Bacillus, an excellent organic-degrading agent, can degrade lignocellulose. Notably, some B. velezensis strains encode lignocellulases. However, their ability to degrade lignocellulose in fermented feed is not much appreciated. This study performed a comparative genomic analysis of twenty-three B. velezensis strains to find common carbohydrate-active enzymes (CAZymes) encoding genes and evaluated their potential to degrade lignocellulose. The comparative genomic and CAZyme database-based analyses identified several potential CAZymes genes that degrade cellulose (GH1, GH4, GH5, GH13, GH16, GH32, PL1, and PL9), hemicellulose (GH11, GH26, GH43, GH51, and CE3) and lignin (AA4, AA6, AA7, and AA10). Furthermore, Illumina RNA-seq transcriptome analysis revealed the expression of more than 1794 genes in B. velezensis CL-4 fermented corn germ meal at 48 h (FCGM 48 h). Gene ontology analysis of expressed genes revealed their enrichment in hydrolase activity (breaking the glycosyl bonds during carbohydrate metabolism), indicating the upregulation of CAZymes. In total, 58 differentially upregulated CAZymes-encoding genes were identified in FCGM 48 h compared to FCGM 0 h. The upregulated CAZymes-encoding genes were related to cellulose (6-phospho-β-galactosidase and 6-phospho-α-glucosidase), starch (α-glucosidase and α-amylase), pectin (pectin lyase), and hemicellulose (arabinan endo-1,5-α-L-arabinosidase, xylan 1,4-beta-xylosidase, α-N-arabinofuranosidase, and acetyl xylan esterase). Importantly, arabinoxylan degradation mainly occurred in FCGM 48 h, followed by partial degradation of cellulose, pectin, and starch. This study can support the development of enzymatic cocktails for the solid-state fermented feed (SFF).
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http://dx.doi.org/10.1186/s13568-023-01510-5 | DOI Listing |
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Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
The harlequin ladybird, , is a predatory beetle used globally to control pests such as aphids and scale insects. Originating from East Asia, this species has become highly invasive since its introduction in the late 19th century to Europe and North America, posing a threat to local biodiversity. Intraguild predation is hypothesized to drive the success of this invasive species, but the underlying mechanisms remain unknown.
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State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan 430062, China.
Horizontal gene transfer (HGT) from bacteria to insects is widely reported and often associated with the adaptation and diversification of insects. However, compelling evidence demonstrating how HGT-conferred metabolic adjustments enable species to adapt to surrounding environment remains scarce. Dietary specialization is an important ecological strategy adopted by animals to reduce inter- and intraspecific competition for limited resources.
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January 2025
Department of Biology, Faculty of Science and Technology, Mount Royal University, Calgary, AB T3E 6K6, Canada.
With over 14 million people living above 3,500 m, the study of acclimatization and adaptation to high altitude in human populations is of increasing importance, where exposure to high altitude (HA) imposes a blood oxygenation and acid-base challenge. A sustained and augmented hypoxic ventilatory response protects oxygenation through ventilatory acclimatization, but elicits hypocapnia and respiratory alkalosis. A subsequent renally mediated compensatory metabolic acidosis corrects pH toward baseline values, with a high degree of interindividual variability.
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Chungbuk National University College of Medicine, Cheongju, Republic of Korea.
Purpose: We aimed to identify the transcriptomic signatures of soft tissue sarcoma (STS) related to radioresistance and establish a model to predict radioresistance.
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PLoS Comput Biol
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Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. This can be effectively applied in genomics when we learn the gene associations in a target tissue, and data from other tissues can be integrated. However, heavy-tail distribution and outliers are common in genomics data, which poses challenges to the effectiveness of current transfer learning approaches.
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