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The constant increase in temperatures under global warming has led to a prolonged aestivation period for Apostichopus japonicus, resulting in considerable losses in production and economic benefits. However, the specific mechanism of aestivation has not been fully elucidated. In this study, we first tried to illustrate the biological mechanisms of aestivation from the perspective of the gut microbiota and metabolites. Significant differences were found in the gut microbiota of aestivating adult A. japonicus (AAJSD group) compared with nonaestivating adult A. japonicus (AAJRT group) and young A. japonicus (YAJRT and YAJSD groups) based on 16S rRNA gene high-throughput sequencing analysis. The abundances of Desulfobacterota, Myxococcota, Bdellovibrionota, and Firmicutes (4 phyla) in the AAJSD group significantly increased. Moreover, the levels of Pseudoalteromonas, Fusibacter, Labilibacter, Litorilituus, Flammeovirga, Polaribacter, Ferrimonas, PB19, and Blfdi19 genera were significantly higher in the AAJSD group than in the other three groups. Further analysis of the LDA effect size showed that species with significant variation in abundance in the AAJSD group, including the phylum Firmicutes and the genera Litorilituus, Fusibacter, and Abilibacter, might be important biomarkers for aestivating adult A. japonicus. In addition, the results of metabolomics analysis showed that there were three distinct metabolic pathways, namely biosynthesis of secondary metabolites, tryptophan metabolism, and sesquiterpenoid and triterpenoid biosynthesis in the AAJSD group compared with the other three groups. Notably, 5-hydroxytryptophan was significantly upregulated in the AAJSD group in the tryptophan metabolism pathway. Moreover, the genera Labilibacter, Litorilituus, Ferrimonas, Flammeovirga, Blfdi19, Fusibacter, Pseudoalteromonas, and PB19 with high abundance in the gut of aestivating adult A. japonicus were positively correlated with the metabolite 5-HTP. These findings suggest that there may be potential biological associations among the gut microbiota, metabolites, and aestivation in A. japonicus. This work may provide a new perspective for further understanding the aestivation mechanism of A. japonicus. [ABSTRACT FROM AUTHOR]

Aeromonas veronii is an important zoonotic and aquatic pathogen. An increasing number of reports indicate that it has caused substantial economic losses in the aquaculture industry, in addition to threatening human health. However, little is known about its pathogenesis. Exploration of new virulence factors of A. veronii would be helpful for further understanding its pathogenesis. Hence, we comparatively analyzed the proteomes of virulent, attenuated, and avirulent strains of A. veronii using tandem mass tag (TMT) protein labeling and found numerous proteins either up‐ or downregulated in the virulent strain. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that these differentially expressed proteins (DEPs) were involved mainly in pathways associated with bacterial chemotaxis and microbial metabolism in diverse environments. Furthermore, the expression levels of lysine decarboxylase, endoribonuclease, maltoporin, pullulanase, and aerolysin were positively correlated with the virulence of the strains, suggesting that their function may be closely related to the virulence of A. veronii. The results of qRT‐PCR and multiple reaction monitoring for some DEPs were consistent with the results of TMT protein labeling. These results suggest that these DEPs may be novel potential virulence factors and will help to further understand the pathogenesis of A. veronii. [ABSTRACT FROM AUTHOR]

With the increase of both magnitude and frequency of hydrological extreme events such as drought and flooding, the significance of adequately modeling hydrological extreme events is fully recognized. Estimation of extreme rainfall/flood for various return periods is of prime importance for hydrological design or risk assessment. However, due to knowledge and data limitation, uncertainty involved in extrapolating beyond available data is huge. In this paper, different sources of uncertainty in statistical modeling of extreme hydrological events are studied in a systematic way. This is done by focusing on several key uncertainty sources using three different case studies. The chosen case studies highlight a number of projects where there have been questions regarding the uncertainty in extreme rainfall/flood estimation. The results show that the uncertainty originated from the methodology is the largest and could be >40% for a return period of 200 years, while the uncertainty caused by ignoring the dependence among multiple hydrological variables seems the smallest. In the end, it is highly recommended that uncertainty in modeling extreme hydrological events be fully recognized and incorporated into a formal hydrological extreme analysis. [ABSTRACT FROM AUTHOR]