Benjamin Merget

Internal Transcribed Spacer 2 (nu ITS2 rRNA) Sequence-Structure Phylogenetics: Towards an Automated Reconstruction of the Green Algal Tree of Life

Background Chloroplast-encoded genes (matK and rbcL) have been formally proposed for use in DNA barcoding efforts targeting embryophytes. Extending such a protocol to chlorophytan green algae, though, is fraught with problems including non homology (matK) and heterogeneity that prevents the creation of a universal PCR toolkit (rbcL). Some have advocated the use of the nuclear-encoded, internal transcribed spacer two (ITS2) as an alternative to the traditional chloroplast markers. However, the ITS2 is broadly perceived to be insufficiently conserved or to be confounded by introgression or biparental inheritance patterns, precluding its broad use in phylogenetic reconstruction or as a DNA barcode. A growing body of evidence has shown that simultaneous analysis of nucleotide data with secondary structure information can overcome at least some of the limitations of ITS2. The goal of this investigation was to assess the feasibility of an automated, sequence-structure approach for analysis of IT2 data from a large sampling of phylum Chlorophyta. Methodology/Principal Findings Sequences and secondary structures from 591 chlorophycean, 741 trebouxiophycean and 938 ulvophycean algae, all obtained from the ITS2 Database, were aligned using a sequence structure-specific scoring matrix. Phylogenetic relationships were reconstructed by Profile Neighbor-Joining coupled with a sequence structure-specific, general time reversible substitution model. Results from analyses of the ITS2 data were robust at multiple nodes and showed considerable congruence with results from published phylogenetic analyses. Conclusions/Significance Our observations on the power of automated, sequence-structure analyses of ITS2 to reconstruct phylum-level phylogenies of the green algae validate this approach to assessing diversity for large sets of chlorophytan taxa. Moreover, our results indicate that objections to the use of ITS2 for DNA barcoding should be weighed against the utility of an automated, data analysis approach with demonstrated power to reconstruct evolutionary patterns for highly divergent lineages.

The ITS2 Database

The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8. The ITS2 Database9 presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11 accurately reannotated10. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12 (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14 search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16 and ProfDistS17 for multiple sequence-structure alignment calculation and Neighbor Joining18 tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.

MycPermCheck: the Mycobacterium tuberculosis permeability prediction tool for small molecules.

MOTIVATION With >8 million new cases in 2010, particularly documented in developing countries, tuberculosis (TB) is still a highly present pandemic and often terminal. This is also due to the emergence of antibiotic-resistant strains (MDR-TB and XDR-TB) of the primary causative TB agent Mycobacterium tuberculosis (MTB). Efforts to develop new effective drugs against MTB are restrained by the unique and largely impermeable composition of the mycobacterial cell wall. RESULTS Based on a database of antimycobacterial substances (CDD TB), 3815 compounds were classified as active and thus permeable. A data mining approach was conducted to gather the physico-chemical similarities of these substances and delimit them from a generic dataset of drug-like molecules. On the basis of the differences in these datasets, a regression model was generated and implemented into the online tool MycPermCheck to predict the permeability probability of small organic compounds. DISCUSSION Given the current lack of precise molecular criteria determining mycobacterial permeability, MycPermCheck represents an unprecedented prediction tool intended to support antimycobacterial drug discovery. It follows a novel knowledge-driven approach to estimate the permeability probability of small organic compounds. As such, MycPermCheck can be used intuitively as an additional selection criterion for potential new inhibitors against MTB. Based on the validation results, its performance is expected to be of high practical value for virtual screening purposes. AVAILABILITY The online tool is freely accessible under the URL http://www.mycpermcheck.aksotriffer.pharmazie.uni-wuerzburg.de

A molecular phylogeny of Hypnales (Bryophyta) inferred from ITS2 sequence-structure data

BackgroundHypnales comprise over 50% of all pleurocarpous mosses. They provide a young radiation complicating phylogenetic analyses. To resolve the hypnalean phylogeny, it is necessary to use a phylogenetic marker providing highly variable features to resolve species on the one hand and conserved features enabling a backbone analysis on the other. Therefore we used highly variable internal transcribed spacer 2 (ITS2) sequences and conserved secondary structures, as deposited with the ITS2 Database, simultaneously.FindingsWe built an accurate and in parts robustly resolved large scale phylogeny for 1,634 currently available hypnalean ITS2 sequence-structure pairs.ConclusionsProfile Neighbor-Joining revealed a possible hypnalean backbone, indicating that most of the hypnalean taxa classified as different moss families are polyphyletic assemblages awaiting taxonomic changes.

Evolutionary Distances in the Twilight Zone—A Rational Kernel Approach

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.

Predicting critical micelle concentration and micelle molecular weight of polysorbate 80 using compendial methods.

This manuscript addresses the capability of compendial methods in controlling polysorbate 80 (PS80) functionality. Based on the analysis of sixteen batches, functionality related characteristics (FRC) including critical micelle concentration (CMC), cloud point, hydrophilic-lipophilic balance (HLB) value and micelle molecular weight were correlated to chemical composition including fatty acids before and after hydrolysis, content of non-esterified polyethylene glycols and sorbitan polyethoxylates, sorbitan- and isosorbide polyethoxylate fatty acid mono- and diesters, polyoxyethylene diesters, and peroxide values. Batches from some suppliers had a high variability in functionality related characteristic (FRC), questioning the ability of the current monograph in controlling these. Interestingly, the combined use of the input parameters oleic acid content and peroxide value - both of which being monographed methods - resulted in a model adequately predicting CMC. Confining the batches to those complying with specifications for peroxide value proved oleic acid content alone as being predictive for CMC. Similarly, a four parameter model based on chemical analyses alone was instrumental in predicting the molecular weight of PS80 micelles. Improved models based on analytical outcome from fingerprint analyses are also presented. A road map controlling PS80 batches with respect to FRC and based on chemical analyses alone is provided for the formulator.

An Ordered Water Channel in Staphylococcus Aureus Fabi: Unraveling the Mechanism of Substrate Recognition and Reduction.

One third of all drugs in clinical use owe their pharmacological activity to the functional inhibition of enzymes, highlighting the importance of enzymatic targets for drug development. Because of the close relationship between inhibition and catalysis, understanding the recognition and turnover of enzymatic substrates is essential for rational drug design. Although the Staphylococcus aureus enoyl-acyl carrier protein reductase (saFabI) involved in bacterial fatty acid biosynthesis constitutes a very promising target for the development of novel, urgently needed anti-staphylococcal agents, the substrate binding mode and catalytic mechanism remained unclear for this enzyme. Using a combined crystallographic, kinetic, and computational approach, we have explored the chemical properties of the saFabI binding cavity, obtaining a consistent mechanistic model for substrate binding and turnover. We identified a water-molecule network linking the active site with a water basin inside the homo-tetrameric protein, which seems to be crucial for the closure of the flexible substrate binding loop as well as for an effective hydride and proton transfer during catalysis. On the basis of our results, we also derive a new model for the FabI-ACP complex that reveals how the ACP-bound acyl-substrate is injected into the FabI binding crevice. These findings support the future development of novel FabI inhibitors that target the FabI-ACP interface leading to the disruption of the interaction between these two proteins.

Anti-trypanosomal activities and structural chemical properties of selected compound classes

Potent compounds do not necessarily make the best drugs in the market. Consequently, with the aim to describe tools that may be fundamental for refining the screening of candidates for animal and preclinical studies and further development, molecules of different structural classes synthesized within the frame of a broad screening platform were evaluated for their trypanocidal activities, cytotoxicities against murine macrophages J774.1 and selectivity indices, as well as for their ligand efficiencies and structural chemical properties. To advance into their modes of action, we also describe the morphological and ultrastructural changes exerted by selected members of each compound class on the parasite Trypanosoma brucei. Our data suggest that the potential organelles targeted are either the flagellar pocket (compound 77, N-Arylpyridinium salt; 15, amino acid derivative with piperazine moieties), the endoplasmic reticulum membrane systems (37, bisquaternary bisnaphthalimide; 77, N-Arylpyridinium salt; 68, piperidine derivative), or mitochondria and kinetoplasts (88, N-Arylpyridinium salt; 68, piperidine derivative). Amino acid derivatives with fumaric acid and piperazine moieties (4, 15) weakly inhibiting cysteine proteases seem to preferentially target acidic compartments. Our results suggest that ligand efficiency indices may be helpful to learn about the relationship between potency and chemical characteristics of the compounds. Interestingly, the correlations found between the physico-chemical parameters of the selected compounds and those of commercial molecules that target specific organelles indicate that our rationale might be helpful to drive compound design toward high activities and acceptable pharmacokinetic properties for all compound families.

Activity-based classification circumvents affinity prediction problems for pyrrolidine carboxamide inhibitors of InhA

Developing reliable structure-based activity prediction models for a particular ligand series can be challenging if the target is flexible and the affinity range of the training compounds is narrow. For a data set of 44 pyrrolidine carboxamide inhibitors of the mycobacterial enoyl-ACP-reductase InhA this proved to be case, as scoring methods of various origin and complexity did not succeed in providing practically useful correlations with experimental inhibition data. In contrast, logistic regression models for activity-based classification trained with combinations of scoring functions led to good separation of the more active inhibitors from the weakest compounds. The approach is suggested as an alternative in cases where classical scoring and ranking procedures fail.

Overcoming safety challenges in CO therapy – Extracorporeal CO delivery under precise feedback control of systemic carboxyhemoglobin levels

ABSTRACT Carbon monoxide (CO) has demonstrated therapeutic potential in multiple inflammatory conditions including intensive care applications such as organ transplantation or sepsis. Approaches to translate these findings into future therapies, however, have been challenged by multiple hurdles including handling and toxicity issues associated with systemic CO delivery. Here, we describe a membrane‐controlled Extracorporeal Carbon Monoxide Release System (ECCORS) for easy implementation into Extracorporeal Membrane Oxygenation (ECMO) setups, which are being used to treat cardiac and respiratory diseases in various intensive care applications. Functionalities of the ECCORS were investigated in a pig model of veno‐arterial ECMO. By precisely controlling CO generation and delivery as a function of systemic carboxyhemoglobin levels, the system allows for an immediate onset of therapeutic CO‐levels while preventing CO‐toxicity. Systemic carboxyhemoglobin levels were profiled in real‐time by monitoring exhaled CO levels as well as by pulse oximetry, enabling self‐contained and automatic feedback control of CO generation within ECCORS. Machine learning based mathematical modeling was performed to increase the predictive power of this approach, laying foundation for high precision systemic CO delivery concepts of tomorrow.