Genome-scale models of metabolism and macromolecular expression (ME-models) explicitly compute the optimal proteome composition of a growing cell. ME-models expand upon the well-established ...genome-scale models of metabolism (M-models), and they enable a new fundamental understanding of cellular growth. ME-models have increased predictive capabilities and accuracy due to their inclusion of the biosynthetic costs for the machinery of life, but they come with a significant increase in model size and complexity. This challenge results in models which are both difficult to compute and challenging to understand conceptually. As a result, ME-models exist for only two organisms (Escherichia coli and Thermotoga maritima) and are still used by relatively few researchers. To address these challenges, we have developed a new software framework called COBRAme for building and simulating ME-models. It is coded in Python and built on COBRApy, a popular platform for using M-models. COBRAme streamlines computation and analysis of ME-models. It provides tools to simplify constructing and editing ME-models to enable ME-model reconstructions for new organisms. We used COBRAme to reconstruct a condensed E. coli ME-model called iJL1678b-ME. This reformulated model gives functionally identical solutions to previous E. coli ME-models while using 1/6 the number of free variables and solving in less than 10 minutes, a marked improvement over the 6 hour solve time of previous ME-model formulations. Errors in previous ME-models were also corrected leading to 52 additional genes that must be expressed in iJL1678b-ME to grow aerobically in glucose minimal in silico media. This manuscript outlines the architecture of COBRAme and demonstrates how ME-models can be created, modified, and shared most efficiently using the new software framework.
The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs ...on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.
Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this ...approach began to demonstrate the ability to predict a range of cellular functions, including cellular growth capabilities on various substrates and the effect of gene knockouts at the genome scale. Thus, much interest has developed in understanding and applying these methods to areas such as metabolic engineering, antibiotic design, and organismal and enzyme evolution. This Primer will get you started.
Genome-scale computational reconstructions of organisms have applications for metabolic engineering, antibiotic design, and organismal and enzyme evolution.
Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main ...directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness. To address this challenge, we reconstruct a genome-scale protein-folding network for Escherichia coli and formulate a computational model, FoldME, that provides statistical descriptions of multiscale cellular response consistent with many datasets. FoldME simulations show (i) that the chaperones act as a system when they respond to unfolding stress rather than achieving efficient folding of any single component of the proteome, (ii) how the proteome is globally balanced between chaperones for folding and the complex machinery synthesizing the proteins in response to perturbation, (iii) how this balancing determines growth rate dependence on temperature and is achieved through nonspecific regulation, and (iv) how thermal instability of the individual protein affects the overall functional state of the proteome. Overall, these results expand our view of cellular regulation, from targeted specific control mechanisms to global regulation through a web of nonspecific competing interactions that modulate the optimal reallocation of cellular resources. The methodology developed in this study enables genome-scale integration of environment-dependent protein properties and a proteome-wide study of cellular stress responses.
The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively ...reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response to iron availability using genome-wide measurements. Integrative data analysis reveals that a total of 81 genes in 42 transcription units are directly regulated by three different modes of Fur regulation, including apo- and holo-Fur activation and holo-Fur repression. We show that Fur connects iron transport and utilization enzymes with negative-feedback loop pairs for iron homeostasis. In addition, direct involvement of Fur in the regulation of DNA synthesis, energy metabolism and biofilm development is found. These results show how Fur exhibits a comprehensive regulatory role affecting many fundamental cellular processes linked to iron metabolism in order to coordinate the overall response of E. coli to iron availability.
Abstract
Background
Recurrent Clostridioides difficile infection (rCDI) is associated with loss of microbial diversity and microbe-derived secondary bile acids, which inhibit C. difficile germination ...and growth. SER-109, an investigational microbiome drug of donor-derived, purified spores, reduced recurrence in a dose-ranging, phase (P) 1 study in subjects with multiple rCDIs.
Methods
In a P2 double-blind trial, subjects with clinical resolution on standard-of-care antibiotics were stratified by age (< or ≥65 years) and randomized 2:1 to single-dose SER-109 or placebo. Subjects were diagnosed at study entry by PCR or toxin testing. Safety, C. difficile–positive diarrhea through week 8, SER-109 engraftment, and bile acid changes were assessed.
Results
89 subjects enrolled (67% female; 80.9% diagnosed by PCR). rCDI rates were lower in the SER-109 arm than placebo (44.1% vs 53.3%) but did not meet statistical significance. In a preplanned analysis, rates were reduced among subjects ≥65 years (45.2% vs 80%, respectively; RR, 1.77; 95% CI, 1.11–2.81), while the <65 group showed no benefit. Early engraftment of SER-109 was associated with nonrecurrence (P < .05) and increased secondary bile acid concentrations (P < .0001). Whole-metagenomic sequencing from this study and the P1 study revealed previously unappreciated dose-dependent engraftment kinetics and confirmed an association between early engraftment and nonrecurrence. Engraftment kinetics suggest that P2 dosing was suboptimal. Adverse events were generally mild to moderate in severity.
Conclusions
Early SER-109 engraftment was associated with reduced CDI recurrence and favorable safety was observed. A higher dose of SER-109 and requirements for toxin testing were implemented in the current P3 trial.
Clinical Trials Registration
NCT02437487, https://clinicaltrials.gov/ct2/show/NCT02437487?term=SER-109&draw= 2&rank=4.
In a phase 2 trial, SER-109, an investigational microbiome drug, did not reduce rates of recurrent CDI, despite a previously successful open-label study. Key contributing factors, which led to a redesign of the currently enrolling phase 3 trial, are highlighted.
Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained ...fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes.
Growth is a fundamental process of life. Growth requirements are well‐characterized experimentally for many microbes; however, we lack a unified model for cellular growth. Such a model must be ...predictive of events at the molecular scale and capable of explaining the high‐level behavior of the cell as a whole. Here, we construct an ME‐Model for Escherichia coli—a genome‐scale model that seamlessly integrates metabolic and gene product expression pathways. The model computes ∼80% of the functional proteome (by mass), which is used by the cell to support growth under a given condition. Metabolism and gene expression are interdependent processes that affect and constrain each other. We formalize these constraints and apply the principle of growth optimization to enable the accurate prediction of multi‐scale phenotypes, ranging from coarse‐grained (growth rate, nutrient uptake, by‐product secretion) to fine‐grained (metabolic fluxes, gene expression levels). Our results unify many existing principles developed to describe bacterial growth.
A constraint‐based approach for integrative modeling of metabolism and gene expression is developed. New constraints on molecular catalysis increase both the accuracy and scope of computable phenotypes corresponding to optimal microbial growth.
Synopsis
A constraint‐based approach for integrative modeling of metabolism and gene expression is developed. New constraints on molecular catalysis increase both the accuracy and scope of computable phenotypes corresponding to optimal microbial growth.
An integrated network of metabolic and gene expression pathways is built for E. coli.
A growth model is developed by adding demands and constraints on molecular catalysis.
Model yields accurate predictions of growth phenotypes from molecules to whole cell.
A few basic principles underlie growth rate optimization at the systems level.
Firmicutes bacteria produce metabolites that maintain the intestinal barrier and mucosal immunity. Firmicutes are reduced in the intestinal microbiota of patients with ulcerative colitis (UC). In a ...phase 1b trial of patients with UC, we evaluated the safety and efficacy of SER-287, an oral formulation of Firmicutes spores, and the effects of vancomycin preconditioning on expansion (engraftment) of SER-287 species in the colon.
We conducted a double-blind trial of SER-287 in 58 adults with active mild-to-moderate UC (modified Mayo scores 4–10, endoscopic subscores ≥1). Participants received 6 days of preconditioning with oral vancomycin (125 mg, 4 times daily) or placebo followed by 8 weeks of oral SER-287 or placebo. Patients were randomly assigned (2:3:3:3) to groups that received placebo followed by either placebo or SER-287 once weekly, or vancomycin followed by SER-287 once weekly, or SER-287 once daily. Clinical end points included safety and clinical remission (modified Mayo score ≤2; endoscopic subscores 0 or 1). Microbiome end points included SER-287 engraftment (dose species detected in stool after but not before SER-287 administration). Engraftment of SER-287 and changes in microbiome composition and associated metabolites were measured by analyses of stool specimens collected at baseline, after preconditioning, and during and 4 weeks after administration of SER-287 or placebo.
Proportions of patients with adverse events did not differ significantly among groups. A higher proportion of patients in the vancomycin/SER-287 daily group (40%) achieved clinical remission at week 8 than patients in the placebo/placebo group (0%), placebo/SER-287 weekly group (13.3%), or vancomycin/SER-287 weekly group (17.7%) (P = .024 for vancomycin/SER-287 daily vs placebo/placebo). By day 7, higher numbers of SER-287 dose species were detected in stool samples from all SER-287 groups compared with the placebo group (P < .05), but this difference was not maintained beyond day 7 in the placebo/SER-287 weekly group. In the vancomycin groups, a greater number of dose species were detected in stool collected on day 10 and all subsequent time points through 4 weeks post dosing compared with the placebo group (P < .05). A higher number of SER-287 dose species were detected in stool samples on days 7 and 10 from subjects who received daily vs weekly SER-287 doses (P < .05). Changes in fecal microbiome composition and metabolites were associated with both vancomycin/SER-287 groups.
In this small phase 1b trial of limited duration, the safety and tolerability of SER-287 were similar to placebo. SER-287 after vancomycin was significantly more effective than placebo for induction of remission in patients with active mild to moderate UC. Engraftment of dose species was facilitated by vancomycin preconditioning and daily dosing of SER-287. ClinicalTrials.gov ID NCT02618187.
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