Shaojing Wang

The development of robust and efficient β-mannanases is key to advancing environmentally friendly industrial processes, such as guar gum fracturing fluid gel-breaking. Here, we report the identification and characterization of MG4, a novel thermotolerant and alkaliphilic β-mannanase mined from the Earth’s Microbiome database. The recombinant enzyme has a molecular weight of 63 kDa. MG4 displayed maximum activity at 65 °C and pH 9.0, and exhibited remarkable stability across a broad pH range (7.0–10.0). It retained over 80% of its activity after incubation at 50 °C for 1 h, and its activity was enhanced more than 40% by Mg²⁺ or Ca²⁺. Moreover, MG4 (20 mg/L) reduced the viscosity of guar gum fracturing fluid to <5 m·PaS within 30 min, outperforming ammonium persulfate (APS, 500 mg/L) which required 1 h, and produced 64.5% less insoluble residue. TEM imaging directly visualized the disruption of the guar gum polymer network by MG4, explaining its efficacy and suggesting reduced formation damage risk compared to chemical breakers. This work characterizes a highly promising biocatalyst whose thermostability, alkaliphily, efficient gel-breaking, low residue yield, and minimal formation damage potential position it as a superior, eco-friendly alternative for petroleum industry applications.

Temperature is very important for the growth of microorganisms. Appropriate temperature conditions can improve the possibility for isolation of currently uncultured microorganisms. The development of metagenomic binning technology had dramatically increased the availability of genomic information of prokaryotes, providing convenience to infer the optimal growth temperature (OGT). Here, we proposed CnnPOGTP, a predictor for OGTs of prokaryotes based on deep learning method using only k-mers distribution derived from genomic sequence. This method was annotation free, and the predicted OGT could be obtained by simply providing the genome sequence to the CnnPOGTP website. http://www.orgene.net/CnnPOGTP. Supplementary data are available at Bioinformatics online.

Effective height is used as a characterization parameter in current ultra-high frequency (UHF) sensor performance test. It describes the sensitivity of sensors to different spectral components of the signals, but is incapable of reflecting the time domain response of sensors, making it inconvenient to carry out UHF detection based on time domain signals. An improved UHF sensor performance test method, including a test system and characterization parameters is proposed. The amplitude-frequency characteristic and phase-frequency characteristic of the effective height is obtained from scattering parameters measured using a vector network analyzer. Further, by calculating the analytic impulse response, extracting three time domain parameters, including peak value of the envelope,envelope width and ringing time. The effect of the test method is discussed after a comparison test of two UHF sensor with different time domain parameters detecting a simulated partial discharge signal. The study shows that the proposed characterization and measurement system is capable of measuring the time domain and frequency domain parameters of UHF sensors and representing their behaviors under partial discharge pulse signals.