Patterns of syntrophic interactions in methanogenic conversion of propionate.

Methanogenesis is central to anaerobic digestion processes. The conversion of propionate as a key intermediate for methanogenesis requires syntrophic interactions between bacterial and archaeal partners. In this study, a series of methanogenic enrichments with propionate as the sole substrate were developed to identify microbial populations specifically involved in syntrophic propionate conversion.

The LacI family protein GlyR3 co-regulates the operon and in .

Background: utilizes a wide variety of free and cellulosomal cellulases and accessory enzymes to hydrolyze polysaccharides present in complex substrates. To date only a few studies have unveiled the details by which the expression of these cellulases are regulated. Recent studies have described the auto regulation of the operon and determined that the -- gene cluster and nearby - gene cluster are co-transcribed as polycistronic mRNA.

The Low Noise Limit in Gene Expression.

Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression.

Transcriptomic analysis of Clostridium thermocellum Populus hydrolysate-tolerant mutant strain shows increased cellular efficiency in response to Populus hydrolysate compared to the wild type strain.

Background: The thermophilic, anaerobic bacterium, Clostridium thermocellum is a model organism for consolidated processing due to its efficient fermentation of cellulose. Constituents of dilute acid pretreatment hydrolysate are known to inhibit C. thermocellum and other microorganisms.

Industrial robustness: understanding the mechanism of tolerance for the Populus hydrolysate-tolerant mutant strain of Clostridium thermocellum.

Background: An industrially robust microorganism that can efficiently degrade and convert lignocellulosic biomass into ethanol and next-generation fuels is required to economically produce future sustainable liquid transportation fuels. The anaerobic, thermophilic, cellulolytic bacterium Clostridium thermocellum is a candidate microorganism for such conversions but it, like many bacteria, is sensitive to potential toxic inhibitors developed in the liquid hydrolysate produced during biomass processing. Microbial processes leading to tolerance of these inhibitory compounds found in the pretreated biomass hydrolysate are likely complex and involve multiple genes.

Kinetic modeling of batch fermentation for Populus hydrolysate tolerant mutant and wild type strains of Clostridium thermocellum.

The extent of inhibition of two strains of Clostridium thermocellum by a Populus hydrolysate was investigated. A Monod-based model of wild type (WT) and Populus hydrolysate tolerant mutant (PM) strains of the cellulolytic bacterium C. thermocellum was developed to quantify growth kinetics in standard media and the extent of inhibition to a Populus hydrolysate.

Transcriptional burst frequency and burst size are equally modulated across the human genome.

Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting--as opposed to constitutive expression--is the predominant mode of expression.

Using risk analysis to predict design flow exceedance of decentralized wastewater management systems.

In small communities, the number of residential units is a more stable indicator of wastewater volume than population. Large communities benefit from averaging because the likelihood of having concurrent large flows from all users is small. In contrast, a single septic system connected to a single residence must be designed to accommodate large flow variations.

Transcriptional bursting from the HIV-1 promoter is a significant source of stochastic noise in HIV-1 gene expression.

Analysis of noise in gene expression has proven a powerful approach for analyzing gene regulatory architecture. To probe the regulatory mechanisms controlling expression of HIV-1, we analyze noise in gene-expression from HIV-1's long terminal repeat (LTR) promoter at different HIV-1 integration sites across the human genome. Flow cytometry analysis of GFP expression from the HIV-1 LTR shows high variability (noise) at each integration site.

Noise in biological circuits.

Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations.

Using noise to probe and characterize gene circuits.

Stochastic fluctuations (or "noise") in the single-cell populations of molecular species are shaped by the structure and biokinetic rates of the underlying gene circuit. The structure of the noise is summarized by its autocorrelation function. In this article, we introduce the noise regulatory vector as a generalized framework for making inferences concerning the structure and biokinetic rates of a gene circuit from its noise autocorrelation function.

Direct quantification of N-(3-oxo-hexanoyl)-L-homoserine lactone in culture supernatant using a whole-cell bioreporter.

The autoinducer N-(3-oxo-hexanoyl)-L-homoserine lactone (3-oxo-C6-HSL) plays a significant role in the quorum-sensing system of the marine bacterium Vibrio fischeri. Upon forming a transcriptional activation complex with LuxR, 3-oxo-C6-HSL induces transcription of the luxICDABEG operon, leading to the increased production of both the 3-oxo-C6-HSL synthase (LuxI) and the bioluminescent proteins. In order to quantitatively analyze this regulatory mechanism, a novel approach was developed to measure 3-oxo-C6-HSL concentrations in V.

Frequency domain analysis of noise in simple gene circuits.

Recent advances in single cell methods have spurred progress in quantifying and analyzing stochastic fluctuations, or noise, in genetic networks. Many of these studies have focused on identifying the sources of noise and quantifying its magnitude, and at the same time, paying less attention to the frequency content of the noise. We have developed a frequency domain approach to extract the information contained in the frequency content of the noise.

The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior.

A key to advancing the understanding of molecular biology in the post-genomic age is the development of accurate predictive models for genetic regulation, protein interaction, metabolism, and other biochemical processes. To facilitate model development, simulation algorithms must provide an accurate representation of the system, while performing the simulation in a reasonable amount of time. Gillespie's stochastic simulation algorithm (SSA) accurately depicts spatially homogeneous models with small populations of chemical species and properly represents noise, but it is often abandoned when modeling larger systems because of its computational complexity.

Statistical distributions of uncertainty and variability in activated sludge model parameters.

All models used in activated sludge design and analysis use parameters to characterize process performance. The values of these parameters are often assumed based on default values recommended in the literature, but to date, no quantitative estimates of the parameter uncertainties have been published. Similarly, little attention has been given to quantifying site-specific parameter variability, even though its occurrence has been observed several times in the literature.

Frequency domain chemical Langevin analysis of stochasticity in gene transcriptional regulation.

We present a frequency domain Langevin approach for stochastic analysis that remains valid for many important gene circuit elements even as molecular populations approach zero. We begin by considering the case of low-rate transcription and show that the previously reported shot noise representation is exact at all mRNA population levels for a constant transcription rate. Next, we consider transcriptional control through protein-DNA interactions at an operator site within the gene promoter region.

Emerging foundations: nano-engineering and bio-microelectronics for environmental biotechnology.

The growth of nanotechnology, the emergence of 'nanobiotechnology', and the incorporation of living organisms in biomicroelectronic devices are revolutionizing the interdisciplinary opportunities for microbiologists to participate in understanding, developing and exploiting microbial processes in and from the environment.

Analysis of noise in quorum sensing.

Noise may play a pivotal role in gene circuit functionality, as demonstrated for the genetic switch in the bacterial phage lambda. Like the lambda switch, bacterial quorum sensing (QS) systems operate within a population and contain a bistable switching element, making it likely that noise plays a functional role in QS circuit operation. Therefore, a detailed analysis of the noise behavior of QS systems is needed.

Frequency domain analysis of noise in autoregulated gene circuits.

We describe a frequency domain technique for the analysis of intrinsic noise within negatively autoregulated gene circuits. This approach is based on the transfer function around the feedback loop (loop transmission) and the equivalent noise bandwidth of the system. The loop transmission, T, is shown to be a determining factor of the dynamics and the noise behavior of autoregulated gene circuits, and this T-based technique provides a simple and flexible method for the analysis of noise arising from any source within the gene circuit.