Bacteria are an influential component of diverse composting microbiomes, but their structure and underlying dynamics are poorly understood. This study analyzed the bacterial communities of 577 compost datasets globally and constructed a substrate-dependent catalog with more than 15 million non-redundant 16S rRNA gene sequences. Using a random-forest machine-learning model, 30 biomarker taxa were identified

This study aims to propose a biological system that allows for direct utilization of flue gas for carbon dioxide capture and utilization by microalgae. The strain Chlorella sp. ABC-001 is employed for its high growth rate as well as lipid and carbohydrate content. Toxicity tests showed that cell growth was unaffected by NO, but the presence of SO2 showed critical damage on cell growth. Hence, an extremophile

Intracellular lipid droplets (LDs), subcellular organelles playing a role in long-term carbon storage, have immense potential in biofuel and dietary lipid production. Monitoring the state of LDs in living cells is of utmost importance for quick biomass harvest and screening promising isolates. Here, a deep-learning-based segmentation model was developed for automatic detection and segmentation of LDs