A halophilic bacterium,named Halomonas sp.NEC-1 was isolated from the Nyer Co Salt Lake on the Xizang Plateau,SW China.The strain exhibited a broad pH tolerance range of 5-11,distinguishing it from Halomonas alkaliphi...A halophilic bacterium,named Halomonas sp.NEC-1 was isolated from the Nyer Co Salt Lake on the Xizang Plateau,SW China.The strain exhibited a broad pH tolerance range of 5-11,distinguishing it from Halomonas alkaliphila despite a 99% genetic similarity.Optimal growth conditions,determined through orthogonal experiments,were found to be 37℃,100-g/L salinity,and an initial pH of 6,resulting in a maximum OD_(600) of 7.98±0.06.Halomonas sp.NEC-1 produced 545.43±25.10 mg/L of ectoine under optimal conditions of 75-g/L salinity,40-g/L sodium glutamate,and an initial pH of 6.This production increased to 1388.81±3.69 mg/L after five rounds of hypo-osmotic shocks.During the shocks,ectoine productivity remained stable at approximately 16.29±0.04 to 17.28±0.48 mg/(L·h),representing a 43.40%-52.11% increase compared to the rate without any shock(11.36±1.05 mg/(L·h)).Additionally,the expression of the ectABC gene cluster,related to ectoine synthesis,significantly increased following the shocks,enhancing ectoine production.The ectoine extract demonstrated notable protective effects on Escherichia coli and plasmid DNA.After 10 min of exposure at 60℃,the colony count of E.coli treated with ectoine extract increased by 342% compared to treatment with distilled water.Furthermore,the ectoine extract protected plasmid DNA from 2,2′-Azobis(2-methylpropionamidine)dihydrochloride-induced damage.This study highlights Halomonas sp.NEC-1 is a promising strain for ectoine production and underscores the potential of microbial resources in salt lakes from Xizang region.展开更多
Whispering gallery mode(WGM)microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity,compact size,and fast response.However,the conventional WGM sensors rely on monit...Whispering gallery mode(WGM)microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity,compact size,and fast response.However,the conventional WGM sensors rely on monitoring the changes of a single mode,and the abundant sensing information in WGM transmission spectra has not been fully utilized.Here,empowered by machine learning(ML),we propose and demonstrate an ergodic spectra sensing method in an optofluidic microcavity for high-precision pressure measurement.The developed ML method realizes the analysis of the full features of optical spectra.The prediction accuracy of 99.97%is obtained with the average error as low as 0.32 kPa in the pressure range of 100 kPa via the training and testing stages.We further achieve the real-time readout of arbitrary unknown pressure within the range of measurement,and a prediction accuracy of 99.51%is obtained.Moreover,we demonstrate that the ergodic spectra sensing accuracy is∼11.5%higher than that of simply extracting resonating modes’wavelength.With the high sensitivity and prediction accuracy,this work opens up a new avenue for integrated intelligent optical sensing.展开更多
基金Supported by the Key Science and Technology Program of Xizang Autonomous Region(No.XZ202301ZY0012N)the Key Fisheries Resources and Environmental Survey Project in the Southwest Region(No.CJW2023034)the National Natural Science Foundation of China(No.42306106)。
文摘A halophilic bacterium,named Halomonas sp.NEC-1 was isolated from the Nyer Co Salt Lake on the Xizang Plateau,SW China.The strain exhibited a broad pH tolerance range of 5-11,distinguishing it from Halomonas alkaliphila despite a 99% genetic similarity.Optimal growth conditions,determined through orthogonal experiments,were found to be 37℃,100-g/L salinity,and an initial pH of 6,resulting in a maximum OD_(600) of 7.98±0.06.Halomonas sp.NEC-1 produced 545.43±25.10 mg/L of ectoine under optimal conditions of 75-g/L salinity,40-g/L sodium glutamate,and an initial pH of 6.This production increased to 1388.81±3.69 mg/L after five rounds of hypo-osmotic shocks.During the shocks,ectoine productivity remained stable at approximately 16.29±0.04 to 17.28±0.48 mg/(L·h),representing a 43.40%-52.11% increase compared to the rate without any shock(11.36±1.05 mg/(L·h)).Additionally,the expression of the ectABC gene cluster,related to ectoine synthesis,significantly increased following the shocks,enhancing ectoine production.The ectoine extract demonstrated notable protective effects on Escherichia coli and plasmid DNA.After 10 min of exposure at 60℃,the colony count of E.coli treated with ectoine extract increased by 342% compared to treatment with distilled water.Furthermore,the ectoine extract protected plasmid DNA from 2,2′-Azobis(2-methylpropionamidine)dihydrochloride-induced damage.This study highlights Halomonas sp.NEC-1 is a promising strain for ectoine production and underscores the potential of microbial resources in salt lakes from Xizang region.
基金National Natural Science Foundation of China(11974058,62005231,62131002)A3 Foresight Program of NSFC(62061146002)+3 种基金Beijing Nova Program from Beijing Municipal Science and Technology Commission(Z201100006820125)Beijing Municipal Natural Science Foundation(Z210004)State Key Laboratory of Information Photonics and Optical Communications,BUPT,China(IPOC2021ZT01)BUPT Excellent Ph.D.Students Foundation(CX2022114).
文摘Whispering gallery mode(WGM)microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity,compact size,and fast response.However,the conventional WGM sensors rely on monitoring the changes of a single mode,and the abundant sensing information in WGM transmission spectra has not been fully utilized.Here,empowered by machine learning(ML),we propose and demonstrate an ergodic spectra sensing method in an optofluidic microcavity for high-precision pressure measurement.The developed ML method realizes the analysis of the full features of optical spectra.The prediction accuracy of 99.97%is obtained with the average error as low as 0.32 kPa in the pressure range of 100 kPa via the training and testing stages.We further achieve the real-time readout of arbitrary unknown pressure within the range of measurement,and a prediction accuracy of 99.51%is obtained.Moreover,we demonstrate that the ergodic spectra sensing accuracy is∼11.5%higher than that of simply extracting resonating modes’wavelength.With the high sensitivity and prediction accuracy,this work opens up a new avenue for integrated intelligent optical sensing.
