Biology subjects

Kleindienst, S.

Publications and source records attributed to Kleindienst, S..

3 recordsLinked to original sources

bioRxiv2020

Response and oil degradation activities of a northeast Atlantic bacterial community to biogenic and synthetic surfactants.

BackgroundAlthough synthetic dispersants are effective in dispersing crude oil, they can alter the natural microbial response to oil and potentially hinder its biodegradation. Biosurfactants, however, are naturally derived products that play a similar role to synthetic dispersants in oil spill response but are easily biodegradable and less toxic. This study investigated the microbial community dynamics, ecological drivers, functional diversity, and oil biodegradation potential of a northeast Atlantic marine microbial community to crude oil when exposed to rhamnolipid or synthetic dispersant Finasol OSR52. ResultsWe found the microbial community composition and diversity were markedly different in the rhamnolipid-amended treatment compared to that with Finasol, with key aromatic hydrocarbon-degrading bacteria like Cycloclasticus being suppressed in the Finasol treatment but not in oil-only and rhamnolipid-amended treatments. Psychrophilic Colwellia and Oleispira dominated the community in both the rhamnolipid and Finasol OSR52 treatments initially but later community structure across treatments diverged significantly: Rhodobacteraceae and Vibrio dominated the Finasol-amended treatment and Colwellia, Oleispira, and later Cycloclasticus and Alcanivorax, dominated the rhamnolipid-amended treatment. Vibrio abundance increased substantially in treatments receiving Finasol, suggesting a potentially important role for these organisms in degrading dispersant components. In fact, Finasol was linked with a negative impact on alpha diversity. Deterministic environmental filtering played a dominant role in regulating the community assembly in all treatments but was strongest in the dispersant-amended treatments. Rhamnolipid-amended and oil-only treatments had the highest functional diversity, however, the overall oil biodegradation was greater in the Finasol treatment, but aromatic biodegradation was highest in the rhamnolipid treatment. ConclusionOverall, the natural marine microbial community in the northeast Atlantic responded differently to crude oil dispersed with either synthetic or biogenic surfactants over time, but oil degradation was more enhanced by the synthetic dispersant. Collectively, our results advance the understanding of how rhamnolipid biosurfactants affect the natural marine microbial community, supporting their potential application in oil spills.

genomics↗

bioRxiv2020

Colwellia and Marinobacter metapangenomes reveal species-specific responses to oil and dispersant exposure in deepsea microbial communities

Over 7 million liters of Corexit EC9500A and EC9527A were applied to the Gulf of Mexico in response to the Deepwater Horizon oil spill. The impacts of dispersants remain under debate and negative, positive, and inconclusive impacts have been reported. Here, metatrancriptomics was applied in the context of metapangenomes to microcosms that simulated environmental conditions comparable to the hydrocarbon-rich 1,100 m deep plume. Within this microcosm study, negative effects of dispersants on microbial hydrocarbon degradation were previously reported based on activity measurements and geochemical data. Transcriptional enrichment of Colwellia, a potential dispersant degrader, followed variable time-dependent trajectories due to interactions between oil, dispersants, and nutrients. The Colwellia metapangenome captured a mixture of environmental responses linked to the Colwellia psychrerythraea 34H genome and to the genomes of other members of the Colwellia genus. The activation of genes involved in lipid degradation, nitrogen metabolism, and membrane composition under oil or nutrient availability, suggested an opportunistic growth strategy for Colwellia. In contrast, transcripts of Marinobacter, a natural hydrocarbon degrader, increased only in oil treatments. Marinobacter transcripts largely recruited to the accessory metapangenome of Marinobacter sp. C18, the closest genomic reference. A complex response involving carbon and lipid metabolism, chemotaxis and a type IV secretion system suggested active energy-dependent processes in Marinobacter. These findings highlight chemistry-dependent responses in the metabolism of key hydrocarbon-degrading bacteria and underscore that dispersant-driven selection could temper the ability of the community to respond to hydrocarbon injection.

microbiology↗

bioRxiv2019

Interpretations of microbial community studies are biased by the selected 16S rRNA gene amplicon sequencing pipeline.

One of the major methods to identify microbial community composition, to unravel microbial population dynamics, and to explore microbial diversity in environmental samples is DNA- or RNA-based 16S rRNA (gene) amplicon sequencing. Subsequent bioinformatics analyses are required to extract valuable information from the high-throughput sequencing approach. However, manifold bioinformatics tools complicate their choice and might cause differences in data interpretation, making the selection of the pipeline a crucial step. Here, we compared the performance of most widely used 16S rRNA gene amplicon sequencing analysis tools (i.e. Mothur, QIIME1, QIIME2, and MEGAN) using mock datasets and environmental samples from contrasting terrestrial and freshwater sites. Our results showed that QIIME2 outcompeted all other investigated tools in sequence recovery (>10 times less false positives), taxonomic assignments (>22% better F-score) and diversity estimates (>5% better assessment), while there was still room for improvement e.g. imperfect sequence recovery (recall up to 87%) or detection of additional false sequences (precision up to 72%). Furthermore, we found that microbial diversity estimates and highest abundant taxa varied among analysis pipelines (i.e. only one in five genera was shared among all analysis tools) when analyzing environmental samples, which might skew biological conclusions. Our findings were subsequently implemented in a high-performance computing conformant workflow following the FAIR (Findable, Accessible, Interoperable, and Re-usable) principle, allowing reproducible 16S rRNA gene amplicon sequence analysis starting from raw sequence files. Our presented workflow can be utilized for future studies, thereby facilitating the analysis of high-throughput DNA- or RNA-based 16S rRNA (gene) sequencing data substantially. ImportanceMicroorganisms play an essential role in biogeochemical cycling events across the globe. Phylogenetic marker gene analysis is a widely used method to explore microbial community dynamics in space and time, to predict the ecological relevance of microbial populations, or to identify microbial key players in biogeochemical cycles. Several computational analysis methods were developed to aid 16S rRNA gene analysis but choosing the best method is not trivial. In this study, we compared popular analysis methods (i.e. Mothur, QIIME1 and 2, and MEGAN) using samples with known microbial composition (i.e. mock community samples) and environmental samples from contrasting habitats (i.e. groundwater, soil, sediment, and river water). Our findings provide guidance for choosing the currently optimal 16S rRNA gene sequencing analysis method and we implemented our recommended pipeline into a reproducible workflow, which follows highest bioinformatics standards and is open source and free to use.

microbiology↗