High-speed multicolor microscopy of repeating dynamic processes - PubMed (original) (raw)
High-speed multicolor microscopy of repeating dynamic processes
Jungho Ohn et al. Genesis. 2011 Jul.
Abstract
Images of multiply labeled fluorescent samples provide unique insights into the localization of molecules, cells, and tissues. The ability to image multiple channels simultaneously at high speed without cross talk is limited to a few colors and requires dedicated multichannel or multispectral detection procedures. Simpler microscopes, in which each color is imaged sequentially, produce a much lower frame rate. Here, we describe a technique to image, at high frame rate, multiply labeled samples that have a repeating motion. We capture images in a single channel at a time over one full occurrence of the motion then repeat acquisition for other channels over subsequent occurrences. We finally build a high-speed multichannel image sequence by combining the images after applying a normalized mutual information-based time registration procedure. We show that this technique is amenable to image the beating heart of a double-labeled embryonic quail in three channels (brightfield, yellow, and mCherry fluorescent proteins) using a fluorescence wide-field microscope equipped with a single monochrome camera and without fast channel switching optics. We experimentally evaluate the accuracy of our method on image series from a two-channel confocal microscope.
Copyright © 2011 Wiley-Liss, Inc.
Figures
Figure 1
Multi-channel microscopy procedure for imaging dynamic samples. a–b All channels are captured simultaneously on microscopes equipped for parallel imaging a Sample undergoing a periodic motion pattern imaged in three channels b Composite image of all channels. c–d Channels are captured sequentially on microscopes equipped with a single detector/camera c Sample undergoing a periodic motion pattern imaged alternatively in three channels d inaccurate composite image due to asynchronous imaging of the channels. e–f Channels captured sequentially at high frame rate over one ore more occurences of the motion pattern e Each channel is captured at full camera frame rate with short delays in between channels f random triggering leads to sequences that are temporally unregistered. g–h Multi-modal registration allows for high-speed multi-modal imaging g Temporal registration procedure of the sequences acquired in panel e. f Aligned images yield composite images at full frame rate.
Figure 2
a–d Anatomical features do not coincide in corresponding frames of three sequentially acquired image sequences showing the looping heart tube of a double-labeled embryonic quail. a Brightfield with outlined myocardium b YFP channels with outlined endocardium c mCherry with outlined myocardium d before temporal registration frames capture different heart contraction phases e–h Anatomical features coincide in corresponding frames after image sequences were temporally registered. e Brightfield with outlined myocardium f YFP channels with outlined endocardium g mCherry with outlined myocardium h after temporal registration frames capture the same heart contraction phase i–k Time-course of the dynamic part of heart beat after temporal registration. All scale bars are 100 μm. See also Movies 1–3.
Figure 3
Temporal registration metric is based on normalized mutual information rather than intensity comparison. a–b Comparing two similar but non-identical frames in the brightfield image sequence (Fig. 2 and e) leads to a non-zero absolute difference image (a) and a spread in their joint histogram (b). c–d Comparing two identical frames in a brightfield image sequence (Fig. 2 with itself) leads to a zero absolute difference image (c) and a joint histogram with values concentrated along the main diagonal (d). e–f Comparing two non-matching frames (brightfield image sequence, Fig. 2 and mCherry, Fig. 2) leads to a non-zero absolute difference image (e) and a spread (marked by arrow) in their joint histogram (f). g–h Comparing two matching frames (brightfield image sequence, Fig. 2 and mCherry, Fig. 2) still leads to a nonzero absolute difference image (g; making absolute difference unsuitable as a base criterion for measuring accurately matched images) but joint histogram exhibits less spread (h, compare in region with arrow marked in f). Normalized mutual information Y, (Studholme et al., 1999), increases for matching frames. (i) Normalized mutual information matrix; bright entries correspond to matching frames. Synchronization is achieved by finding a maximum merit path through the matrix to match the test and reference sequences (red line).
Figure 4
Validation procedure for multi-modal synchronization of microscopy images. a Synchronously-acquired transmission and fluorescence channels. b a reference sequence A and a test sequence B are extracted; synchronization matches reference sequence A to its correct temporal position by maximizing mutual information with sequence B. c two reference sequences, C and E, and two test sequences, D and F are extracted from the synchronously acquired data; d intra-modal and inter-modal synchronization of the reference sequences to the test sequences yield consistent (within 0.5 frames) synchronization to a subsequent cardiac cycle in the test sequences. See also Movie 4.
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