A simple strategy guides the complex metabolic regulation in Escherichia coli

A way to decipher the complexity of the cellular metabolism is to study the effect of different external perturbations. Through an analysis over a sufficiently large set of gene knockouts and growing conditions, one aims to find a unifying principle that governs the metabolic regulation. For instance, it is known that the cessation of the microorganism proliferation after a gene deletion is only transient. However, we do not know the guiding principle that determines the partial or complete recovery of the growth rate, the corresponding redistribution of the metabolic fluxes and the possible different phenotypes. In spite of this large variety in the observed metabolic adjustments, we show that responses of E. coli to several different perturbations can always be derived from a sequence of greedy and myopic resilencings. This simple mechanism provides a detailed explanation for the experimental dynamics both at cellular (proliferation rate) and molecular level ((13)C-determined fluxes), also in case of appearance of multiple phenotypes. As additional support, we identified an example of a simple network motif that is capable of implementing this myopic greediness in the regulation of the metabolism

Multi-objective optimization of genome-scale metabolic models: the case of ethanol production

Ethanol is among the largest fermentation product used worldwide, accounting for more than 90% of all biofuel produced in the last decade. However current production methods of ethanol are unable to meet the requirements of increasing global demand, because of low yields on glucose sources. In this work, we present an in silico multi-objective optimization and analyses of eight genome-scale metabolic networks for the overproduction of ethanol within the engineered cell. We introduce MOME (multi-objective metabolic engineering) algorithm, that models both gene knockouts and enzymes up and down regulation using the Redirector framework. In a multi-step approach, MOME tackles the multi-objective optimization of biomass and ethanol production in the engineered strain; and performs genetic design and clustering analyses on the optimization results. We find in silico E. coli Pareto optimal strains with a knockout cost of 14 characterized by an ethanol production up to 19.74mmolgDW−1h−1 (+832.88% with respect to wild-type) and biomass production of 0.02h−1 (−98.06% ). The analyses on E. coli highlighted a single knockout strategy producing 16.49mmolgDW−1h−1 (+679.29% ) ethanol, with biomass equals to 0.23h−1 (−77.45% ). We also discuss results obtained by applying MOME to metabolic models of: (i) S. aureus; (ii) S. enterica; (iii) Y. pestis; (iv) S. cerevisiae; (v) C. reinhardtii; (vi) Y. lipolytica. We finally present a set of simulations in which constrains over essential genes and minimum allowable biomass were included. A bound over the maximum allowable biomass was also added, along with other settings representing rich media compositions. In the same conditions the maximum improvement in ethanol production is +195.24%

Whole genome analysis of linezolid resistance in Streptococcus pneumoniae reveals resistance and compensatory mutations

<p>Abstract</p> <p>Background</p> <p>Several mutations were present in the genome of <it>Streptococcus pneumoniae </it>linezolid-resistant strains but the role of several of these mutations had not been experimentally tested. To analyze the role of these mutations, we reconstituted resistance by serial whole genome transformation of a novel resistant isolate into two strains with sensitive background. We sequenced the parent mutant and two independent transformants exhibiting similar minimum inhibitory concentration to linezolid.</p> <p>Results</p> <p>Comparative genomic analyses revealed that transformants acquired G2576T transversions in every gene copy of 23S rRNA and that the number of altered copies correlated with the level of linezolid resistance and cross-resistance to florfenicol and chloramphenicol. One of the transformants also acquired a mutation present in the parent mutant leading to the overexpression of an ABC transporter (spr1021). The acquisition of these mutations conferred a fitness cost however, which was further enhanced by the acquisition of a mutation in a RNA methyltransferase implicated in resistance. Interestingly, the fitness of the transformants could be restored in part by the acquisition of altered copies of the L3 and L16 ribosomal proteins and by mutations leading to the overexpression of the spr1887 ABC transporter that were present in the original linezolid-resistant mutant.</p> <p>Conclusions</p> <p>Our results demonstrate the usefulness of whole genome approaches at detecting major determinants of resistance as well as compensatory mutations that alleviate the fitness cost associated with resistance.</p

Genetic Basis of Growth Adaptation of Escherichia coli after Deletion of pgi, a Major Metabolic Gene

Bacterial survival requires adaptation to different environmental perturbations such as exposure to antibiotics, changes in temperature or oxygen levels, DNA damage, and alternative nutrient sources. During adaptation, bacteria often develop beneficial mutations that confer increased fitness in the new environment. Adaptation to the loss of a major non-essential gene product that cripples growth, however, has not been studied at the whole-genome level. We investigated the ability of Escherichia coli K-12 MG1655 to overcome the loss of phosphoglucose isomerase (pgi) by adaptively evolving ten replicates of E. coli lacking pgi for 50 days in glucose M9 minimal medium and by characterizing endpoint clones through whole-genome re-sequencing and phenotype profiling. We found that 1) the growth rates for all ten endpoint clones increased approximately 3-fold over the 50-day period; 2) two to five mutations arose during adaptation, most frequently in the NADH/NADPH transhydrogenases udhA and pntAB and in the stress-associated sigma factor rpoS; and 3) despite similar growth rates, at least three distinct endpoint phenotypes developed as defined by different rates of acetate and formate secretion. These results demonstrate that E. coli can adapt to the loss of a major metabolic gene product with only a handful of mutations and that adaptation can result in multiple, alternative phenotypes

MS/MS networking guided analysis of molecule and gene cluster families

The paper introduces the concepts of molecular families (MFs) and gene cluster families (GCFs). We define MFs as structurally related molecules based on their mass spectral fragmentation patterns, whereas GCFs are biosynthetic gene clusters that show similar gene cluster organization with a high degree of sequence similarity. We use MS/MS networking as a tool to map the molecular network of more than 60 organisms, most of which are unsequenced, and locate their nonribosomal peptide MFs. These MFs from unsequenced organisms are then connected to GCFs of publicly available genome sequences of closely related organisms

Metabolic role of pyrophosphate-linked phosphofructokinasepfkfor C1 assimilation inMethylotuvimicrobium alcaliphilum20Z

Background Methanotrophs is a promising biocatalyst in biotechnological applications with their ability to utilize single carbon (C1) feedstock to produce high-value compounds. Understanding the behavior of biological networks of methanotrophic bacteria in different parameters is vital to systems biology and metabolic engineering. Interestingly, methanotrophic bacteria possess the pyrophosphate-dependent 6-phosphofructokinase (PPi-PFK) instead of the ATP-dependent 6-phosphofructokinase, indicating their potentials to serve as promising model for investigation the role of inorganic pyrophosphate (PPi) and PPi-dependent glycolysis in bacteria. Gene knockout experiments along with global-omics approaches can be used for studying gene functions as well as unraveling regulatory networks that rely on the gene product. Results In this study, we performed gene knockout and RNA-seq experiments inMethylotuvimicrobium alcaliphilum20Z to investigate the functional roles of PPi-PFK in C1 metabolism when cells were grown on methane and methanol, highlighting its metabolic importance in C1 assimilation inM. alcaliphilum20Z. We further conducted adaptive laboratory evolution (ALE) to investigate regulatory architecture inpfkknockout strain. Whole-genome resequencing and RNA-seq approaches were performed to characterize the genetic and metabolic responses of adaptation topfkknockout. A number of mutations, as well as gene expression profiles, were identified inpfkALE strain to overcome insufficient C1 assimilation pathway which limits the growth in the unevolved strain. Conclusions This study first revealed the regulatory roles of PPi-PFK on C1 metabolism and then provided novel insights into mechanism of adaptation to the loss of this major metabolic enzyme as well as an improved basis for future strain design in type I methanotrophs

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry techniques are well-suited to high-throughput characterization of natural products, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social molecular networking (GNPS, http://gnps.ucsd.edu), an open-access knowledge base for community wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of ‘living data’ through continuous reanalysis of deposited data