Artificial Soils Reveal Individual Factor Controls on Microbial Processes

Soil matrix properties influence microbial behaviors that underlie nutrient cycling, greenhouse gas production, and soil formation. However, the dynamic and heterogeneous nature of soils makes it challenging to untangle the effects of different matrix properties on microbial behaviors. To address this challenge, we developed a tunable artificial soil recipe and used these materials to study the abiotic mechanisms driving soil microbial growth and communication. When we used standardized matrices with varying textures to culture gas-reporting biosensors, we found that a Gram-negative bacterium (Escherichia coli) grew best in synthetic silt soils, remaining active over a wide range of soil matric potentials, while a Gram-positive bacterium (Bacillus subtilis) preferred sandy soils, sporulating at low water potentials. Soil texture, mineralogy, and alkalinity all attenuated the bioavailability of an acyl-homoserine lactone (AHL) signaling molecule that controls community-level microbial behaviors. Texture controlled the timing of AHL sensing, while AHL bioavailability was decreased ~10⁵-fold by mineralogy and ~10³-fold by alkalinity. Finally, we built artificial soils with a range of complexities that converge on the properties of one Mollisol. As artificial soil complexity increased to more closely resemble the Mollisol, microbial behaviors approached those occurring in the natural soil, with the notable exception of organic matter. IMPORTANCE Understanding environmental controls on soil microbes is difficult because many abiotic parameters vary simultaneously and uncontrollably when different natural soils are compared, preventing mechanistic determination of any individual soil parameter's effect on microbial behaviors. We describe how soil texture, mineralogy, pH, and organic matter content can be varied individually within artificial soils to study their effects on soil microbes. Using microbial biosensors that report by producing a rare indicator gas, we identify soil properties that control microbial growth and attenuate the bioavailability of a diffusible chemical used to control community-level behaviors. We find that artificial soils differentially affect signal bioavailability and the growth of Gram-negative (Escherichia coli) and Gram-positive (Bacillus subtilis) microbes. These artificial soils are useful for studying the mechanisms that underlie soil controls on microbial fitness, signaling, and gene transfer.

Design and evaluation of an incoherent feed-forward loop for an arsenic biosensor based on standard iGEM parts

The diversity and flexibility of life offers a wide variety of molecules and systems useful for biosensing. A biosensor device should be robust, specific and reliable. Inorganic arsenic is a highly toxic water contaminant with worldwide distribution that poses a threat to public health. With the goal of developing an arsenic biosensor, we designed an incoherent feed-forward loop (I-FFL) genetic circuit to correlate its output pulse with the input signal in a relatively time-independent manner. The system was conceived exclusively based on the available BioBricks in the iGEM Registry of Standard Biological Parts. The expected behavior in silico was achieved; upon arsenic addition, the system generates a short-delayed reporter protein pulse that is dose dependent to the contaminant levels. This work is an example of the power and variety of the iGEM Registry of Standard Biological Parts, which can be reused in different sophisticated system designs like I-FFLs. Besides the scientific results, one of the main impacts of this synthetic biology project is the influence it had on team’s members training and career choices which are summarized at the end of this article.

Complete alanine scanning of the Escherichia coli RbsB ribose binding protein reveals residues important for chemoreceptor signaling and periplasmic abundance

The Escherichia coli RbsB ribose binding protein has been used as a scaffold for predicting new ligand binding functions through in silico modeling, yet with limited success and reproducibility. In order to possibly improve the success of predictive modeling on RbsB, we study here the influence of individual residues on RbsB-mediated signaling in a near complete library of alanine-substituted RbsB mutants. Among a total of 232 tested mutants, we found 10 which no longer activated GFPmut2 reporter expression in E. coli from a ribose-RbsB hybrid receptor signaling chain, and 13 with significantly lower GFPmut2 induction than wild-type. Quantitative mass spectrometry abundance measurements of 25 mutants and wild-type RbsB in periplasmic space showed four categories of effects. Some (such as D89A) seem correctly produced and translocated but fail to be induced with ribose. Others (such as N190A) show lower induction probably as a result of less efficient production, folding and translocation. The third (such as N41A or K29A) have defects in both induction and abundance. The fourth category consists of semi-constitutive mutants with increased periplasmic abundance but maintenance of ribose induction. Our data show how RbsB modeling should include ligand-binding as well as folding, translocation and receptor binding.