Krill oil treatment ameliorates lipid metabolism imbalance in chronic unpredicted mild stress-induced depression-like behavior in mice.

The pathology of depression involves various factors including the interaction between genes and the environment. The deficiency of n-3 polyunsaturated fatty acids (n-3 PUFAs) in the brain and depressive symptoms are closely related. Krill oil contains abundant amounts of n-3 PUFAs incorporated in phosphatidylcholine. However, the effect of krill oil treatment on depression-like behaviors induced by chronic stress and its molecular mechanism in the brain remain poorly understood. Here, we used a chronic unpredictable mild stress (CUMS) model to evaluate the effect of krill oil on depression-like behaviors and explored its molecular mechanism through lipid metabolomics and mRNA profiles in the whole brain. We observed that CUMS-induced depression-like behaviors were ameliorated by krill oil supplementation in mice. The metabolism of glycerophospholipids and sphingolipids was disrupted by CUMS treatment, which were ameliorated after krill oil supplementation. Further analysis found that differently expressed genes after krill oil supplementation were mainly enriched in the membrane structures and neuroactive ligand-receptor interaction pathway, which may be responsible for the amelioration of CUMS-induced depression-like behaviors. Altogether, our results uncovered the relationship between lipid metabolism and CUMS, and provided new strategies for the prevention and treatment of depression.

The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights.

Antarctic krill (Euphausia superba) is Earth's most abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research.

Assembly and Network Stability of Planktonic Microorganisms under the Influence of Salinity Gradient: an Arctic Case Study from the Lena River Estuary to the Laptev Sea.

The diversity and primary productivity in the Arctic ecosystem are rapidly changing due to global warming. Microorganisms play a vital role in biogeochemical cycling. However, the diversity of planktonic microorganism communities in the Laptev Sea, one of the most important marginal seas of the Western Arctic Ocean, have not been studied sufficiently in depth. The diversity and community structure of the planktonic microorganisms in the surface water were investigated at 20 stations on the Lena River flowing into the Laptev Sea. Multivariate statistical analyses demonstrated clear spatial patterns in the α diversity and community structure for microorganisms under different salinity levels. Co-occurrence networks of microbial communities revealed that spatial variation promoted differentiation of the characteristics and stability of microbial networks in the Laptev Sea. Contrary to expectations, abundant taxa were found to not have a large influence on the stability and resilience of microbial interactions in the region. On the contrary, less-abundant taxa were found to have far greater influence. The stability and resilience of the prokaryotic and microeukaryotic networks in the Lena River estuary and the continental shelf provided valuable insights into the impact of freshwater and land inflow disturbances on microbial assemblage. Overall, these results enhance our understanding of the composition of microbial communities and provide insights into how spatial changes of abundant versus rare species alter the nature and stability of microbial networks from the Lena River estuary to the Laptev Sea. In addition, this study explored microbial interactions and their ability to resist future disturbances. IMPORTANCE The regime of the Laptev Sea depends closely on the runoff of the Lena River. Microorganisms are essential components of aquatic food webs and play a significant role in polar ecosystems. In this study, we provided a basic microbial data set as well as new insights into the microbial networks from the Lena River estuary to the Laptev Sea, while exploring their potential to resist future disturbances. A comprehensive and systematic study of the community structure and function of the planktonic microorganisms in the Laptev Sea would greatly enhance our understanding of how polar microbial communities respond to the salinity gradient under climate warming.

A method to analyze the sensitivity ranking of various abiotic factors to acoustic densities of fishery resources in the surface mixed layer and bottom cold water layer of the coastal area of low latitude: a case study in the northern South China Sea.

This is an exploratory analysis combining artificial intelligence algorithms, fishery acoustics technology, and a variety of abiotic factors in low-latitude coastal waters. This approach can be used to analyze the sensitivity level between the acoustic density of fishery resources and various abiotic factors in the surface mixed layer (the water layer above the constant thermocline) and the bottom cold water layer (the water layer below the constant thermocline). The fishery acoustic technology is used to obtain the acoustic density of fishery resources in each water layer, which is characterized by Nautical Area Scattering Coefficient values (NASC), and the artificial intelligence algorithm is used to rank the sensitivity of various abiotic factors and NASC values of two water layers, and the grades are classified according to the cumulative contribution percentage. We found that stratified or multidimensional analysis of the sensitivity of abiotic factors is necessary. One factor could have different levels of sensitivity in different water layers, such as temperature, nitrite, water depth, and salinity. Besides, eXtreme Gradient Boosting and random forests models performed better than the linear regression model, with 0.2 to 0.4 greater R2 value. The performance of the models had smaller fluctuations with a larger sample size.