GenomeFingerprinter and universal genome fingerprint analysis for systematic comparative genomics

How to compare whole genome sequences at large scale has not been achieved via conventional methods based on pair-wisely base-to-base comparison; nevertheless, no attention was paid to handle in-one-sitting a number of genomes crossing genetic category (chromosome, plasmid, and phage) with farther divergences (much less or no homologous) over large size ranges (from Kbp to Mbp). We created a new method, GenomeFingerprinter, to unambiguously produce three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections to illustrate whole genome fingerprints. We further developed a set of concepts and tools and thereby established a new method, universal genome fingerprint analysis. We demonstrated their applications through case studies on over a hundred of genome sequences. Particularly, we defined the total genetic component configuration (TGCC) (i.e., chromosome, plasmid, and phage) for describing a strain as a system, and the universal genome fingerprint map (UGFM) of TGCC for differentiating a strain as a universal system, as well as the systematic comparative genomics (SCG) for comparing in-one-sitting a number of genomes crossing genetic category in diverse strains. By using UGFM, UGFM-TGCC, and UGFM-TGCC-SCG, we compared a number of genome sequences with farther divergences (chromosome, plasmid, and phage; bacterium, archaeal bacterium, and virus) over large size ranges (6Kbp~5Mbp), giving new insights into critical problematic issues in microbial genomics in the post-genomic era. This paper provided a new method for rapidly computing, geometrically visualizing, and intuitively comparing genome sequences at fingerprint level, and hence established a new method of universal genome fingerprint analysis for systematic comparative genomics.Comment: 63 pages, 15 figures, 5 table

Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected

Antimicrobial peptide expression in a wild tobacco plant reveals the limits of host-microbe-manipulations in the field

Plant-microbe associations are thought to be beneficial for plant growth and resistance against biotic or abiotic stresses, but for natural ecosystems, the ecological analysis of microbiome function remains in its infancy. We used transformed wild tobacco plants (Nicotiana attenuata) which constitutively express an antimicrobial peptide (Mc-AMP1) of the common ice plant, to establish an ecological tool for plant-microbe studies in the field. Transgenic plants showed in planta activity against plant-beneficial bacteria and were phenotyped within the plants´ natural habitat regarding growth, fitness and the resistance against herbivores. Multiple field experiments, conducted over 3 years, indicated no differences compared to isogenic controls. Pyrosequencing analysis of the root-associated microbial communities showed no major alterations but marginal effects at the genus level. Experimental infiltrations revealed a high heterogeneity in peptide tolerance among native isolates and suggests that the diversity of natural microbial communities can be a major obstacle for microbiome manipulations in nature

Shotgun metagenome data of a defined mock community using Oxford Nanopore, PacBio and Illumina technologies.

Metagenomic sequence data from defined mock communities is crucial for the assessment of sequencing platform performance and downstream analyses, including assembly, binning and taxonomic assignment. We report a comparison of shotgun metagenome sequencing and assembly metrics of a defined microbial mock community using the Oxford Nanopore Technologies (ONT) MinION, PacBio and Illumina sequencing platforms. Our synthetic microbial community BMock12 consists of 12 bacterial strains with genome sizes spanning 3.2-7.2 Mbp, 40-73% GC content, and 1.5-7.3% repeats. Size selection of both PacBio and ONT sequencing libraries prior to sequencing was essential to yield comparable relative abundances of organisms among all sequencing technologies. While the Illumina-based metagenome assembly yielded good coverage with few misassemblies, contiguity was greatly improved by both, Illumina + ONT and Illumina + PacBio hybrid assemblies but increased misassemblies, most notably in genomes with high sequence similarity to each other. Our resulting datasets allow evaluation and benchmarking of bioinformatics software on Illumina, PacBio and ONT platforms in parallel

Depression, Relationship Quality, and Couples’ Demand/Withdraw and Demand/Submit Sequential Interactions

This study investigated the associations among depression, relationship quality, and demand/withdraw and demand/submit behavior in couples’ conflict interactions. Two 10-min conflict interactions were coded for each couple (N = 97) using Structural Analysis of Social Behavior (SASB; Benjamin, 1979a, 1987, 2000a). Depression was assessed categorically (via the presence of depressive disorders) and dimensionally (via symptom reports). Results revealed that relationship quality was negatively associated with demanding behavior, as well as receiving submissive or withdrawing behavior from one’s partner. Relationship quality was positively associated with withdrawal. Demanding behavior was positively associated with women’s depression symptoms but negatively associated with men’s depression symptoms. Sequential analysis revealed couples’ behavior was highly stable across time. Initiation of demand/withdraw and demand/submit sequences were negatively associated with partners’ relationship adjustment. Female demand/male withdraw was positively associated with men’s depression diagnosis. Results underscore the importance of sequential analysis when investigating associations among depression, relationship quality, and couples’ interpersonal behavior