Bacterial genome sequencing

Complex natural product production methods and options

Natural products have had a major impact upon quality of life, with antibiotics as a classic example of having a transformative impact upon human health. In this contribution, we will highlight both historic and emerging methods of natural product bio-manufacturing. Traditional methods of natural product production relied upon native cellular host systems. In this context, pragmatic and effective methodologies were established to enable widespread access to natural products. In reviewing such strategies, we will also highlight the development of heterologous natural product biosynthesis, which relies instead on a surrogate host system theoretically capable of advanced production potential. In comparing native and heterologous systems, we will comment on the base organisms used for natural product biosynthesis and how the properties of such cellular hosts dictate scaled engineering practices to facilitate compound distribution. In concluding the article, we will examine novel efforts in production practices that entirely eliminate the constraints of cellular production hosts. That is, cell free production efforts will be introduced and reviewed for the purpose of complex natural product biosynthesis. Included in this final analysis will be research efforts made on our part to test the cell free biosynthesis of the complex polyketide antibiotic natural product erythromycin.

White biotechnology: State of the art strategies for the development of biocatalysts for biorefining

White biotechnology is a term that is now often used to describe the implementation of biotechnology in the industrial sphere. Biocatalysts (enzymes and microorganisms) are the key tools of white biotechnology, which is considered to be one of the key technological drivers for the growing bioeconomy. Biocatalysts are already present in sectors such as the chemical and agro-food industries, and are used to manufacture products as diverse as antibiotics, paper pulp, bread or advanced polymers. This review proposes an original and global overview of highly complementary fields of biotechnology at both enzyme and microorganism level. A certain number of state of the art approaches that are now being used to improve the industrial fitness of biocatalysts particularly focused on the biorefinery sector are presented. The first part deals with the technologies that underpin the development of industrial biocatalysts, notably the discovery of new enzymes and enzyme improvement using directed evolution techniques. The second part describes the toolbox available by the cell engineer to shape the metabolism of microorganisms. And finally the last part focuses on the 'omic' technologies that are vital for understanding and guide microbial engineering toward more efficient microbial biocatalysts. Altogether, these techniques and strategies will undoubtedly help to achieve the challenging task of developing consolidated bioprocessing (i.e. CBP) readily available for industrial purpose.

Genome sequence of Pseudomonas putida Idaho, a unique organic-solvent-tolerant bacterium

Pseudomonas putida Idaho is an organic-solvent-tolerant strain which can degrade and adapt to high concentrations of organic solvents. Here, we announce its first draft genome sequence (6,363,067 bp). We annotated 192 coding sequences (CDSs) responsible for aromatic compound metabolism, 40 CDSs encoding phospholipid synthesis, and 212 CDSs related to stress response.

A c-type cytochrome and a transcriptional regulator responsible for enhanced extracellular electron transfer in Geobacter sulfurreducens revealed by adaptive evolution

The stimulation of subsurface microbial metabolism often associated with engineered bioremediation of groundwater contaminants presents subsurface microorganisms, which are adapted for slow growth and metabolism in the subsurface, with new selective pressures. In order to better understand how Geobacter species might adapt to selective pressure for faster metal reduction in the subsurface, Geobacter sulfurreducens was put under selective pressure for rapid Fe(III) oxide reduction. The genomes of two resultant strains with rates of Fe(III) oxide reduction that were 10-fold higher than those of the parent strain were resequenced. Both strains contain either a single base-pair change or a 1 nucleotide insertion in a GEMM riboswitch upstream of GSU1761, a gene coding for the periplasmic c-type cytochrome designated PgcA. GSU1771, a gene coding for a SARP regulator, was also mutated in both strains. Introduction of either of the GEMM riboswitch mutations upstream of pgcA in the wild-type increased the abundance of pgcA transcripts, consistent with increased expression of pgcA in the adapted strains. One of the mutations doubled the rate of Fe(III) oxide reduction. Interruption of GSU1771 doubled the Fe(III) oxide reduction rate. This was associated with an increased in expression of pilA, the gene encoding the structural protein for the pili thought to function as microbial nanowires. The combination of the GSU1771 interruption with either of the pgcA mutations resulted in a strain that reduced Fe(III) as fast as the comparable adapted strain. These results suggest that the accumulation of a small number of beneficial mutations under selective pressure, similar to that potentially present during bioremediation, can greatly enhance the capacity for Fe(III) oxide reduction in G. sulfurreducens. Furthermore, the results emphasize the importance of the c-type cytochrome PgcA and pili in Fe(III) oxide reduction and demonstrate how adaptive evolution studies can aid in the elucidation of complex mechanisms, such as extracellular electron transfer.

Mutation detection with next-generation resequencing through a mediator genome

The affordability of next generation sequencing (NGS) is transforming the field of mutation analysis in bacteria. The genetic basis for phenotype alteration can be identified directly by sequencing the entire genome of the mutant and comparing it to the wild-type (WT) genome, thus identifying acquired mutations. A major limitation for this approach is the need for an a-priori sequenced reference genome for the WT organism, as the short reads of most current NGS approaches usually prohibit de-novo genome assembly. To overcome this limitation we propose a general framework that utilizes the genome of relative organisms as mediators for comparing WT and mutant bacteria. Under this framework, both mutant and WT genomes are sequenced with NGS, and the short sequencing reads are mapped to the mediator genome. Variations between the mutant and the mediator that recur in the WT are ignored, thus pinpointing the differences between the mutant and the WT. To validate this approach we sequenced the genome of Bdellovibrio bacteriovorus 109J, an obligatory bacterial predator, and its prey-independent mutant, and compared both to the mediator species Bdellovibrio bacteriovorus HD100. Although the mutant and the mediator sequences differed in more than 28,000 nucleotide positions, our approach enabled pinpointing the single causative mutation. Experimental validation in 53 additional mutants further established the implicated gene. Our approach extends the applicability of NGS-based mutant analyses beyond the domain of available reference genomes.

FINDSITE-metal: integrating evolutionary information and machine learning for structure-based metal-binding site prediction at the proteome level

The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this article, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal-binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal-binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal-binding sites are detected with the best predicted binding site at rank 1 and within the top two ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium, and magnesium ions, the binding metal can be predicted with high, typically 70% to 90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal-binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/.

The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement

Exhaustive exploration of molecular interactions at the level of complete proteomes requires efficient and reliable computational approaches to protein function inference. Ligand docking and ranking techniques show considerable promise in their ability to quantify the interactions between proteins and small molecules. Despite the advances in the development of docking approaches and scoring functions, the genome-wide application of many ligand docking/screening algorithms is limited by the quality of the binding sites in theoretical receptor models constructed by protein structure prediction. In this study, we describe a new template-based method for the local refinement of ligand-binding regions in protein models using remotely related templates identified by threading. We designed a Support Vector Regression (SVR) model that selects correct binding site geometries in a large ensemble of multiple receptor conformations. The SVR model employs several scoring functions that impose geometrical restraints on the Cα positions, account for the specific chemical environment within a binding site and optimize the interactions with putative ligands. The SVR score is well correlated with the RMSD from the native structure; in 47% (70%) of the cases, the Pearson's correlation coefficient is >0.5 (>0.3). When applied to weakly homologous models, the average heavy atom, local RMSD from the native structure of the top-ranked (best of top five) binding site geometries is 3.1Å (2.9Å) for roughly half of the targets; this represents a 0.1 (0.3)Å average improvement over the original predicted structure. Focusing on the subset of strongly conserved residues, the average heavy atom RMSD is 2.6Å (2.3Å). Furthermore, we estimate the upper bound of template-based binding site refinement using only weakly related proteins to be ∼2.6Å RMSD. This value also corresponds to the plasticity of the ligand-binding regions in distant homologues. The Binding Site Refinement (BSR) approach is available to the scientific community as a web server that can be accessed at http://cssb.biology.gatech.edu/bsr/.

High-resolution typing by integration of genome sequencing data in a large tuberculosis cluster

To investigate whether genome sequencing yields more useful markers than those currently used to study the epidemiology of tuberculosis, it was applied to three Mycobacterium tuberculosis isolates of the Harlingen outbreak. Our findings suggest that single nucleotide polymorphisms can be used to identify transmission chains in restriction fragment length polymorphism clusters.

The next-generation sequencing technology and application

As one of the key technologies in biomedical research, DNA sequencing has not only improved its productivity with an exponential growth rate but also been applied to new areas of application over the past few years. This is largely due to the advent of newer generations of sequencing platforms, offering ever-faster and cheaper ways to analyze sequences. In our previous review, we looked into technical characteristics of the next-generation sequencers and provided prospective insights into their future development. In this article, we present a brief overview of the advantages and shortcomings of key commercially available platforms with a focus on their suitability for a broad range of applications.

The human superorganism - of microbes and men

Albert Einstein once said that "The true value of a human being can be found in the degree to which he has attained liberation from the self". For years our traditional view of 'self' was restricted to our own bodies; composed of eukaryote cells encoded by our genome. However, in the era of omics technologies and systems biology, this view now extends beyond the traditional limitations of our own core being to include our resident microbial communities. These prokaryote cells outnumber our own cells by a factor of ten and contain at least ten times more DNA than our own genome. In exchange for food and shelter, this symbiont provides us, the host, with metabolic functions far beyond the scope of our own physiological capabilities. In this respect the human body can be considered a superorganism; a communal group of human and microbial cells all working for the benefit of the collective - a view which most certainly attains liberation from self.

Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison

The pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH). While enabling the taxonomist, in principle, to obtain an estimate of the overall similarity between the genomes of two strains, this technique is tedious and error-prone and cannot be used to incrementally build up a comparative database. Recent technological progress in the area of genome sequencing calls for bioinformatics methods to replace the wet-lab DDH by in-silico genome-to-genome comparison. Here we investigate state-of-the-art methods for inferring whole-genome distances in their ability to mimic DDH. Algorithms to efficiently determine high-scoring segment pairs or maximally unique matches perform well as a basis of inferring intergenomic distances. The examined distance functions, which are able to cope with heavily reduced genomes and repetitive sequence regions, outperform previously described ones regarding the correlation with and error ratios in emulating DDH. Simulation of incompletely sequenced genomes indicates that some distance formulas are very robust against missing fractions of genomic information. Digitally derived genome-to-genome distances show a better correlation with 16S rRNA gene sequence distances than DDH values. The future perspectives of genome-informed taxonomy are discussed, and the investigated methods are made available as a web service for genome-based species delineation.

The extracellular biology of the lactobacilli

Lactobacilli belong to the lactic acid bacteria, which play a key role in industrial and artisan food raw-material fermentation, including a large variety of fermented dairy products. Next to their role in fermentation processes, specific strains of Lactobacillus are currently marketed as health-promoting cultures or probiotics. The last decade has witnessed the completion of a large number of Lactobacillus genome sequences, including the genome sequences of some of the probiotic species and strains. This development opens avenues to unravel the Lactobacillus-associated health-promoting activity at the molecular level. It is generally considered likely that an important part of the Lactobacillus effector molecules that participate in the proposed health-promoting interactions with the host (intestinal) system resides in the bacterial cell envelope. For this reason, it is important to accurately predict the Lactobacillus exoproteomes. Extensive annotation of these exoproteomes, combined with comparative analysis of species- or strain-specific exoproteomes, may identify candidate effector molecules, which may support specific effects on host physiology associated with particular Lactobacillus strains. Candidate health-promoting effector molecules of lactobacilli can then be validated via mutant approaches, which will allow for improved strain selection procedures, improved product quality control criteria and molecular science-based health claims.

Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations

Escherichia coli strains that have evolved in the laboratory in response to lactate minimal media show a wide range of different genetic adaptations.

Background

Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes.

Results

In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains. This mutation conferred an approximately 15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in an approximately 30% increase to growth rate when introduced to a background already harboring two adaptive mutations. Additionally, most endpoints had a mutation in a regulatory gene (crp or relA, for example) or the RNA polymerase.

Conclusions

The 82 base-pair deletion found in the rph-pyrE operon of many endpoints may function to relieve a pyrimidine biosynthesis defect present in MG1655. In contrast, a variety of regulators acquire mutations in the different endpoints, suggesting flexibility in overcoming regulatory challenges in the adaptation.