Designing sequential transcription logic: a simple genetic circuit for conditional memory

The ability to learn and respond to recurrent events depends on the capacity to remember transient biological signals received in the past. Moreover, it may be desirable to remember or ignore these transient signals conditioned upon other signals that are active at specific points in time or in unique environments. Here, we propose a simple genetic circuit in bacteria that is capable of conditionally memorizing a signal in the form of a transcription factor concentration. The circuit behaves similarly to a "data latch" in an electronic circuit, i.e. it reads and stores an input signal only when conditioned to do so by a "read command". Our circuit is of the same size as the well-known genetic toggle switch (an unconditional latch) which consists of two mutually repressing genes, but is complemented with a "regulatory front end" involving protein heterodimerization as a simple way to implement conditional control. Deterministic and stochastic analysis of the circuit dynamics indicate that an experimental implementation is feasible based on well-characterized genes and proteins. It is not known, to which extent molecular networks are able to conditionally store information in natural contexts for bacteria. However, our results suggest that such sequential logic elements may be readily implemented by cells through the combination of existing protein-protein interactions and simple transcriptional regulation.Comment: 20 pages, 5 figures; supplementary material available upon request from the author

Genome-Scale Identification Method Applied to Find Cryptic Aminoglycoside Resistance Genes in Pseudomonas aeruginosa

BACKGROUND:The ability of bacteria to rapidly evolve resistance to antibiotics is a critical public health problem. Resistance leads to increased disease severity and death rates, as well as imposes pressure towards the discovery and development of new antibiotic therapies. Improving understanding of the evolution and genetic basis of resistance is a fundamental goal in the field of microbiology. RESULTS:We have applied a new genomic method, Scalar Analysis of Library Enrichments (SCALEs), to identify genomic regions that, given increased copy number, may lead to aminoglycoside resistance in Pseudomonas aeruginosa at the genome scale. We report the result of selections on highly representative genomic libraries for three different aminoglycoside antibiotics (amikacin, gentamicin, and tobramycin). At the genome-scale, we show significant (p<0.05) overlap in genes identified for each aminoglycoside evaluated. Among the genomic segments identified, we confirmed increased resistance associated with an increased copy number of several genomic regions, including the ORF of PA5471, recently implicated in MexXY efflux pump related aminoglycoside resistance, PA4943-PA4946 (encoding a probable GTP-binding protein, a predicted host factor I protein, a delta 2-isopentenylpyrophosphate transferase, and DNA mismatch repair protein mutL), PA0960-PA0963 (encoding hypothetical proteins, a probable cold shock protein, a probable DNA-binding stress protein, and aspartyl-tRNA synthetase), a segment of PA4967 (encoding a topoisomerase IV subunit B), as well as a chimeric clone containing two inserts including the ORFs PA0547 and PA2326 (encoding a probable transcriptional regulator and a probable hypothetical protein, respectively). CONCLUSIONS:The studies reported here demonstrate the application of new a genomic method, SCALEs, which can be used to improve understanding of the evolution of antibiotic resistance in P. aeruginosa. In our demonstration studies, we identified a significant number of genomic regions that increased resistance to multiple aminoglycosides. We identified genetic regions that include open reading frames that encode for products from many functional categories, including genes related to O-antigen synthesis, DNA repair, and transcriptional and translational processes

Noise regulation by quorum sensing in low mRNA copy number systems

<p>Abstract</p> <p>Background</p> <p>Cells must face the ubiquitous presence of noise at the level of signaling molecules. The latter constitutes a major challenge for the regulation of cellular functions including communication processes. In the context of prokaryotic communication, the so-called quorum sensing (QS) mechanism relies on small diffusive molecules that are produced and detected by cells. This poses the intriguing question of how bacteria cope with the fluctuations for setting up a reliable information exchange.</p> <p>Results</p> <p>We present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold. Within that framework we study, both numerically and analytically, the role that diffusion plays in the regulation of the dynamics and the fluctuations of signaling molecules. In addition, we unveil the contribution of different sources of noise, intrinsic and transcriptional, in the QS mechanism.</p> <p>Conclusions</p> <p>The interplay between noisy sources and the communication process produces a repertoire of dynamics that depends on the diffusion rate. Importantly, the total noise shows a non-monotonic behavior as a function of the diffusion rate. QS systems seems to avoid values of the diffusion that maximize the total noise. These results point towards the direction that bacteria have adapted their communication mechanisms in order to improve the signal-to-noise ratio.</p

Bifurcations of Limit Cycles in a Reduced Model of the Xenopus Tadpole Central Pattern Generator

This work was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC, grant numbers BB/L002353/1; BB/L000814/1; BB/L00111X/1). AF was supported by a PhD studentship from Plymouth University.We present the study of a minimal microcircuit controlling locomotion in two-day-old Xenopus tadpoles. During swimming, neurons in the spinal central pattern generator (CPG) generate anti-phase oscillations between left and right half-centres. Experimental recordings show that the same CPG neurons can also generate transient bouts of long-lasting in-phase oscillations between left-right centres. These synchronous episodes are rarely recorded and have no identified behavioural purpose. However, metamorphosing tadpoles require both anti-phase and in-phase oscillations for swimming locomotion. Previous models have shown the ability to generate biologically realistic patterns of synchrony and swimming oscillations in tadpoles, but a mathematical description of how these oscillations appear is still missing. We define a simplified model that incorporates the key operating principles of tadpole locomotion. The model generates the various outputs seen in experimental recordings, including swimming and synchrony. To study the model, we perform detailed one- and two-parameter bifurcation analysis. This reveals the critical boundaries that separate different dynamical regimes and demonstrates the existence of parameter regions of bi-stable swimming and synchrony. We show that swimming is stable in a significantly larger range of parameters, and can be initiated more robustly, than synchrony. Our results can explain the appearance of long-lasting synchrony bouts seen in experiments at the start of a swimming episode.Publisher PDFPeer reviewe

The effect of conjugated linoleic acid supplementation after weight loss on body weight regain, body composition, and resting metabolic rate in overweight subjects

The effect of conjugated linoleic acid supplementation after weight loss on body weight regain, body composition, and resting metabolic rate in overweight subjects. Kamphuis MM, Lejeune MP, Saris WH, Westerterp-Plantenga MS. Department of Human Biology, Faculty of Health Sciences, Maastricht University, The Netherlands. [email protected] OBJECTIVE: To study the effects of 13 weeks conjugated linoleic acid (CLA) supplementation in overweight subjects after weight loss on weight regain, body composition, resting metabolic rate, substrate oxidation, and blood plasma parameters. DESIGN: This study had a double-blind, placebo-controlled randomized design. Subjects were first submitted to a very-low-calorie diet (VLCD 2.1 MJ/d) for 3 weeks after which they started with the 13-week intervention period. They either received 1.8 g CLA or placebo per day (low dosage, LD) or 3.6 g CLA or placebo per day (high dosage, HD). SUBJECTS: A total of 26 men and 28 women (age 37.8+/-7.7 y; body mass index (BMI) 27.8+/-1.5 kg/m(2)). MEASUREMENTS: Before VLCD (t=-3), after VLCD but before CLA or placebo intervention (t=0) and after 13-week CLA or placebo intervention (t=13), body weight, body composition (hydrodensitometry and deuterium dilution), resting metabolic rate, substrate oxidation, physical activity, and blood plasma parameters (glucose, insulin, triacylglycerol, free fatty acids, glycerol and beta-hydroxy butyrate) were measured. RESULTS: The VLCD significantly lowered body weight (6.9+/-1.7%), %body fat, fat mass, fat-free mass, resting metabolic rate, respiratory quotient and plasma glucose, insulin, and triacylglycerol concentrations, while free fatty acids, glycerol and beta-hydroxy butyrate concentrations were increased. Multiple regression analysis showed that at the end of the 13-week intervention, CLA did not affect %body weight regain (CLA LD 47.9+/-88.2%, CLA HD 27.4+/-29.8%, Placebo LD 32.0+/-42.8%, Placebo HD 22.5+/-37.9%). The regain of fat-free mass was increased by CLA (LD 6.2+/-3.9, HD 4.6+/-2.4%) compared to placebo (LD 2.8+/-3.2%, HD 3.4+/-3.6%), independent of %body weight regain and physical activity. As a consequence of an increased regain of fat-free mass by CLA, resting metabolic rate was increased by CLA (LD 12.0+/-11.4%, HD 13.7+/-14.4%) compared to placebo (LD 9.1+/-11.0%, HD 8.6+/-8.5%). Substrate oxidation and blood plasma parameters were not affected by CLA. CONCLUSION: In conclusion, the regain of fat-free mass was favorably, dose-independently affected by a 13-week consumption of 1.8 or 3.6 g CLA/day and consequently increased the resting metabolic rate. However, it did not result in improved body weight maintenance after weight loss