Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1026058 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26322612_1.fastq.gz | Fastqsanger.gz | |||
| SRR26322612_2.fastq.gz | Fastqsanger.gz | |||
| SRR26322613_1.fastq.gz | Fastqsanger.gz | |||
| SRR26322613_2.fastq.gz | Fastqsanger.gz | |||
| SRR26322614_1.fastq.gz | Fastqsanger.gz |
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2021-06-01 | E-MTAB-9439 | biostudies-arrayexpress
Project description:Due to its high altitude and extreme climate conditions, the Tibetan plateau is a region vulnerable to the impact of climate changes and anthropogenic perturbation, thus understanding how its microbial communities function may be of high importance. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, aiming to explore potential microbial responses to climate changes and anthropogenic perturbation. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities in treatment site were distinct, compared with those in control site, e.g. shrubland vs grassland, grazing site vs ungrazing site, or warmer site vs colder site. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes.
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Project description:Purpose: Protozoan predators affect the structure of bacterial communities, but investigations into how predation influences bacterial evolution and antagonistic behaviours are scarce. We performed a 20-day predator-prey evolution experiment on solid media to investigate the adaptive traits that arise in bacterial prey under continuous protozoan predation. Methods: Pseudomonas fluorescens SBW25 and a wild Acanthamoeba sp. isolate as a predator prey pair co-evolved for 20 days yielded both previously described (Wrinkly Spreader; WS) and novel colony morphotype (Wrinkly Fried Egg; WFE) isolates with conferred grazing resistance. These isolates were subjected to RNAseq profiling with and without predation to determine transcriptional changes contributing to grazing resistance. Results: For differential gene expression the WT SBW25 without predation was used as a baseline. For the WS condition, a total of 881 differentially expressed genes (DEGs) were identified, of which 424 were upregulated and 457 were downregulated. In the WFE condition, a total of 908 DEGs were identified, of which 475 were upregulated and 434 were downregulated. Among all DEGs, 335 upregulated and 313 downregulated genes were shared between the WS1 and WFE conditions Conclusions: Our findings suggest that protozoan predation can profoundly influence the course of genetic and phenotypic evolution in a short period of time. Together, the differential expression results suggest expression of features that would be expected to increase biofilm formation in WFE according to previous studies. However, increased expression of these traits may not lead to a stronger biofilm, but may still provide predation resistance. For example, fibrils may increase the effective profile size of a bacterial cell. Increased Fap-mediated biofilm formation also induces increased alginate synthesis in P. aeruginosa PA01, an exopolysaccharide that protects mucoid P. aeruginosa against macrophage killing. Interestingly, we found increased expression of alginate biosynthesis genes in both WFE and WS1 (algA, algF), suggesting alternate mechanisms leading to increased alginate production in these two strains.
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