Engineering microbes for tolerance to next-generation biofuels

A major challenge when using microorganisms to produce bulk chemicals such as biofuels is that the production targets are often toxic to cells. Many biofuels are known to reduce cell viability through damage to the cell membrane and interference with essential physiological processes. Therefore, cells must trade off biofuel production and survival, reducing potential yields. Recently, there have been several efforts towards engineering strains for biofuel tolerance. Promising methods include engineering biofuel export systems, heat shock proteins, membrane modifications, more general stress responses, and approaches that integrate multiple tolerance strategies. In addition, in situ recovery methods and media supplements can help to ease the burden of end-product toxicity and may be used in combination with genetic approaches. Recent advances in systems and synthetic biology provide a framework for tolerance engineering. This review highlights recent targeted approaches towards improving microbial tolerance to next-generation biofuels with a particular emphasis on strategies that will improve production

A Multi-Model Approach to Identification of Biosynthetic Pathways

We present an identification framework for biochemical systems that allows multiple candidate models to be compared. This framework is designed to select a model that fits the data while maintaining model simplicity. The model identification task is divided into a parameter estimation stage and a model comparison stage. Model selection is based on calculating Akaike's information criterion, which is a systematic method for determining the model that best represents a set of experimental data. Two case studies are presented: a simulated transcriptional control circuit and a system of oscillators that has been built and characterized in vitro. In both examples the multi-model framework is able to discriminate between model candidates to select the one that best describes the data

Regulatory activity revealed by dynamic correlations in gene expression noise

Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or 'noise', in gene expression propagate through active, but not inactive, regulatory links^(1,2). Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, 'extrinsic', noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits

Modeling suggests that gene circuit architecture controls phenotypic variability in a bacterial persistence network

Abstract Background: Bacterial persistence is a non-inherited bet-hedging mechanism where a subpopulation of cells enters a dormant state, allowing those cells to survive environmental stress such as treatment with antibiotics. Persister cells are not mutants; they are formed by natural stochastic variation in gene expression. Understanding how regulatory architecture influences the level of phenotypic variability can help us explain how the frequency of persistence events can be tuned. Results: We present a model of the regulatory network controlling the HipBA toxin-antitoxin system from Escherichia coli. Using a biologically realistic model we first determine that the persistence phenotype is not the result of bistability within the network. Next, we develop a stochastic model and show that cells can enter persistence due to random fluctuations in transcription, translation, degradation, and complex formation. We then examine alternative gene circuit architectures for controlling hipBA expression and show that networks with more noise (more persisters) and less noise (fewer persisters) are straightforward to achieve. Thus, we propose that the gene circuit architecture can be used to tune the frequency of persistence, a trait that can be selected for by evolution. Conclusions: We develop deterministic and stochastic models describing how the regulation of toxin and antitoxin expression influences phenotypic variation within a population. Persistence events are the result of stochastic fluctuations in toxin levels that cross a threshold, and their frequency is controlled by the regulatory topology governing gene expression

Ecological insights into abyssal bentho-pelagic fish at 4000 m depth using a multi-beam echosounder on a remotely operated vehicle

Ecological and behavioral data on mobile, low density, benthopelagic animals is difficult to collect in the abyssal environment. However, these species occupy an important position in the abyssal food chain. At-depth ROV-mounted echosounder studies provide a powerful tool to gather in-situ information on abyssal benthopelagic assemblages and discern their distribution, behavior and habitat associations. This study presents a new perspective on mobile benthopelagic assemblages at the long-term study site, Station M (∼4000 m), using a Seabat T20-S MBES mounted on the ROV Doc Ricketts. The targets (∼45 m off the seafloor) are believed to be the abyssal grenadier of the species Coryphaenoides armatus or C. yaquinae, species known to dominate the mobile benthopelagic fauna at Station M. The swimming behavior of the targets indicated little evidence of avoidance or attraction to the slowly moving ROV and demonstrates the effectiveness of this platform to collect data on benthopelagic fish. The information on targets in close (<1 m) association with the seafloor from the MBES corresponded well to target densities recorded by the video transects. However, in addition the MBES resolved the distribution of targets up to 45 m above the seafloor. Target density had a small peak close to the seafloor (<1 m) but increased in density with height above the seafloor, exceeding the maximum near-bottom density by ∼50 times. ROV-mounted MBES surveys can effectively provide data on the distribution and behavior of benthopelagic fish and further understanding of the pelagic-benthic links in the abyssal deep-sea.acceptedVersio

Vision as a compensatory mechanism for disturbance rejection in upwind flight

Recent experimental results demonstrate that flies possess a robust tendency to orient towards the frontally-centered focus of the visual motion field that typically occurs during upwind flight. We present a closed loop flight model, with a control algorithm based on feedback of the location of the visual focus of contraction, which is affected by changes in wind direction. The feasibility of visually guided upwind orientation is demonstrated with a model derived from current understanding of the biomechanics and sensorimotor computation of insects. The matched filter approach used to model the visual system computations compares extremely well with open-loop experimental data

A synthetic three-color scaffold for monitoring genetic regulation and noise

Background: Current methods for analyzing the dynamics of natural regulatory networks, and quantifying synthetic circuit function, are limited by the lack of well-characterized genetic measurement tools. Fluorescent reporters have been used to measure dynamic gene expression, but recent attempts to monitor multiple genes simultaneously in single cells have not focused on independent, isolated measurements. Multiple reporters can be used to observe interactions between natural genes, or to facilitate the ‘debugging’ of biologically engineered genetic networks. Using three distinguishable reporter genes in a single cell can reveal information not obtainable from only one or two reporters. One application of multiple reporters is the use of genetic noise to reveal regulatory connections between genes. Experiments in both natural and synthetic systems would benefit from a well-characterized platform for expressing multiple reporter genes and synthetic network components. Results: We describe such a plasmid-based platform for the design and optimization of synthetic gene networks, and for analysis of endogenous gene networks. This network scaffold consists of three distinguishable fluorescent reporter genes controlled by inducible promoters, with conveniently placed restriction sites to make modifications straightforward. We quantitatively characterize the scaffold in Escherichia coli with single-cell fluorescence imaging and time-lapse microscopy. The three spectrally distinct reporters allow independent monitoring of genetic regulation and analysis of genetic noise. As a novel application of this tool we show that the presence of genetic noise can reveal transcriptional co-regulation due to a hidden factor, and can distinguish constitutive from regulated gene expression. Conclusion: We have constructed a general chassis where three promoters from natural genes or components of synthetic networks can be easily inserted and independently monitored on a single construct using optimized fluorescent protein reporters. We have quantitatively characterized the baseline behavior of the chassis so that it can be used to measure dynamic gene regulation and noise. Overall, the system will be useful both for analyzing natural genetic networks and assembling synthetic ones

Vision as a compensatory mechanism for disturbance rejection in upwind flight

Recent experimental results demonstrate that flies possess a robust tendency to orient towards the frontally-centered focus of the visual motion field that typically occurs during upwind flight. We present a closed loop flight model, with a control algorithm based on feedback of the location of the visual focus of contraction, which is affected by changes in wind direction. The feasibility of visually guided upwind orientation is demonstrated with a model derived from current understanding of the biomechanics and sensorimotor computation of insects. The matched filter approach used to model the visual system computations compares extremely well with open-loop experimental data