PubMed

Recent Publications

Digital Microfluidics for Immunoprecipitation.

Digital Microfluidics for Immunoprecipitation.

Anal Chem. 2016 Oct 4;:

Authors: Seale B, Lam C, Rackus DG, Chamberlain MD, Liu C, Wheeler AR

Abstract
Immunoprecipitation (IP) is a common method for isolating a targeted protein from a complex sample such as blood, serum, or cell lysate. In particular, IP is often used as the primary means of target purification for the analysis by mass spectrometry of novel biologically derived pharmaceuticals, with particular utility for the identification of molecules bound to a protein target. Unfortunately, IP is a labor-intensive technique, is difficult to perform in parallel, and has limited options for automation. Furthermore, the technique is typically limited to large sample volumes, making the application of IP cleanup to precious samples nearly impossible. In recognition of these challenges, we introduce a method for performing microscale IP using magnetic particles and digital microfluidics (DMF-IP). The new method allows for 80% recovery of model proteins from approximately microliter volumes of serum in a sample-to-answer run time of approximately 25 min. Uniquely, analytes are eluted from these small samples in a format compatible with direct analysis by mass spectrometry. To extend the technique to be useful for large samples, we also developed a macro-to-microscale interface called preconcentration using liquid intake by paper (P-CLIP). This technique allows for efficient analysis of samples >100× larger than are typically processed on microfluidic devices. As described herein, DMF-IP and P-CLIP-DMF-IP are rapid, automated, and multiplexed methods that have the potential to reduce the time and effort required for IP sample preparations with applications in the fields of pharmacy, biomarker discovery, and protein biology.

PMID: 27700039 [PubMed - as supplied by publisher]



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The Power of OMICs.

The Power of OMICs.

Biochem Biophys Res Commun. 2016 Sep 20;

Authors: Stagljar I

Abstract
Over the past two decades, the field of systems biology, which encompasses the numerous, widely popular "OMICs" approaches, has driven many significant advances in biomedical research, enabling researchers to generate huge datasets at multiple levels of biological organization. Despite such successes, some scientists still think that "OMICs"-based research introduces a lot of chaos into the biomedical field and claim that the resultant data are often not reproducible and do not reveal deep mechanistic aspects of biological processes. In this editorial, I argue the following: first, that "OMICs" technologies have improved significantly to yield much better datasets; and second, that follow-up studies on components identified in "OMICs" analyses have yielded many valuable biological insights.

PMID: 27663662 [PubMed - as supplied by publisher]



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Angling for A Better View.

Related Articles

Angling for A Better View.

Biophys J. 2016 Sep 20;111(6):1141-2

Authors: Yip CM

PMID: 27653472 [PubMed - in process]



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Resolving coiled shapes reveals new reorientation behaviors in C. elegans.

Resolving coiled shapes reveals new reorientation behaviors in C. elegans.

Elife. 2016;5

Authors: Broekmans OD, Rodgers JB, Ryu WS, Stephens GJ

Abstract
We exploit the reduced space of C. elegans postures to develop a novel tracking algorithm which captures both simple shapes and also self-occluding coils, an important, yet unexplored, component of 2D worm behavior. We apply our algorithm to show that visually complex, coiled sequences are a superposition of two simpler patterns: the body wave dynamics and a head-curvature pulse. We demonstrate the precise Ω-turn dynamics of an escape response and uncover a surprising new dichotomy in spontaneous, large-amplitude coils; deep reorientations occur not only through classical Ω-shaped postures but also through larger postural excitations which we label here as δ-turns. We find that omega and delta turns occur independently, suggesting a distinct triggering mechanism, and are the serpentine analog of a random left-right step. Finally, we show that omega and delta turns occur with approximately equal rates and adapt to food-free conditions on a similar timescale, a simple strategy to avoid navigational bias.

PMID: 27644113 [PubMed - as supplied by publisher]



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Cellular adaptation to biomechanical stress across length scales in tissue homeostasis and disease.

Cellular adaptation to biomechanical stress across length scales in tissue homeostasis and disease.

Semin Cell Dev Biol. 2016 Sep 15;

Authors: Weaver VM, Gilbert PM

Abstract
Human tissues are remarkably adaptable and robust, harboring the collective ability to detect and respond to external stresses while maintaining tissue integrity. Following injury, many tissues have the capacity to repair the damage - and restore form and function - by deploying cellular and molecular mechanisms reminiscent of developmental programs. Indeed, it is increasingly clear that cancer and chronic conditions that develop with age arise as a result of cells and tissues re-implementing and deregulating a selection of developmental programs. Therefore, understanding the fundamental molecular mechanisms that drive cell and tissue responses is a necessity when designing therapies to treat human conditions. Extracellular matrix stiffness synergizes with chemical cues to drive single cell and collective cell behavior in culture and acts to establish and maintain tissue homeostasis in the body. This review will highlight recent advances that elucidate the impact of matrix mechanics on cell behavior and fate across these length scales during times of homeostasis and in disease states.

PMID: 27641825 [PubMed - as supplied by publisher]



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Foraging success under uncertainty: search tradeoffs and optimal space use.

Foraging success under uncertainty: search tradeoffs and optimal space use.

Ecol Lett. 2016 Sep 15;

Authors: Bartumeus F, Campos D, Ryu WS, Lloret-Cabot R, Méndez V, Catalan J

Abstract
Understanding the structural complexity and the main drivers of animal search behaviour is pivotal to foraging ecology. Yet, the role of uncertainty as a generative mechanism of movement patterns is poorly understood. Novel insights from search theory suggest that organisms should collect and assess new information from the environment by producing complex exploratory strategies. Based on an extension of the first passage time theory, and using simple equations and simulations, we unveil the elementary heuristics behind search behaviour. In particular, we show that normal diffusion is not enough for determining optimal exploratory behaviour but anomalous diffusion is required. Searching organisms go through two critical sequential phases (approach and detection) and experience fundamental search tradeoffs that may limit their encounter rates. Using experimental data, we show that biological search includes elements not fully considered in contemporary physical search theory. In particular, the need to consider search movement as a non-stationary process that brings the organism from one informational state to another. For example, the transition from remaining in an area to departing from it may occur through an exploratory state where cognitive search is challenged. Therefore, a more comprehensive view of foraging ecology requires including current perspectives about movement under uncertainty.

PMID: 27634051 [PubMed - as supplied by publisher]



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Strategies to Develop Inhibitors of Motif-Mediated Protein-Protein Interactions as Drug Leads.

Strategies to Develop Inhibitors of Motif-Mediated Protein-Protein Interactions as Drug Leads.

Annu Rev Pharmacol Toxicol. 2016 Sep 8;

Authors: Corbi-Verge C, Garton M, Nim S, Kim PM

Abstract
Protein-protein interactions are fundamental for virtually all functions of the cell. A large fraction of these interactions involve short peptide motifs, and there has been increased interest in targeting them using peptide-based therapeutics. Peptides benefit from being specific, relatively safe, and easy to produce. They are also easy to modify using chemical synthesis and molecular biology techniques. However, significant challenges remain regarding the use of peptides as therapeutic agents. Identification of peptide motifs is difficult, and peptides typically display low cell permeability and sensitivity to enzymatic degradation. In this review, we outline the principal highthroughput methodologies for motif discovery and describe current methods for overcoming pharmacokinetic and bioavailability limitations. Expected final online publication date for the Annual Review of Pharmacology and Toxicology Volume 57 is January 06, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

PMID: 27618737 [PubMed - as supplied by publisher]



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Rapid Bacterial Detection via an All-Electronic CMOS Biosensor.

Rapid Bacterial Detection via an All-Electronic CMOS Biosensor.

PLoS One. 2016;11(9):e0162438

Authors: Nikkhoo N, Cumby N, Gulak PG, Maxwell KL

Abstract
The timely and accurate diagnosis of infectious diseases is one of the greatest challenges currently facing modern medicine. The development of innovative techniques for the rapid and accurate identification of bacterial pathogens in point-of-care facilities using low-cost, portable instruments is essential. We have developed a novel all-electronic biosensor that is able to identify bacteria in less than ten minutes. This technology exploits bacteriocins, protein toxins naturally produced by bacteria, as the selective biological detection element. The bacteriocins are integrated with an array of potassium-selective sensors in Complementary Metal Oxide Semiconductor technology to provide an inexpensive bacterial biosensor. An electronic platform connects the CMOS sensor to a computer for processing and real-time visualization. We have used this technology to successfully identify both Gram-positive and Gram-negative bacteria commonly found in human infections.

PMID: 27618185 [PubMed - as supplied by publisher]



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Exploring Quantitative Yeast Phenomics with Single-Cell Analysis of DNA Damage Foci.

Exploring Quantitative Yeast Phenomics with Single-Cell Analysis of DNA Damage Foci.

Cell Syst. 2016 Sep 7;

Authors: Styles EB, Founk KJ, Zamparo LA, Sing TL, Altintas D, Ribeyre C, Ribaud V, Rougemont J, Mayhew D, Costanzo M, Usaj M, Verster AJ, Koch EN, Novarina D, Graf M, Luke B, Muzi-Falconi M, Myers CL, Mitra RD, Shore D, Brown GW, Zhang Z, Boone C, Andrews BJ

Abstract
A significant challenge of functional genomics is to develop methods for genome-scale acquisition and analysis of cell biological data. Here, we present an integrated method that combines genome-wide genetic perturbation of Saccharomyces cerevisiae with high-content screening to facilitate the genetic description of sub-cellular structures and compartment morphology. As proof of principle, we used a Rad52-GFP marker to examine DNA damage foci in ∼20 million single cells from ∼5,000 different mutant backgrounds in the context of selected genetic or chemical perturbations. Phenotypes were classified using a machine learning-based automated image analysis pipeline. 345 mutants were identified that had elevated numbers of DNA damage foci, almost half of which were identified only in sensitized backgrounds. Subsequent analysis of Vid22, a protein implicated in the DNA damage response, revealed that it acts together with the Sgs1 helicase at sites of DNA damage and preferentially binds G-quadruplex regions of the genome. This approach is extensible to numerous other cell biological markers and experimental systems.

PMID: 27617677 [PubMed - as supplied by publisher]



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The health care and life sciences community profile for dataset descriptions.

The health care and life sciences community profile for dataset descriptions.

PeerJ. 2016;4:e2331

Authors: Dumontier M, Gray AJ, Marshall MS, Alexiev V, Ansell P, Bader G, Baran J, Bolleman JT, Callahan A, Cruz-Toledo J, Gaudet P, Gombocz EA, Gonzalez-Beltran AN, Groth P, Haendel M, Ito M, Jupp S, Juty N, Katayama T, Kobayashi N, Krishnaswami K, Laibe C, Le Novère N, Lin S, Malone J, Miller M, Mungall CJ, Rietveld L, Wimalaratne SM, Yamaguchi A

Abstract
Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

PMID: 27602295 [PubMed]



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