Bistable behavior of the lac operon in E. coli when induced with a mixture of lactose and TMG

Hybrid de novo Genome Assembly of Erwinia sp. E602 and Bioinformatic Analysis Characterized a New Plasmid-Borne lac Operon Under Positive Selection

Our previous study identified a new β-galactosidase in Erwinia sp. E602. To further understand the lactose metabolism in this strain, de novo genome assembly was conducted by using a strategy combining Illumina and PacBio sequencing technology. The whole genome of Erwinia sp. E602 includes a 4.8 Mb chromosome and a 326 kb large plasmid. A total of 4,739 genes, including 4,543 protein-coding genes, 25 rRNAs, 82 tRNAs and 7 other ncRNAs genes were annotated. The plasmid was the largest one characterized in genus Erwinia by far, and it contained a number of genes and pathways responsible for lactose metabolism and regulation. Moreover, a new plasmid-borne lac operon that lacked a typical β-galactoside transacetylase (lacA) gene was identified in the strain. Phylogenetic analysis showed that the genes lacY and lacZ in the operon were under positive selection, indicating the adaptation of lactose metabolism to the environment in Erwinia sp. E602. Our current study demonstrated that the hybrid de novo genome assembly using Illumina and PacBio sequencing technologies, as well as the metabolic pathway analysis, provided a useful strategy for better understanding of the evolution of undiscovered microbial species or strains.

A practical guide to mechanistic systems modeling in biology using a logic-based approach

Mechanistic computational models enable the study of regulatory mechanisms implicated in various biological processes. These models provide a means to analyze the dynamics of the systems they describe, and to study and interrogate their properties, and provide insights about the emerging behavior of the system in the presence of single or combined perturbations. Aimed at those who are new to computational modeling, we present here a practical hands-on protocol breaking down the process of mechanistic modeling of biological systems in a succession of precise steps. The protocol provides a framework that includes defining the model scope, choosing validation criteria, selecting the appropriate modeling approach, constructing a model and simulating the model. To ensure broad accessibility of the protocol, we use a logical modeling framework, which presents a lower mathematical barrier of entry, and two easy-to-use and popular modeling software tools: Cell Collective and GINsim. The complete modeling workflow is applied to a well-studied and familiar biological process-the lac operon regulatory system. The protocol can be completed by users with little to no prior computational modeling experience approximately within 3 h.

The Crabtree Effect Shapes the Saccharomyces cerevisiae Lag Phase during the Switch between Different Carbon Sources

When faced with environmental changes, microbes often enter a temporary growth arrest during which they reprogram the expression of specific genes to adapt to the new conditions. A prime example of such a lag phase occurs when microbes need to switch from glucose to other, less-preferred carbon sources. Despite its industrial relevance, the genetic network that determines the duration of the lag phase has not been studied in much detail. Here, we performed a genome-wide Bar-Seq screen to identify genetic determinants of the Saccharomyces cerevisiae glucose-to-galactose lag phase. The results show that genes involved in respiration, and specifically those encoding complexes III and IV of the electron transport chain, are needed for efficient growth resumption after the lag phase. Anaerobic growth experiments confirmed the importance of respiratory energy conversion in determining the lag phase duration. Moreover, overexpression of the central regulator of respiration, HAP4, leads to significantly shorter lag phases. Together, these results suggest that the glucose-induced repression of respiration, known as the Crabtree effect, is a major determinant of microbial fitness in fluctuating carbon environments.IMPORTANCE The lag phase is arguably one of the prime characteristics of microbial growth. Longer lag phases result in lower competitive fitness in variable environments, and the duration of the lag phase is also important in many industrial processes where long lag phases lead to sluggish, less efficient fermentations. Despite the immense importance of the lag phase, surprisingly little is known about the exact molecular processes that determine its duration. Our study uses the molecular toolbox of S. cerevisiae combined with detailed growth experiments to reveal how the transition from fermentative to respirative metabolism is a key bottleneck for cells to overcome the lag phase. Together, our findings not only yield insight into the key molecular processes and genes that influence lag duration but also open routes to increase the efficiency of industrial fermentations and offer an experimental framework to study other types of lag behavior.

The utility of simple mathematical models in understanding gene regulatory dynamics

In this review, we survey work that has been carried out in the attempts of biomathematicians to understand the dynamic behaviour of simple bacterial operons starting with the initial work of the 1960's. We concentrate on the simplest of situations, discussing both repressible and inducible systems and then turning to concrete examples related to the biology of the lactose and tryptophan operons. We conclude with a brief discussion of the role of both extrinsic noise and so-called intrinsic noise in the form of translational and/or transcriptional bursting.