Genome mining of metagenomic data has become the preferred method for the bioprospecting of novel compounds by cataloguing secondary metabolite potential. However, the accurate detection of BGCs requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until recently with new long-read technologies.

Marine microorganisms are increasingly recognized as primary producers of marine secondary metabolites, drawing growing research interest. Many of these organisms are unculturable, posing challenges for study. Metagenomic techniques enable research on these unculturable microorganisms, identifying various biosynthetic gene clusters (BGCs) related to marine microbial secondary metabolites, thereby unveiling their secrets. This review comprehensively analyses metagenomic methods used in discovering marine microbial secondary metabolites, highlighting tools commonly employed in BGC identification, and discussing the potential and challenges in this field. It emphasizes the key role of metagenomics in unveiling secondary metabolites, particularly in marine sponges and tunicates. The review also explores current limitations in studying these metabolites through metagenomics, noting how long‐read sequencing technologies and the evolution of computational biology tools offer more possibilities for BGC discovery. Furthermore, the development of synthetic biology allows experimental validation of computationally identified BGCs, showcasing the vast potential of metagenomics in mining marine microbial secondary metabolites.

A modified Cylindrical-Focused Laser Differential Interferometer (CFLDI) system was used to measure the density fluctuations generated by a Mach 6 turbulent boundary layer on a flat plate. The amplitude, spectrum statistics and correlation scale of density fluctuations were analyzed at different wall-normal heights across the boundary layer. Direct Numerical Simulation (DNS) under similar conditions was also performed to verify the accuracy of the experimental results. The experiments show that the CFLDI system herewith can accurately represent the statistical characteristics of density fluctuations with a bandwidth of 3~200 kHz. As the distance from the wall increases, the amplitude of density fluctuations peaks at y/δ ≈ 0.8 and levels off after y/δ ≈ 1.5. As the measuring position moves into the freestream, the characteristic frequency of the density fluctuations decreases rapidly, while its integral time scale gradually increases. Similar phenomena were also found for pressure fluctuations.

Introduction: In metabolic engineering and synthetic biology applications, promoters with appropriate strengths are critical. However, it is time-consuming and laborious to annotate promoter strength by experiments. Nowadays, constructing mutation-based synthetic promoter libraries that span multiple orders of magnitude of promoter strength is receiving increasing attention. A number of machine learning (ML) methods are applied to synthetic promoter strength prediction, but existing models are limited by the excessive proximity between synthetic promoters.Methods: In order to enhance ML models to better predict the synthetic promoter strength, we propose EVMP(Extended Vision Mutant Priority), a universal framework which utilize mutation information more effectively. In EVMP, synthetic promoters are equivalently transformed into base promoter and corresponding k-mer mutations, which are input into BaseEncoder and VarEncoder, respectively. EVMP also provides optional data augmentation, which generates multiple copies of the data by selecting different base promoters for the same synthetic promoter.Results: In Trc synthetic promoter library, EVMP was applied to multiple ML models and the model effect was enhanced to varying extents, up to 61.30% (MAE), while the SOTA(state-of-the-art) record was improved by 15.25% (MAE) and 4.03% (R²). Data augmentation based on multiple base promoters further improved the model performance by 17.95% (MAE) and 7.25% (R²) compared with non-EVMP SOTA record.Discussion: In further study, extended vision (or k-mer) is shown to be essential for EVMP. We also found that EVMP can alleviate the over-smoothing phenomenon, which may contributes to its effectiveness. Our work suggests that EVMP can highlight the mutation information of synthetic promoters and significantly improve the prediction accuracy of strength. The source code is publicly available on GitHub: https://github.com/Tiny-Snow/EVMP.

The study of marine microbial communities is crucial for comprehending the distribution patterns, adaptations to the environment, and the functioning of marine microorganisms. Despite being one of the largest biomes on Earth, the bacterioplankton communities in the Northwest Pacific Ocean (NWPO) remain understudied. In this research, we aimed to investigate the structure of the surface bacterioplankton communities in different water masses of the NWPO. We utilized metagenomic sequencing techniques and cited previous 16S rRNA data to explore the distribution patterns of bacterioplankton in different seasons. Our results revealed that Cyanobacteria, Proteobacteria, Bacteroidetes, and Actinobacteria dominated the microbial communities, accounting for over 95% of the total. During spring, we observed significant differentiation in community structure between the different water masses. For instance, Prochlorococcus and Pseudoalteromonas were primarily distributed in the nutrient-deficient subtropical countercurrent zone, while Flavobacteriaceae and Rhodobacteraceae were found in the Kuroshio-Oyashio mixing zone. During summer, the surface planktonic bacteria communities became homogenized across regions, with Cyanobacteria becoming the dominant group (68.6% to 84.9% relative abundance). The metabolic processes of the microorganisms were dominated by carbohydrate metabolism, followed by amino acid transport and metabolism. However, there was a low relative abundance of functional genes involved in carbohydrate metabolism in the Kuroshio-Oyashio mixing zone. The metagenomic data had assembled 37 metagenomic-assembled genomes (MAGs), which belong to Proteobacteria, Bacteroidetes, and Euryarchaeota. In conclusion, our findings highlight the diversity of the surface bacterioplankton community composition in the NWPO, and its distinct geographic distribution characteristics and seasonal variations.

Objectives: To investigate changes in brain functional activity among occupational noise-induced hearing loss (NIHL) with tinnitus patients, using resting-state brain magnetic resonance imaging (Rs-fMRI) and voxel-based morphometry (VBM). Methods: Mild (27) and Relative severe (15) patient groups, 30 matched healthy group, scanned by Rs-fMRI and T1WI 3D fast spoiled gradient echo, FSPGR, using voxel-based morphometry and amplitude of low frequency fluctuation to analyze the differences. Results: Brain gray matter volume was significantly different among the three groups in the left occipitotemporal lateral gyrus, the anterior cingulate gyrus, the bilateral angular gyrus, the precuneus, and near the midline area of the cerebellum. The Rs-fMRI changes showed that amplitude of low frequency fluctuation differed significantly among the three groups in the right superior temporal gyrus, the right inferior frontal gyrus, and the right angular gyrus. Conclusion: All this provides a new perspective for understanding the pathophysiological mechanism of occupational noise-induced hearing loss and provides some theoretical bases for subsequent treatment.