Structure, toxicity and antibiotic activity of gramicidin S and derivatives

Development of new antibiotics is declining whereas antibiotic resistance is rising, heralding a post-antibiotic era. Antimicrobial peptides such as gramicidin S (GS), exclusively topically used due to its hemolytic side-effect, could still be interesting as therapeutic compounds. By modifying the amino-acid composition of GS, we synthesized GS analogues. We now show that derivative VK7 has a lower MIC (7.8–31.2 μg/ml, median 15.6 μg/ml) against strains of multi-drug resistant (MDR) Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa than GS has (3.9–62.5 μg/ml, median 31.3 μg/ml). Low MICs for both VK7 and GS were observed for Staphylococcus aureus and Enterococcus faecium

Identifying Personalized Metabolic Signatures in Breast Cancer.

Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism, and reactive oxygen species (ROS) detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach

A regression model approach to enable cell morphology correction in high-throughput flow cytometry

Large variations in cell size and shape can undermine traditional gating methods for analyzing flow cytometry data. Correcting for these effects enables analysis of high-throughput data sets, including >5000 yeast samples with diverse cell morphologies

Exploiting combinatorial cultivation conditions to infer transcriptional regulation

BACKGROUND: Regulatory networks often employ the model that attributes changes in gene expression levels, as observed across different cellular conditions, to changes in the activity of transcription factors (TFs). Although the actual conditions that trigger a change in TF activity should form an integral part of the generated regulatory network, they are usually lacking. This is due to the fact that the large heterogeneity in the employed conditions and the continuous changes in environmental parameters in the often used shake-flask cultures, prevent the unambiguous modeling of the cultivation conditions within the computational framework. RESULTS: We designed an experimental setup that allows us to explicitly model the cultivation conditions and use these to infer the activity of TFs. The yeast Saccharomyces cerevisiae was cultivated under four different nutrient limitations in both aerobic and anaerobic chemostat cultures. In the chemostats, environmental and growth parameters are accurately controlled. Consequently, the measured transcriptional response can be directly correlated with changes in the limited nutrient or oxygen concentration. We devised a tailor-made computational approach that exploits the systematic setup of the cultivation conditions in order to identify the individual and combined effects of nutrient limitations and oxygen availability on expression behavior and TF activity. CONCLUSION: Incorporating the actual growth conditions when inferring regulatory relationships provides detailed insight in the functionality of the TFs that are triggered by changes in the employed cultivation conditions. For example, our results confirm the established role of TF Hap4 in both aerobic regulation and glucose derepression. Among the numerous inferred condition-specific regulatory associations between gene sets and TFs, also many novel putative regulatory mechanisms, such as the possible role of Tye7 in sulfur metabolism, were identified

Older and younger adults are influenced differently by dark pattern designs

Considering that prior research has found older users undergo a different privacy decision-making process compared to younger adults, more research is needed to inform the behavioral privacy disclosure effects of these strategies for different age groups. To address this gap, we used an existing dataset of an experiment with a photo-tagging Facebook application. This experiment had a 2x2x5 between-subjects design where the manipulations were common dark pattern design strategies: framing (positive vs. negative), privacy defaults (opt-in vs. opt-out), and justification messages (positive normative, negative normative, positive rationale, negative rationale, none). We compared older (above 65 years old, N=44) and young adults (18 to 25 years old, N=162) privacy concerns and disclosure behaviors (i.e., accepting or refusing automated photo tagging) in the scope of dark pattern design. Overall, we find support for the effectiveness of dark pattern designs in the sense that positive framing and opt-out privacy defaults significantly increased disclosure behavior, while negative justification messages significantly decreased privacy concerns. Regarding older adults, our results show that certain dark patterns do lead to more disclosure than for younger adults, but also to increased privacy concerns for older adults than for younger

What am I not seeing? An Interactive Approach to Social Content Discovery in Microblogs

In this paper, we focus on the informational and user experience benefits of user-driven topic exploration in microblog communities, such as Twitter, in an inspectable, controllable and personalized manner. To this end, we introduce ``HopTopics'' -- a novel interactive tool for exploring content that is popular just beyond a user's typical information horizon in a microblog, as defined by the network of individuals that they are connected to. We present results of a user study (N=122) to evaluate HopTopics with varying complexity against a typical microblog feed in both personalized and non-personalized conditions. Results show that the HopTopics system, leveraging content from both the direct and extended network of a user, succeeds in giving users a better sense of control and transparency. Moreover, participants had a poor mental model for the degree of novel content discovered when presented with non-personalized data in the Inspectable interface

Evaluation of the antigen-experienced B-cell receptor repertoire in healthy children and adults

Upon antigen recognition via their B cell receptor (BR), B cells migrate to the germinal center where they undergo somatic hypermutation (SHM) to increase their affinity for the antigen, and class switch recombination (CSR) to change the effector function of the secreted antibodies. These steps are essential to create an antigen-experienced BR repertoire that efficiently protects the body against pathogens. At the same time, the BR repertoire should be selected to protect against responses to self-antigen or harmless antigens. Insights into the processes of SHM, selection, and CSR can be obtained by studying the antigen-experienced BR repertoire. Currently, a large reference data set of healthy children and adults, which ranges from neonates to the elderly, is not available. In this study, we analyzed the antigen-experienced repertoire of 38 healthy donors (HD), ranging from cord blood to 74 years old, by sequencing IGA and IGG transcripts using next generation sequencing. This resulted in a large, freely available reference data set containing 412,890 IGA and IGG transcripts. We used this data set to study mutation levels, SHM patterns, antigenic selection, and CSR from birth to elderly HD. Only small differences were observed in SHM patterns, while the mutation levels increase in early childhood and stabilize at 6 years of age at around 7%. Furthermore, comparison of the antigen-experienced repertoire with sequences from the naive immune repertoire showed that features associated with autoimmunity such as long CDR3 length and IGHV4-34 usage are reduced in the antigen-experienced repertoire. Moreover, IGA2 and IGG2 usage was increased in HD in higher age categories, while IGG1 usage was decreased. In addition, we studied clonal relationship in the different samples. Clonally related sequences were found with different subclasses. Interestingly, we found transcripts with the same CDR1-CDR3 sequence, but different subclasses. Together, these data suggest that a single antigen can provoke a B-cell response with BR of different subclasses and that, during the course of an immune response, some B cells change their isotype without acquiring additional SHM or can directly switch to different isotypes

Combinatorial effects of environmental parameters on transcriptional regulation in Saccharomyces cerevisiae: A quantitative analysis of a compendium of chemostat-based transcriptome data

<p>Abstract</p> <p>Background</p> <p>Microorganisms adapt their transcriptome by integrating multiple chemical and physical signals from their environment. Shake-flask cultivation does not allow precise manipulation of individual culture parameters and therefore precludes a quantitative analysis of the (combinatorial) influence of these parameters on transcriptional regulation. Steady-state chemostat cultures, which do enable accurate control, measurement and manipulation of individual cultivation parameters (e.g. specific growth rate, temperature, identity of the growth-limiting nutrient) appear to provide a promising experimental platform for such a combinatorial analysis.</p> <p>Results</p> <p>A microarray compendium of 170 steady-state chemostat cultures of the yeast <it>Saccharomyces cerevisiae </it>is presented and analyzed. The 170 microarrays encompass 55 unique conditions, which can be characterized by the combined settings of 10 different cultivation parameters. By applying a regression model to assess the impact of (combinations of) cultivation parameters on the transcriptome, most <it>S. cerevisiae </it>genes were shown to be influenced by multiple cultivation parameters, and in many cases by combinatorial effects of cultivation parameters. The inclusion of these combinatorial effects in the regression model led to higher explained variance of the gene expression patterns and resulted in higher function enrichment in subsequent analysis. We further demonstrate the usefulness of the compendium and regression analysis for interpretation of shake-flask-based transcriptome studies and for guiding functional analysis of (uncharacterized) genes and pathways.</p> <p>Conclusion</p> <p>Modeling the combinatorial effects of environmental parameters on the transcriptome is crucial for understanding transcriptional regulation. Chemostat cultivation offers a powerful tool for such an approach.</p