In Silico Genomic Fingerprints of the Bacillus anthracis Group Obtained by Virtual Hybridization

Phylogenomic study and classification of mitochondrial DNA through virtual genomic fingerprints

In the present study, we evaluated the ability of the Virtual Analysis Method for Phylogenomic fingerprint Estimation (VAMPhyRE) toolkit to classify human mitochondrial DNA (mtDNA) haplogroups. In total, 357 random mtDNA sequences were obtained from different haplogroups, based on the classification of PhyloTree. Additionally, we included a control group of five sequences (Pan paniscus, Pan troglodytes, Homo sapiens neanderthalensis, Yoruba15, and the revised Cambridge reference sequence). VAMPhyRE employs a virtual hybridization technique, using probes that specifically bind to their complementary sequences in the genome. We used 65,536 probes of 8 nucleotides to identify potential sites where hybridization occurs between the mtDNA and the specific probe, forming different heteroduplexes and thus, creating a unique and specific genomic fingerprint for each sequence. Genomic fingerprints were compared, and a table of distances was calculated to obtain a mitochondrial phylogenomic tree with the macrohaplogroups, L, N, M, and R, and their corresponding haplogroups, according to universal nomenclature. The results obtained suggest an accuracy of 97.25% for the distribution of the 357 mtDNA sequences in the four macrohaplogroups and their corresponding haplogroups when compared with other mtDNA classification tools that require reference sequences and do not offer an analysis based on an evolutionary approach. These data are available online at http://biomedbiotec.encb.ipn.mx/VAMPhyRE/.

Whole Genome Sequence and Phylogenetic Analysis Show Helicobacter pylori Strains from Latin America Have Followed a Unique Evolution Pathway

Helicobacter pylori (HP) genetics may determine its clinical outcomes. Despite high prevalence of HP infection in Latin America (LA), there have been no phylogenetic studies in the region. We aimed to understand the structure of HP populations in LA mestizo individuals, where gastric cancer incidence remains high. The genome of 107 HP strains from Mexico, Nicaragua and Colombia were analyzed with 59 publicly available worldwide genomes. To study bacterial relationship on whole genome level we propose a virtual hybridization technique using thousands of high-entropy 13 bp DNA probes to generate fingerprints. Phylogenetic virtual genome fingerprint (VGF) was compared with Multi Locus Sequence Analysis (MLST) and with phylogenetic analyses of cagPAI virulence island sequences. With MLST some Nicaraguan and Mexican strains clustered close to Africa isolates, whereas European isolates were spread without clustering and intermingled with LA isolates. VGF analysis resulted in increased resolution of populations, separating European from LA strains. Furthermore, clusters with exclusively Colombian, Mexican, or Nicaraguan strains were observed, where the Colombian cluster separated from Europe, Asia, and Africa, while Nicaraguan and Mexican clades grouped close to Africa. In addition, a mixed large LA cluster including Mexican, Colombian, Nicaraguan, Peruvian, and Salvadorian strains was observed; all LA clusters separated from the Amerind clade. With cagPAI sequence analyses LA clades clearly separated from Europe, Asia and Amerind, and Colombian strains formed a single cluster. A NeighborNet analyses suggested frequent and recent recombination events particularly among LA strains. Results suggests that in the new world, H. pylori has evolved to fit mestizo LA populations, already 500 years after the Spanish colonization. This co-adaption may account for regional variability in gastric cancer risk.

Computational Modeling and Analysis of Microarray Data: New Horizons

High-throughput microarray technologies have long been a source of data for a wide range of biomedical investigations. Over the decades, variants have been developed and sophistication of measurements has improved, with generated data providing both valuable insight and considerable analytical challenge. The cost-effectiveness of microarrays, as well as their fundamental applicability, made them a first choice for much early genomic research and efforts to improve accessibility, quality and interpretation have continued unabated. In recent years, however, the emergence of new generations of sequencing methods and, importantly, reduction of costs, has seen a preferred shift in much genomic research to the use of sequence data, both less ‘noisy’ and, arguably, with species information more directly targeted and easily interpreted. Nevertheless, new microarray data are still being generated and, together with their considerable legacy, can offer a complementary perspective on biological systems and disease pathogenesis. The challenge now is to exploit novel methods for enhancing and combining these data with those generated by alternative high-throughput techniques, such as sequencing, to provide added value. Augmentation and integration of microarray data and the new horizons this opens up, provide the theme for the papers in this Special Issue.