Low-Cost, High-Throughput Sequencing of DNA Assemblies Using a Highly Multiplexed Nextera Process.

In recent years, next-generation sequencing (NGS) technology has greatly reduced the cost of sequencing whole genomes, whereas the cost of sequence verification of plasmids via Sanger sequencing has remained high. Consequently, industrial-scale strain engineers either limit the number of designs or take short cuts in quality control. Here, we show that over 4000 plasmids can be completely sequenced in one Illumina MiSeq run for less than $3 each (15× coverage), which is a 20-fold reduction over using Sanger sequencing (2× coverage). We reduced the volume of the Nextera tagmentation reaction by 100-fold and developed an automated workflow to prepare thousands of samples for sequencing. We also developed software to track the samples and associated sequence data and to rapidly identify correctly assembled constructs having the fewest defects. As DNA synthesis and assembly become a centralized commodity, this NGS quality control (QC) process will be essential to groups operating high-throughput pipelines for DNA construction.

Novel metabolic features in Acinetobacter baylyi ADP1 revealed by a multiomics approach.

Expansive knowledge of bacterial metabolism has been gained from genome sequencing output, but the high proportion of genes lacking a proper functional annotation in a given genome still impedes the accurate prediction of the metabolism of a cell. To access to a more global view of the functioning of the soil bacterium Acinetobacter baylyi ADP1, we adopted a multi 'omics' approach. Application of RNA-seq transcriptomics and LC/MS-based metabolomics, along with the systematic phenotyping of the complete collection of single-gene deletion mutants of A. baylyi ADP1 made possible to interrogate on the metabolic perturbations encountered by the bacterium upon a biotic change. Shifting the sole carbon source from succinate to quinate elicited in the cell not only a specific transcriptional response, necessary to catabolize the new carbon source, but also a major reorganization of the transcription pattern. Here, the expression of more than 12 % of the total number of genes was affected, most of them being of unknown function. These perturbations were ultimately reflected in the metabolome, in which the concentration of about 50 % of the LC/MS-detected metabolites was impacted. And the differential regulation of many genes of unknown function is probably related to the synthesis of the numerous unidentified compounds that were present exclusively in quinate-grown cells. Together, these data suggest that A. baylyi ADP1 metabolism involves unsuspected enzymatic reactions that await discovery.

Rapid and reliable DNA assembly via ligase cycling reaction.

Assembly of DNA parts into DNA constructs is a foundational technology in the emerging field of synthetic biology. An efficient DNA assembly method is particularly important for high-throughput, automated DNA assembly in biofabrication facilities and therefore we investigated one-step, scarless DNA assembly via ligase cycling reaction (LCR). LCR assembly uses single-stranded bridging oligos complementary to the ends of neighboring DNA parts, a thermostable ligase to join DNA backbones, and multiple denaturation-annealing-ligation temperature cycles to assemble complex DNA constructs. The efficiency of LCR assembly was improved ca. 4-fold using designed optimization experiments and response surface methodology. Under these optimized conditions, LCR enabled one-step assembly of up to 20 DNA parts and up to 20 kb DNA constructs with very few single-nucleotide polymorphisms (<1 per 25 kb) and insertions/deletions (<1 per 50 kb). Experimental comparison of various sequence-independent DNA assembly methods showed that circular polymerase extension cloning (CPEC) and Gibson isothermal assembly did not enable assembly of more than four DNA parts with more than 50% of clones being correct. Yeast homologous recombination and LCR both enabled reliable assembly of up to 12 DNA parts with 60-100% of individual clones being correct, but LCR assembly provides a much faster and easier workflow than yeast homologous recombination. LCR combines reliable assembly of many DNA parts via a cheap, rapid, and convenient workflow and thereby outperforms existing DNA assembly methods. LCR assembly is expected to become the method of choice for both manual and automated high-throughput assembly of DNA parts into DNA constructs.

Genome-wide transcriptional responses of two metal-tolerant symbiotic Mesorhizobium isolates to zinc and cadmium exposure.

BACKGROUND: Mesorhizobium metallidurans STM 2683T and Mesorhizobium sp. strain STM 4661 were isolated from nodules of the metallicolous legume Anthyllis vulneraria from distant mining spoils. They tolerate unusually high Zinc and Cadmium concentrations as compared to other mesorhizobia. This work aims to study the gene expression profiles associated with Zinc or Cadmium exposure and to identify genes involved in metal tolerance in these two metallicolous Mesorhizobium strains of interest for mine phytostabilization purposes. RESULTS: The draft genomes of the two Mezorhizobium strains were sequenced and used to map RNAseq data obtained after Zinc or Cadmium stresses. Comparative genomics and transcriptomics allowed the rapid discovery of metal-specific or/and strain-specific genes. Respectively 1.05% (72/6,844) and 0.97% (68/6,994) predicted Coding DNA Sequences (CDS) for STM 2683 and STM 4661 were significantly differentially expressed upon metal exposure. Among these, a significant number of CDS involved in transport (13/72 and 13/68 for STM 2683 and STM 4661, respectively) and sequestration (15/72 and 16/68 for STM 2683 and STM 4661, respectively) were identified. Thirteen CDS presented homologs in both strains and were differentially regulated by Zinc and/or Cadmium. For instance, several PIB-type ATPases and genes likely to participate in metal sequestration were identified. Among the conserved CDS that showed differential regulation in the two isolates, we also found znuABC homologs encoding for a high affinity ABC-type Zinc import system probably involved in Zinc homeostasis. Additionally, global analyses suggested that both metals also repressed significantly the translational machinery. CONCLUSIONS: The comparative RNAseq-based approach revealed a relatively low number of genes significantly regulated in the two Mesorhizobium strains. Very few of them were involved in the non-specific metal response, indicating that the approach was well suited for identifying genes that specifically respond to Zinc and Cadmium. Among significantly up-regulated genes, several encode metal efflux and sequestration systems which can be considered as the most widely represented mechanisms of rhizobial metal tolerance. Downstream functional studies will increase successful phytostabilization strategies by selecting appropriate metallicolous rhizobial partners.

Core and panmetabolism in Escherichia coli.

Escherichia coli exhibits a wide range of lifestyles encompassing commensalism and various pathogenic behaviors which its highly dynamic genome contributes to develop. How environmental and host factors shape the genetic structure of E. coli strains remains, however, largely unknown. Following a previous study of E. coli genomic diversity, we investigated its diversity at the metabolic level by building and analyzing the genome-scale metabolic networks of 29 E. coli strains (8 commensal and 21 pathogenic strains, including 6 Shigella strains). Using a tailor-made reconstruction strategy, we significantly improved the completeness and accuracy of the metabolic networks over default automatic reconstruction processes. Among the 1,545 reactions forming E. coli panmetabolism, 885 reactions were common to all strains. This high proportion of core reactions (57%) was found to be in sharp contrast to the low proportion (13%) of core genes in the E. coli pangenome, suggesting less diversity of metabolic functions compared to that of all gene functions. Core reactions were significantly overrepresented among biosynthetic reactions compared to the more variable degradation processes. Differences between metabolic networks were found to follow E. coli phylogeny rather than pathogenic phenotypes, except for Shigella networks, which were significantly more distant from the others. This suggests that most metabolic changes in non-Shigella strains were not driven by their pathogenic phenotypes. Using a supervised method, we were yet able to identify small sets of reactions related to pathogenicity or commensalism. The quality of our reconstructed networks also makes them reliable bases for building metabolic models.

Acinetobacter baylyi ADP1 as a model for metabolic system biology.

Information produced by the annotation of an 'average bacterial genome' can be separated into three parts. One-third represents what we know, another third what we think we know, and the last third what we know we do not know. Knowledge of metabolism is also described by this three thirds rule. Understanding how a cell operates will require a better knowledge of the two ignored thirds of its parts. Moreover, metabolism needs to be further investigated using organisms whose life styles are different from those of model organisms. In this short review, we present Acinetobacter baylyi ADP1 as an environmental model especially suitable for large-scale genetic manipulation. Resources have been constructed in the past few years that can form the basis for diverse metabolic studies: the genome sequence, a single gene mutant collection, and a genome-scale metabolic model.

Genome-scale models of bacterial metabolism: reconstruction and applications.

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.

Iterative reconstruction of a global metabolic model of Acinetobacter baylyi ADP1 using high-throughput growth phenotype and gene essentiality data.

BACKGROUND: Genome-scale metabolic models are powerful tools to study global properties of metabolic networks. They provide a way to integrate various types of biological information in a single framework, providing a structured representation of available knowledge on the metabolism of the respective species. RESULTS: We reconstructed a constraint-based metabolic model of Acinetobacter baylyi ADP1, a soil bacterium of interest for environmental and biotechnological applications with large-spectrum biodegradation capabilities. Following initial reconstruction from genome annotation and the literature, we iteratively refined the model by comparing its predictions with the results of large-scale experiments: (1) high-throughput growth phenotypes of the wild-type strain on 190 distinct environments, (2) genome-wide gene essentialities from a knockout mutant library, and (3) large-scale growth phenotypes of all mutant strains on 8 minimal media. Out of 1412 predictions, 1262 were initially consistent with our experimental observations. Inconsistencies were systematically examined, leading in 65 cases to model corrections. The predictions of the final version of the model, which included three rounds of refinements, are consistent with the experimental results for (1) 91% of the wild-type growth phenotypes, (2) 94% of the gene essentiality results, and (3) 94% of the mutant growth phenotypes. To facilitate the exploitation of the metabolic model, we provide a web interface allowing online predictions and visualization of results on metabolic maps. CONCLUSION: The iterative reconstruction procedure led to significant model improvements, showing that genome-wide mutant phenotypes on several media can significantly facilitate the transition from genome annotation to a high-quality model.

A complete collection of single-gene deletion mutants of Acinetobacter baylyi ADP1.

We have constructed a collection of single-gene deletion mutants for all dispensable genes of the soil bacterium Acinetobacter baylyi ADP1. A total of 2594 deletion mutants were obtained, whereas 499 (16%) were not, and are therefore candidate essential genes for life on minimal medium. This essentiality data set is 88% consistent with the Escherichia coli data set inferred from the Keio mutant collection profiled for growth on minimal medium, while 80% of the orthologous genes described as essential in Pseudomonas aeruginosa are also essential in ADP1. Several strategies were undertaken to investigate ADP1 metabolism by (1) searching for discrepancies between our essentiality data and current metabolic knowledge, (2) comparing this essentiality data set to those from other organisms, (3) systematic phenotyping of the mutant collection on a variety of carbon sources (quinate, 2-3 butanediol, glucose, etc.). This collection provides a new resource for the study of gene function by forward and reverse genetic approaches and constitutes a robust experimental data source for systems biology approaches.