Barry G. Hall

Building Phylogenetic Trees from Molecular Data with MEGA

Phylogenetic analysis is sometimes regarded as being an intimidating, complex process that requires expertise and years of experience. In fact, it is a fairly straightforward process that can be learned quickly and applied effectively. This Protocol describes the several steps required to produce a phylogenetic tree from molecular data for novices. In the example illustrated here, the program MEGA is used to implement all those steps, thereby eliminating the need to learn several programs, and to deal with multiple file formats from one step to another (Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. 2011. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 28:2731-2739). The first step, identification of a set of homologous sequences and downloading those sequences, is implemented by MEGAs own browser built on top of the Google Chrome toolkit. For the second step, alignment of those sequences, MEGA offers two different algorithms: ClustalW and MUSCLE. For the third step, construction of a phylogenetic tree from the aligned sequences, MEGA offers many different methods. Here we illustrate the maximum likelihood method, beginning with MEGAs Models feature, which permits selecting the most suitable substitution model. Finally, MEGA provides a powerful and flexible interface for the final step, actually drawing the tree for publication. Here a step-by-step protocol is presented in sufficient detail to allow a novice to start with a sequence of interest and to build a publication-quality tree illustrating the evolution of an appropriate set of homologs of that sequence. MEGA is available for use on PCs and Macs from www.megasoftware.net.

When Whole-Genome Alignments Just Won't Work: kSNP v2 Software for Alignment-Free SNP Discovery and Phylogenetics of Hundreds of Microbial Genomes

Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four “raw read” genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths.

A pseudouridine synthase required for the formation of two universally conserved pseudouridines in ribosomal RNA is essential for normal growth of Escherichia coli

Escherichia coli rRNA contains 10 pseudouridines of unknown function. They are made by synthases, each of which is specific for one or more pseudouridines. Here we show that the sfhB (yfil) ORF of E. coli is a pseudouridine synthase gene by cloning, protein overexpression, and reaction in vitro with rRNA transcripts. Gene disruption by miniTn10(cam) insertion revealed that this synthase gene, here renamed rluD, codes for a synthase which is solely responsible in vivo for synthesis of the three pseudouridines clustered in a stem-loop at positions 1911, 1915, and 1917 of 23S RNA. The absence of RluD results in severe growth inhibition. Both the absence of pseudouridine and the growth defect could be reversed by insertion of a plasmid carrying the rluD gene into the mutant cell, clearly linking both effects to the absence of RIuD. This is the first report of a major physiological defect due to the deletion of any pseudouridine synthase. Growth inhibition may be due to the lack of one or more of the 23S RNA pseudouridines made by this synthase since pseudouridines 1915 and 1917 are universally conserved and are located in proximity to the decoding center of the ribosome where they could be involved in modulating codon recognition.

Growth Rates Made Easy

In the 1960s-1980s, determination of bacterial growth rates was an important tool in microbial genetics, biochemistry, molecular biology, and microbial physiology. The exciting technical developments of the 1990s and the 2000s eclipsed that tool; as a result, many investigators today lack experience with growth rate measurements. Recently, investigators in a number of areas have started to use measurements of bacterial growth rates for a variety of purposes. Those measurements have been greatly facilitated by the availability of microwell plate readers that permit the simultaneous measurements on up to 384 different cultures. Only the exponential (logarithmic) portions of the resulting growth curves are useful for determining growth rates, and manual determination of that portion and calculation of growth rates can be tedious for high-throughput purposes. Here, we introduce the program GrowthRates that uses plate reader output files to automatically determine the exponential portion of the curve and to automatically calculate the growth rate, the maximum culture density, and the duration of the growth lag phase. GrowthRates is freely available for Macintosh, Windows, and Linux. We discuss the effects of culture volume, the classical bacterial growth curve, and the differences between determinations in rich media and minimal (mineral salts) media. This protocol covers calibration of the plate reader, growth of culture inocula for both rich and minimal media, and experimental setup. As a guide to reliability, we report typical day-to-day variation in growth rates and variation within experiments with respect to position of wells within the plates.

kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome

UNLABELLED We announce the release of kSNP3.0, a program for SNP identification and phylogenetic analysis without genome alignment or the requirement for reference genomes. kSNP3.0 is a significantly improved version of kSNP v2. AVAILABILITY AND IMPLEMENTATION kSNP3.0 is implemented as a package of stand-alone executables for Linux and Mac OS X under the open-source BSD license. The executable packages, source code and a full User Guide are freely available at https://sourceforge.net/projects/ksnp/files/ CONTACT barryghall@gmail.com.

Origin and Evolution of the AmpC β-Lactamases of Citrobacter freundii

ABSTRACT To determine whether the widespread clinical use of β-lactams has been selective for Citrobacter freundii-derived alleles of plasmid ampC genes, we generated a Bayesian consensus phylogeny of the published ampC sequences and compared the MICs of 16 β-lactam antibiotics for Escherichia coli strains containing cloned copies of the C. freundii ampC alleles. We found that for the majority of compounds investigated, there has been essentially no increase in β-lactam resistance conferred by those alleles. We also found that ampC alleles from the chromosomes of two β-lactam-sensitive C. freundii strains isolated in the 1920s, before the clinical use of antibiotics, were as effective at providing β-lactam resistance in E. coli as were the plasmid-borne alleles from β-lactam-resistant clinical isolates. These results suggest that selection for increased resistance to β-lactam antibiotics has not been a significant force directing the evolution of the C. freundii ampC alleles found in β-lactam-resistant clinical isolates.

Predicting the evolution of antibiotic resistance genes

Antibiotic resistance is thought to evolve rapidly in response to antibiotic use. At present, we lack effective tools to assess how rapidly existing resistance genes are likely to evolve to yield resistance to newly introduced drugs. To address this problem, a method has been developed for in vitro evolution experiments to help predict how long it will take antibiotic resistance to arise — potentially allowing informed decisions about usage to be made.

Phylogenetic analysis shows that the OXA beta-lactamase genes have been on plasmids for millions of years.

The OXA genes encode a class of b-lactamases that confer resistance to a wide range of b-lactam antibiotics. To determine whether the diversity of the OXA b-lactamases is the result of recent or ancient events, and to determine whether mobilization of the OXA genes from chromosomes to plasmids occurred recently or long ago, we have constructed a Bayesian phylogeny of the OXA b-lactamase genes. Analysis of that phylogeny shows that much of the diversity is the result of ancient events and that the OXA genes were mobilized from chromosomes to plasmids on at least two independent occasions that occurred millions of years ago. That observation contradicts the commonly held impression that mobilization of antibiotic resistance genes is strictly the result of modern use of antibiotics.

Adaptive mutagenesis: a process that generates almost exclusively beneficial mutations

Adaptive mutations are spontaneous mutations that occur in microorganisms during periods of prolonged stress in non-dividing or very slowly dividing populations and that are specific to the environmental challenge that causes that stress. This article reviews the literature on adaptive mutagenesis since 1993. The evidence that adaptive mutagenesis is both real and general is considered. The most widely used system for studying adaptive mutagenesis, reversion of an F′-borne lacI33 allele, is shown to be a special case that reflects more about F-plasmid biology than about adaptive mutagenesis in general. New evidence demonstrating that adaptive mutagenesis is, indeed, specific is discussed. A variety of genes whose products affect adaptive mutagenesis are discussed. A model to explain that specificity and new evidence in support of that model are considered, as are potential roles of adaptive mutagenesis in evolution and practical aspects of adaptive mutagenesis.

Comparative Genomic Analyses of 17 Clinical Isolates of Gardnerella vaginalis Provide Evidence of Multiple Genetically Isolated Clades Consistent with Subspeciation into Genovars

Gardnerella vaginalis is associated with a spectrum of clinical conditions, suggesting high degrees of genetic heterogeneity among stains. Seventeen G. vaginalis isolates were subjected to a battery of comparative genomic analyses to determine their level of relatedness. For each measure, the degree of difference among the G. vaginalis strains was the highest observed among 23 pathogenic bacterial species for which at least eight genomes are available. Genome sizes ranged from 1.491 to 1.716 Mb; GC contents ranged from 41.18% to 43.40%; and the core genome, consisting of only 746 genes, makes up only 51.6% of each strains genome on average and accounts for only 27% of the species supragenome. Neighbor-grouping analyses, using both distributed gene possession data and core gene allelic data, each identified two major sets of strains, each of which is composed of two groups. Each of the four groups has its own characteristic genome size, GC ratio, and greatly expanded core gene content, making the genomic diversity of each group within the range for other bacterial species. To test whether these 4 groups corresponded to genetically isolated clades, we inferred the phylogeny of each distributed gene that was present in at least two strains and absent in at least two strains; this analysis identified frequent homologous recombination within groups but not between groups or sets. G. vaginalis appears to include four nonrecombining groups/clades of organisms with distinct gene pools and genomic properties, which may confer distinct ecological properties. Consequently, it may be appropriate to treat these four groups as separate species.