Automated longitudinal monitoring of in vivo protein aggregation in neurodegenerative disease C. elegans models
© Cornaglia et al. 2016
Received: 17 September 2015
Accepted: 1 February 2016
Published: 9 February 2016
While many biological studies can be performed on cell-based systems, the investigation of molecular pathways related to complex human dysfunctions – e.g. neurodegenerative diseases – often requires long-term studies in animal models. The nematode Caenorhabditis elegans represents one of the best model organisms for many of these tests and, therefore, versatile and automated systems for accurate time-resolved analyses on C. elegans are becoming highly desirable tools in the field.
We describe a new multi-functional platform for C. elegans analytical research, enabling automated worm isolation and culture, reversible worm immobilization and long-term high-resolution imaging, and this under active control of the main culture parameters, including temperature. We employ our platform for in vivo observation of biomolecules and automated analysis of protein aggregation in a C. elegans model for amyotrophic lateral sclerosis (ALS). Our device allows monitoring the growth rate and development of each worm, at single animal resolution, within a matrix of microfluidic chambers. We demonstrate the progression of individual protein aggregates, i.e. mutated human superoxide dismutase 1 - Yellow Fluorescent Protein (SOD1-YFP) fusion proteins in the body wall muscles, for each worm and over several days. Moreover, by combining reversible worm immobilization and on-chip high-resolution imaging, our method allows precisely localizing the expression of biomolecules within the worms’ tissues, as well as monitoring the evolution of single aggregates over consecutive days at the sub-cellular level. We also show the suitability of our system for protein aggregation monitoring in a C. elegans Huntington disease (HD) model, and demonstrate the system’s ability to study long-term doxycycline treatment-linked modification of protein aggregation profiles in the ALS model.
Our microfluidic-based method allows analyzing in vivo the long-term dynamics of protein aggregation phenomena in C. elegans at unprecedented resolution. Pharmacological screenings on neurodegenerative disease C. elegans models may strongly benefit from this method in the near future, because of its full automation and high-throughput potential.
KeywordsCaenorhabditis elegans Neurodegenerative disease Amyotrophic lateral sclerosis (ALS) Huntington disease (HD) Doxycycline treatment Protein aggregation Longitudinal time-resolved analysis High-resolution imaging Worm immobilization Temperature control Microfluidics
The growing incidence of neurodegenerative diseases (NDs) urges for a complete understanding of the molecular processes underlying neurodegeneration, as a first step towards the final promise of a new class of therapeutics for these diseases. Cellular models have been exploited for some of these studies [1, 2], but the high complexity of the molecular mechanisms implicated in NDs increasingly demands in vivo models for the investigation of complex phenotypes, which are determined by the interplay among different tissues and pathways . The nematode Caenorhabditis elegans represents a very convenient model organism for such in vivo tests, mainly because of its very fast life cycle, combined with the ease of its genetic manipulation and the relatively high level of conserved mechanisms between C. elegans and humans . In the last two decades, several protein-misfolding disorders, including age-related NDs, have been successfully modeled in C. elegans indeed ; libraries of transgenic worms are currently available for the research of the molecular mechanisms underlying Alzheimer’s, Parkinson’s and Huntington’s diseases, as well as ALS . Transgenic expression of disease genes in C. elegans is typically visualized via fluorescently tagged proteins within its transparent tissues. In most of the NDs, specific proteins self-assemble into aggregated species and cellular toxicity can be induced by the protein misfolding and aggregation process itself . Therefore, the spatio-temporal-resolved observation of protein expression and aggregation, associated with the quantification and localization of these aggregates is a key analytical method for the in vivo monitoring of disease evolution. Unfortunately, conventional C. elegans handling and imaging techniques do not allow accurate monitoring of aggregate progression in individual worms over time, since nematodes are typically cultured in large populations on agar plates and irreversibly immobilized by means of anesthetics for high-resolution imaging.
The advent of microfluidics within the C. elegans research community is progressively revolutionizing the field [6–9]. In particular, several miniaturized devices proved their potential in neurobiology studies, such as the investigation of C. elegans oxygen sensation , olfactory  and chemosensory  neuronal activity, exploratory and learning behavior , neurotoxin-induced responses , neuromuscular function , and nerve regeneration [16, 17]. In the neurodegeneration research field, Càceres et al.  recently proposed a microscale system for high-throughput visual screens on worms. This system exploited a curved microchannel geometry to trigger the positioning of nematodes into lateral orientations and facilitate the inspection of D-type motor neurons. Although this device allowed efficiently screening mutants carrying neurodegenerative defects, it did not permit longitudinal monitoring of the worms. Other microfluidic platforms have instead demonstrated the feasibility of continuous worm culture and observation. For example, Krajniak et al.  showed the microfluidic culture of L1-L3 larvae over periods of 12–36 h, whilst introducing a method for worms’ reversible immobilization based on a thermo-sensitive sol–gel transition. Other studies demonstrated the applicability of this immobilization method in different microfluidic formats [20–22]. However, protein aggregation monitoring within ND disease models typically requires worm culture and repeated high-resolution imaging of the same worm over significantly longer time periods (e.g. > 3 days). This imposes severe requirements in terms of system robustness and automation, related to the simultaneous and strict control of environmental conditions, like worm feeding, fluidic exchanges, temperature of the microfluidic environment, etc.. In this perspective, Rohde et al.  demonstrated an elegant automated system for in vivo time-lapse imaging and high-throughput screening of C. elegans in standard multiwell plates, which employed an in-well cooling apparatus for reversible worm immobilization. However, the use of this device for protein aggregation monitoring at single animal resolution is less trivial, as it did not have microfluidics on-board and could not exploit brightfield transmission microscopy as analytical tool. Here we introduce a microfluidic-based methodology for long-term and high-resolution monitoring of protein aggregation and automated analysis of C. elegans ND models. Specifically, we demonstrate the feasibility of in vivo observation, over 4 days at single animal resolution, of SOD1 aggregation in the AM725 C. elegans transgenic strain, which we use as a biological model system for the investigation of the human ALS disease. This is enabled by our microfluidic platform, which co-integrates the following options and functionalities: (i) a method for fast confinement of worms of desired age in microfluidic chambers, by means of pure passive hydrodynamics with no need of any active components, such as integrated valves; (ii) a technique for continuous worm feeding and progeny removal, to preserve the on-chip worm identity over long-term studies; (iii) a method for reversible C. elegans immobilization using a hydrogel, enabling high-resolution imaging at arbitrarily selected moments of their whole lifespan; (iv) an integrated active temperature control system, both to set precise environmental conditions for C. elegans maintenance and to automatically steer the worm immobilization/release process; (v) a compact device assembly, readily adaptable to host different microfluidic designs and suitable for automated multi-dimensional imaging on any upright or inverted microscope.
Results and discussion
Worm arraying via passive valves
Temperature control system design and characterization
Automated worm culture and imaging protocol
The cross-shape of our chips, with in- and outflows along two orthogonal directions, is designed to decouple the worms’ dispensing operation (in the In1-Out1 direction) from the worm culture and imaging protocol. Along the In2-Out2 direction, adjacent chambers are connected by narrow filters – 5 × 14 μm2 in section – allowing perfusion of liquids across the whole chamber matrix, while preventing any inter-chamber exchange of worms, even under over-pressure conditions. Also, after worm dispensing, the In1-Out1 flow direction can be employed during the culture experiments for evacuating the progeny of the adult worms under analysis. Each switching between the two flow directions is simply controlled by two external valves at the two chip outlets.
Long-term protein aggregation analysis in an amyotrophic lateral sclerosis (ALS) C. elegans model
A second set of studies is then conducted by imaging the immobilized worms through a 63× oil immersion objective (NA 1.4). Many aggregates in AM725 worms, unlike in other analogous SOD1-transgenic strains – e.g. pUnc-54::SOD1-G85R::YFP (G85R) and pUnc-54::SOD1- G93A::YFP (G93A) –, appear as irregular, elongated foci . This feature could be observed before by confocal imaging of paralyzed worms. We are now able to confirm this observation in alive immobilized worms and provide a precise sub-cellular mapping of their protein aggregation pattern at high spatio-temporal resolution by using a standard fluorescent microscope (Fig. 7d). Moreover, the possibility to take quasi-instantaneous brightfield and fluorescent pictures in our chip allows accurately locating each fluorescent signal inside the C. elegans body. In combination with reversible worm immobilization, this opens the possibility of following the temporal evolution of protein aggregation at precise locations within the worm tissues and monitoring aggregate progression in vivo, not only at single-worm, but even at the single-cell level (Fig. 7e).
Long-term protein aggregation analysis in a Huntington disease (HD) C. elegans model
To ascertain that this approach is not specific only for the ALS model, we monitor the dynamics of protein aggregation in a different C. elegans model of neurodegenerative diseases, i.e. a Huntington disease (HD) model (Additional file 1: Supplementary Note 6). More particularly, we employ a HD model expressing YFP fused to stretches of 35 glutamine residues (AM140 transgenic strain) . Our system allows the observation of distinct aggregation patterns for this model and allows following the long-term evolution of both aggregate size and number, with results in line with what has been previously reported . Furthermore, the specificity of the approach to monitor the aggregates is validated by using a strain expressing the YFP only in the body wall muscles (AM134 strain) and showing only a diffuse fluorescence in these tissues .
Modifying long-term protein aggregation in an ALS C. elegans model by doxycycline treatment
Protein aggregation diseases are often associated with movement disorders, and worm models of neurodegenerative diseases also recapitulate this feature [31, 35, 47–49]. Interestingly, doxycycline treatment significantly slows down the progressive loss of motility in the ALS strain, as observed on NGM plates (Fig. 8e). Since doxycycline is known to affect the mitochondrial translation in eukaryote systems , we then employ a genetic approach to impact on the mitochondrial translation machinery. We silence by RNAi the gene mrps-5 (mitochondrial ribosomal protein S5), an important molecular actor for the mitochondrial translation , and we could observe similar effects on the motility in the ALS model (Fig. 8f). All together, these results show that doxycycline can prevent the size expansion of aggregates in a C. elegans model of ALS, and this improvement correlates with a delay in the loss of motility.
We introduce a new analytical technique and device for automated time-resolved studies on C. elegans nematodes down to single-worm resolution. Our platform is based on a multi-functional approach, where several functionalities are integrated into a single miniaturized device, to allow fully automated worm analyses. The device is moreover designed to be compatible with different microfluidic designs and readily suitable for different sets of studies.
In our platform, C. elegans nematodes are loaded into a microfluidic chip, where they are directly distributed among a set of culture chambers via a “passive valving” method. Geometrical constraints on the chip allow retaining only worms of desired size inside the device, whereas an automated on-chip culture protocol is established to ensure their correct feeding and development. Active control of the chip temperature ensures moreover running worm cultures at desired temperatures, with minimal variation throughout long-term analyses. For screening purposes and high-throughput-like experiments, our platform can be readily used in imaging experiments with standard low-magnification microscope objectives. Moreover, to allow longitudinal high-resolution imaging of the worms, we optimize an automated procedure for reversible worm immobilization on-chip. This protocol is based on the thermoreversible gelation of PF127 polymer inside the device, managed by the closed-loop temperature control system as well. Any worms’ progeny is periodically washed out of the chip, with no risk of mixing the identities of the worms under analysis. Therefore, tests at single-worm resolution can be easily performed on our platform. Finally, all the microfluidic designs used in our studies are conceived in a “chamber-matrix” format, which allows easy automation of the imaging process as well.
We fully characterize the different functionalities of our platform, both theoretically and experimentally. We demonstrate fast and precise temperature management on the device and provide calibration curves for its use both in open-loop mode and in closed-loop configuration. We characterize the different integrated worm handling protocols – i.e. on-chip worm loading, feeding, immobilization, imaging – and provide details for their use on the platform. We then employ our device to tackle the challenging task of analyzing the dynamics of protein aggregation in ALS worm models over long-term experiments. Our results show that the device ensures reliable culture and reproducible growth rate of the worms over several days. The possibility of isolating single worms in separated chambers allows collecting population statistics, while preserving at the same time all the information related to the single nematodes under test. For high-resolution imaging experiments, we employ the on-chip immobilization protocol to temporarily immobilize the worms in a reversible way and periodically collect data about protein aggregation in their tissues via high-resolution fluorescent imaging. Our results show that the amount of SOD1-YFP aggregates in an ALS C. elegans model (AM725 transgenic worms) linearly increases over the whole analyzed period (i.e. day 1 to day 4 of adult life). Combined brightfield and fluorescent imaging at high magnification allows moreover mapping the geometry of the aggregates, precisely locate them within the tissues of each worm and following their progression over consecutive days. We also demonstrate the suitability of our system for protein aggregation monitoring in a C. elegans Huntington disease (HD) model, and demonstrate the systems’s ability to study long-term doxycycline treatment-linked modification of protein aggregation profiles in the ALS model. In fact, the relatively short period needed for the quantification of a significant increase in SOD1-YFP aggregates opens the possibility for future studies of rapid identification of ALS modifiers . Because of its good performance in terms of automation and versatility, we envision that our system could be employed to address many other challenging biological questions on C. elegans, related in particular to the study of neurodegenerative diseases – such as Parkinson’s, and Alzheimer’s disease – which are all modelled in worms .
Our platform could moreover be used for studies of C. elegans movement disorders, for quantifying other phenotypes such as pharyngeal pumping rates, motility, etc. or more generally could be used in chemical or biological laboratories that do in vivo studies and analyses of multicellular organisms.
Chemicals and materials
Four-inch 550 μm thick Si and float glass wafers, de-ionized water (DIW) were obtained from the Center of Micro- and Nanotechnology of EPFL. GM 1070 SU-8 negative photoresist was purchased from Gersteltec (Pully, Switzerland). PDMS Sylgard 184 was acquired from Dow Corning (Wiesbaden, Germany). 1 mL borosilicate H-TLL-PE syringes were purchased from Innovative Laborsysteme GmbH (Stutzerbach, Germany). Microline ethyl vinyl acetate tube with 0.51 mm inner and 1.52 mm outer diameters was bought from Fisher Scientific (Wohlen, Switzerland). Pluronic F-127 was purchased from Sigma-Aldrich (Buchs, Switzerland). M9 buffer was obtained by adding 3 g KH2PO4, 6 g Na2HPO4, 5 g NaCl, 1 mL 1 M MgSO4, H2O to 1 l and sterilization by autoclaving. S-medium buffer was obtained by adding 10 mL 1 M potassium citrate pH 6, 10 mL trace metals solution (1.86 g disodium EDTA, 0.69 g FeSO4 · 7H2O, 0.2 g MnCl2 · 4H2O, 0.29 g ZnSO4 · 7H2O and 0.025 g CuSO4 · 5H2O, H2O to 1 l) 3 mL 1 M CaCl2, 3 mL 1 M MgSO4, 1 mL [50 mg/mL] carbenicillin, 0.5 mL tween 20 to 1 l S Basal (5.85 g NaCl, 1 g K2HPO4, 6 g KH2PO4, 1 mL [5 mg/mL] cholesterol, H2O to 1 l) and sterilization by autoclaving. Pluronic F127 solution was prepared by diluting 25 % (weight/volume) Pluronic F127 in water. Aluminum and polymethylmetacrylate (PMMA) assembly parts were fabricated at the engineering workshop of EPFL. Thermoelectric modules were bought from TE Technology, Inc. (Traverse City, MI, USA), heat sinks from Advanced Thermal Solutions, Inc. (Norwood, MA, USA) and RTD sensors from Innovative Sensor Technology AG (Ebnat-Kappel, Switzerland), while a proportional-integral-derivative (PID) temperature controller was purchased from BelektroniG GmbH (Freital, Germany).
C. elegans strains and culture
C. elegans strains were cultured at 20 °C on NGM agar plates seeded with the Escherichia coli strain OP50. Strains used were wild-type Bristol N2, AM725 (rmIs290[unc-54p::Hsa-sod-1(127X)::YFP]), AM134 (rmIs126[unc-54p::Q0::YFP]), AM140 (rmIs132[unc-54p::Q35::YFP]) and SJ4100 (zcIs13[hsp-6::GFP]) and were provided by the Caenorhabditis Genetics Center (University of Minnesota). Worms were suspended in S-medium solution prior to each microfluidic experiment. For microfluidic experiments, the E. coli strain HT115 was suspended in S-medium at a concentration of 1.4 × 109 cells/mL. Bacterial feeding RNAi experiments were carried out as described . The clone used was mrps-5 (E02A10.1). For on-plate motility assays, doxycycline was added at the indicated concentration just before pouring the plates. Animals were exposed to compounds from eggs until the day of the experiment.
C. elegans movement was recorded for 45 s at different days of adulthood using a Nikon DS-L2/DS-Fi1 camera and controller setup, attached to both a computer and a standard brightfield microscope. Five plates of worms, with 10 worms per plate were measured in each condition. Using these video recordings, the movement traces of worms during all recording periods were calculated by following the organism centroids using a modified version of the Parallel Worm Tracker for MATLAB . The average worm speed during the recording periods was then calculated for each plate and each condition.
Fabrication of the microfluidic chips
Microfluidic devices were prepared by soft lithography  using 2-layer SU-8 molds. Briefly, conventional photolithography was used to pattern a 14 μm-thick layer of SU-8 photoresist on 4-in. wafers. A ~110 μm-thick layer of SU-8 was then patterned on top of the first one. Layer thicknesses were confirmed by mechanical profilometer measurements. The silicon mold was then diced in 20 mm × 20 mm microchips, which were inserted at the bottom of an aluminum/PMMA mold for PDMS casting (Additional file 1: Supplementary Note 1). 1.5 mm diameter steel pins were used to define the lateral connections of the device for the external tubing insertion. A liquid PDMS mixture (10:1 base:cross-linker weight ratio) was degassed, injected into the mold and cured at 100 °C for 1 h. Upon extraction from the mold, each PDMS chip was bonded by plasma-activation to a 150 μm-thick, 32 × 24 mm2 glass coverslip. The chip was then connected to external tubing and enclosed in the device assembly as reported in Fig. 1a.
Image acquisition and processing
The microfluidic platform was placed within an inverted microscope (Axio Observer, Zeiss) equipped with two illumination systems: (i) a precisExcite High-Power LED illumination system (Visitron, Puchheim, Germany) for brightfield imaging and (ii) a Lambda DG4 illumination system (Sutter instruments, Novato, CA, USA) for fluorescence imaging. The microscope had a motorized xy-stage and the automated imaging process was controlled using VisiView Premier Image acquisition software (Visitron, Puchheim, Germany). Images were acquired through a Hamamatsu Orca-ER CCD camera (Hamamatsu, Solothurn, Switzerland). Image processing was performed with Fiji software (http://imagej.nih.gov/ij; version 1.47b). In particular, worm areas were measured by processing time-lapse brightfield pictures as follows. Each frame was first converted to a binary image by applying a threshold to the full stack of time-lapse images and transforming it into a set of binary masks. Each stack of masks was then analyzed using the “particle analysis” Fiji plugin, which allows directly extracting area values for each picture in the stack. The same method was then applied to the stacks of fluorescence images, in order to calculate aggregate area values. In this case, we applied a systematic thresholding algorithm which was based on a variational approach, assuring that all aggregates in an image were effectively counted (i.e. by not setting the threshold too low), while not resulting in artificial size reduction of the aggregates (which would be the case by fixing a too high threshold). The “particle analysis” plugin allowed measuring the number and the average size of the aggregates identified in each picture.
Additional material is available: supplementary notes on (i) 3D PDMS chip casting with lateral fluidic connections; (ii) temperature control system: theoretical considerations; (iii) heat exchange dynamics in the device; (iv) inflow pre-thermalization study; (v) worm viability and culture tests; (vi) protein aggregation analysis in a Huntington disease C. elegans model. Supplementary videos on: (i) L1 worm loading via passive valves, and (ii) AM725 worm immobilization by PF127 gelation.
Work in MG laboratory was supported by the Ecole Polytechnique Fédérale de Lausanne and the EU Ideas program (ERC-2012-AdG-320404). The authors thank R. Padovani, A. Sayah (Laboratory of Microsystems LMIS2 at EPFL), and P. Maoddi (Physics Department of the European Organization for Nuclear Research - CERN) for very fruitful discussions about the project and P. Abdel-Sayed (Biomedical Orthopedics Laboratory at EPFL) for his help with PF127 viscosity measurements. JA is the Nestlé Chair in Energy Metabolism. Work in the JA laboratory is supported by the Ecole Polytechnique Fédérale de Lausanne, the EU Ideas program (ERC-2008-AdG-23118), the NIH (R01AG043930), the Swiss National Science Foundation (31003A-124713) and Systems X (51RTP0-151019). LM is supported by a FRM fellowship.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Kunze A, Lengacher S, Dirren E, Aebischer P, Magistretti PJ, Renaud P. Astrocyte-neuron co-culture on microchips based on the model of SOD mutation to mimic ALS. Integr Biol. 2013;5:964–75.View ArticleGoogle Scholar
- Choi SH, Kim YH, Hebisch M, Sliwinski C, Lee S, D'Avanzo C, et al. A three-dimensional human neural cell culture model of Alzheimer's disease. Nature. 2014;515:274–U293.PubMed CentralView ArticlePubMedGoogle Scholar
- Li J, Le WD. Modeling neurodegenerative diseases in Caenorhabditis elegans. Exp Neurol. 2013;250:94–103.View ArticlePubMedGoogle Scholar
- Lai CH, Chou CY, Ch'ang LY, Liu CS, Lin WC. Identification of novel human genes evolutionarily conserved in Caenorhabditis elegans by comparative proteomics. Genome Res. 2000;10:703–13.PubMed CentralView ArticlePubMedGoogle Scholar
- Nussbaum-Krammer CI, Morimoto RI. Caenorhabditis elegans as a model system for studying non-cell-autonomous mechanisms in protein-misfolding diseases. Dis Model Mech. 2014;7:31–9.PubMed CentralView ArticlePubMedGoogle Scholar
- Chronis N. Worm chips: Microtools for C. elegans biology. Lab Chip. 2010;10:432–7.View ArticlePubMedGoogle Scholar
- Hulme SE, Whitesides GM. Chemistry and the Worm: Caenorhabditis elegans as a Platform for Integrating Chemical and Biological Research. Angew Chem Int Edit. 2011;50:4774–807.View ArticleGoogle Scholar
- Sivagnanam V, Gijs MA. Exploring living multicellular organisms, organs, and tissues using microfluidic systems. Chem Rev. 2013;113:3214–47.View ArticlePubMedGoogle Scholar
- Bakhtina NA, Korvink JG. Microfluidic laboratories for C. elegans enhance fundamental studies in biology. RSC Adv. 2014;4:4691–709.View ArticleGoogle Scholar
- Zimmer M, Gray JM, Pokala N, Chang AJ, Karow DS, Marletta MA, et al. Neurons Detect Increases and Decreases in Oxygen Levels Using Distinct Guanylate Cyclases. Neuron. 2009;61:865–79.PubMed CentralView ArticlePubMedGoogle Scholar
- Chalasani SH, Chronis N, Tsunozaki M, Gray JM, Ramot D, Goodman MB, et al. Dissecting a circuit for olfactory behaviour in Caenorhabditis elegans. Nature. 2007;450. 63.Google Scholar
- Chung KH, Crane MM, Lu H. Automated on-chip rapid microscopy, phenotyping and sorting of C. elegans. Nat Methods. 2008;5:637–43.View ArticlePubMedGoogle Scholar
- Qin JH, Wheeler AR. Maze exploration and learning in C-elegans. Lab Chip. 2007;7:186–92.View ArticlePubMedGoogle Scholar
- Ma H, Jiang L, Shi WW, Qin JH, Lin BC. A programmable microvalve-based microfluidic array for characterization of neurotoxin-induced responses of individual C. elegans. Biomicrofluidics. 2009;3(4):44114.View ArticlePubMedGoogle Scholar
- Lockery SR, Hulme SE, Roberts WM, Robinson KJ, Laromaine A, Lindsay TH, et al. A microfluidic device for whole-animal drug screening using electrophysiological measures in the nematode C. elegans. Lab Chip. 2012;12:2211–20.PubMed CentralView ArticlePubMedGoogle Scholar
- Guo SX, Bourgeois F, Chokshi T, Durr NJ, Hilliard MA, Chronis N, et al. Femtosecond laser nanoaxotomy lab-on-achip for in vivo nerve regeneration studies. Nat Methods. 2008;5:531–3.PubMed CentralView ArticlePubMedGoogle Scholar
- Samara C, Rohde CB, Gilleland CL, Norton S, Haggarty SJ, Yanik MF. Large-scale in vivo femtosecond laser neurosurgery screen reveals small-molecule enhancer of regeneration. Proc Natl Acad Sci U S A. 2010;107:18342–7.PubMed CentralView ArticlePubMedGoogle Scholar
- Caceres ID, Valmas N, Hilliard MA, Lu H. Laterally Orienting C. elegans Using Geometry at Microscale for High-Throughput Visual Screens in Neurodegeneration and Neuronal Development Studies. PloS one. 2012;7:e35037.PubMed CentralView ArticleGoogle Scholar
- Krajniak J, Lu H. Long-term high-resolution imaging and culture of C. elegans in chip-gel hybrid microfluidic device for developmental studies. Lab Chip. 2010;10:1862–8.View ArticlePubMedGoogle Scholar
- Krajniak J, Hao Y, Mak HY, Lu H. CLIP-continuous live imaging platform for direct observation of C. elegans physiological processes. Lab Chip. 2013;13:2963–71.View ArticlePubMedGoogle Scholar
- Hwang H, Krajniak J, Matsunaga Y, Benian GM, Lu H. On-demand optical immobilization of Caenorhabditis elegans for high-resolution imaging and microinjection. Lab Chip. 2014;14:3498–501.PubMed CentralView ArticlePubMedGoogle Scholar
- Aubry G, Zhan M, Lu H. Hydrogel-droplet microfluidic platform for high-resolution imaging and sorting of early larval Caenorhabditis elegans. Lab Chip. 2015;15:1424–31.View ArticlePubMedGoogle Scholar
- Rohde CB, Yanik MF. Subcellular in vivo time-lapse imaging and optical manipulation of Caenorhabditis elegans in standard multiwell plates. Nat Commun. 2011;2:271.View ArticlePubMedGoogle Scholar
- Chung K, Zhan M, Srinivasan J, Sternberg PW, Gong E, Schroeder FC, et al. Microfluidic chamber arrays for whole-organism behavior-based chemical screening. Lab Chip. 2011;11:3689–97.PubMed CentralView ArticlePubMedGoogle Scholar
- Shen XN, Arratia PE. Undulatory Swimming in Viscoelastic Fluids. Phys Rev Lett. 2011;106:208101.View ArticlePubMedGoogle Scholar
- Kiernan MC, Vucic S, Cheah BC, Turner MR, Eisen A, Hardiman O, et al. Amyotrophic lateral sclerosis. Lancet. 2011;377:942–55.View ArticlePubMedGoogle Scholar
- Kiernan MC. ALS and neuromuscular disease: in search of the Holy Grail. Lancet Neurol. 2014;13:13–4.View ArticlePubMedGoogle Scholar
- Jonsson PA, Ernhill K, Andersen PM, Bergemalm D, Brannstrom T, Gredal O, et al. Minute quantities of misfolded mutant superoxide dismutase-1 cause amyotrophic lateral sclerosis. Brain. 2004;127:73–88.View ArticlePubMedGoogle Scholar
- Rakhit R, Robertson J, Vande Velde C, Horne P, Ruth DM, Griffin J, et al. An immunological epitope selective for pathological monomer-misfolded SOD1 in ALS. Nat Med. 2007;13:754–9.View ArticlePubMedGoogle Scholar
- Pratt AJ, Shin DS, Merz GE, Rambo RP, Lancaster WA, Dyer KN, et al. Aggregation propensities of superoxide dismutase G93 hotspot mutants mirror ALS clinical phenotypes. Proc Natl Acad Sci U S A. 2014;111:E4568–76.PubMed CentralView ArticlePubMedGoogle Scholar
- Gidalevitz T, Krupinski T, Garcia S, Morimoto RI. Destabilizing protein polymorphisms in the genetic background direct phenotypic expression of mutant SOD1 toxicity. PLoS Genet. 2009;5:e1000399.PubMed CentralView ArticlePubMedGoogle Scholar
- Jadiya P, Fatima S, Baghel T, Mir SS, Nazir A. A Systematic RNAi screen of neuroprotective genes identifies novel modulators of alpha-synuclein-associated effects in transgenic caenorhabditis elegans. mol neurobiol. 2015.Google Scholar
- Nollen EA, Garcia SM, van Haaften G, Kim S, Chavez A, Morimoto RI, et al. Genome-wide RNA interference screen identifies previously undescribed regulators of polyglutamine aggregation. Proc Natl Acad Sci U S A. 2004;101:6403–8.PubMed CentralView ArticlePubMedGoogle Scholar
- van Ham TJ, Thijssen KL, Breitling R, Hofstra RM, Plasterk RH, Nollen EA. C elegans model identifies genetic modifiers of alpha-synuclein inclusion formation during aging. PLoS genetics. 2008;4:e1000027.PubMed CentralView ArticlePubMedGoogle Scholar
- Morley JF, Brignull HR, Weyers JJ, Morimoto RI. The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans. Proc Natl Acad Sci U S A. 2002;99:10417–22.PubMed CentralView ArticlePubMedGoogle Scholar
- Renton AE, Chio A, Traynor BJ. State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci. 2014;17:17–23.PubMed CentralView ArticlePubMedGoogle Scholar
- Cozzolino M, Ferri A, Carri MT. Amyotrophic lateral sclerosis: from current developments in the laboratory to clinical implications. Antioxid Redox Signal. 2008;10:405–43.View ArticlePubMedGoogle Scholar
- Wong PC, Pardo CA, Borchelt DR, Lee MK, Copeland NG, Jenkins NA, et al. An adverse property of a familial ALS-linked SOD1 mutation causes motor neuron disease characterized by vacuolar degeneration of mitochondria. Neuron. 1995;14:1105–16.View ArticlePubMedGoogle Scholar
- Kong J, Xu Z. Massive mitochondrial degeneration in motor neurons triggers the onset of amyotrophic lateral sclerosis in mice expressing a mutant SOD1. J Neurosci. 1998;18:3241–50.PubMedGoogle Scholar
- Andreux PA, Houtkooper RH, Auwerx J. Pharmacological approaches to restore mitochondrial function. Nat Rev Drug Discov. 2013;12:465–83.PubMed CentralView ArticlePubMedGoogle Scholar
- Mouchiroud L, Houtkooper RH, Moullan N, Katsyuba E, Ryu D, Canto C, et al. The NAD(+)/Sirtuin Pathway Modulates Longevity through Activation of Mitochondrial UPR and FOXO Signaling. Cell. 2013;154:430–41.PubMed CentralView ArticlePubMedGoogle Scholar
- Houtkooper RH, Mouchiroud L, Ryu D, Moullan N, Katsyuba E, Knott G, et al. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature. 2013;497:451–7.View ArticlePubMedGoogle Scholar
- Durieux J, Wolff S, Dillin A. The cell-non-autonomous nature of electron transport chain-mediated longevity. Cell. 2011;144:79–91.PubMed CentralView ArticlePubMedGoogle Scholar
- Jovaisaite V, Mouchiroud L, Auwerx J. The mitochondrial unfolded protein response, a conserved stress response pathway with implications in health and disease. J Exp Biol. 2014;217:137–43.PubMed CentralView ArticlePubMedGoogle Scholar
- Moullan N, Mouchiroud L, Wang X, Ryu D, Williams EG, Mottis A, et al. Tetracyclines Disturb Mitochondrial Function across Eukaryotic Models: A Call for Caution in Biomedical Research. Cell reports. 2015. doi:10.1016/j.celrep.2015.02.034.PubMedGoogle Scholar
- Yoneda T, Benedetti C, Urano F, Clark SG, Harding HP, Ron D. Compartment-specific perturbation of protein handling activates genes encoding mitochondrial chaperones. J Cell Sci. 2004;117:4055–66.View ArticlePubMedGoogle Scholar
- Brignull HR, Moore FE, Tang SJ, Morimoto RI. Polyglutamine proteins at the pathogenic threshold display neuron-specific aggregation in a pan-neuronal Caenorhabditis elegans model. J Neurosci. 2006;26:7597–606.View ArticlePubMedGoogle Scholar
- Lakso M, Vartiainen S, Moilanen AM, Sirvio J, Thomas JH, Nass R, et al. Dopaminergic neuronal loss and motor deficits in Caenorhabditis elegans overexpressing human alpha-synuclein. J Neurochem. 2003;86:165–72.View ArticlePubMedGoogle Scholar
- Regitz C, Wenzel U. Amyloid-beta (Abeta1-42)-induced paralysis in Caenorhabditis elegans is reduced by restricted cholesterol supply. Neurosci Lett. 2014;576:93–6.View ArticlePubMedGoogle Scholar
- Riboldi G, Nizzardo M, Simone C, Falcone M, Bresolin N, Comi GP, et al. ALS genetic modifiers that increase survival of SOD1 mice and are suitable for therapeutic development. Prog Neurobiol. 2011;95:133–48.View ArticlePubMedGoogle Scholar
- Kamath RS, Martinez-Campos M, Zipperlen P, Fraser AG, Ahringer J. Effectiveness of specific RNA-mediated interference through ingested double-stranded RNA in Caenorhabditis elegans. Genome Biol. 2001;2:RESEARCH0002.PubMed CentralPubMedGoogle Scholar
- Ramot D, Johnson BE, Berry Jr TL, Carnell L, Goodman MB. The Parallel Worm Tracker: a platform for measuring average speed and drug-induced paralysis in nematodes. PLoS One. 2008;3:e2208.PubMed CentralView ArticlePubMedGoogle Scholar
- Xia YN, Whitesides GM. Soft lithography. Angew Chem Int Ed. 1998;37:551–75.View ArticleGoogle Scholar