Mulberry (Morus alba L.) leaves are not only used as the main feed for silkworms (Bombyx mori) but also as an added feed for livestock and poultry. In order to rapidly select high-quality mulberry leaves, a hand-held near-infrared (NIR) spectrometer combined with partial least squares (PLS) regression and wavelength optimization methods were used to establish a predictive model for the quantitative determination of water content in fresh mulberry leaves, as well as crude protein and soluble sugar in dried mulberry leaves. For the water content in fresh mulberry leaves, the R-square of the calibration set ( ${\mathrm{R}}_{\mathrm{C}}^2$ ), R-square of the cross-validation set ( ${\mathrm{R}}_{\mathrm{C}\mathrm{V}}^2$ ) and R-square of the prediction set ( ${\mathrm{R}}_{\mathrm{P}}^2$ ) are 0.93, 0.90 and 0.91, respectively, the corresponding root mean square error of calibration set (RMSEC), root mean square error of cross-validation set (RMSECV) and root mean square error of prediction set (RMSEP) are 0.96%, 1.13%, and 1.18%, respectively. The ${\mathrm{R}}_{\mathrm{C}}^2$ , ${\mathrm{R}}_{\mathrm{C}\mathrm{V}}^2$ and ${\mathrm{R}}_{\mathrm{P}}^2$ of the crude protein prediction model are 0.91, 0.83 and 0.92, respectively, and the corresponding RMSEC, RMSECV and RMSEP are 0.71%, 0.97% and 0.61%, respectively. The soluble sugar prediction model has ${\mathrm{R}}_{\mathrm{C}}^2$ , ${\mathrm{R}}_{\mathrm{C}\mathrm{V}}^2$ , and ${\mathrm{R}}_{\mathrm{P}}^2$ of 0.64, 0.51, and 0.71, respectively, and the corresponding RMSEC, RMSECV, and RMSEP are 2.33%, 2.73%, and 2.36%, respectively. Therefore, the use of handheld NIR spectrometers combined with wavelength optimization can fastly detect the water content in fresh mulberry leaves and crude protein in dried mulberry leaves. However, it is a slightly lower predictive performance for soluble sugar in mulberry leaves.

Plipastatin, an antimicrobial peptide produced by Bacillus subtilis, exhibits remarkable antimicrobial activity against a diverse range of pathogenic bacteria and fungi. However, the practical application of plipastatin has been significantly hampered by its low yield in wild Bacillus species. Here, the native promoters of both the plipastatin operon and the sfp gene in the mono-producing strain M-24 were replaced by the constitutive promoter P₄₃, resulting in plipastatin titers being increased by 27% (607 mg/mL) and 50% (717 mg/mL), respectively. Overexpression of long chain fatty acid coenzyme A ligase (LCFA) increased the yield of plipastatin by 105% (980 mg/mL). A new efflux transporter, YoeA, was identified as a MATE (multidrug and toxic compound extrusion) family member, overexpression of yoeA enhanced plipastatin production to 1233 mg/mL, an increase of 157%, and knockout of yoeA decreased plipastatin production by 70%; in contrast, overexpression or knockout of yoeA in mono-producing surfactin and iturin engineered strains only slightly affected their production, demonstrating that YoeA acts as the major exporter for plipastatin. Co-overexpression of lcfA and yoeA improved plipastatin production to 1890 mg/mL, which was further elevated to 2060 mg/mL after abrB gene deletion. Lastly, the use of optimized culture medium achieved 2514 mg/mL plipastatin production, which was 5.26-fold higher than that of the initial strain. These results suggest that multiple strain engineering is an effective strategy for increasing lipopeptide production, and identification of the novel transport efflux protein YoeA provides new insights into the regulation and industrial application of plipastatin.

Next-generation sequencing (NGS) makes a large mass of sequences. As a technology that allows the sequence of deoxyribonucleic acid (DNA) molecules larger than one million base pairs, it has been applied in the food research and medical fields. In the food sector, NGS has been used in food safety for the detection of species authenticity of food products and for mostly discovering novel industrial enzymes. The soil ecosystem houses a great number of non-culturable microbes thus novels enzymes can still be discovered to date. The conventional methods used in enzyme discovery have less chances to identify novel gene clusters and bioactivities. Therefore, there is a dire need for high-throughput technology, together with advanced bioinformatics for the search of novel enzymes or biocatalysts from soil metagenomes. This review article thus gives a summary of the progress in the application of next-generation sequencing in the identification and characterization of novel enzymes with a special focus on enzymes from the soil environment.