@article{AmpattuHagmannLiangetal.2017, author = {Ampattu, Biju Joseph and Hagmann, Laura and Liang, Chunguang and Dittrich, Marcus and Schl{\"u}ter, Andreas and Blom, Jochen and Krol, Elizaveta and Goesmann, Alexander and Becker, Anke and Dandekar, Thomas and M{\"u}ller, Tobias and Schoen, Christoph}, title = {Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence}, series = {BMC Genomics}, volume = {18}, journal = {BMC Genomics}, number = {282}, doi = {10.1186/s12864-017-3616-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157534}, year = {2017}, abstract = {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.}, language = {en} } @article{AydinliLiangDandekar2022, author = {Aydinli, Muharrem and Liang, Chunguang and Dandekar, Thomas}, title = {Motif and conserved module analysis in DNA (promoters, enhancers) and RNA (lncRNA, mRNA) using AlModules}, series = {Scientific Reports}, volume = {12}, journal = {Scientific Reports}, number = {1}, doi = {10.1038/s41598-022-21732-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-301268}, year = {2022}, abstract = {Nucleic acid motifs consist of conserved and variable nucleotide regions. For functional action, several motifs are combined to modules. The tool AIModules allows identification of such motifs including combinations of them and conservation in several nucleic acid stretches. AIModules recognizes conserved motifs and combinations of motifs (modules) allowing a number of interesting biological applications such as analysis of promoter and transcription factor binding sites (TFBS), identification of conserved modules shared between several gene families, e.g. promoter regions, but also analysis of shared and conserved other DNA motifs such as enhancers and silencers, in mRNA (motifs or regulatory elements e.g. for polyadenylation) and lncRNAs. The tool AIModules presented here is an integrated solution for motif analysis, offered as a Web service as well as downloadable software. Several nucleotide sequences are queried for TFBSs using predefined matrices from the JASPAR DB or by using one's own matrices for diverse types of DNA or RNA motif discovery. Furthermore, AIModules can find TFBSs common to two or more sequences. Demanding high or low conservation, AIModules outperforms other solutions in speed and finds more modules (specific combinations of TFBS) than alternative available software. The application also searches RNA motifs such as polyadenylation site or RNA-protein binding motifs as well as DNA motifs such as enhancers as well as user-specified motif combinations (https://bioinfo-wuerz.de/aimodules/; alternative entry pages: https://aimodules.heinzelab.de or https://www.biozentrum.uni-wuerzburg.de/bioinfo/computing/aimodules). The application is free and open source whether used online, on-site, or locally.}, language = {en} } @article{DandekarLiangKrueger2013, author = {Dandekar, Thomas and Liang, Chunguang and Kr{\"u}ger, Beate}, title = {GoSynthetic database tool to analyse natural and engineered molecular processes}, series = {Database}, journal = {Database}, doi = {10.1093/database/bat043}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-97023}, year = {2013}, abstract = {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.}, language = {en} } @article{DongBoeppleThieletal.2023, author = {Dong, Meng and B{\"o}pple, Kathrin and Thiel, Julia and Winkler, Bernd and Liang, Chunguang and Schueler, Julia and Davies, Emma J. and Barry, Simon T. and Metsalu, Tauno and M{\"u}rdter, Thomas E. and Sauer, Georg and Ott, German and Schwab, Matthias and Aulitzky, Walter E.}, title = {Perfusion air culture of precision-cut tumor slices: an ex vivo system to evaluate individual drug response under controlled culture conditions}, series = {Cells}, volume = {12}, journal = {Cells}, number = {5}, issn = {2073-4409}, doi = {10.3390/cells12050807}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311030}, year = {2023}, abstract = {Precision-cut tumor slices (PCTS) maintain tissue heterogeneity concerning different cell types and preserve the tumor microenvironment (TME). Typically, PCTS are cultured statically on a filter support at an air-liquid interface, which gives rise to intra-slice gradients during culture. To overcome this problem, we developed a perfusion air culture (PAC) system that can provide a continuous and controlled oxygen medium, and drug supply. This makes it an adaptable ex vivo system for evaluating drug responses in a tissue-specific microenvironment. PCTS from mouse xenografts (MCF-7, H1437) and primary human ovarian tumors (primary OV) cultured in the PAC system maintained the morphology, proliferation, and TME for more than 7 days, and no intra-slice gradients were observed. Cultured PCTS were analyzed for DNA damage, apoptosis, and transcriptional biomarkers for the cellular stress response. For the primary OV slices, cisplatin treatment induced a diverse increase in the cleavage of caspase-3 and PD-L1 expression, indicating a heterogeneous response to drug treatment between patients. Immune cells were preserved throughout the culturing period, indicating that immune therapy can be analyzed. The novel PAC system is suitable for assessing individual drug responses and can thus be used as a preclinical model to predict in vivo therapy responses.}, language = {en} } @article{FoersterBeisserGrohmeetal.2012, author = {F{\"o}rster, Frank and Beisser, Daniela and Grohme, Markus A. and Liang, Chunguang and Mali, Brahim and Siegl, Alexander Matthias and Engelmann, Julia C. and Shkumatov, Alexander V. and Schokraie, Elham and M{\"u}ller, Tobias and Schn{\"o}lzer, Martina and Schill, Ralph O. and Frohme, Marcus and Dandekar, Thomas}, title = {Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations}, series = {Bioinformatics and biology insights}, volume = {6}, journal = {Bioinformatics and biology insights}, doi = {10.4137/BBI.S9150}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123089}, pages = {69-96}, year = {2012}, abstract = {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.}, language = {en} } @article{KaltdorfBreitenbachKarletal.2023, author = {Kaltdorf, Martin and Breitenbach, Tim and Karl, Stefan and Fuchs, Maximilian and Kessie, David Komla and Psota, Eric and Prelog, Martina and Sarukhanyan, Edita and Ebert, Regina and Jakob, Franz and Dandekar, Gudrun and Naseem, Muhammad and Liang, Chunguang and Dandekar, Thomas}, title = {Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis}, series = {Scientific Reports}, volume = {13}, journal = {Scientific Reports}, doi = {10.1038/s41598-022-27098-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313303}, year = {2023}, abstract = {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.}, language = {en} } @article{KaltdorfSrivastavaGuptaetal.2016, author = {Kaltdorf, Martin and Srivastava, Mugdha and Gupta, Shishir K. and Liang, Chunguang and Binder, Jasmin and Dietl, Anna-Maria and Meir, Zohar and Haas, Hubertus and Osherov, Nir and Krappmann, Sven and Dandekar, Thomas}, title = {Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach}, series = {Frontiers in Molecular Bioscience}, volume = {3}, journal = {Frontiers in Molecular Bioscience}, doi = {10.3389/fmolb.2016.00022}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147396}, pages = {22}, year = {2016}, abstract = {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.}, language = {en} } @article{KunzLiangNillaetal.2016, author = {Kunz, Meik and Liang, Chunguang and Nilla, Santosh and Cecil, Alexander and Dandekar, Thomas}, title = {The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development}, series = {Database}, volume = {2016}, journal = {Database}, doi = {10.1093/database/baw041}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147369}, pages = {baw041}, year = {2016}, abstract = {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.}, language = {en} } @phdthesis{Liang2009, author = {Liang, Chunguang}, title = {Tools for functional genomics applied to Staphylococci, Listeriae, Vaccinia virus and other organisms}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-48051}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2009}, abstract = {Genome sequence analysis A combination of genome analysis application has been established here during this project. This offers an efficient platform to interactively compare similar genome regions and reveal loci differences. The genes and operons can be rapidly analyzed and local collinear blocks (LCBs) categorized according to their function. The features of interests are parsed, recognized, and clustered into reports. Phylogenetic relationships can be readily examined such as the evolution of critical factors or a certain highly-conserved region. The resulting platform-independent software packages (GENOVA and inGeno), have been proven to be efficient and easy to handle in a number of projects. The capabilities of the software allowed the investigation of virulence factors, e.g., rsbU, strains' biological design, and in particular pathogenicity feature storage and management. We have successfully investigated the genomes of Staphylococcus aureus strains (COL, N315, 8325, RN1HG, Newman), Listeria spp. (welshimeri, innocua and monocytogenes), E.coli strains (O157:H7 and MG1655) and Vaccinia strains (WR, Copenhagen, Lister, LIVP, GLV-1h68 and parental strains). Metabolic network analysis Our YANAsquare package offers a workbench to rapidly establish the metabolic network of such as Staphylococcous aureus bacteria in genome-scale size as well as metabolic networks of interest such as the murine phagosome lipid signalling network. YANAsquare recruits reactions from online databases using an integrated KEGG browser. This reduces the efforts in building large metabolic networks. The involved calculation routines (METATOOL-derived wrapper or native Java implementation) readily obtain all possible flux modes (EM/EP) for metabolite fluxes within the network. Advanced layout algorithms visualize the topological structure of the network. In addition, the generated structure can be dynamically modified in the graphic interface. The generated network as well as the manipulated layout can be validated and stored (XML file: scheme of SBML level-2). This format can be further parsed and analyzed by other systems biology software, such as CellDesigner. Moreover, the integrated robustness-evaluation routine is able to examine the synthesis rates affected by each single mutation throughout the whole network. We have successfully applied the method to simulate single and multiple gene knockouts, and the affected fluxes are comprehensively revealed. Recently we applied the method to proteomic data and extra-cellular metabolite data of Staphylococci, the physiological changes regarding the flux distribution are studied. Calculations at different time points, including different conditions such as hypoxia or stress, show a good fit to experimental data. Moreover, using the proteomic data (enzyme amounts) calculated from 2D-Gel-EP experiments our study provides a way to compare the fluxome and the enzyme expression. Oncolytic vaccinia virus (VACV) We investigated the genetic differences between the de novo sequence of the recombinant oncolytic GLV-1h68 and other related VACVs, including function predictions for all found genome differences. Our phylogenetic analysis indicates that GLV-1h68 is closest to Lister strains but has lost several ORFs present in its parental LIVP strain, including genes encoding CrmE and a viral Golgi anti-apoptotic protein, v-GAAP. Functions of viral genes were either strain-specific, tissue-specific or host-specific comparing viral genes in the Lister, WR and COP strains. This helps to rationally design more optimized oncolytic virus strains to benefit cancer therapy in human patients. Identified differences from the comparison in open reading frames (ORFs) include genes for host-range selection, virulence and immune modulation proteins, e.g. ankyrin-like proteins, serine proteinase inhibitor SPI-2/CrmA, tumor necrosis factor (TNF) receptor homolog CrmC, semaphorin-like and interleukin-1 receptor homolog proteins. The contribution of foreign gene expression cassettes in the therapeutic and oncolytic virus GLV-1h68 was studied, including the F14.5L, J2R and A56R loci. The contribution of F14.5L inactivation to the reduced virulence is demonstrated by comparing the virulence data of GLV-1h68 with its F14.5L-null and revertant viruses. The comparison suggests that insertion of a foreign gene expression cassette in a nonessential locus in the viral genome is a practical way to attenuate VACVs, especially if the nonessential locus itself contains a virulence gene. This reduces the virulence of the virus without compromising too much the replication competency of the virus, the key to its oncolytic activity. The reduced pathogenicity of GLV-1h68 was confirmed by our experimental collaboration partners in male mice bearing C6 rat glioma and in immunocompetent mice bearing B16-F10 murine melanoma. In conclusion, bioinformatics and experimental data show that GLV-1h68 is a promising engineered VACV variant for anticancer therapy with tumor-specific replication, reduced pathogenicity and benign tissue tropism.}, subject = {Genanalyse}, language = {en} } @article{LiangBencurovaPsotaetal.2021, author = {Liang, Chunguang and Bencurova, Elena and Psota, Eric and Neurgaonkar, Priya and Prelog, Martina and Scheller, Carsten and Dandekar, Thomas}, title = {Population-predicted MHC class II epitope presentation of SARS-CoV-2 structural proteins correlates to the case fatality rates of COVID-19 in different countries}, series = {International Journal of Molecular Sciences}, volume = {22}, journal = {International Journal of Molecular Sciences}, number = {5}, issn = {1422-0067}, doi = {10.3390/ijms22052630}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-258936}, year = {2021}, abstract = {We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.}, language = {en} }