Intelligent and multi-modal spectroscopy platform for Physical and Life science
Image comparison of a fluorescently labelled BPAE cell, recorded with a widefield fluorescence microscope and a SRRF-Stream enabled iXon Life 888 EMCCD camera. A x63 objective was used, with further 2x magnification and 560nm illumination. 100 raw ‘input’ images were recorded for every resultant super-resolution image, resulting in a super-resolution image rate of 0.5 Hz. For a fair comparison without SRRF-Stream, 100 standard widefield images were recorded and then averaged. While the original image was of a larger field of cells, a zoomed ROI of one cell is shown here in order to more easily display a line intensity profile comparison through a small region. The improvement in resolving power is readily apparent.
This image comparison of a fluorescently labelled U2OS cell line* was recorded with an Andor Dragonfly confocal spinning disk fluorescence microscope and a SRRF-Stream enabled iXon Life 888 EMCCD camera. A x63 objective was used, with further 2x magnification and 488nm illumination. An unprecedented improvement in resolving power can observed in the level of detail in the mitotic spindle. This is further evidenced in the comparative line intensity profile drawn through this region.
*U2OS cell line was fixed, stained with anti-alpha-tubulin primary antibody(green, AF488) and phalloidin (red, rhodamine) to visualize F-actin, DAPIstaining to visualize nuclei. Samples prepared by Klebanovych A.,Laboratory of Biology of Cytoskeleton, IMG of the AS CR, v.v.i.
HCV infected cells stained with anti-NS5A. Here we are comparing Widefield (WF), Structured Illumination Microscopy (SIM) and SRRF images (SRRF of the widefield image). The images are of the same field of cells, recorded on the same microscope, using identical objective and optical path. The only difference being that SIM was recorded using an sCMOS detector with 6.5 m pixels whereas the Widefield and resultant SRRF was recorded using an iXon EMCCD detector with 16 m pixels. The superior resolving power of SRRF is evident, indicative that SRRF is achieving a greater than 2-fold improvement over the classical diffraction limit. SIM is theoretically limited to a 2-fold reduction of the classical diffraction limit. Sample courtesy of the Grove lab at UCL.
Mammalian cell undergoing mitoses. Blue represents DNA staining, Green microtubules and Red kinetochores. Left image shows a widefield z-stack and right image the equivalent acquired with SRRF-Stream. Sample courtesy of Phil Auckland at Warwick University, imaging by the Henriques laboratory at University College London (UCL).
200s time-lapse of a live BSC-40 cell labelled with cell mask and imaged with 635nm LED illumination. The first 100 frames correspond to widefield imaging with a 1 second exposure; the second 100 frames correspond to SRRF-Stream imaging where each frame is produced from SRRF-Stream processing of 50 images (20ms exposure time). Sample preparation by David Albrecht (Ricardo Henriques and Jason Mercer labs at UCL).
Comparative images of Clathrin coated pits of live HeLa cells, labelled with mCherry, recorded on a widefield microscope at 2 FPS. 100 raw ‘input’ images were recorded for every resultant super-resolution image, resulting in a super-resolution image rate of 2 FPS. A line intensity profile is shown through a small region of the SRRF-Stream image, indicating resolution of structures that are 150nm apart. Sample preparation by Caron Jacobs (Ricardo Henriques and Mark Marsh labs at UCL).
Comparative 3D projection montages of fission yeast lifeAct expressing strain. Recorded with standard widefield versus SRRF-Stream widefield, using identical exposure times. Strain courtesy of Mohan Balasubramanian’s laboratory (U. Warwick) Sample courtesy of Gautam Dey (Buzz Baum laboratory at UCL).
Comparative standard widefield and widefield SRRF-Stream images of blood platelets, red membrane, green internal granules. Sample courtesy of Cutler laboratory at UCL.
A still widefield image of a live HeLa cell expressing tubulin-GFP followed by a SRRF-Stream time-lapse of the same region at 1fps (SRRF-Stream analysis of 50 frames at 20ms exposure). Sample preparation by David Albrecht (Ricardo Henriques and Jason Mercer labs at UCL).
With its ability to smash through the classical diffraction limit, and furthermore, to accomplish this in real time, with non-complex sample labelling, conventional equipment and with low intensity illumination, SRRF-Stream paves the way to unlock previously unseen cellular structure and behaviour, at unprecedented spatio-temporal resolution in a low-photodamage friendly manner.
Adopting the recently developed SRRF technology from the lab of Dr Ricardo Henriques, University College London (UCL), and working in close collaboration with Dr Henriques, Andor have enhanced the technology to run optimally on iXon EMCCD cameras. Andor are also expert in advanced GPU processing optimization techniques, employed in this instance to execute the SRRF algorithm up to 30x faster than the existing ImageJ-based post processing implementation of SRRF (NanoJ-SRRF). This significant acceleration enables workflow enhancement, by allowing data acquisition and SRRF processing to operate in parallel.
Processing Speed Comparison - SRRF Stream vs NanoJ-SRRF
This graph compares the rate of processing of blocks of 100 raw input images (1024 x 1024 pixels), to yield resultant SRRF super-resolution images of 4096 x 4096 pixels. SRRF-Stream is compared to NanoJ-SRRF, the processing occurring on the same Nvidia GTX 1070 GPU card. The SRRF-Stream acceleration subsequently allows data acquisition and processing to happen in parallel, yielding a further workflow improvement over NanoJ-SRRF.
Since processing is now much faster than the camera can acquire data, ‘SRRF-Stream enabled’ cameras now accomplish real time super-resolution, with large field of view super-resolution images.
Having thoroughly tested SRRF-Stream in our own lab, we are very impressed by both the workflow and also the ability to now utilise larger fields of view for live cell super-resolution. By seamlessly combining the SRRF algorithm with the high-performance of the iXon, we have accomplished the world’s first super-resolution camera for fluorescence microscopy.
* The Nvidia GPU card should have Compute Capability v3.0 or above and 4GB or greater on-board GPU RAM. Note that Andor have done a lot of testing using the ‘mid-range’ GTX 1070 and found that, with SRRF-Stream, it is more than adequate to process data much faster than the rate of iXon data acquisition.
Provided you currently own an iXon Ultra 888, iXon Ultra 897, iXon Life 888 or iXon Life 897 model, Andor can upgrade your camera to unlock SRRF-Stream super-resolution microscopy capability.
PLEASE NOTE: If upgrading an iXon 888 model, you also need to request the SRRF-Stream Camera Optimization process.
In order to make SRRF-Stream widely accessible, it has been fully integrated into MicroManager(64-bit) open source microscopy software platform.
The Learning Center hosts a wide range of tutorial videos, technical articles and webinars to guide you through the range of products for all your imaging needs. We have provided some links below which will get you started on some of our most recent uploads.