Suchergebnisse

Science lives from the curiosity to get to the bottom of problems and from the subsequent discussion, where scientists exchange knowledge and opinions to finally come up with new questions. However, as a recent study showed, the vast majority of the experiments conducted within publications can often only be replicated partially, if at all, which contributes to the rising disbelief from society into scientific practice [1]. The high level of exclusivity of scientific experiments is often due to a lack of available instruments and knowledge of their use, as well as their high cost makes it impossible for many researchers to replicate their experiments. Particularly in high-resolution microscopy, which is an essential tool for many different scientific disciplines such as cell biology or biochemistry this is a problem to be solved if we aim for realistic interdisciplinary scientific exchange. With the ever-growing open-source optical toolbox UC2 ("You.See.Too.") [2] we show that this is not only important but also possible. With UC2, we are trying to democratize optics and microscopy in particular. To achieve this, UC2 relies on widely available components and 3D-printed parts so that it can be easily built by anyone, anywhere. Through online platforms such as GitHub [3], we enable anyone to use, replicate, and customize it for individual purposes open-source licenses. Additionally, we invite users from around the world to share their designs with the community in order to create an iterative and decentralized optimization loop. This way, completely new collaborations can be created, from the field of education to the realm of cutting-edge biology. In the ongoing Corona pandemic, we were able to show that state-of-the-art microscopic imaging can be realized even where access to such equipment is very limited, but no less urgently necessary. Also, we were able to detect and even optically resolve the SARS-CoV2 coronavirus in the high-safety biological laboratory. The open-source nature of UC2 allows connecting with other open projects to unite the expertise of scientists from around the world, together with approaching the goal of making cutting-edge tools available to all. Additionally scaling up the production of the UC2-components and organizing interdisciplinary workshops, we hope to lower the entry barriers to get creative with optics and think science easily out of the box.

The number of samples in biological experiments is continuously increasing, but complex protocols and human error in many cases lead to suboptimal data quality and hence difficulties in reproducing scientific findings. Laboratory automation can alleviate many of these problems by precisely reproducing machine-readable protocols. These instruments generally require high up-front investments, and due to the lack of open application programming interfaces (APIs), they are notoriously difficult for scientists to customize and control outside of the vendor-supplied software. Here, automated, high-throughput experiments are demonstrated for interdisciplinary research in life science that can be replicated on a modest budget, using open tools to ensure reproducibility by combining the tools OpenFlexure, Opentrons, ImJoy, and UC2. This automated sample preparation and imaging pipeline can easily be replicated and established in many laboratories as well as in educational contexts through easy-to-understand algorithms and easy-to-build microscopes. Additionally, the creation of feedback loops, with later pipetting or imaging steps depending on the analysis of previously acquired images, enables the realization of fully autonomous "smart" microscopy experiments. All documents and source files are publicly available to prove the concept of smart lab automation using inexpensive, open tools. It is believed this democratizes access to the power and repeatability of automated experiments.

Super-resolution microscopy allows for stunning images with a resolution well beyond the optical diffraction limit, but the imaging techniques are demanding in terms of instrumentation and software. Using scientific-grade cameras, solid-state lasers and top-shelf microscopy objective lenses drives the price and complexity of the system, limiting its use to well-funded institutions. However, by harnessing recent developments in CMOS image sensor technology and low-cost illumination strategies, super-resolution microscopy can be made available to the mass-markets for a fraction of the price. Here, we present a 3D printed, self-contained super-resolution microscope with a price tag below 1000 $ including the objective and a cellphone. The system relies on a cellphone to both acquire and process images as well as control the hardware, and a photonic-chip enabled illumination. The system exhibits 100nm optical resolution using single-molecule localization microscopy and can provide live super-resolution imaging using light intensity fluctuation methods. Furthermore, due to its compactness, we demonstrate its potential use inside bench-top incubators and high biological safety level environments imaging SARS-CoV-2 viroids. By the development of low-cost instrumentation and by sharing the designs and manuals, the stage for democratizing super-resolution imaging is set. ; B.S.A. acknowledges funding from European Commission ERC Starting Grant (336716) and ERC PoC 957464 and ), Research Council of Norway (Grant 288565). We acknowledge funding by the DFG Transregio Project TRR166, TP04 (PT) and the Leibniz ScienceCampus InfectoOptics SAS-2015-HKI-LWC (AJ). The authors further acknowledge the support of this work by a grant from the IZKF (ACSP02) (SDE). The study was further funded by the Deutsche Forschungsge-meinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy (EXC 2051, Project-ID 390713860). This work was financially supported by the Deutsche Forschungsge- 10 meinschaft through the Cluster of Excellence "Balance of the Microverse" under Germany's Excellence Strategy – EXC 2051 – Project-ID 690 390713860. We thank Fatina Siwczak and Swen Carlstedt for fruitful discussions. We further thank Merete Storflor and S¨oren Abel (Infection Biology Research Group, UiT) for providing the Ecoli samples and Deanna Wolfson (Optics group, UiT) for help with preparation of the Ecoli samples. We would like to thank Sindy Burgold-Voigt and Ralf Ehricht from Leibniz IPHT Jena for their great methodical contribution and the fruitful discussions. We thank especially Ingo Fuchs who helped a lot in understanding the principles of the acquisition process of cellphone cameras as well as his support of the software design. Pablo Carravilla acknowledges the Basque Government postdoctoral program (POS 2019 2 0022) for funding his position. pMDLg/pRRE and pRSV-Rev were a gift from Didier Trono (Addgene plasmid #12251 and #12253; http://n2t.net/addgene:12251 and http://n2t.net/addgene:12253; RRID:Addgene 12251 and RRID:Addgene 12253). K.O.S is supported by a Career fellowship from the South-Eastern Norway Regional Health Authority ; No