Günter Jäger

Genome-wide comparison of medieval and modern Mycobacterium leprae

Leprosy: Ancient and Modern In medieval Europe, leprosy was greatly feared: Sufferers had to wear bells and were shunned and kept isolated from society. Although leprosy largely disappeared from Europe in the 16th century, elsewhere in the world almost a quarter of a million cases are still reported annually, despite the availability of effective drugs. Schuenemann et al. (p. 179, published online 13 June; see the 14 June News story by Gibbons, p. 1278) probed the origins of leprosy bacilli by using a genomic capture-based approach on DNA obtained from skeletal remains from the 10th to 14th centuries. Because the unique mycolic acids of this mycobacterium protect its DNA, for one Danish sample over 100-fold, coverage of the genome was possible. Sequencing suggests a link between the middle-eastern and medieval European strains, which falls in line with social historical expectations that the returning expeditionary forces of antiquity originally spread the pathogen. Subsequently, Europeans took the bacterium westward to the Americas. Overall, ancient and modern strains remain remarkably similar, with no apparent loss of virulence genes, indicating it was most probably improvements in social conditions that led to leprosys demise in Europe. Five European individuals who lived during the Middle Ages provide a look backward at leprosy. Leprosy was endemic in Europe until the Middle Ages. Using DNA array capture, we have obtained genome sequences of Mycobacterium leprae from skeletons of five medieval leprosy cases from the United Kingdom, Sweden, and Denmark. In one case, the DNA was so well preserved that full de novo assembly of the ancient bacterial genome could be achieved through shotgun sequencing alone. The ancient M. leprae sequences were compared with those of 11 modern strains, representing diverse genotypes and geographic origins. The comparisons revealed remarkable genomic conservation during the past 1000 years, a European origin for leprosy in the Americas, and the presence of an M. leprae genotype in medieval Europe now commonly associated with the Middle East. The exceptional preservation of M. leprae biomarkers, both DNA and mycolic acids, in ancient skeletons has major implications for palaeomicrobiology and human pathogen evolution.

EAGER: efficient ancient genome reconstruction.

BackgroundThe automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process.ResultsHere we introduce EAGER, a time-efficient pipeline, which greatly simplifies the analysis of large-scale genomic data sets. EAGER provides features to preprocess, map, authenticate, and assess the quality of ancient DNA samples. Additionally, EAGER comprises tools to genotype samples to discover, filter, and analyze variants.ConclusionsEAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.

Parallel detection of ancient pathogens via array-based DNA capture

DNA capture coupled with next generation sequencing is highly suitable for the study of ancient pathogens. Screening for pathogens can, however, be meticulous when assays are restricted to the enrichment of single organisms, which is common practice. Here, we report on an array-based DNA capture screening technique for the parallel detection of nearly 100 pathogens that could have potentially left behind molecular signatures in preserved ancient tissues. We demonstrate the sensitivity of our method through evaluation of its performance with a library known to harbour ancient Mycobacterium leprae DNA. This rapid and economical technique will be highly useful for the identification of historical diseases that are difficult to characterize based on archaeological information alone.

GenomeRing: alignment visualization based on SuperGenome coordinates

Motivation: The number of completely sequenced genomes is continuously rising, allowing for comparative analyses of genomic variation. Such analyses are often based on whole-genome alignments to elucidate structural differences arising from insertions, deletions or from rearrangement events. Computational tools that can visualize genome alignments in a meaningful manner are needed to help researchers gain new insights into the underlying data. Such visualizations typically are either realized in a linear fashion as in genome browsers or by using a circular approach, where relationships between genomic regions are indicated by arcs. Both methods allow for the integration of additional information such as experimental data or annotations. However, providing a visualization that still allows for a quick and comprehensive interpretation of all important genomic variations together with various supplemental data, which may be highly heterogeneous, remains a challenge. Results: Here, we present two complementary approaches to tackle this problem. First, we propose the SuperGenome concept for the computation of a common coordinate system for all genomes in a multiple alignment. This coordinate system allows for the consistent placement of genome annotations in the presence of insertions, deletions and rearrangements. Second, we present the GenomeRing visualization that, based on the SuperGenome, creates an interactive overview visualization of the multiple genome alignment in a circular layout. We demonstrate our methods by applying them to an alignment of Campylobacter jejuni strains for the discovery of genomic islands as well as to an alignment of Helicobacter pylori, which we visualize in combination with gene expression data. Availability: GenomeRing and example data is available at http://it.inf.uni-tuebingen.de/software/genomering/ Contact: kay.nieselt@uni-tuebingen.de

Origin of modern syphilis and emergence of a pandemic Treponema pallidum cluster

The abrupt onslaught of the syphilis pandemic that started in the late fifteenth century established this devastating infectious disease as one of the most feared in human history1. Surprisingly, despite the availability of effective antibiotic treatment since the mid-twentieth century, this bacterial infection, which is caused by Treponema pallidum subsp. pallidum (TPA), has been re-emerging globally in the last few decades with an estimated 10.6 million cases in 2008 (ref. 2). Although resistance to penicillin has not yet been identified, an increasing number of strains fail to respond to the second-line antibiotic azithromycin3. Little is known about the genetic patterns in current infections or the evolutionary origins of the disease due to the low quantities of treponemal DNA in clinical samples and difficulties in cultivating the pathogen4. Here, we used DNA capture and whole-genome sequencing to successfully interrogate genome-wide variation from syphilis patient specimens, combined with laboratory samples of TPA and two other subspecies. Phylogenetic comparisons based on the sequenced genomes indicate that the TPA strains examined share a common ancestor after the fifteenth century, within the early modern era. Moreover, most contemporary strains are azithromycin-resistant and are members of a globally dominant cluster, named here as SS14-Ω. The cluster diversified from a common ancestor in the mid-twentieth century subsequent to the discovery of antibiotics. Its recent phylogenetic divergence and global presence point to the emergence of a pandemic strain cluster.

Engineering E. coli for large-scale production – Strategies considering ATP expenses and transcriptional responses

Microbial producers such as Escherichia coli are evolutionarily trained to adapt to changing substrate availabilities. Being exposed to large-scale production conditions, their complex, multilayered regulatory programs are frequently activated because they face changing substrate supply due to limited mixing. Here, we show that E. coli can adopt both short- and long-term strategies to withstand these stress conditions. Experiments in which glucose availability was changed over a short time scale were performed in a two-compartment bioreactor system. Quick metabolic responses were observed during the first 30s of glucose shortage, and after 70s, fundamental transcriptional programs were initiated. Since cells are fluctuating under simulated large-scale conditions, this scenario represents a continuous on/off switching of about 600 genes. Furthermore, the resulting ATP maintenance demands were increased by about 40-50%, allowing us to conclude that hyper-producing strains could become ATP-limited under large-scale production conditions. Based on the observed transcriptional patterns, we identified a number of candidate gene deletions that may reduce unwanted ATP losses. In summary, we present a theoretical framework that provides biological targets that could be used to engineer novel E. coli strains such that large-scale performance equals laboratory-scale expectations.

iHAT: interactive Hierarchical Aggregation Table for Genetic Association Data

In the search for single-nucleotide polymorphisms which influence the observable phenotype, genome wide association studies have become an important technique for the identification of associations between genotype and phenotype of a diverse set of sequence-based data. We present a methodology for the visual assessment of single-nucleotide polymorphisms using interactive hierarchical aggregation techniques combined with methods known from traditional sequence browsers and cluster heatmaps. Our tool, the interactive Hierarchical Aggregation Table (iHAT), facilitates the visualization of multiple sequence alignments, associated metadata, and hierarchical clusterings. Different color maps and aggregation strategies as well as filtering options support the user in finding correlations between sequences and metadata. Similar to other visualizations such as parallel coordinates or heatmaps, iHAT relies on the human pattern-recognition ability for spotting patterns that might indicate correlation or anticorrelation. We demonstrate iHAT using artificial and real-world datasets for DNA and protein association studies as well as expression Quantitative Trait Locus data.

Interferon Kappa Inhibits Human Papillomavirus 31 Transcription by Inducing Sp100 Proteins

ABSTRACT High-risk human papillomaviruses (hr-HPV) establish persistent infections in keratinocytes, which can lead to cancer of the anogenital tract. Interferons (IFNs) are a family of secreted cytokines that induce IFN-stimulated genes (ISGs), many of which display antiviral activities. Transcriptome studies have indicated that established hr-HPV-positive cell lines display a reduced expression of ISGs, which correlates with decreased levels of interferon kappa (IFN-κ), a type I IFN constitutively expressed in keratinocytes. Prior studies have also suggested that IFN-β has anti-hr-HPV activity but the underlying mechanisms are not well understood. The downregulation of IFN-κ by hr-HPV raises the possibility that IFN-κ has anti-HPV activity. Using doxycycline-inducible IFN-κ expression in CIN612-9E cells, which maintain extrachromosomally replicating HPV31 genomes, we demonstrated that IFN-κ inhibits the growth of these cells and reduces viral transcription and replication. Interestingly, the initiation of viral early transcription was already inhibited at 4 to 6 h after IFN-κ expression. This was also observed with recombinant IFN-β, suggesting a common mechanism of IFNs. Transcriptome sequencing (RNA-seq) analysis identified 1,367 IFN-κ-regulated genes, of which 221 were modulated >2-fold. The majority of those (71%) matched known ISGs, confirming that IFN-κ acts as a bona fide type I IFN in hr-HPV-positive keratinocytes. RNA interference (RNAi) and cotransfection experiments indicated that the inhibition of viral transcription is mainly due to the induction of Sp100 proteins by IFN-κ. Consistent with published data showing that Sp100 acts as a restriction factor for HPV18 infection, our results suggest that hr-HPV target IFN-κ to prevent Sp100 expression and identify Sp100 as an ISG with anti-HPV activity. IMPORTANCE High-risk HPV can establish persistent infections which may progress to anogenital cancers. hr-HPV interfere with the expression of interferon (IFN)-stimulated genes (ISGs), which is due to reduced levels of IFN-κ, an IFN that is constitutively expressed in human keratinocytes. This study reveals that IFN-κ rapidly inhibits HPV transcription and that this is due to the induction of Sp100 proteins. Thus, Sp100 represents an ISG for hr-HPV.

Transcriptional response of Escherichia coli to ammonia and glucose fluctuations

In large‐scale production processes, metabolic control is typically achieved by limited supply of essential nutrients such as glucose or ammonia. With increasing bioreactor dimensions, microbial producers such as Escherichia coli are exposed to changing substrate availabilities due to limited mixing. In turn, cells sense and respond to these dynamic conditions leading to frequent activation of their regulatory programmes. Previously, we characterized short‐ and long‐term strategies of cells to adapt to glucose fluctuations. Here, we focused on fluctuating ammonia supply while studying a continuously running two‐compartment bioreactor system comprising a stirred tank reactor (STR) and a plug‐flow reactor (PFR). The alarmone ppGpp rapidly accumulated in PFR, initiating considerable transcriptional responses after 70 s. About 400 genes were repeatedly switched on/off when E. coli returned to the STR. E. coli revealed highly diverging long‐term transcriptional responses in ammonia compared to glucose fluctuations. In contrast, the induction of stringent regulation was a common feature of both short‐term responses. Cellular ATP demands for coping with fluctuating ammonia supply were found to increase maintenance by 15%. The identification of genes contributing to the increased ATP demand together with the elucidation of regulatory mechanisms may help to create robust cells and processes for large‐scale application.

TIALA — Time series alignment analysis

The analysis of time series expression data is widely employed for investigating biological mechanisms. Microarrays are often used to generate time series for several different experimental conditions. These time series then need to be compared to each other. For a successful comparison it is necessary to perform a time series alignment because the experiments can differ in the number of time points, as well as in the time points themselves. In this work we propose a novel visual analytics approach for the analysis of multiple time series experiments in parallel. Our time series alignment analysis tool Tiala allows one to align multiple time series experiments and to visually explore the aligned expression profiles. A two- and three-dimensional visualization strategy was implemented that is especially designed to enhance the display of multiple aligned time series expression profiles. Tiala is available as a part of the microarray data analysis software Mayday. Mayday itself is open source software distributed under the terms of the GNU General Public License. It is available from http://www.microarray-analysis.org. We apply our approach to time series showing abiotic stress responses of Arabidopsis thaliana and to data sets from two replicates of the antibiotics producing bacterium Streptomyces coelicolor.