Augmenting the Calvin-Benson-Bassham cycle by a synthetic malyl-CoA-glycerate carbon fixation pathway.

The Calvin-Benson-Bassham (CBB) cycle is presumably evolved for optimal synthesis of C3 sugars, but not for the production of C2 metabolite acetyl-CoA. The carbon loss in producing acetyl-CoA from decarboxylation of C3 sugar limits the maximum carbon yield of photosynthesis. Here we design a synthetic malyl-CoA-glycerate (MCG) pathway to augment the CBB cycle for efficient acetyl-CoA synthesis. This pathway converts a C3 metabolite to two acetyl-CoA by fixation of one additional CO2 equivalent, or assimilates glyoxylate, a photorespiration intermediate, to produce acetyl-CoA without net carbon loss. We first functionally demonstrate the design of the MCG pathway in vitro and in Escherichia coli. We then implement the pathway in a photosynthetic organism Synechococcus elongates PCC7942, and show that it increases the intracellular acetyl-CoA pool and enhances bicarbonate assimilation by roughly 2-fold. This work provides a strategy to improve carbon fixation efficiency in photosynthetic organisms

Fish Swimming in a Kármán Vortex Street:Kinematics, Sensory Biology and Energetics

Fishes often live in environments characterized by complex flows. To study the mechanisms of how fishes interact with unsteady flows, the periodic shedding of vortices behind cylinders has been employed to great effect. In particular, fishes that hold station in a vortex street (i.e., K?rm?n gaiting) show swimming kinematics that are distinct from their patterns of motion during freestream swimming in uniform flows, although both behaviors can be modeled as an undulatory body wave. K?rm?n gait kinematics are largely preserved across flow velocities. Larger fish have a shorter body wavelength and slower body wave speed than smaller fish, in contrast to freestream swimming where body wavelength and wave speed increases with size. The opportunity for K?rm?n gaiting only occurs under specific conditions of flow velocity and depends on the length of the fish; this is reflected in the highest probability of K?rm?n gaiting at intermediate flow velocities. Fish typically K?rm?n gait in a region of the cylinder wake where the velocity deficit is about 40% of the nominal flow. The lateral line plays a role in tuning the kinematics of the K?rm?n gait, since blocking it leads to aberrant kinematics. Vision allows fish to maintain a consistent position relative to the cylinder. In the dark, fish do not show the same preference to hold station behind a cylinder though K?rm?n gait kinematics are the same. When oxygen consumption level is measured, it reveals that K?rm?n gaiting represents about half of the cost of swimming in the freestreamauthorsversionPeer reviewe

An integrated network approach identifies the isobutanol response network of Escherichia coli

Isobutanol has emerged as a potential biofuel due to recent metabolic engineering efforts. Here we used gene expression and transcription network connectivity data, genetic knockouts, and network component analysis (NCA) to map the initial isobutanol response network of Escherichia coli under aerobic conditions. NCA revealed profound perturbations to respiration. Further investigation showed ArcA as an important mediator of this response. Quinone/quinol malfunction was postulated to activate ArcA, Fur, and PhoB in this study. In support of this hypothesis, quinone-linked ArcA and Fur target expressions were significantly less perturbed by isobutanol under fermentative growth whereas quinol-linked PhoB target expressions remained activated, and isobutanol impeded growth on glycerol, which requires quinones, more than on glucose. In addition, ethanol, n-butanol, and isobutanol response networks were compared. n-Butanol and isobutanol responses were qualitatively similar, whereas ethanol had notable induction differences of pspABCDE and ndh, whose gene products manage proton motive force. The network described here could aid design and comprehension of alcohol tolerance, whereas the approach provides a general framework to characterize complex phenomena at the systems level

Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway.

The ability to biosynthetically produce chemicals beyond what is commonly found in Nature requires the discovery of novel enzyme function. Here we utilize two approaches to discover enzymes that enable specific production of longer-chain (C5-C8) alcohols from sugar. The first approach combines bioinformatics and molecular modelling to mine sequence databases, resulting in a diverse panel of enzymes capable of catalysing the targeted reaction. The median catalytic efficiency of the computationally selected enzymes is 75-fold greater than a panel of naively selected homologues. This integrative genomic mining approach establishes a unique avenue for enzyme function discovery in the rapidly expanding sequence databases. The second approach uses computational enzyme design to reprogramme specificity. Both approaches result in enzymes with >100-fold increase in specificity for the targeted reaction. When enzymes from either approach are integrated in vivo, longer-chain alcohol production increases over 10-fold and represents >95% of the total alcohol products

Trimming of mammalian transcriptional networks using network component analysis

<p>Abstract</p> <p>Background</p> <p>Network Component Analysis (NCA) has been used to deduce the activities of transcription factors (TFs) from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies.</p> <p>Results</p> <p>We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number) and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict <it>Eno1 </it>as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network.</p> <p>Conclusions</p> <p>The advantage of our new algorithm, relative to the original NCA, is that our algorithm can identify the important TF-gene interactions. Identifying the important TF-gene interactions is crucial for understanding the roles of pleiotropic global regulators, such as p53. Also, our algorithm has been developed to overcome NCA's inability to analyze large networks where multiple TFs regulate a single gene. Thus, our algorithm extends the applicability of NCA to the realm of mammalian regulatory network analysis.</p

Single-cell zeroth-order protein degradation enhances the robustness of synthetic oscillator

In Escherichia coli, protein degradation in synthetic circuits is commonly achieved by the ssrA-tagged degradation system. In this work, we show that the degradation kinetics for the green fluorescent protein fused with the native ssrA tag in each cell exhibits the zeroth-order limit of the Michaelis–Menten kinetics, rather than the commonly assumed first-order. When measured in a population, the wide distribution of protein levels in the cells distorts the true kinetics and results in a first-order protein degradation kinetics as a population average. Using the synthetic gene-metabolic oscillator constructed previously, we demonstrated theoretically that the zeroth-order kinetics significantly enlarges the parameter space for oscillation and thus enhances the robustness of the design under parametric uncertainty

Low-density series expansions for directed percolation I: A new efficient algorithm with applications to the square lattice

A new algorithm for the derivation of low-density series for percolation on directed lattices is introduced and applied to the square lattice bond and site problems. Numerical evidence shows that the computational complexity grows exponentially, but with a growth factor \lambda < \protect{\sqrt[8]{2}}, which is much smaller than the growth factor \lambda = \protect{\sqrt[4]{2}} of the previous best algorithm. For bond (site) percolation on the directed square lattice the series has been extended to order 171 (158). Analysis of the series yields sharper estimates of the critical points and exponents.Comment: 20 pages, 8 figures (3 of them > 1Mb

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SUMMARY Measuring the rate of consumption of oxygen (M O2 ) during swimming reveals the energetics of fish locomotion. We show that rainbow trout have substantially different oxygen requirements for station holding depending on which hydrodynamic microhabitats they choose to occupy around a cylinder. We used intermittent flow respirometry to show that an energetics hierarchy, whereby certain behaviors are more energetically costly than others, exists both across behaviors at a fixed flow velocity and across speeds for a single behavior. At 3.5Ls -1 (L is total body length) entraining has the lowest M O2 , followed by Kármán gaiting, bow waking and then free stream swimming. As flow speed increases the costs associated with a particular behavior around the cylinder changes in unexpected ways compared with free stream swimming. At times, M O2 actually decreases as flow velocity increases. Entraining demands the least oxygen at 1.8Ls -1 and 3.5Ls , whereas bow waking requires the least oxygen at 5.0Ls . Consequently, a behavior at one speed may have a similar cost to another behavior at another speed. We directly confirm that fish Kármán gaiting in a vortex street gain an energetic advantage from vortices beyond the benefit of swimming in a velocity deficit. We propose that the ability to exploit velocity gradients as well as stabilization costs shape the complex patterns of oxygen consumption for behaviors around cylinders. Measuring M O2 for station holding in turbulent flows advances our attempts to develop ecologically relevant approaches to evaluating fish swimming performance