Engineering Escherichia coli for Effective Expression of Plant Genes

Department Of Biomedical EngineeringVarious plant-derived useful chemicals have been used for human from ancient to modern time. Because of difference of genetic characters between bacteria and plant, it could cause low plant protein expression or formation of inclusion body composed by insoluble protein precipitates. There are generally two methods for enhancement of heterologous protein expression in E. coli. In order to change rare tRNA abundance and chaperone expression level, we conducted chromosomally integrated promoter mutant libraries using recombination with single-strand DNA oligonucleotides. Some chaperone promoter mutants showed enhancement of Arabidopsis???s protein expression level. The tRNA and chaperone promoter mutants also showed significant increases in target Arabidopsis???s protein expression. We developed E. coli mutants for optimal plant protein expression. It is applicable to pharmaceutical production of plant-derived useful chemicals from E. coli.ope

Switchable Gene Expression in Escherichia coli Using a Miniaturized Photobioreactor

We present a light-switchable gene expression system for both inducible and switchable control of gene expression at a single cell level in Escherichia coli using a previously constructed light-sensing system. The lambda cl repressor gene with an LVA degradation tag was expressed under the control of the ompC promoter on the chromosome. The green fluorescent protein (GFP) gene fused to a lambda repressor-repressible promoter was used as a reporter. This light-switchable system allows rapid and reversible induction or repression of expression of the target gene at any desired time. This system also ensures homogenous expression across the entire cell population. We also report the design of a miniaturized photobioreactor to be used in combination with the light-switchable gene expression system. The miniaturized photobioreactor helps to reduce unintended induction of the light receptor due to environmental disturbances and allows precise control over the duration of induction. This system would be a good tool for switchable, homogenous, strong, and highly regulatable expression of target genes over a wide range of induction times. Hence, it could be applied to study gene function, optimize metabolic pathways, and control biological systems both spatially and temporally.open0

Capacitor-Less Low-Power Neuron Circuit with Multi-Gate Feedback Field Effect Transistor

Recently, research on artificial neuron circuits imitating biological systems has been actively studied. The neuron circuit can implement an artificial neural network (ANN) capable of low-power parallel processing by configuring a biological neural network system in hardware. Conventional CMOS analog neuron circuits require many MOSFETs and membrane capacitors. Additionally, it has low energy efficiency in the first inverter stage connected to the capacitor. In this paper, we propose a low-power neuron circuit with a multi-gate feedback field effect transistor (FBFET) that can perform integration without a capacitor to solve the problem of an analog neuron circuit. The multi-gate FBFET has a low off-current due to its low operating voltage and excellent sub-threshold characteristics. We replace the n-channel MOSFET of the inverter with FBFET to suppress leakage current. FBFET devices and neuron circuits were analyzed using TACD and SPICE mixed-mode simulation. As a result, we found that the neuron circuit with multi-gate FBFET has a low subthreshold slope and can completely suppress energy consumption. We also verified the temporal and spatial integration of neuron circuits

Method for Measuring the Surface Velocity Field of a River Using Images Acquired by a Moving Drone

Hovering drones use ground control points to measure the surface flow velocity of rivers. This study aims to use only GPS data and images captured by a drone to extract the flowrate at a designated absolute position. Using GPS data, the moving directions of the drone and of the image were calculated, and each image point was converted into a physical UTM (Universal Transverse Mercator) coordinate system. After determining the range of observation by selecting the start and end frames, all images of the measurement cross section were divided into reference frames (measurement subsections), and the flowrate was calculated with spatiotemporal volume obtained by gathering images for 1 sec (30 frames) for all measurement subsections. The results were comparable with those obtained using the existing hovering drone image analysis method

Capacitor-Less Low-Power Neuron Circuit with Multi-Gate Feedback Field Effect Transistor

Recently, research on artificial neuron circuits imitating biological systems has been actively studied. The neuron circuit can implement an artificial neural network (ANN) capable of low-power parallel processing by configuring a biological neural network system in hardware. Conventional CMOS analog neuron circuits require many MOSFETs and membrane capacitors. Additionally, it has low energy efficiency in the first inverter stage connected to the capacitor. In this paper, we propose a low-power neuron circuit with a multi-gate feedback field effect transistor (FBFET) that can perform integration without a capacitor to solve the problem of an analog neuron circuit. The multi-gate FBFET has a low off-current due to its low operating voltage and excellent sub-threshold characteristics. We replace the n-channel MOSFET of the inverter with FBFET to suppress leakage current. FBFET devices and neuron circuits were analyzed using TACD and SPICE mixed-mode simulation. As a result, we found that the neuron circuit with multi-gate FBFET has a low subthreshold slope and can completely suppress energy consumption. We also verified the temporal and spatial integration of neuron circuits

A warm-up strategy with or without voluntary contraction on athletic performance, lower-leg temperature, and blood lactate concentration.

It is unclear whether temperature-related warm-up effects can be accomplished by passive warm-up (e.g., by external heat). Therefore, this study compared the effects of two different warm-up protocols with and without voluntary contraction on subsequent sprinting and jumping performance. Eighteen healthy male collegiate students (23.3 ± 2.4 years, 173.8 ± 7.2 cm, 70.5 ± 9.3 kg) randomly experienced 10 min of active (jogging on a treadmill; belt speed: 9.0 km/h at a 1% incline) and passive warm-up (lying down in the warm-up chamber; inner ambient temperature set at 35°C) protocols, followed by ten sets of intermittent exercises in two separate sessions. Athletic performance, lower-leg muscle temperature, and blood lactate concentration were statistically compared using analysis of variance with Tukey-Kramer post-hoc comparisons. Cohen's d effect sizes (ES) were also calculated. There was no warm-up protocol effect over time on 20 m sprint times (condition × time: F9,323 = 1.26, p = 0.25). Maximal vertical jump heights were different (condition × time: F9,323 = 2.0, p = 0.04) such that subjects who performed the active warm-up protocol jumped higher (51.4 cm) than those who did the passive warm-up (49.2 cm, p = 0.04). There was a warm-up protocol effect over time on lower-leg muscle temperature (condition × time: F12,425 = 13.99, p<0.0001) in that there was a 5.5% and 5.8% increase after active (32.8 to 34.6°C, ES = 2.91) and passive (32.9 to 34.9°C, ES = 3.28) warm-up protocols, respectively. Blood lactate concentration was different (condition × time: F2,85 = 3.61, p = 0.03) since the values at the post-warm-up measurements were different between warm-up conditions (active: 4.1 mmol/L; passive: 1.5 mmol/L, p = 0.004, ES = 1.69). Subsequent sprint and jump performance did not differ between the duration- and muscle temperature-matched active and passive warm-up protocols. Non-thermal effects from the warm-up activity may be minimal for sprinting and jumping performance in recreationally active males

Probability-based Data Reception in AoI-sensitive Wireless Networks

This paper considers a downlink cellular network in which a base station (BS) transmits multi-type data to a user. In this network, we analyze the weighted sum age of information (AoI) violation probability and develop a probability-based receiving data determination (PRD) policy that stochastically selects one of the data types. We then express an optimal receiving data probability and obtain the closed-form expression of that in the special case. Finally, we show that the proposed policy always outperforms the baseline schemes. © 2022 IEEE