A Model for the Regulation of Lipopolysaccharide Synthesis during Outer Membrane Biogenesis in Escherichia Coli

The role of systems biology in the interpretation and analysis of important biological events is gaining rapid acceptance in a number of biological fields. Here a computational systems approach was applied to investigate the production and regulation of Escherichia coli’s (E. coli) outer membrane. The outer membrane comprises of phospholipids in the inner leaflet, and lipopolysaccharides (LPS) in the outer leaflet. LPS is an endotoxin that elicits a strong immune response from humans and its biosynthesis is in part, regulated via degradation of LpxC and WaaA enzymes by the protease FtsH. Despite a substantial amount of research conducted on LPS synthesis, there is remarkably little information on its regulation.The model of the outer membrane synthesis was completed in two phases; firstly a model of lipid A (representing the LPS pathway) was constructed followed by an integrated pathway model which incorporated fatty acids biosynthesis pathway (representing phospholipid production). The parameters used to construct the model were derived from published datasets where available, and estimated when necessary prior to model fitting. Model validation was carried out using a combination of published datasets alongside subsequent experimental data from this research.Model findings suggested that the FtsH-mediated LpxC degradation signal arises from levels of lipid A disaccharide, the substrate for LpxK. This was subsequently validated experimentally using an lpxK overexpression system. Analysis of the integrated model further refined this mechanism indicating the catalytic activity of LpxK appears to be dependent on the concentration of unsaturated fatty acids. This is biologically important because it assists in maintaining LPS/phospholipids homeostasis.Further crosstalk between the fatty acids and lipid A biosynthetic pathways was revealed by experimental observations that LpxC is additionally regulated by an unidentified protease whose activity is independent of lipid A disaccharide concentration, but could be induced in vitro by palmitic acid. The biological relevance of this acute mechanism is not obvious; however, experiments aimed at causing abrupt damage to the cell wall or membrane (by antimicrobials) suggest that under conditions which directly damage membrane structure, LPS regulation via this unidentified protease may be crucial.Computational analysis into the regulation of WaaA suggested that its proteolytic regulation does not affect the LPS synthetic rate. Subsequent experimental analysis provided evidence that WaaA regulation is aimed at controlling the quality of LPS synthesized by preventing glycosylation of undesirable lipid acceptors. Overexpression of waaA resulted in increased levels of 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo) sugar whereas, levels of heptose were not elevated in comparison to non-overexpressed cells. This implies that an uncontrolled production of WaaA does not increase LPS level but rather re-glycosylates lipid A precursors. This is the first time experimental data has been produced attempting to explain the regulation of WaaA.Computation of flux coefficient indicates that LpxC is the rate-limiting step when pathway regulation is ignored, but LpxK becomes the limiting step if feedback regulation is included as it is in vivo. Thus, in contrast to LpxC, LpxK may represent a more appropriate target for novel drug development. Overall, the findings of this work provide novel insights into the complex biogenesis of the E. coli outer membrane

A model for the proteolytic regulation of LpxC in the lipopolysaccharide pathway of Escherichia coli

Lipopolysaccharide (LPS) is an essential structural component found in Gram-negative bacteria. The molecule is comprised of a highly conserved lipid A and a variable outer core consisting of various sugars. LPS plays important roles in membrane stability in the bacterial cell and is also a potent activator of the human immune system. Despite its obvious importance, little is understood regarding the regulation of the individual enzymes involved or the pathway as a whole. LpxA and LpxC catalyze the first two steps in the LPS pathway. The reaction catalyzed by LpxA possesses a highly unfavourable equilibrium constant with no evidence of coupling to an energetically favourable reaction. In our model the presence of the second enzyme LpxC was sufficient to abate this unfavourable reaction and confirming previous studies suggesting that this reaction is the first committed step in LPS synthesis. It is believed that the protease FtsH regulates LpxC activity via cleavage. It is also suspected that the activity of FtsH is regulated by a metabolite produced by the LPS pathway; however, it is not known which one. In order to investigate these mechanisms, we obtained kinetic parameters from literature and developed estimates for other simulation parameters. Our simulations suggest that under modest increases in LpxC activity, FtsH is able to regulate the rate of product formation. However, under extreme increases in LpxC activities such as over-expression or asymmetrical cell division then FtsH activation may not be sufficient to regulate this first stage of synthesis

A Complete Pathway Model for Lipid A Biosynthesis in Escherichia coli.

Lipid A is a highly conserved component of lipopolysaccharide (LPS), itself a major component of the outer membrane of Gram-negative bacteria. Lipid A is essential to cells and elicits a strong immune response from humans and other animals. We developed a quantitative model of the nine enzyme-catalyzed steps of Escherichia coli lipid A biosynthesis, drawing parameters from the experimental literature. This model accounts for biosynthesis regulation, which occurs through regulated degradation of the LpxC and WaaA (also called KdtA) enzymes. The LpxC degradation signal appears to arise from the lipid A disaccharide concentration, which we deduced from prior results, model results, and new LpxK overexpression results. The model agrees reasonably well with many experimental findings, including the lipid A production rate, the behaviors of mutants with defective LpxA enzymes, correlations between LpxC half-lives and cell generation times, and the effects of LpxK overexpression on LpxC concentrations. Its predictions also differ from some experimental results, which suggest modifications to the current understanding of the lipid A pathway, such as the possibility that LpxD can replace LpxA and that there may be metabolic channeling between LpxH and LpxB. The model shows that WaaA regulation may serve to regulate the lipid A production rate when the 3-deoxy-D-manno-oct-2-ulosonic acid (KDO) concentration is low and/or to control the number of KDO residues that get attached to lipid A. Computation of flux control coefficients showed that LpxC is the rate-limiting enzyme if pathway regulation is ignored, but that LpxK is the rate-limiting enzyme if pathway regulation is present, as it is in real cells. Control also shifts to other enzymes if the pathway substrate concentrations are not in excess. Based on these results, we suggest that LpxK may be a much better drug target than LpxC, which has been pursued most often

Duan_protein_structures2024

Alphafold protein structures from bacteria and phage genomes</p

High throughput in situ metagenomic measurement of bacterial replication at ultra-low sequencing coverage.

We developed Growth Rate InDex (GRiD) for estimating in situ growth rates of ultra-low coverage (\u3e0.2×) and de novo-assembled metagenomes. Applying GRiD to human and environmental metagenomic datasets to demonstrate its versatility, we uncovered new associations with previously uncharacterized bacteria whose growth rates were associated with several disease characteristics or environmental interactions. In addition, with GRiD-MG (metagenomic), a high-throughput implementation of GRiD, we estimated growth dynamics of 1756 bacteria species from a healthy skin metagenomic dataset and identified a new Staphylococcus-Corynebacterium antagonism likely mediated by antimicrobial production in the skin. GRiD-MG significantly increases the ability to extract growth rate inferences from complex metagenomic data with minimal input from the user