Design of a tunable bacterial gene expression system using engineered σ factors.

Extracytoplasmic function (ECF) σ factors selectively upregulate expression of specific genes in bacteria. These σ factors, belonging to the σ70 family, are much smaller than the primary, housekeeping σ factor with two helical domains that interact with the Pribnow box and the -35 element of the promoter DNA. Structural studies reveal that promoter specificity in a σ factor is determined by the interactions between a loop (L3) and the Pribnow box element. Similarly, the efficiency of transcription initiation is governed by the polypeptide linker between the two promoter-binding domains. Both these polypeptide segments are dynamic and poorly conserved among ECF σ factor homologs. This feature hitherto limited insights from protein-DNA interactions to be correlated with transcription initiation efficiency. Here, we describe an approach to characterize these features that govern the dynamic range of gene expression using chimeric Escherichia coli σE. The L3 loop and linker polypeptides in these σE chimeras were replaced by the corresponding segments from 10 annotated and functional Mycobacterium tuberculosis ECF σ's. In vitro and in vivo measurements to determine the effect of these polypeptide replacements provided an experimentally validated σE chimera- gene expression level data set. We illustrate the utility of this chimeric σE library in improving the efficiency of a biosynthetic pathway in E. coli. In a two-enzyme step, unaffected by feedback inhibition and substrate concentration, we show an increase in desired product levels by altering the relative intracellular levels of the target enzymes using this library of σ factors. The chimeric σE library thus demonstrates the feasibility of engineering σ factors to achieve bespoke expression levels of target genes for diverse applications in synthetic microbiology. IMPORTANCE: The synthesis of organic compounds involves the action of multiple enzymes in a biosynthetic pathway. Incorporating such biosynthetic pathways into microbes often leads to substantial cellular and metabolic stress resulting in low titers of the target compound. This limitation can be offset, in part, by optimizing enzyme efficiency and cellular enzyme concentration. The former involves significant efforts to achieve improvements in catalytic efficiency with the caveat that the metabolic load on a microbial cell imposed by the overexpression of the exogenous enzyme could result in reduced cell fitness. Here, we demonstrate the feasibility of engineered σ factors to modulate gene expression levels without significant genetic engineering. We note that changing the sequence of two flexible polypeptide loops without any changes to the structural scaffold of the transcription initiation factor σE could modulate the expression levels of the target genes. This ability provides a route to improve the efficiency of a biosynthetic pathway without altering the overall genomic makeup. The σE chimera library thus provides an avenue for pre-determined conditional gene expression of specific genes in Escherichia coli.

Surface exposed and charged residues drive thermostability in fungi.

Fungi, though mesophilic, include thermophilic and thermostable species, as well. The thermostability of proteins observed in these fungi is most likely to be attributed to several molecular factors, such as the presence of salt bridges and hydrogen bond interactions between side chains. These factors cannot be generalized for all fungi. Factors impacting thermostability can guide how fungal thermophilic proteins gain thermostability. We curated a dataset of proteins for 14 thermophilic fungi and their evolutionarily closer mesophiles. Additionally, the proteome of Chaetomium thermophilum and its evolutionarily related mesophile Chaetomium globosum was analyzed. Using eggNOG, we categorized the proteomes into clusters of orthologous groups (COGs). While the individual count of proteins is over-represented in mesophiles (for COGs S, G, L, and Q), there are certain features that are significantly enriched in thermophiles (such as charged residues, exposed residues, polar residues, etc.). Since fungi are known to be cellulolytic and chitinolytic by nature, we selected 37 existing carbohydrate-active enzymes (CAZyme) families in Eurotiales, Mucorales, and Sordariales. We looked at closely similar sequences and their modeled structures for further comparison. Comparing solvent accessibilities of thermophilic and mesophilic proteins, exposed and intermediate residues are observed higher in thermophiles whereas buried residues are observed higher in mesophiles. For specific five CAZYme families (GH7, GH11, GH18, GH45, and CBM1) we looked at position-specific substitutions between thermophiles and mesophiles. We also found that there are relatively more intramolecular interactions in thermophiles compared to mesophiles. Thus, we found factors such as surface exposed residues and charged residues that are highly likely to impart thermostability in fungi, and this study sets the stage for further studies in the area of fungal thermostability.

Experimental and computational studies of cellulases as bioethanol enzymes.

Bioethanol industries and bioprocesses have many challenges that constantly impede commercialization of the end product. One of the bottlenecks in the bioethanol industry is the challenge of discovering highly efficient catalysts that can improve biomass conversion. The current promising bioethanol conversion catalysts are microorganism-based cellulolytic enzymes, but lack optimization for high bioethanol conversion, due to biological and other factors. A better understanding of molecular underpinnings of cellulolytic enzyme mechanisms and significant ways to improve them can accelerate the bioethanol commercial production process. In order to do this, experimental methods are the primary choice to evaluate and characterize cellulase's properties, but they are time-consuming and expensive. A time-saving, complementary approach involves computational methods that evaluate the same properties and improves our atomistic-level understanding of enzymatic mechanism of action. Theoretical methods in many cases have proposed research routes for subsequent experimental testing and validation, reducing the overall research cost. Having a plethora of tools to evaluate cellulases and the yield of the enzymatic process will aid in planning more optimized experimental setups. Thus, there is a need to connect the computational evaluation methods with the experimental methods to overcome the bottlenecks in the bioethanol industry. This review discusses various experimental and computational methods and their use in evaluating the multiple properties of cellulases.