TY  - JOUR
A1  - Kunz, Meik
A1  - Liang, Chunguang
A1  - Nilla, Santosh
A1  - Cecil, Alexander
A1  - Dandekar, Thomas
T1  - The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development
JF  - Database
N2  - The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure–activity relationships.
KW  - drug-minded protein
KW  - database
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147369
VL  - 2016
ER  - 
TY  - JOUR
A1  - Kaltdorf, Martin
A1  - Srivastava, Mugdha
A1  - Gupta, Shishir K.
A1  - Liang, Chunguang
A1  - Binder, Jasmin
A1  - Dietl, Anna-Maria
A1  - Meir, Zohar
A1  - Haas, Hubertus
A1  - Osherov, Nir
A1  - Krappmann, Sven
A1  - Dandekar, Thomas
T1  - Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach
JF  - Frontiers in Molecular Bioscience
N2  - New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.
KW  - metabolism
KW  - targets
KW  - antimycotics
KW  - modeling
KW  - structure
KW  - interaction
KW  - fungicide
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147396
VL  - 3
ER  - 
TY  - JOUR
A1  - Cecil, Alexander
A1  - Rikanovic, Carina
A1  - Ohlsen, Knut
A1  - Liang, Chunguang
A1  - Bernhardt, Jorg
A1  - Oelschlaeger, Tobias A.
A1  - Gulder, Tanja
A1  - Bringmann, Gerd
A1  - Holzgrabe, Ulrike
A1  - Unger, Matthias
A1  - Dandekar, Thomas
T1  - Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells
N2  - Background: Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results: Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions: The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics.
KW  - Staphylococcus aureus
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-68802
ER  - 
TY  - JOUR
A1  - Förster, Frank
A1  - Beisser, Daniela
A1  - Grohme, Markus A.
A1  - Liang, Chunguang
A1  - Mali, Brahim
A1  - Siegl, Alexander Matthias
A1  - Engelmann, Julia C.
A1  - Shkumatov, Alexander V.
A1  - Schokraie, Elham
A1  - Müller, Tobias
A1  - Schnölzer, Martina
A1  - Schill, Ralph O.
A1  - Frohme, Marcus
A1  - Dandekar, Thomas
T1  - Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations
JF  - Bioinformatics and biology insights
N2  - Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade \(Milnesium\) \(tardigradum\) were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from \(Hypsibius\) \(dujardini\), revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for \(M.\) \(tardigradum\) are different from typical motifs known from higher animals. \(M.\) \(tardigradum\) and \(H.\) \(dujardini\) protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of \(M.\) \(tardigradum\). These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and \(M.\) \(tardigradum\) in particular so highly stress resistant.
KW  - RNA
KW  - expressed sequence tag
KW  - cluster
KW  - protein familiy
KW  - adaption
KW  - tardigrada
KW  - transcriptome
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-123089
N1  - This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.
VL  - 6
ER  - 
TY  - JOUR
A1  - Dandekar, Thomas
A1  - Liang, Chunguang
A1  - Krüger, Beate
T1  - GoSynthetic database tool to analyse natural and engineered molecular processes
JF  - Database
N2  - An essential topic for synthetic biologists is to understand the structure and function of biological processes and involved proteins and plan experiments accordingly. Remarkable progress has been made in recent years towards this goal. However, efforts to collect and present all information on processes and functions are still cumbersome. The database tool GoSynthetic provides a new, simple and fast way to analyse biological processes applying a hierarchical database. Four different search modes are implemented. Furthermore, protein interaction data, cross-links to organism-specific databases (17 organisms including six model organisms and their interactions), COG/KOG, GO and IntAct are warehoused. The built in connection to technical and engineering terms enables a simple switching between biological concepts and concepts from engineering, electronics and synthetic biology. The current version of GoSynthetic covers more than one million processes, proteins, COGs and GOs. It is illustrated by various application examples probing process differences and designing modifications.
KW  - Bioinformatik
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-97023
ER  - 
TY  - JOUR
A1  - Ratzka, Carolin
A1  - Förster, Frank
A1  - Liang, Chunguang
A1  - Kupper, Maria
A1  - Dandekar, Thomas
A1  - Feldhaar, Heike
A1  - Gross, Roy
T1  - Molecular characterization of antimicrobial peptide genes of the carpenter ant Camponotus floridanus
N2  - The production of antimicrobial peptides (AMPs) is a major defense mechanism against pathogen infestation and of particular importance for insects relying exclusively on an innate immune system. Here, we report on the characterization of three AMPs from the carpenter ant Camponotus floridanus. Due to sequence similarities and amino acid composition these peptides can be classified into the cysteine-rich (e.g. defensin) and glycine-rich (e.g. hymenoptaecin) AMP groups, respectively. The gene and cDNA sequences of these AMPs were established and their expression was shown to be induced by microbial challenge. We characterized two different defensin genes. The defensin-2 gene has a single intron, whereas the defensin-1 gene has two introns. The deduced amino acid sequence of the C. floridanus defensins is very similar to other known ant defensins with the exception of a short C-terminal extension of defensin-1. The hymenoptaecin gene has a single intron and a very peculiar domain structure. The corresponding precursor protein consists of a signal- and a pro-sequence followed by a hymenoptaecin-like domain and six directly repeated hymenoptaecin domains. Each of the hymenoptaecin domains is flanked by an EAEP-spacer sequence and a RR-site known to be a proteolytic processing site. Thus, proteolytic processing of the multipeptide precursor may generate several mature AMPs leading to an amplification of the immune response. Bioinformatical analyses revealed the presence of hymenoptaecin genes with similar multipeptide precursor structure in genomes of other ant species suggesting an evolutionary conserved important role of this gene in ant immunity.
KW  - Biologie
KW  - Camponotus floridanus
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-75985
ER  - 
TY  - JOUR
A1  - Kaltdorf, Martin
A1  - Breitenbach, Tim
A1  - Karl, Stefan
A1  - Fuchs, Maximilian
A1  - Kessie, David Komla
A1  - Psota, Eric
A1  - Prelog, Martina
A1  - Sarukhanyan, Edita
A1  - Ebert, Regina
A1  - Jakob, Franz
A1  - Dandekar, Gudrun
A1  - Naseem, Muhammad
A1  - Liang, Chunguang
A1  - Dandekar, Thomas
T1  - Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis
JF  - Scientific Reports
N2  - The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
KW  - cellular signalling networks
KW  - computer modelling
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313303
VL  - 13
ER  - 
TY  - JOUR
A1  - Liang, Chunguang
A1  - Rios-Miguel, Ana B.
A1  - Jarick, Marcel
A1  - Neurgaonkar, Priya
A1  - Girard, Myriam
A1  - François, Patrice
A1  - Schrenzel, Jacques
A1  - Ibrahim, Eslam S.
A1  - Ohlsen, Knut
A1  - Dandekar, Thomas
T1  - Staphylococcus aureus transcriptome data and metabolic modelling investigate the interplay of Ser/Thr kinase PknB, its phosphatase Stp, the glmR/yvcK regulon and the cdaA operon for metabolic adaptation
JF  - Microorganisms
N2  - Serine/threonine kinase PknB and its corresponding phosphatase Stp are important regulators of many cell functions in the pathogen S. aureus. Genome-scale gene expression data of S. aureus strain NewHG (sigB\(^+\)) elucidated their effect on physiological functions. Moreover, metabolic modelling from these data inferred metabolic adaptations. We compared wild-type to deletion strains lacking pknB, stp or both. Ser/Thr phosphorylation of target proteins by PknB switched amino acid catabolism off and gluconeogenesis on to provide the cell with sufficient components. We revealed a significant impact of PknB and Stp on peptidoglycan, nucleotide and aromatic amino acid synthesis, as well as catabolism involving aspartate transaminase. Moreover, pyrimidine synthesis was dramatically impaired by stp deletion but only slightly by functional loss of PknB. In double knockouts, higher activity concerned genes involved in peptidoglycan, purine and aromatic amino acid synthesis from glucose but lower activity of pyrimidine synthesis from glucose compared to the wild type. A second transcriptome dataset from S. aureus NCTC 8325 (sigB\(^−\)) validated the predictions. For this metabolic adaptation, PknB was found to interact with CdaA and the yvcK/glmR regulon. The involved GlmR structure and the GlmS riboswitch were modelled. Furthermore, PknB phosphorylation lowered the expression of many virulence factors, and the study shed light on S. aureus infection processes.
KW  - metabolism
KW  - flux balance analysis
KW  - phosphorylation
KW  - regulation
KW  - riboswitch
KW  - PknB
KW  - Stp
KW  - yvcK/glmR operon
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-248459
SN  - 2076-2607
VL  - 9
IS  - 10
ER  - 
TY  - JOUR
A1  - Ampattu, Biju Joseph
A1  - Hagmann, Laura
A1  - Liang, Chunguang
A1  - Dittrich, Marcus
A1  - Schlüter, Andreas
A1  - Blom, Jochen
A1  - Krol, Elizaveta
A1  - Goesmann, Alexander
A1  - Becker, Anke
A1  - Dandekar, Thomas
A1  - Müller, Tobias
A1  - Schoen, Christoph
T1  - Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence
JF  - BMC Genomics
N2  - Background:
Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence.
Results:
Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region.
Conclusions:
Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.
KW  - neisseria meningitidis
KW  - MITE
KW  - virulenceregulatory evolution
KW  - systems biology
KW  - metabolism
KW  - cryptic
KW  - genetic variation
KW  - stringent response
KW  - relA
Y1  - 2017
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-157534
VL  - 18
IS  - 282
ER  - 
TY  - JOUR
A1  - Prada, Juan Pablo
A1  - Maag, Luca Estelle
A1  - Siegmund, Laura
A1  - Bencurova, Elena
A1  - Liang, Chunguang
A1  - Koutsilieri, Eleni
A1  - Dandekar, Thomas
A1  - Scheller, Carsten
T1  - Estimation of R0 for the spread of SARS-CoV-2 in Germany from excess mortality
JF  - Scientific Reports
N2  - For SARS-CoV-2, R0 calculations in the range of 2–3 dominate the literature, but much higher estimates have also been published. Because capacity for RT-PCR testing increased greatly in the early phase of the Covid-19 pandemic, R0 determinations based on these incidence values are subject to strong bias. We propose to use Covid-19-induced excess mortality to determine R0 regardless of RT-PCR testing capacity. We used data from the Robert Koch Institute (RKI) on the incidence of Covid cases, Covid-related deaths, number of RT-PCR tests performed, and excess mortality calculated from data from the Federal Statistical Office in Germany. We determined R0 using exponential growth estimates with a serial interval of 4.7 days. We used only datasets that were not yet under the influence of policy measures (e.g., lockdowns or school closures). The uncorrected R0 value for the spread of SARS-CoV-2 based on RT-PCR incidence data was 2.56 (95% CI 2.52–2.60) for Covid-19 cases and 2.03 (95% CI 1.96–2.10) for Covid-19-related deaths. However, because the number of RT-PCR tests increased by a growth factor of 1.381 during the same period, these R0 values must be corrected accordingly (R0corrected = R0uncorrected/1.381), yielding 1.86 for Covid-19 cases and 1.47 for Covid-19 deaths. The R0 value based on excess deaths was calculated to be 1.34 (95% CI 1.32–1.37). A sine-function-based adjustment for seasonal effects of 40% corresponds to a maximum value of R0January = 1.68 and a minimum value of R0July = 1.01. Our calculations show an R0 that is much lower than previously thought. This relatively low range of R0 fits very well with the observed seasonal pattern of infection across Europe in 2020 and 2021, including the emergence of more contagious escape variants such as delta or omicron. In general, our study shows that excess mortality can be used as a reliable surrogate to determine the R0 in pandemic situations.
KW  - SARS-CoV-2
KW  - R0
KW  - mortality
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-301415
VL  - 12
IS  - 1
ER  -