scholarly journals Metabolic and spatio-taxonomic response of uncultivated seafloor bacteria following the Deepwater Horizon oil spill

2016 ◽  
Author(s):  
KM Handley ◽  
YM Piceno ◽  
P Hu ◽  
LM Tom ◽  
OU Mason ◽  
...  

AbstractThe release of 700 million liters of oil into the Gulf of Mexico over a few months in 2010 produced dramatic changes in the microbial ecology of the water and sediment. Previous 4 studies have examined the phylogeny and function of these changes, but until now a 5 fundamental examination of the extant hydrocarbon metabolisms that supported these 6 changes had not been performed. Here, we reconstructed the genomes of 57 widespread 7 uncultivated bacteria from post spill sediments, and recovered their gene expression 8 pattern across the seafloor. These genomes comprised a common collection of bacteria 9 that were highly enriched in heavily affected sediments around the wellhead. While rare in distal sediments, some members were still detectable at sites up to 60 km away. Many of these genomes exhibited phylogenetic clustering indicative of common trait selection by the environment, and within half we identified 264 genes associated with hydrocarbon degradation. Observed alkane degradation ability was near ubiquitous among candidate hydrocarbon degraders, while just 3 harbored elaborate gene inventories for the degradation of alkanes and (poly)aromatic hydrocarbons. Differential gene expression profiles revealed a spill-promoted microbial sulfur cycle alongside gene up-regulation associated with polyaromatic hydrocarbon degradation. Gene expression associated with alkane degradation was widespread, although active alkane degrader identities changed along the pollution gradient. The resulting analysis suggests a broad metabolic capacity to respond to oil exists across a large array of usually rare bacteria.

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 301-301
Author(s):  
Chaoyang Li ◽  
Qianglin Liu ◽  
Matt Welborn ◽  
Leshan Wang ◽  
Yuxia Li ◽  
...  

Abstract The amount of intramuscular fat directly influences the meat quality. However, significant differences in the ability to accumulate intramuscular fat are present among different beef cattle breeds. While Wagyu, a cattle breed that originated from Japan, is renowned for abundant intramuscular fat, Brahman cattle generally have very little intramuscular fat accumulation and produce tougher meat. We identified that bovine intramuscular fat is derived from a group of bipotent progenitor cells named fibro/adipogenic progenitors (FAPs) which also give rise to fibroblasts. Thus, the variation in intramuscular fat development between Wagyu and Brahman is likely attributed to the difference in FAPs between these two breeds. In order to understand the gene expression difference between FAPs of the two breeds, single-cell RNA-seq was performed using total single-nucleated cells isolated from the longissimus muscle of young purebred Wagyu, purebred Brahman, and Wagyu-Brahman cross cattle. FAPs constitute the largest single-nucleated cell population in both Wagyu and Brahman skeletal muscle. Multiple subpopulations of FAPs with different gene expression profiles were identified, suggesting that FAP is a heterogeneous population. A unique FAP cluster expressing lower levels of fibrillar collagen and extracellular remodeling enzyme genes but higher levels of select proadipogenic genes was identified exclusively in Wagyu skeletal muscle, which likely contributes to the robust intramuscular adipogenic efficiency of Wagyu FAPs. In conclusion, the difference in the cellular composition and gene expression of FAPs between Wagyu and Brahman cattle likely contribute to their distinct meat quality.


2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582635-s-0036-1582635 ◽  
Author(s):  
Sibylle Grad ◽  
Ying Zhang ◽  
Olga Rozhnova ◽  
Elena Schelkunova ◽  
Mikhail Mikhailovsky ◽  
...  

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


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