Invariant Distribution of Promoter Activities in Escherichia coli

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources

Mycobacterium tuberculosis Responds to Chloride and pH as Synergistic Cues to the Immune Status of its Host Cell

PubMed ID: 23592993This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Stage-specific fluorescence intensity of GFP and mCherry during sporulation In Bacillus Subtilis

<p>Abstract</p> <p>Background</p> <p>Fluorescent proteins are powerful molecular biology tools that have been used to study the subcellular dynamics of proteins within live cells for well over a decade. Two fluorescent proteins commonly used to enable dual protein labelling are GFP (green) and mCherry (red). Sporulation in the Gram positive bacterium <it>Bacillus subtilis </it>has been studied for many years as a paradigm for understanding the molecular basis for differential gene expression. As sporulation initiates, cells undergo an asymmetric division leading to differential gene expression in the small prespore and large mother cell compartments. Use of two fluorescent protein reporters permits time resolved examination of differential gene expression either in the same compartments or between compartments. Due to the spectral properties of GFP and mCherry, they are considered an ideal combination for co-localisation and co-expression experiments. They can also be used in combination with fluorescent DNA stains such as DAPI to correlate protein localisation patterns with the developmental stage of sporulation which can be linked to well characterised changes in DNA staining patterns.</p> <p>Findings</p> <p>While observing the recruitment of the transcription machinery into the forespore of sporulating <it>Bacillus subtilis</it>, we noticed the occurrence of stage-specific fluorescence intensity differences between GFP and mCherry. During vegetative growth and the initial stages of sporulation, fluorescence from both GFP and mCherry fusions behaved similarly. During stage II-III of sporulation we found that mCherry fluorescence was considerably diminished, whilst GFP signals remained clearly visible. This fluorescence pattern reversed during the final stage of sporulation with strong mCherry and low GFP fluorescence. These trends were observed in reciprocal tagging experiments indicating a direct effect of sporulation on fluorescent protein fluorophores.</p> <p>Conclusions</p> <p>Great care should be taken when interpreting the results of protein localisation and quantitative gene expression patterns using fluorescent proteins in experiments involving intracellular physiological change. We believe changes in the subcellular environment of the sporulating cell leads to conditions that differently alter the spectral properties of GFP and mCherry making an accurate interpretation of expression profiles technically challenging.</p

Green Fluorescent Protein Labeling of Listeria, Salmonella, and Escherichia coli O157:H7 for Safety-Related Studies

Many food safety-related studies require tracking of introduced foodborne pathogens to monitor their fate in complex environments. The green fluorescent protein (GFP) gene (gfp) provides an easily detectable phenotype so has been used to label many microorganisms for ecological studies. The objectives of this study were to label major foodborne pathogens and related bacteria, including Listeria monocytogenes, Listeria innocua, Salmonella, and Escherichia coli O157:H7 strains, with GFP and characterize the labeled strains for stability of the GFP plasmid and the plasmid's effect on bacterial growth. GFP plasmids were introduced into these strains by a CaCl2 procedure, conjugation or electroporation. Stability of the label was determined through sequential propagation of labeled strains in the absence of selective pressure, and rates of plasmid-loss were calculated. Stability of the GFP plasmid varied among the labeled species and strains, with the most stable GFP label observed in E. coli O157:H7. When grown in nonselective media for two consecutive subcultures (ca. 20 generations), the rates of plasmid loss among labeled E. coli O157:H7, Salmonella and Listeria strains ranged from 0%–30%, 15.8%–99.9% and 8.1%–93.4%, respectively. Complete loss (>99.99%) of the plasmid occurred in some labeled strains after five consecutive subcultures in the absence of selective pressure, whereas it remained stable in others. The GFP plasmid had an insignificant effect on growth of most labeled strains. E. coli O157:H7, Salmonella and Listeria strains can be effectively labeled with the GFP plasmid which can be stable in some isolates for many generations without adversely affecting growth rates

Cyanobacterial Cell Lineage Analysis of the Spatiotemporal hetR Expression Profile during Heterocyst Pattern Formation in Anabaena sp. PCC 7120

Diazotrophic heterocyst formation in the filamentous cyanobacterium, Anabaena sp. PCC 7120, is one of the simplest pattern formations known to occur in cell differentiation. Most previous studies on heterocyst patterning were based on statistical analysis using cells collected or observed at different times from a liquid culture, which would mask stochastic fluctuations affecting the process of pattern formation dynamics in a single bacterial filament. In order to analyze the spatiotemporal dynamics of heterocyst formation at the single filament level, here we developed a culture system to monitor simultaneously bacterial development, gene expression, and phycobilisome fluorescence. We also developed micro-liquid chamber arrays to analyze multiple Anabaena filaments at the same time. Cell lineage analyses demonstrated that the initial distributions of hetR::gfp and phycobilisome fluorescence signals at nitrogen step-down were not correlated with the resulting distribution of developed heterocysts. Time-lapse observations also revealed a dynamic hetR expression profile at the single-filament level, including transient upregulation accompanying cell division, which did not always lead to heterocyst development. In addition, some cells differentiated into heterocysts without cell division after nitrogen step-down, suggesting that cell division in the mother cells is not an essential requirement for heterocyst differentiation

Cell Wall Antibiotics Provoke Accumulation of Anchored mCherry in the Cross Wall of Staphylococcus aureus

A fluorescence microscopy method to directly follow the localization of defined proteins in Staphylococcus was hampered by the unstable fluorescence of fluorescent proteins. Here, we constructed plasmid (pCX) encoded red fluorescence (RF) mCherry (mCh) hybrids, namely mCh-cyto (no signal peptide and no sorting sequence), mCh-sec (with signal peptide), and mCh-cw (with signal peptide and cell wall sorting sequence). The S. aureus clones targeted mCh-fusion proteins into the cytosol, the supernatant and the cell envelope respectively; in all cases mCherry exhibited bright fluorescence. In staphylococci two types of signal peptides (SP) can be distinguished: the +YSIRK motif SPlip and the −YSIRK motif SPsasF. mCh-hybrids supplied with the +YSIRK motif SPlip were always expressed higher than those with −YSIRK motif SPsasF. To study the location of the anchoring process and also the influence of SP type, mCh-cw was supplied on the one hand with +YSIRK motif (mCh-cw1) and the other hand with -YSIRK motif (mCh-cw2). MCh-cw1 preferentially localized at the cross wall, while mCh-cw2 preferentially localized at the peripheral wall. Interestingly, when treated with sub-lethal concentrations of penicillin or moenomycin, both mCh-cw1 and mCh-cw2 were concentrated at the cross wall. The shift from the peripheral wall to the cross wall required Sortase A (SrtA), as in the srtA mutant this effect was blunted. The effect is most likely due to antibiotic mediated increase of free anchoring sites (Lipid II) at the cross wall, the substrate of SrtA, leading to a preferential incorporation of anchored proteins at the cross wall

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization

<p>Abstract</p> <p>Background</p> <p>Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer.</p> <p>Results</p> <p>The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment.</p> <p>Conclusion</p> <p>Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at <it><url>http://www.visualgenedeveloper.net</url></it>.</p