| 1. |
- Aftab, Obaid, 1984-, et al.
(författare)
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Detection of cell aggregation and altered cell viability by automated label-free video microscopy : A promising alternative to endpoint viability assays in high throughput screening
- 2015
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Ingår i: Journal of Biomolecular Screening. - : Elsevier BV. - 1087-0571 .- 1552-454X. ; 20:3, s. 372-381
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Tidskriftsartikel (refereegranskat)abstract
- Automated phase-contrast video microscopy now makes it feasible to monitor a high-throughput (HT) screening experiment in a 384-well microtiter plate format by collecting one time-lapse video per well. Being a very cost-effective and label-free monitoring method, its potential as an alternative to cell viability assays was evaluated. Three simple morphology feature extraction and comparison algorithms were developed and implemented for analysis of differentially time-evolving morphologies (DTEMs) monitored in phase-contrast microscopy videos. The most promising layout, pixel histogram hierarchy comparison (PHHC), was able to detect several compounds that did not induce any significant change in cell viability, but made the cell population appear as spheroidal cell aggregates. According to recent reports, all these compounds seem to be involved in inhibition of platelet-derived growth factor receptor (PDGFR) signaling. Thus, automated quantification of DTEM (AQDTEM) holds strong promise as an alternative or complement to viability assays in HT in vitro screening of chemical compounds.
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| 2. |
- Aftab, Obaid, 1984-, et al.
(författare)
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Label-free detection and dynamic monitoring of drug-induced intracellular vesicle formation enabled using a 2-dimensional matched filter
- 2014
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Ingår i: Autophagy. - : Informa UK Limited. - 1554-8627 .- 1554-8635. ; 10:1, s. 57-69
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of vesicle formation and degradation is a central issue in autophagy research and microscopy imaging is revolutionizing the study of such dynamic events inside living cells. A limiting factor is the need for labeling techniques that are labor intensive, expensive, and not always completely reliable. To enable label-free analyses we introduced a generic computational algorithm, the label-free vesicle detector (LFVD), which relies on a matched filter designed to identify circular vesicles within cells using only phase-contrast microscopy images. First, the usefulness of the LFVD is illustrated by presenting successful detections of autophagy modulating drugs found by analyzing the human colorectal carcinoma cell line HCT116 exposed to each substance among 1266 pharmacologically active compounds. Some top hits were characterized with respect to their activity as autophagy modulators using independent in vitro labeling of acidic organelles, detection of LC3-II protein, and analysis of the autophagic flux. Selected detection results for 2 additional cell lines (DLD1 and RKO) demonstrate the generality of the method. In a second experiment, label-free monitoring of dose-dependent vesicle formation kinetics is demonstrated by recorded detection of vesicles over time at different drug concentrations. In conclusion, label-free detection and dynamic monitoring of vesicle formation during autophagy is enabled using the LFVD approach introduced.
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| 3. |
- Aftab, Obaid, 1984-, et al.
(författare)
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Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing
- 2014
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Ingår i: Apoptosis (London). - : Springer Science and Business Media LLC. - 1360-8185 .- 1573-675X. ; 19:9, s. 1411-1418
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Tidskriftsartikel (refereegranskat)abstract
- Label free time-lapse microscopy has opened a new avenue to the study of time evolving events in living cells. When combined with automated image analysis it provides a powerful tool that enables automated large-scale spatiotemporal quantification at the cell population level. Very few attempts, however, have been reported regarding the design of image analysis algorithms dedicated to the detection of apoptotic cells in such time-lapse microscopy images. In particular, none of the reported attempts is based on sufficiently fast signal processing algorithms to enable large-scale detection of apoptosis within hours/days without access to high-end computers. Here we show that it is indeed possible to successfully detect chemically induced apoptosis by applying a two-dimensional linear matched filter tailored to the detection of objects with the typical features of an apoptotic cell in phase-contrast images. First a set of recorded computational detections of apoptosis was validated by comparison with apoptosis specific caspase activity readouts obtained via a fluorescence based assay. Then a large screen encompassing 2,866 drug like compounds was performed using the human colorectal carcinoma cell line HCT116. In addition to many well known inducers (positive controls) the screening resulted in the detection of two compounds here reported for the first time to induce apoptosis.
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| 4. |
- Aftab, Obaid, 1984-, et al.
(författare)
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Label free quantification of time evolving morphologies using time-lapse video microscopy enables identity control of cell lines and discovery of chemically induced differential activity in iso-genic cell line pairs
- 2015
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - 0169-7439 .- 1873-3239. ; 141, s. 24-32
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Tidskriftsartikel (refereegranskat)abstract
- Label free time-lapse video microscopy based monitoring of time evolving cell population morphology has potential to offer a simple and cost effective method for identity control of cell lines. Such morphology monitoring also has potential to offer discovery of chemically induced differential changes between pairs of cell lines of interest, for example where one in a pair of cell lines is normal/sensitive and the other malignant/resistant. A new simple algorithm, pixel histogram hierarchy comparison (PHHC), for comparison of time evolving morphologies (TEM) in phase contrast time-lapse microscopy movies was applied to a set of 10 different cell lines and three different iso-genic colon cancer cell line pairs, each pair being genetically identical except for a single mutation. PHHC quantifies differences in morphology by comparing pixel histogram intensities at six different resolutions. Unsupervised clustering and machine learning based classification methods were found to accurately identify cell lines, including their respective iso-genic variants, through time-evolving morphology. Using this experimental setting, drugs with differential activity in iso-genic cell line pairs were likewise identified. Thus, this is a cost effective and expedient alternative to conventional molecular profiling techniques and might be useful as part of the quality control in research incorporating cell line models, e.g. in any cell/tumor biology or toxicology project involving drug/agent differential activity in pairs of cell line models.
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| 5. |
- Herman, Stephanie, et al.
(författare)
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Mass spectrometry based metabolomics for in vitro systems pharmacology : pitfalls, challenges, and computational solutions.
- 2017
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Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 13:7
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Mass spectrometry based metabolomics has become a promising complement and alternative to transcriptomics and proteomics in many fields including in vitro systems pharmacology. Despite several merits, metabolomics based on liquid chromatography mass spectrometry (LC-MS) is a developing area that is yet attached to several pitfalls and challenges. To reach a level of high reliability and robustness, these issues need to be tackled by implementation of refined experimental and computational protocols.OBJECTIVES: This study illustrates some key pitfalls in LC-MS based metabolomics and introduces an automated computational procedure to compensate for them.METHOD: Non-cancerous mammary gland derived cells were exposed to 27 chemicals from four pharmacological classes plus a set of six pesticides. Changes in the metabolome of cell lysates were assessed after 24 h using LC-MS. A data processing pipeline was established and evaluated to handle issues including contaminants, carry over effects, intensity decay and inherent methodology variability and biases. A key component in this pipeline is a latent variable method called OOS-DA (optimal orthonormal system for discriminant analysis), being theoretically more easily motivated than PLS-DA in this context, as it is rooted in pattern classification rather than regression modeling.RESULT: The pipeline is shown to reduce experimental variability/biases and is used to confirm that LC-MS spectra hold drug class specific information.CONCLUSION: LC-MS based metabolomics is a promising methodology, but comes with pitfalls and challenges. Key difficulties can be largely overcome by means of a computational procedure of the kind introduced and demonstrated here. The pipeline is freely available on www.github.com/stephanieherman/MS-data-processing.
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| 6. |
- Kashif, Muhammad, et al.
(författare)
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A Pragmatic Definition of Therapeutic Synergy Suitable for Clinically Relevant In Vitro Multicompound Analyses
- 2014
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Ingår i: Molecular Cancer Therapeutics. - 1535-7163 .- 1538-8514. ; 13:7, s. 1964-1976
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Tidskriftsartikel (refereegranskat)abstract
- For decades, the standard procedure when screening for candidate anticancer drug combinations has been to search for synergy, defined as any positive deviation from trivial cases like when the drugs are regarded as diluted versions of each other (Loewe additivity), independent actions (Bliss independence), or no interaction terms in a response surface model (no interaction). Here, we show that this kind of conventional synergy analysis may be completely misleading when the goal is to detect if there is a promising in vitro therapeutic window. Motivated by this result, and the fact that a drug combination offering a promising therapeutic window seldom is interesting if one of its constituent drugs can provide the same window alone, the largely overlooked concept of therapeutic synergy (TS) is reintroduced. In vitro TS is said to occur when the largest therapeutic window obtained by the best drug combination cannot be achieved by any single drug within the concentration range studied. Using this definition of TS, we introduce a procedure that enables its use in modern massively parallel experiments supported by a statistical omnibus test for TS designed to avoid the multiple testing problem. Finally, we suggest how one may perform TS analysis, via computational predictions of the reference cell responses, when only the target cell responses are available. In conclusion, the conventional error-prone search for promising drug combinations may be improved by replacing conventional (toxicology-rooted) synergy analysis with an analysis focused on (clinically motivated) TS.
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