Kinetic Cell-Based Morphological Screening: Prediction of Mechanism of Compound Action and Off-Target Effects

SummaryWe describe a cell-based kinetic profiling approach using impedance readout for monitoring the effect of small molecule compounds. This noninvasive readout allows continuous sampling of cellular responses to biologically active compounds and the ensuing kinetic profile provides information regarding the temporal interaction of compounds with cells. The utility of this approach was tested by screening a library containing FDA approved drugs, experimental compounds, and nature compounds. Compounds with similar activity produced similar impedance-based time-dependent cell response profiles (TCRPs). The compounds were clustered based on TCRP similarity. We identified novel mechanisms for existing drugs, confirmed previously reported calcium modulating activity for COX-2 inhibitor celecoxib, and identified an additional mechanism for the experimental compound monastrol. We also identified and characterized a new antimitotic agent. Our findings indicate that the TCRP approach provides predictive mechanistic information for small molecule compounds

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

A general modeling and visualization tool for comparing different members of a group: application to studying tau-mediated regulation of microtubule dynamics

<p>Abstract</p> <p>Background</p> <p>Innumerable biological investigations require comparing collections of molecules, cells or organisms to one another with respect to one or more of their properties. Almost all of these comparisons are performed manually, which can be susceptible to inadvertent bias as well as miss subtle effects. The development and application of computer-assisted analytical and interpretive tools could help address these issues and thereby dramatically improve these investigations.</p> <p>Results</p> <p>We have developed novel computer-assisted analytical and interpretive tools and applied them to recent studies examining the ability of 3-repeat and 4-repeat tau to regulate the dynamic behavior of microtubules in vitro. More specifically, we have developed an automated and objective method to define growth, shortening and attenuation events from real time videos of dynamic microtubules, and demonstrated its validity by comparing it to manually assessed data. Additionally, we have used the same data to develop a general strategy of building different models of interest, computing appropriate dissimilarity functions to compare them, and embedding them on a two-dimensional plot for visualization and easy comparison. Application of these methods to assess microtubule growth rates and growth rate distributions established the validity of the embedding procedure and revealed non-linearity in the relationship between the tau:tubulin molar ratio and growth rate distribution.</p> <p>Conclusion</p> <p>This work addresses the need of the biological community for rigorously quantitative and generally applicable computational tools for comparative studies. The two-dimensional embedding method retains the inherent structure of the data, and yet markedly simplifies comparison between models and parameters of different samples. Most notably, even in cases where numerous parameters exist by which to compare the different samples, our embedding procedure provides a generally applicable computational strategy to detect subtle relationships between different molecules or conditions that might otherwise escape manual analyses.</p

VISTA Variables in the <i>Vía Láctea</i> (VVV): Halfway Status and Results

The VISTA Variables in the Vía Láctea (VVV) survey is one of six near-infrared ESO public surveys, and is now in its fourth year of observing. Although far from being complete, the VVV survey has already delivered many results, some directly connected to the intended science goals (detection of variable stars, microlensing events, new star clusters), others concerning more exotic objects, e.g., novae. Now, at the end of the fourth observing period, and comprising roughly 50% of the proposed observations, the status of the survey, as well some of results based on the VVV data, are presented.Facultad de Ciencias Astronómicas y Geofísica

VISTA Variables in the <i>Vía Láctea</i> (VVV): Halfway Status and Results

The VISTA Variables in the Vía Láctea (VVV) survey is one of six near-infrared ESO public surveys, and is now in its fourth year of observing. Although far from being complete, the VVV survey has already delivered many results, some directly connected to the intended science goals (detection of variable stars, microlensing events, new star clusters), others concerning more exotic objects, e.g., novae. Now, at the end of the fourth observing period, and comprising roughly 50% of the proposed observations, the status of the survey, as well some of results based on the VVV data, are presented.Facultad de Ciencias Astronómicas y Geofísica

Was it Uruguay or Coffee? The causes of the beef jerky industry’s decline in southern Brazil (1850 – 1889)

What caused the decline of the beef jerky’s production in Brazil? The main sustenance for slaves, beef jerky was the most important industry in southern Brazil. Nevertheless, by 1850, producers were already worried that they could not compete with Uruguayan industry. Traditional interpretations impute the decline to labor markets differences in productivity, since Brazil used slaves while Uruguay had abolished slavery in 1842. Recent research also raises the possibility of a Brazilian “Dutch Disease”, resulting from the coffee exports boom. We test both hypothesis and argue that Brazilian production’s decline was associated with structural changes in demand for low quality meat. Trade protection policies created disincentives for Brazilian producers to increase productivity and diversify its cattle industry

Factors That Drive Peptide Assembly and Fibril Formation: Experimental and Theoretical Analysis of Sup35 NNQQNY Mutants

Residue mutations have substantial effects on aggregation kinetics and propensities of amyloid peptides and their aggregate morphologies. Such effects are attributed to conformational transitions accessed by various types of oligomers such as steric zipper or single β-sheet. We have studied the aggregation propensities of six NNQQNY mutants: NVVVVY, NNVVNV, NNVVNY, VIQVVY, NVVQIY, and NVQVVY in water using a combination of ion-mobility mass spectrometry, transmission electron microscopy, atomic force microscopy, and all-atom molecular dynamics simulations. Our data show a strong correlation between the tendency to form early β-sheet oligomers and the subsequent aggregation propensity. Our molecular dynamics simulations indicate that the stability of a steric zipper structure can enhance the propensity for fibril formation. Such stability can be attained by either hydrophobic interactions in the mutant peptide or polar side-chain interdigitations in the wild-type peptide. The overall results display only modest agreement with the aggregation propensity prediction methods such as PASTA, Zyggregator, and RosettaProfile, suggesting the need for better parametrization and model peptides for these algorithms