Ten years of pan-genome analyses

Microarray long oligo probe designing for Escherichia coli: an in-silico DNA marker extraction

INTRODUCTION

Urinary tract infections are predominant diseases which may be caused by different pathogenic microorganisms, particularly Escherichia coli (E.coli). DNA microarray technology is an accurate, rapid, sensitive, and specific diagnostic tool which may lead to definite diagnosis and treatment of several infectious diseases. DNA microarray is a multi-process method in which probe designing plays an important. Therefore, the authors of the present study have tried to design a range of effective and proper long oligo microarray probes for detection and identification of different strains of pathogenic E.coli and in particular, uropathogenic E.coli (UPEC).

MATERIAL AND METHODS

E.coli O26 H11 11368 uid41021 was selected as the standard strain for probe designing. This strain encompasses the largest nucleotide sequence and the most number of genes among other pathogenic strains of E.coli. For performing this in silico survey, NCBI database, GReview Server, PanSeq Server, Oligoanalyzer tool, and AlleleID 7.7 were used to design accurate, appropriate, effective, and flexible long oligo microarray probes. Moreover, the genome of E.coli and its closely related microorganisms were compared.

RESULTS

In this study, 15 long oligo microarray probes were designed for detecting and identifying different strains of E.coli such as UPEC. These probes possessed the best physico-chemical characteristics. The functional and structural properties of the designed probes were recognized by practical tools and softwares.

CONCLUSIONS

The use of reliable advanced technologies and methodologies for probe designing guarentees the high quality of microarray probes and makes DNA microarray technology more flexible and an effective diagnostic technique.

Update on Genomic Databases and Resources at the National Center for Biotechnology Information

The National Center for Biotechnology Information (NCBI), as a primary public repository of genomic sequence data, collects and maintains enormous amounts of heterogeneous data. Data for genomes, genes, gene expressions, gene variation, gene families, proteins, and protein domains are integrated with the analytical, search, and retrieval resources through the NCBI website, text-based search and retrieval system, provides a fast and easy way to navigate across diverse biological databases.Comparative genome analysis tools lead to further understanding of evolution processes quickening the pace of discovery. Recent technological innovations have ignited an explosion in genome sequencing that has fundamentally changed our understanding of the biology of living organisms. This huge increase in DNA sequence data presents new challenges for the information management system and the visualization tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data.

Genomic perspectives on the evolution and spread of bacterial pathogens

Since the first complete sequencing of a free-living organism, Haemophilus influenzae, genomics has been used to probe both the biology of bacterial pathogens and their evolution. Single-genome approaches provided information on the repertoire of virulence determinants and host-interaction factors, and, along with comparative analyses, allowed the proposal of hypotheses to explain the evolution of many of these traits. These analyses suggested many bacterial pathogens to be of relatively recent origin and identified genome degradation as a key aspect of host adaptation. The advent of very-high-throughput sequencing has allowed for detailed phylogenetic analysis of many important pathogens, revealing patterns of global and local spread, and recent evolution in response to pressure from therapeutics and the human immune system. Such analyses have shown that bacteria can evolve and transmit very rapidly, with emerging clones showing adaptation and global spread over years or decades. The resolution achieved with whole-genome sequencing has shown considerable benefits in clinical microbiology, enabling accurate outbreak tracking within hospitals and across continents. Continued large-scale sequencing promises many further insights into genetic determinants of drug resistance, virulence and transmission in bacterial pathogens.

The Dynamics of Genetic Interactions between Vibrio metoecus and Vibrio cholerae, Two Close Relatives Co-Occurring in the Environment

Vibrio metoecus is the closest relative of Vibrio cholerae, the causative agent of the potent diarrheal disease cholera. Although the pathogenic potential of this new species is yet to be studied in depth, it has been co-isolated with V. cholerae in coastal waters and found in clinical specimens in the United States. We used these two organisms to investigate the genetic interaction between closely related species in their natural environment. The genomes of 20 V. cholerae and 4 V. metoecus strains isolated from a brackish coastal pond on the US east coast, as well as 4 clinical V. metoecus strains were sequenced and compared with reference strains. Whole genome comparison shows 86-87% average nucleotide identity (ANI) in their core genes between the two species. On the other hand, the chromosomal integron, which occupies approximately 3% of their genomes, shows higher conservation in ANI between species than any other region of their genomes. The ANI of 93-94% observed in this region is not significantly greater within than between species, meaning that it does not follow species boundaries. Vibrio metoecus does not encode toxigenic V. cholerae major virulence factors, the cholera toxin and toxin-coregulated pilus. However, some of the pathogenicity islands found in pandemic V. cholerae were either present in the common ancestor it shares with V. metoecus, or acquired by clinical and environmental V. metoecus in partial fragments. The virulence factors of V. cholerae are therefore both more ancient and more widespread than previously believed. There is high interspecies recombination in the core genome, which has been detected in 24% of the single-copy core genes, including genes involved in pathogenicity. Vibrio metoecus was six times more often the recipient of DNA from V. cholerae as it was the donor, indicating a strong bias in the direction of gene transfer in the environment.

Structural and Computational Biology in the Design of Immunogenic Vaccine Antigens

Vaccination is historically one of the most important medical interventions for the prevention of infectious disease. Previously, vaccines were typically made of rather crude mixtures of inactivated or attenuated causative agents. However, over the last 10–20 years, several important technological and computational advances have enabled major progress in the discovery and design of potently immunogenic recombinant protein vaccine antigens. Here we discuss three key breakthrough approaches that have potentiated structural and computational vaccine design. Firstly, genomic sciences gave birth to the field of reverse vaccinology, which has enabled the rapid computational identification of potential vaccine antigens. Secondly, major advances in structural biology, experimental epitope mapping, and computational epitope prediction have yielded molecular insights into the immunogenic determinants defining protective antigens, enabling their rational optimization. Thirdly, and most recently, computational approaches have been used to convert this wealth of structural and immunological information into the design of improved vaccine antigens. This review aims to illustrate the growing power of combining sequencing, structural and computational approaches, and we discuss how this may drive the design of novel immunogens suitable for future vaccines urgently needed to increase the global prevention of infectious disease.

MinION nanopore sequencing of an influenza genome

Influenza epidemics and pandemics have significant impacts on economies, morbidity and mortality worldwide. The ability to rapidly and accurately sequence influenza viruses is instrumental in the prevention and mitigation of influenza. All eight influenza genes from an influenza A virus were amplified by PCR simultaneously and then subjected to sequencing on a MinION nanopore sequencer. A complete influenza virus genome was obtained that shared greater than 99% identity with sequence data obtained from Illumina MiSeq and traditional Sanger-sequencing. The laboratory infrastructure and computing resources used to perform this experiment on the MinION nanopore sequencer would be available in most molecular laboratories around the world. Using this system, the concept of portability, and thus sequencing influenza viruses in the clinic or field is now tenable.

Pan-Tetris: an interactive visualisation for Pan-genomes

Background

Large-scale genome projects have paved the way to microbial pan-genome analyses. Pan-genomes describe the union of all genes shared by all members of the species or taxon under investigation. They offer a framework to assess the genomic diversity of a given collection of individual genomes and moreover they help to consolidate gene predictions and annotations. The computation of pan-genomes is often a challenge, and many techniques that use a global alignment-independent approach run the risk of not separating paralogs from orthologs. Also alignment-based approaches which take the gene neighbourhood into account often need additional manual curation of the results. This is quite time consuming and so far there is no visualisation tool available that offers an interactive GUI for the pan-genome to support curating pan-genomic computations or annotations of orthologous genes.

Results

We introduce Pan-Tetris, a Java based interactive software tool that provides a clearly structured and suitable way for the visual inspection of gene occurrences in a pan-genome table. The main features of Pan-Tetris are a standard coordinate based presentation of multiple genomes complemented by easy to use tools compensating for algorithmic weaknesses in the pan-genome generation workflow. We demonstrate an application of Pan-Tetris to the pan-genome of Staphylococcus aureus.

Conclusions

Pan-Tetris is currently the only interactive pan-genome visualisation tool. Pan-Tetris is available from http://bit.ly/1vVxYZT

A novel method of consensus pan-chromosome assembly and large-scale comparative analysis reveal the highly flexible pan-genome of Acinetobacter baumannii

Background

Infections by pan-drug resistant Acinetobacter baumannii plague military and civilian healthcare systems. Previous A. baumannii pan-genomic studies used modest sample sizes of low diversity and comparisons to a single reference genome, limiting our understanding of gene order and content. A consensus representation of multiple genomes will provide a better framework for comparison. A large-scale comparative study will identify genomic determinants associated with their diversity and adaptation as a successful pathogen.

Results

We determine draft-level genomic sequence of 50 diverse military isolates and conduct the largest bacterial pan-genome analysis of 249 genomes. The pan-genome of A. baumannii is open when the input genomes are normalized for diversity with 1867 core proteins and a paralog-collapsed pan-genome size of 11,694 proteins. We developed a novel graph-based algorithm and use it to assemble the first consensus pan-chromosome, identifying both the order and orientation of core genes and flexible genomic regions. Comparative genome analyses demonstrate the existence of novel resistance islands and isolates with increased numbers of resistance island insertions over time, from single insertions in the 1950s to triple insertions in 2011. Gene clusters responsible for carbon utilization, siderophore production, and pilus assembly demonstrate frequent gain or loss among isolates.

Conclusions

The highly variable and dynamic nature of the A. baumannii genome may be the result of its success in rapidly adapting to both abiotic and biotic environments through the gain and loss of gene clusters controlling fitness. Importantly, some archaic adaptation mechanisms appear to have reemerged among recent isolates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0701-6) contains supplementary material, which is available to authorized users.

Roary: rapid large-scale prokaryote pan genome analysis

Summary: A typical prokaryote population sequencing study can now consist of hundreds or thousands of isolates. Interrogating these datasets can provide detailed insights into the genetic structure of prokaryotic genomes. We introduce Roary, a tool that rapidly builds large-scale pan genomes, identifying the core and accessory genes. Roary makes construction of the pan genome of thousands of prokaryote samples possible on a standard desktop without compromising on the accuracy of results. Using a single CPU Roary can produce a pan genome consisting of 1000 isolates in 4.5 hours using 13 GB of RAM, with further speedups possible using multiple processors.

Availability and implementation: Roary is implemented in Perl and is freely available under an open source GPLv3 license from http://sanger-pathogens.github.io/Roary

Contact:roary@sanger.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Measurably evolving pathogens in the genomic era

Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of 'measurably evolving populations' and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. We argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale, and we highlight important analytical challenges to be overcome to infer pathogen population dynamics from genomic data.

Phytopathogen emergence in the genomics era

Phytopathogens are a global threat to plant agriculture and biodiversity. The genomics era has lead to an exponential rise in comparative gene and genome studies of both economically significant and insignificant microorganisms. In this review we highlight some recent comparisons and discuss how they identify shared genes or genomic regions associated with host virulence. The two major mechanisms of rapid genome adaptation - horizontal gene transfer and hybridisation - are reviewed and we consider how intra-specific pan-genome sequences encode alternative host specificity. We also discuss the power that access to expansive gene databases provides in aiding the study of phytopathogen emergence. These databases can rapidly enable the identification of an unknown pathogen and its origin, as well as genomic adaptations required for emergence.

The advent of genome-wide association studies for bacteria

Significant advances in sequencing technologies and genome-wide association studies (GWAS) have revealed substantial insight into the genetic architecture of human phenotypes. In recent years, the application of this approach in bacteria has begun to reveal the genetic basis of bacterial host preference, antibiotic resistance, and virulence. Here, we consider relevant differences between bacterial and human genome dynamics, apply GWAS to a global sample of Mycobacterium tuberculosis genomes to highlight the impacts of linkage disequilibrium, population stratification, and natural selection, and finally compare the traditional GWAS against phyC, a contrasting method of mapping genotype to phenotype based upon evolutionary convergence. We discuss strengths and weaknesses of both methods, and make suggestions for factors to be considered in future bacterial GWAS.

A brief review of software tools for pangenomics

Since the proposal for pangenomic study, there have been a dozen software tools actively in use for pangenomic analysis. By the end of 2014, Panseq and the pan-genomes analysis pipeline (PGAP) ranked as the top two most popular packages according to cumulative citations of peer-reviewed scientific publications. The functions of the software packages and tools, albeit variable among them, include categorizing orthologous genes, calculating pangenomic profiles, integrating gene annotations, and constructing phylogenies. As epigenomic elements are being gradually revealed in prokaryotes, it is expected that pangenomic databases and toolkits have to be extended to handle information of detailed functional annotations for genes and non-protein-coding sequences including non-coding RNAs, insertion elements, and conserved structural elements. To develop better bioinformatic tools, user feedback and integration of novel features are both of essence.