Christian Rückert-Reed

Dr. Christian Rückert-Reed

CeBiTec, Bielefeld University, Bielefeld, North Rhine-Westphalia, Germany
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Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 September 2005 in Nucleic Acids Research
Verified
Journal Article
Open access
RORoss Overbeek
Ross Overbeek
TBTadhg Begley
Tadhg Begley
RBRalph M Butler
Ralph M Butler
JCJomuna V Choudhuri
Jomuna V Choudhuri
HCHan-Yu Chuang
Han-Yu Chuang
VVVeronika Vonstein
Veronika Vonstein
The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms.

1 September 2003 in Journal of Biotechnology
Verified
Journal Article
Closed access
JKJörn Kalinowski
Jörn Kalinowski
BBBrigitte Bathe
Brigitte Bathe
DBDaniela Bartels
Daniela Bartels
NBNicole Bischoff
Nicole Bischoff
MBMichael Bott
Michael Bott
ATAndreas Tauch
Andreas Tauch

29 January 2014 in Nature
Verified
Journal Article
Open access
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MWMicheal C. Wilson
Micheal C. Wilson
Tetsushi MoriTetsushi Mori
Tetsushi Mori
CRChristian Rückert-Reed
Christian Rückert-Reed
AUAgustinus R. Uria
Agustinus R. Uria
MHMaximilian J. Helf
Maximilian J. Helf
JPJörn Piel
Jörn Piel
Cultivated bacteria such as actinomycetes are a highly useful source of biomedically important natural products. However, such ‘talented’ producers represent only a minute fraction of the entire, mostly uncultivated, prokaryotic diversity. The uncultured majority is generally perceived as a large, untapped resource of new drug candidates, but so far it is unknown whether taxa containing talented bacteria indeed exist. Here we report the single-cell- and metagenomics-based discovery of such producers. Two phylotypes of the candidate genus ‘Entotheonella’ with genomes of greater than 9 megabases and multiple, distinct biosynthetic gene clusters co-inhabit the chemically and microbially rich marine sponge Theonella swinhoei. Almost all bioactive polyketides and peptides known from this animal were attributed to a single phylotype. ‘Entotheonella’ spp. are widely distributed in sponges and belong to an environmental taxon proposed here as candidate phylum ‘Tectomicrobia’. The pronounced bioactivities and chemical uniqueness of ‘Entotheonella’ compounds provide significant opportunities for ecological studies and drug discovery.

12 February 2013 in PLOS Medicine
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ARAndreas Roetzer
Andreas Roetzer
RDRoland Diel
Roland Diel
TKThomas A Kohl
Thomas A Kohl
CRChristian Rückert-Reed
Christian Rückert-Reed
UNUlrich Nübel
Ulrich Nübel
Stefan NiemannStefan Niemann
Stefan Niemann
Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context. Please see later in the article for the Editors' Summary Tuberculosis—a contagious bacterial disease that usually infects the lungs—is a major public health problem, particularly in low- and middle-income countries. In 2011, an estimated 8.7 million people developed tuberculosis globally, and 1.4 million people died from the disease. Tuberculosis is second only to HIV/AIDS in terms of global deaths from a single infectious agent. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is readily spread in airborne droplets when people with active disease cough or sneeze. The characteristic symptoms of tuberculosis include persistent cough, weight loss, fever, and night sweats. Diagnostic tests for the disease include sputum smear analysis (examination of mucus coughed up from the lungs for the presence of M. tuberculosis), mycobacterial culture (growth of M. tuberculosis from sputum), and chest X-rays. Tuberculosis can be cured by taking several antibiotics daily for at least six months, although the recent emergence of multidrug-resistant M. tuberculosis is making tuberculosis harder to treat. Although efforts to reduce the global burden of tuberculosis are showing some improvements, the annual decline in the number of people developing tuberculosis continues to be slow. To develop optimized control strategies, experts need to be able to accurately track M. tuberculosis transmission within human populations. Because M. tuberculosis, like all bacteria, accumulates genetic changes over time, there are many different strains (genetic variants) of M. tuberculosis. Genotyping methods have been developed that identify different bacterial strains by examining specific regions of the bacterial genome (blueprint), but because these methods examine only a small part of the genome, they may not distinguish between related transmission chains. That is, traditional strain genotyping methods may not be able to determine accurately where a tuberculosis outbreak started or how it spread through a population. In this longitudinal cohort study, the researchers compare the ability of whole genome sequencing (WGS), which is rapidly becoming widely available, and traditional genotyping to provide information about a recent German tuberculosis outbreak. In a longitudinal cohort study, a population is followed over time to analyze the occurrence of a specific disease. During long-term (1997–2010) population-based molecular epidemiological surveillance (disease surveillance that uses molecular techniques rather than reports of illness) in Hamburg and Schleswig-Holstein, the researchers identified a large tuberculosis outbreak caused by M. tuberculosis isolates of the Haarlem lineage using classical strain typing. The researchers examined each of the 86 isolates from this outbreak using WGS and classical genotyping and asked whether the results of these two approaches correlated with contact tracing data (information is routinely collected about the people a patient with tuberculosis has recently met so that these contacts can be tested for tuberculosis and treated if necessary) and with the spatio-temporal distribution of outbreak cases. WGS of the isolates identified 85 single nucleotide polymorphisms (SNPs; genomic sequence variants in which single building blocks, or nucleotides, are altered) that subdivided the outbreak into seven clusters of isolates and 36 unique isolates. The WGS results showed that the first isolates of the outbreak were incorrectly clustered by classical genotyping and that one strain—the “Hamburg clone”—started expanding in 1998. Notably, the genome-based clustering patterns were in better accordance with contact tracing data and with the geographical distribution of cases than clustering patterns based on classical genotyping, and they identified eight confirmed human-to-human transmission chains that involved 31 patients and a maximum of three SNPs. Finally, the researchers used their WGS results to estimate that the Hamburg clone emerged between 1993 and 1997, shortly before the discovery of the tuberculosis outbreak through epidemiological surveillance. These findings show that WGS can be used to identify specific strains within large tuberculosis outbreaks more accurately than classical genotyping. They also provide new information about the evolution of M. tuberculosis during outbreaks and indicate how WGS data should be interpreted in future genome-based molecular epidemiology studies. WGS has the potential to improve the molecular epidemiological surveillance and control of tuberculosis and of other infectious diseases. Importantly, note the researchers, ongoing reductions in the cost of WGS, the increased availability of “bench top” genome sequencers, and bioinformatics developments should all accelerate the implementation of WGS as a standard method for the identification of transmission chains in infectious disease outbreaks. Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001387.

28 October 2007 in Nature Biotechnology
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Journal Article
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SSSusanne Schneiker
Susanne Schneiker
OPOlena Perlova
Olena Perlova
OKOlaf Kaiser
Olaf Kaiser
KGKlaus Gerth
Klaus Gerth
AAAysel Alici
Aysel Alici
RMRolf Müller
Rolf Müller
The genus Sorangium synthesizes approximately half of the secondary metabolites isolated from myxobacteria, including the anti-cancer metabolite epothilone. We report the complete genome sequence of the model Sorangium strain S. cellulosum So ce56, which produces several natural products and has morphological and physiological properties typical of the genus. The circular genome, comprising 13,033,779 base pairs, is the largest bacterial genome sequenced to date. No global synteny with the genome of Myxococcus xanthus is apparent, revealing an unanticipated level of divergence between these myxobacteria. A large percentage of the genome is devoted to regulation, particularly post-translational phosphorylation, which probably supports the strain's complex, social lifestyle. This regulatory network includes the highest number of eukaryotic protein kinase–like kinases discovered in any organism. Seventeen secondary metabolite loci are encoded in the genome, as well as many enzymes with potential utility in industry.

1 November 2005 in Journal of Bacteriology
Verified
Journal Article
Closed access
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FTFrank Thieme
Frank Thieme
RKRalf Koebnik
Ralf Koebnik
TBThomas Bekel
Thomas Bekel
CBCarolin Berger
Carolin Berger
JBJens Boch
Jens Boch
OKOlaf Kaiser
Olaf Kaiser
The gram-negative plant-pathogenic bacteriumXanthomonas campestrispv. vesicatoria is the causative agent of bacterial spot disease in pepper and tomato plants, which leads to economically important yield losses. This pathosystem has become a well-established model for studying bacterial infection strategies. Here, we present the whole-genome sequence of the pepper-pathogenicXanthomonas campestrispv. vesicatoria strain 85-10, which comprises a 5.17-Mb circular chromosome and four plasmids. The genome has a high G+C content (64.75%) and signatures of extensive genome plasticity. Whole-genome comparisons revealed a gene order similar to bothXanthomonas axonopodispv. citri andXanthomonas campestrispv. campestris and a structure completely different fromXanthomonas oryzaepv. oryzae. A total of 548 coding sequences (12.2%) are unique toX. campestrispv. vesicatoria. In addition to a type III secretion system, which is essential for pathogenicity, the genome of strain 85-10 encodes all other types of protein secretion systems described so far in gram-negative bacteria. Remarkably, one of the putative type IV secretion systems encoded on the largest plasmid is similar to the Icm/Dot systems of the human pathogensLegionella pneumophilaandCoxiella burnetii. Comparisons with other completely sequenced plant pathogens predicted six novel type III effector proteins and several other virulence factors, including adhesins, cell wall-degrading enzymes, and extracellular polysaccharides.