regarding degradation of hydrocarbons (in contaminated samples) or syntrophic carbon cycling (in uncontaminated samples). With this study we demonstrate that after severe crude oil contamination a rapid establishment of endemic hydrocarbon degrading communities takes place under favorable temperature conditions. Therefore, both endemism and trophic correlations of bacterial degraders need to be considered in order to develop effective cleanup strategies.

An assessment of the diversity of culturable bacteria from main root of sugar beet.

The partial sequences of the 16S rRNA genes of 531 bacteria isolated from the main root of the sugar beet (Beta vulgaris L.) were determined and subsequently grouped into 155 operational taxonomic units by clustering analysis (≥99% identity). The most abundant phylum was Proteobacteria (72.5-77.2%), followed by Actinobacteria (9.8-16.6%) and Bacteroidetes (4.3-15.4%). Alphaproteobacteria (46.7-64.8%) was the most dominant class within Proteobacteria. Four strains belonging to Verrucomicrobia were also isolated. Phylogenetic analysis revealed that the Verrucomicrobia bacterial strains were closely related to Haloferula or Verrucomicrobium.

Land use intensity controls actinobacterial community structure.

Actinobacteria are major producers of secondary metabolites; however, it is unclear how they are distributed in the environment. DNA was extracted from forest, pasture and cultivated soils, street sediments (dust and material in place), and sediments affected by animal activity (e.g. guano, vermicompost) and characterised with two actinobacterial and a bacterial-specific 16S rDNA primer set. Amplicons (140/156) generated with the two actinobacterial-specific and amplicons (471) generated with bacterial-specific primers were analysed. Amplicons from actinobacterial-specific primer were disproportionately actinomycetal from animal-affected (soil) samples and street sediments and either verrucomicrobial (i.e. non-actinobacterial) and from a novel non-actinomycetal actinobacterial group for soils. Actinobacterial amplified ribosomal DNA restriction analysis and terminal restriction fragment length polymorphism fingerprints clustered by land use, with cultivated soils clustering apart from uncultivated soils. Actinobacterial amplicons generated with eubacterial primers were overwhelmingly from (116/126) street sediments; acidobacterial amplicons from soils (74/75). In two street samples, >90% of clones were actinomycetal. Actinomycetes are selected in terrestrial soils and sediments by cultivation, urbanisation and animal activity.

An assessment of actinobacterial diversity in the marine environment.

The 16S rRNA gene sequence diversity within the Phylum Actinobacteria was assessed from four sources: PCR-generated V6 sequence tags derived from seawater samples, metagenomic data from the Global Ocean Sampling (GOS) expedition, marine-derived sequences maintained in the Ribosomal Database Project (RDP), and select cultured strains for which sequence data is not yet available in the RDP. This meta-analysis revealed remarkable levels of phylogenetic diversity and confirms the existence of major, deeply rooted, and as of yet uncharacterized lineages within the phylum. A dramatic incongruence among cultured strains and those detected using culture-independent techniques was also revealed. Redundancy among the actinobacteria detected using culture-independent techniques suggests that greater sequence coverage or improved DNA extraction efficiencies may be required to detect the rare phylotypes that can be readily cultured from marine samples. Conversely, new strategies need to be developed for the cultivation of frequently observed but yet to be cultured marine actinobacteria.

A method for the selection of production media for actinomycete strains based on their metabolite HPLC profiles.

The manipulation of growth conditions of microorganisms is a common strategy used by pharmaceutical companies to improve the quantities and spectra of secondary metabolites with potential therapeutic interest. In this work, the effects of fermentation media on secondary metabolite production from a set of Actinomycetes was statistically compared. For this purpose, we created an automated method for comparing the ability of microorganisms to produce different secondary metabolites. HPLC analyses guided the selection of those media in which a wider chemical diversity was obtained from microorganisms inoculated in a wide spectrum of production media. Fermented media yielding a better secondary metabolite profile were included in subsequent drug discovery screening.