Chenli Liu

Sequential Establishment of Stripe Patterns in an Expanding Cell Population

A synthetic circuit implementing density-controlled bacterial motility autonomously produces a tunable stripe pattern. Periodic stripe patterns are ubiquitous in living organisms, yet the underlying developmental processes are complex and difficult to disentangle. We describe a synthetic genetic circuit that couples cell density and motility. This system enabled programmed Escherichia coli cells to form periodic stripes of high and low cell densities sequentially and autonomously. Theoretical and experimental analyses reveal that the spatial structure arises from a recurrent aggregation process at the front of the continuously expanding cell population. The number of stripes formed could be tuned by modulating the basal expression of a single gene. The results establish motility control as a simple route to establishing recurrent structures without requiring an extrinsic pacemaker.

Salvianolic acid B inhibits hydrogen peroxide-induced endothelial cell apoptosis through regulating PI3K/Akt signaling.

Background Salvianolic acid B (Sal B) is one of the most bioactive components of Salvia miltiorrhiza, a traditional Chinese herbal medicine that has been commonly used for prevention and treatment of cerebrovascular disorders. However, the mechanism responsible for such protective effects remains largely unknown. It has been considered that cerebral endothelium apoptosis caused by reactive oxygen species including hydrogen peroxide (H2O2) is implicated in the pathogenesis of cerebrovascular disorders. Methodology and Principal Findings By examining the effect of Sal B on H2O2-induced apoptosis in rat cerebral microvascular endothelial cells (rCMECs), we found that Sal B pretreatment significantly attenuated H2O2-induced apoptosis in rCMECs. We next examined the signaling cascade(s) involved in Sal B-mediated anti-apoptotic effects. We showed that H2O2 induces rCMECs apoptosis mainly through the PI3K/ERK pathway, since a PI3K inhibitor (LY294002) blocked ERK activation caused by H2O2 and a specific inhibitor of MEK (U0126) protected cells from apoptosis. On the other hand, blockage of the PI3K/Akt pathway abrogated the protective effect conferred by Sal B and potentated H2O2-induced apoptosis, suggesting that Sal B prevents H2O2-induced apoptosis predominantly through the PI3K/Akt (upstream of ERK) pathway. Significance Our findings provide the first evidence that H2O2 induces rCMECs apoptosis via the PI3K/MEK/ERK pathway and that Sal B protects rCMECs against H2O2-induced apoptosis through the PI3K/Akt/Raf/MEK/ERK pathway.

Multiple alkane hydroxylase systems in a marine alkane degrader, Alcanivorax dieselolei B-5

Alcanivorax dieselolei strain B-5 is a marine bacterium that can utilize a broad range of n-alkanes (C(5) -C(36) ) as sole carbon source. However, the mechanisms responsible for this trait remain to be established. Here we report on the characterization of four alkane hydroxylases from A. dieselolei, including two homologues of AlkB (AlkB1 and AlkB2), a CYP153 homologue (P450), as well as an AlmA-like (AlmA) alkane hydroxylase. Heterologous expression of alkB1, alkB2, p450 and almA in Pseudomonas putida GPo12 (pGEc47ΔB) or P. fluorescens KOB2Δ1 verified their functions in alkane oxidation. Quantitative real-time RT-PCR analysis showed that these genes could be induced by alkanes ranging from C(8) to C(36) . Notably, the expression of the p450 and almA genes was only upregulated in the presence of medium-chain (C(8) -C(16) ) or long-chain (C(22) -C(36) ) n-alkanes, respectively; while alkB1 and alkB2 responded to both medium- and long-chain n-alkanes (C(12) -C(26) ). Moreover, branched alkanes (pristane and phytane) significantly elevated alkB1 and almA expression levels. Our findings demonstrate that the multiple alkane hydroxylase systems ensure the utilization of substrates of a broad chain length range.

Interrogating the Escherichia coli cell cycle by cell dimension perturbations

Significance How bacteria regulate cell division to achieve cell size homeostasis, with concomitant coordination of DNA replication, is a fundamental question. Currently, there exist several competing models for cell cycle regulation in Escherichia coli. We performed experiments where we systematically perturbed cell dimensions and found that average cell volume scales exponentially with the product of the growth rate and the time from initiation of DNA replication to the corresponding cell division. Our data support a model in which cells initiate replication on average at a constant volume per origin and divide a constant time thereafter. Bacteria tightly regulate and coordinate the various events in their cell cycles to duplicate themselves accurately and to control their cell sizes. Growth of Escherichia coli, in particular, follows a relation known as Schaechter’s growth law. This law says that the average cell volume scales exponentially with growth rate, with a scaling exponent equal to the time from initiation of a round of DNA replication to the cell division at which the corresponding sister chromosomes segregate. Here, we sought to test the robustness of the growth law to systematic perturbations in cell dimensions achieved by varying the expression levels of mreB and ftsZ. We found that decreasing the mreB level resulted in increased cell width, with little change in cell length, whereas decreasing the ftsZ level resulted in increased cell length. Furthermore, the time from replication termination to cell division increased with the perturbed dimension in both cases. Moreover, the growth law remained valid over a range of growth conditions and dimension perturbations. The growth law can be quantitatively interpreted as a consequence of a tight coupling of cell division to replication initiation. Thus, its robustness to perturbations in cell dimensions strongly supports models in which the timing of replication initiation governs that of cell division, and cell volume is the key phenomenological variable governing the timing of replication initiation. These conclusions are discussed in the context of our recently proposed “adder-per-origin” model, in which cells add a constant volume per origin between initiations and divide a constant time after initiation.

Alcanivorax hongdengensis sp. nov., an alkane-degrading bacterium isolated from surface seawater of the straits of Malacca and Singapore, producing a lipopeptide as its biosurfactant

A taxonomic study was carried out on strain A-11-3(T), which was isolated from an oil-enriched consortia from the surface seawater of Hong-Deng dock in the Straits of Malacca and Singapore. Cells were aerobic, Gram-negative, non-spore-forming irregular rods. The strain was catalase- and oxidase-negative. It grew on a restricted spectrum of organic compounds, including some organic acids and alkanes. 16S rRNA gene sequence comparisons showed that strain A-11-3(T) was most closely related to the type strains of Alcanivorax jadensis (96.8 % sequence similarity), Alcanivorax borkumensis (96.8 %), Alcanivorax dieselolei (94.8 %), Alcanivorax venustensis (94.2 %) and Alcanivorax balearicus (94.0 %). The predominant fatty acids were C(16 : 0) (31.2 %), C(18 : 1)omega7c (24.8 %), C(18 : 0) (9.6 %), C(12 : 0) (8.3 %), C(16 : 1)omega7c (8.3 %) and C(16 : 0) 3-OH (5.1 %). The G+C content of the genomic DNA was 54.7 mol%. Moreover, the strain produced lipopeptides as its surface-active compounds. According to physiological and biochemical tests, DNA-DNA hybridization results and sequence comparisons of the 16S-23S internal transcribed spacer, the gyrB gene and the alkane hydroxylase gene alkB1, strain A-11-3(T) was affiliated with the genus Alcanivorax but could be readily distinguished from recognized Alcanivorax species. Therefore strain A-11-3(T) represents a novel species of the genus Alcanivorax for which the name Alcanivorax hongdengensis sp. nov. is proposed. The type strain is A-11-3(T) (=CGMCC 1.7084(T)=LMG 24624(T)=MCCC 1A01496(T)).

Stripe formation in bacterial systems with density-suppressed motility

Engineered bacteria in which motility is reduced by local cell density generate periodic stripes of high and low density when spotted on agar plates. We study theoretically the origin and mechanism of this process in a kinetic model that includes growth and density-suppressed motility of the cells. The spreading of a region of immotile cells into an initially cell-free region is analyzed. From the calculated front profile we provide an analytic ansatz to determine the phase boundary between the stripe and the no-stripe phases. The influence of various parameters on the phase boundary is discussed.

Construction of precise support vector machine based models for predicting promoter strength

BackgroundThe prediction of the prokaryotic promoter strength based on its sequence is of great importance not only in the fundamental research of life sciences but also in the applied aspect of synthetic biology. Much advance has been made to build quantitative models for strength prediction, especially the introduction of machine learning methods such as artificial neural network (ANN) has significantly improve the prediction accuracy. As one of the most important machine learning methods, support vector machine (SVM) is more powerful to learn knowledge from small sample dataset and thus supposed to work in this problem.MethodsTo confirm this, we constructed SVM based models to quantitatively predict the promoter strength. A library of 100 promoter sequences and strength values was randomly divided into two datasets, including a training set (⩾10 sequences) for model training and a test set (⩾10 sequences) for model test.ResultsThe results indicate that the prediction performance increases with an increase of the size of training set, and the best performance was achieved at the size of 90 sequences. After optimization of the model parameters, a high-performance model was finally trained, with a high squared correlation coefficient for fitting the training set (R2 > 0.99) and the test set (R2 > 0.98), both of which are better than that of ANN obtained by our previous work.ConclusionsOur results demonstrate the SVM-based models can be employed for the quantitative prediction of promoter strength.

Coupling metagenomics with cultivation to select host-specific probiotic micro-organisms for subtropical aquaculture

To demonstrate a nonempirical workflow to select host‐specific probiotics for aquaculture industry.

Synthetic biology: a new approach to study biological pattern formation

The principles and molecular mechanisms underlying biological pattern formation are difficult to elucidate in most cases due to the overwhelming physiologic complexity associated with the natural context. The understanding of a particular mechanism, not to speak of underlying universal principles, is difficult due to the diversity and uncertainty of the biological systems. Although current genetic and biochemical approaches have greatly advanced our understanding of pattern formation, the progress mainly relies on experimental phenotypes obtained from time-consuming studies of gain or loss of function mutants. It is prevailingly considered that synthetic biology will come to the application age, but more importantly synthetic biology can be used to understand the life. Using periodic stripe pattern formation as a paradigm, we discuss how to apply synthetic biology in understanding biological pattern formation and hereafter foster the applications like tissue engineering.

Applications of microfluidics in quantitative biology

Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high‐throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel‐based microfluidics and droplet‐based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future.