Design of growth‐dependent biosensors based on destabilized GFP for the detection of physiological behavior of Escherichia coli in heterogeneous bioreactors

In this work, we present the design and characterization of Green Fluorescent Protein (GFP)‐based reporter systems designed to describe cellular activity in “complex,” heterogeneous bioreactors. The reporter systems consist of Escherichia coli strains carrying growth dependent promoters fused to genes expressing stable and unstable variants of GFP, respectively. The response of Escherichia coli cells to transient exposure to glucose was studied in a two‐compartment scale down bioreactor (SDR) consisting of a well‐stirred tank reactor (STR) connected to a plug‐flow reactor (PFR). Such a SDR system is employed to mimic the situation of high glucose concentration and oxygen limitation that often encountered in large‐scale, fed‐batch bioreactors and the response of E. coli was simulated by continuously pumping microbial cells from STR to the PFR. We found that repeated addition of concentrated glucose pulses with varied frequency at the entrance of the PFR had consequences on strain physiological behavior. The GFP expressions were significantly marked after 10 h of cultivation in STR (control reactor) and SDR, whereas, growth rates were rather similar. Additional experiments in chemostat with programmed glucose perturbation suggested that the activities of the promoters were linked with the substrate limitation signal. Taken together with immunoblot analysis, we suppose protein leakage is responsible for the overexpression of fis and the related promoters, such as rrnB in this case study, but additional works are required in order to confirm this relationship. This investigation is useful for a better understanding of the fast dynamic phenomena occurring in heterogeneous large‐scale bioreactors. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 553–563, 2013     

Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA–RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.     

Biological Signal Processing with a Genetic Toggle Switch

Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems.     

A Novel Utility Function for Energy-Efficient Power Control Game in Cognitive Radio Networks

Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence.     

Predicting protein subcellular location using digital signal processing

The biological functions of a protein are closely related to its attributes in a cell. With the rapid accumulation of newly found protein sequence data in databanks, it is highly desirable to develop an automated method for predicting the subcellular location of proteins. The establishment of such a predictor will expedite the functional determination of newly found proteins and the process of prioritizing genes and proteins identified by genomic efforts as potential molecular targets for drug design. The traditional algorithms for predicting these attributes were based solely on amino acid composition in which no sequence order effect was taken into account. To improve the prediction quality, it is necessary to incorporate such an effect. However, the number of possible patterns in protein sequences is extremely large, posing a formidable difficulty for realizing this goal. To deal with such difficulty, a well-developed tool in digital signal processing named digital Fourier transform (DFT) [1] was introduced. After being translated to a digital signal according to the hydrophobicity of each amino acid, a protein was analyzed by DFT within the frequency domain. A set of frequency spectrum parameters, thus obtained, were regarded as the factors to represent the sequence order effect. A significant improvement in prediction quality was observed by incorporating the frequency spectrum parameters with the conventional amino acid composition. One of the crucial merits of this approach is that many existing tools in mathematics and engineering can be easily applied in the predicting process. It is anticipated that digital signal processing may serve as a useful vehicle for many other protein science areas.     

Enhanced-contrast two-photon optogenetic pH sensing and pH-resolved brain imaging

We present experiments on cell cultures and brain slices that demonstrate two-photon optogenetic pH sensing and pH-resolved brain imaging using a laser driver whose spectrum is carefully tailored to provide the maximum contrast of a ratiometric two-photon fluorescence readout from a high-brightness genetically encoded yellow-fluorescent-protein-based sensor, SypHer3s. Two spectrally isolated components of this laser field are set to induce two-photon-excited fluorescence (2PEF) by driving SypHer3s through one of two excitation pathways—via either the protonated or deprotonated states of its chromophore. With the spectrum of the laser field accurately adjusted for a maximum contrast of these two 2PEF signals, the ratio of their intensities is shown to provide a remarkably broad dynamic range for pH measurements, enabling high-contrast optogenetic deep-brain pH sensing and pH-resolved 2PEF imaging within a vast class of biological systems, ranging from cell cultures to the living brain.     

Segmental 2:4 digit ratio. Unilateral, bilateral and hand-type differences in men

Most studies of the 2:4 digit ratio (DR) of the human hand have analyzed its possibilities for use as an indicator of the functional, psychological, and, with rare exception, morphological features of the body. Each of the functional flexor segments (each phalanx) contributes to the common variability of the total digital length. The aim of this study was to determine patterns in the relationships between each segmental digit ratio (SDR) and the overall 2:4 DR. We studied the variability of the SDRs in comparison with the general 2:4 DR of 202 young males aged 16–21 years. The length of the functional segments of the digits was measured between the flexor skin furrows on the palmar surface. The change in the SDR means that values can be ranked as follows: proximal SDR (SDR-P) > DR > distal SDR (SDR-D) > medial SDR (SDR-M). Bilateral differences are inherent in the segmental SDR-P. Most quantitative regularities inherent in the total 2:4 DR are also intrinsic to the 2:4 DR of the distal segment of the digit; in particular, this phenomenon is displayed in hands of the ulnar (male) type. Overall, the values of the distal rather than the other functional flexor segments of the second and fourth digits are similar in magnitude to the general 2:4 DR. At the same time, the greatest correlation and hence, the largest contribution to the total variability in the general DR is from the variability of the SDR-P values. Our data demonstrate the importance of various digit segment sizes in determining their overall length and the derivative ratios.     

How bacteria talk to each other: regulation of gene expression by quorum sensing

Quorum sensing, or the control of gene expression in response to cell density, is used by both gram-negative and gram-positive bacteria to regulate a variety of physiological functions. In all cases, quorum sensing involves the production and detection of extracellular signalling molecules called autoinducers. While universal signalling themes exist, variations in the design of the extracellular signals, the signal detection apparatuses, and the biochemical mechanisms of signal relay have allowed quorum sensing systems to be exquisitely adapted for their varied uses. Recent studies show that quorum sensing modulates both intra- and inter-species cell-cell communication, and it plays a major role in enabling bacteria to architect complex community structures.     

泥沙输移比及其尺度依存研究进展

泥沙输移比是反映流域侵蚀产沙及输移能力的指标,对评价水土保持减沙效益有重要意义。基于对国内外泥沙输移比研究的系统梳理,1阐述了泥沙输移比的内涵,并对泥沙输移比基本定义中不同学科常用的表征变量作了清晰的界定,流域产沙量所涵尺度较流域输沙量小,且泥沙输移比与归槽率无论在内涵及定量描述上均不可等同;2归纳提出泥沙输移比现存的测算方法,包括4种形式的类比计算法和3种形式的建模计算法,并分别评述了其优缺点;3揭示了泥沙输移比的影响因素随时空尺度变化表现出分异性;4基于对泥沙输移比内涵与测算中的"尺度问题"以及泥沙输移比是否存在尺度效应等问题剖析,明确了泥沙输移比客观存在着尺度依存性及其尺度域。     

Analysis of nonstationarity in renal autoregulation mechanisms using time-varying transfer and coherence functions

The extent to which renal blood flow dynamics vary in time and whether such variation contributes substantively to dynamic complexity have emerged as important questions. Data from Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR) were analyzed by time-varying transfer functions (TVTF) and time-varying coherence functions (TVCF). Both TVTF and TVCF allow quantification of nonstationarity in the frequency ranges associated with the autoregulatory mechanisms. TVTF analysis shows that autoregulatory gain in SDR and SHR varies in time and that SHR exhibit significantly more nonstationarity than SDR. TVTF gain in the frequency range associated with the myogenic mechanism was significantly higher in SDR than in SHR, but no statistical difference was found with tubuloglomerular (TGF) gain. Furthermore, TVCF analysis revealed that the coherence in both strains is significantly nonstationary and that low-frequency coherence was negatively correlated with autoregulatory gain. TVCF in the frequency range from 0.1 to 0.3 Hz was significantly higher in SDR (7 out of 7, >0.5) than in SHR (5 out of 6, <0.5), and consistent for all time points. For TGF frequency range (0.03-0.05 Hz), coherence exhibited substantial nonstationarity in both strains. Five of six SHR had mean coherence (<0.5), while four of seven SDR exhibited coherence (<0.5). Together, these results demonstrate substantial nonstationarity in autoregulatory dynamics in both SHR and SDR. Furthermore, they indicate that the nonstationarity accounts for most of the dynamic complexity in SDR, but that it accounts for only a part of the dynamic complexity in SHR.     

Frequency equalized compounding for effective speckle reduction in medical ultrasound imaging

Frequency compounding (FC) is commonly used to reduce the speckle variance in order to enhance contrast resolution by averaging two or more uncorrelated sub-band images. However, due to the frequency dependent attenuation, the contrast resolution cannot be enhanced to the theoretical limit when imaging deep-lying tissue. In this paper, we propose the frequency equalized compounding (FEC) method to achieve contrast enhancement in the area of imaging as a whole. In this proposed method, a sub-band signal is divided into several zones along the imaging depth (or time), and the center frequencies and weighting factors for each zone are estimated; the estimated values are used in dynamic quadrature demodulation (DQDM) and image compounding respectively. The performance of the proposed method was evaluated through simulations and experiments. During the evaluation, the contrast resolution was quantified by speckle's signal-to-noise ratio (SSNR) in speckle regions and contrast-to-noise ratio (CNR) in hyper- and hypoechoic regions. Theoretical values of the SSNR and the CNR by the FC were computed by multiplying the SSNR and CNR values measured from the original image by $\sqrt{N}$, where N is the number of sub-bands used in the compounding. From in vitro phantom experiments, it was learned that the SSNR and CNR values from the proposed method were similar to the theoretical values; the maximum and minimum errors from the theoretical value were 9% and 1% while those of the conventional FC (CFC) method were 25% and 7%. Similar results were obtained from the in vivo experiments with RF data acquired from the liver and the kidney. In addition, signal-to-noise ratio (SNR) improvement was measured. The SNR also improved due to the DQDM; maximum improvements for the in vitro and the in vivo experiments were 2.3 dB and 4.8 dB higher the results from the CFC method. These results demonstrate that the proposed FEC method can improve the contrast resolution up to a theoretically achievable value and may be useful in imaging technically difficult patients.     

Hilbert-Huang transform for analysis of heart rate variability in cardiac health

This paper introduces a modified technique based on Hilbert-Huang transform (HHT) to improve the spectrum estimates of heart rate variability (HRV). In order to make the beat-to-beat (RR) interval be a function of time and produce an evenly sampled time series, we first adopt a preprocessing method to interpolate and resample the original RR interval. Then, the HHT, which is based on the empirical mode decomposition (EMD) approach to decompose the HRV signal into several monocomponent signals that become analytic signals by means of Hilbert transform, is proposed to extract the features of preprocessed time series and to characterize the dynamic behaviors of parasympathetic and sympathetic nervous system of heart. At last, the frequency behaviors of the Hilbert spectrum and Hilbert marginal spectrum (HMS) are studied to estimate the spectral traits of HRV signals. In this paper, two kinds of experiment data are used to compare our method with the conventional power spectral density (PSD) estimation. The analysis results of the simulated HRV series show that interpolation and resampling are basic requirements for HRV data processing, and HMS is superior to PSD estimation. On the other hand, in order to further prove the superiority of our approach, real HRV signals are collected from seven young health subjects under the condition that autonomic nervous system (ANS) is blocked by certain acute selective blocking drugs: atropine and metoprolol. The high-frequency power/total power ratio and low-frequency power/high-frequency power ratio indicate that compared with the Fourier spectrum based on principal dynamic mode, our method is more sensitive and effective to identify the low-frequency and high-frequency bands of HRV.     

Biosonar-inspired technology: goals, challenges and insights

Bioinspired engineering based on biosonar systems in nature is reviewed and discussed in terms of the merits of different approaches and their results: biosonar systems are attractive technological paragons because of their capabilities, built-in task-specific knowledge, intelligent system integration and diversity. Insights from the diverse set of sensing tasks solved by bats are relevant to a wide range of application areas such as sonar, biomedical ultrasound, non-destructive testing, sensors for autonomous systems and wireless communication. Challenges in the design of bioinspired sonar systems are posed by transducer performance, actuation for sensor mobility, design, actuation and integration of beamforming baffle shapes, echo encoding for signal processing, estimation algorithms and their implementations, as well as system integration and feedback control. The discussed examples of experimental systems have capabilities that include localization and tracking using binaural and multiple-band hearing as well as self-generated dynamic cues, classification of small deterministic and large random targets, beamforming with bioinspired baffle shapes, neuromorphic spike processing, artifact rejection in sonar maps and passing range estimation. In future research, bioinspired engineering could capitalize on some of its strengths to serve as a model system for basic automation methodologies for the bioinspired engineering process.     

An implantable telemetry device to measure intra-articular tibial forces

Tibial forces are important because they determine polyethylene wear, stress distribution in the implant, and stress transfer to underlying bone. Theoretic estimates of tibiofemoral forces have varied between three and six times the body weight depending on the mathematical models used and the type of activity analyzed. An implantable telemetry system was therefore developed to directly measure tibiofemoral compressive forces. This system was tested in a cadaver knee in a dynamic knee rig. A total knee tibial arthroplasty prosthesis was instrumented with four force transducers located at the four corners of the tibial tray. These transducers measured the total compressive forces on the tibial tray and the location of the center of pressure. A microprocessor performed analog-to-digital signal conversion and performed pulse code modulation of a surface acoustic wave radio frequency oscillator. This signal was then transmitted through a single pin hermetic feed-through tantalum wire antenna located at the tip of the stem. The radio frequency signal was received by an external antenna connected to a receiver and to a computer for data acquisition. The prosthesis was powered by external coil induction. The tibial transducer accurately measured both the magnitude and the location of precisely applied external loads. Successful transmission of the radio frequency signal up to a range of 3m was achieved through cadaveric bone, bone cement, and soft tissue. Reasonable accuracy was obtained in measuring loads applied through a polyethylene insert. The implant was also able to detect unicondylar loading with liftoff.     

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.     

基于小波变换的医学图像编码方法

高分辨率的医学图像具有很大的信息量,影响了整个数字化的远程医疗系统的实时性,因此必须在保证不丢失关键诊断信息的前提下,对医学图像进行必要的压缩。本文提出了在给定小波基下,基于二维小波分解和重构的快速压缩方法。该方法使用了向量量化技术并采用LBG算法设计码本。实验结果证明,采用该方法可获得较高的压缩比和符合诊断要求的压缩图像。     

A stability analysis of the power-law steady state of marine size spectra

This paper investigates the stability of the power-law steady state often observed in marine ecosystems. Three dynamical systems are considered, describing the abundance of organisms as a function of body mass and time: a “jump-growth” equation, a first order approximation which is the widely used McKendrick–von Foerster equation, and a second order approximation which is the McKendrick–von Foerster equation with a diffusion term. All of these yield a power-law steady state. We derive, for the first time, the eigenvalue spectrum for the linearised evolution operator, under certain constraints on the parameters. This provides new knowledge of the stability properties of the power-law steady state. It is shown analytically that the steady state of the McKendrick–von Foerster equation without the diffusion term is always unstable. Furthermore, numerical plots show that eigenvalue spectra of the McKendrick–von Foerster equation with diffusion give a good approximation to those of the jump-growth equation. The steady state is more likely to be stable with a low preferred predator:prey mass ratio, a large diet breadth and a high feeding efficiency. The effects of demographic stochasticity are also investigated and it is concluded that these are likely to be small in real systems.     

Comparison of audio recording system performance for detecting and monitoring songbirds

ABSTRACT Acoustic recording systems are being used more frequently to estimate habitat occupancy or relative abundance, and to monitor population trends over time. A potential concern with digital recording systems is that changes in technology could affect detectability of birds and cause bias in trend estimates based on counts of birds detected. We evaluated several currently available commercial recording systems ranging from low‐cost multipurpose digital recorders to custom‐designed wildlife recorders (US$250–$7000 price range) to examine possible differences among systems in species detection. We made recordings during Breeding Bird Surveys (BBS) counts using several units concurrently, and asked several expert birders to listen to the recordings in a factorial design. We found that birders detected, on average, 10% fewer species on some units compared to others, though there was high variance. Analysis of a subset of recordings, using spectrograms and repeated listening, suggested that ～90% of species on each BBS stop could be clearly detected on all units. The remaining species could be identified on at least one unit, but were hard or impossible to detect on others. We found that the recording unit with the lowest empirical signal‐to‐noise‐ratio (SNR) had the lowest number of birds detected on the BBS recordings, and that frequency‐specific SNR differed among units. Missed detections were likely related to variation in internal noise and frequency‐dependent sensitivity of the units, and were an issue for all systems regardless of price. We caution that researchers using recorders need to consider variation among recording systems in their study design, particularly for long‐term monitoring programs.     

Collection mode surface plasmon fibre sensors: a new biosensing platform

Sensors based on surface plasmon resonance (SPR) allow rapid, label-free, highly sensitive detection, and indeed this phenomenon underpins the only label-free optical biosensing technology that is available commercially. In these sensors, the existence of surface plasmons is inferred indirectly from absorption features that correspond to the coupling of light into a thin metallic film. Although SPR is not intrinsically a radiative process, when the metallic coating which support the plasmonic wave exhibits a significant surface roughness, the surface plasmon can itself couple to the local photon states, and emit light. Here we show that using silver coated optical fibres, this novel SPR transducing mechanism offers significant advantages compare to traditional reflectance based measurements such as lower dependency on the metallic thickness and higher signal to noise ratio. Furthermore, we show that more complex sensor architectures with multiple sensing regions scattered along a single optical fibre enable multiplexed detection and dynamic self referencing of the sensing signal. Moreover, this alternative approach allows to combine two different sensing technologies, SPR and fluorescence sensing within the same device, which has never been demonstrated previously. As a preliminary proof of concept of potential application, this approach has been used to demonstrate the detection of the seasonal influenza A virus.