Technology drives innovation, and nowhere is that more true than in biological microscopy. Read on to learn about some of our favorite technologies.
We specialize in measurements, data analysis, and complex modeling related to the determination of protein dynamics in vivo. In most cases, this involves some combination of FRAP, inverse FRAP, and photoactivation. This has allowed us to perform detailed investigations of the biased diffusion of Cdc42 in budding yeast which is involved in polarity maintenance (Smith et al., J Cell Biol., 2013 ; Das et al., Nat Cell Biol., 2012 ; Slaughter et al., Nat Commun., 2013).
In addition, we have used FRAP to understand the stability of prion-like proteins involved in long term memory in fruit flies (Majumdar et al., Cell, 2012), to discover novel dynamics of the yeast kinetochore (Shivaraju et al., Cell, 2012; Dhatchinamoorthy et al., J Cell Biol., 2017 ), and to elucidate mechanisms of exocytosis in C. Elegans (Hollopeter et al., eLife, 2014).
The Stowers microscopy center routinely uses FRET to assess protein-protein interactions in vivo. In one recent example, we used FRET after UV microirradiation-induced DNA damage to explore the interaction between Elongin and Cullin (Weems et al., J Biol Chem., 2015). We have also utilized FRET in vitro to distinguish between potential structural orientations of nucleation promoting factors in the structure of the Arp2/3 complex (Xu et al., EMBO J., 2012).
Traditionally, FCS has been a technique devoted to simplistic measurements of protein diffusion and interactions in vitro and occasionally in vivo. Our experts at Stowers have worked hard to extend this technique to new model systems (Drosophila oocytes: Bonner et al., PNAS, 2013; Mouse oocytes: Yi et al., Nat Cell Biol., 2011).
In addition, we have used FCS in unique ways. Most recently, we have used line scanning FCCS to determine interactions of nuclear membrane proteins associated with centrosome and nuclear pore complex insertion (Chen et al., J Cell Biol., 2014). In 2012, we used FCS to perform calibrated imaging, measuring the numbers of GFP molecules at complexes (nuclear pore complexes and centromeres) in live yeast cells down to 8 molecules (Shivaraju et al., Cell, 2012).
Our three favorite tools for processing images are ImageJ, Imaris, and custom code.
For analyses in 2D, we leverage the broad capabilities of ImageJ. Nothing beats Imaris for 3D data visualization. If neither of those software packages will do the job, we usually code it ourself!
None of the major technological and biological imaging breakthroughs we have made in the last decade would be possible without stellar image processing support. Custom programming underlies the vast majority of collaborative papers we publish. If you want to benefit from our developments, please utilize our github repositories (https://github.com/jayunruh; https://github.com/jouyun/smc-plugins) or our ImageJ plugins website (http://research.stowers.org/imagejplugins/).
One of the major challenges facing modern time-lapse microscopy is sample manipulation. Our fully equipped microfabrication facility works collaboratively with the Stowers investigators to create custom flow chambers for everything from planaria to drosophila ovaries.
When it comes to embryonic imaging, one quickly discovers the limitations of traditional microscopes with respect to speed, sample size, and penetration. SPIM has been developed in recent years as the solution to these problems.
Our expert-built SPIM instrument has been transformative in enabling large scale planarian (Thi-Kim et al., eLife, 2015) and fruit fly embryo (Nakajima et al., Nature, 2013) imaging. In the former case, SPIM was crucial to finding rare, potentially tumorigenic, responses to errors in cell division.
The super-resolution revolution is sweeping through the biological community, culminating in the Nobel Prizes given in 2015. As with most new technologies, super-resolution microscopy requires careful tailoring for each new biological application.
At Stowers, we are fully equipped to perform structured illumination (SIM), PALM, and STORM superresolution experiments all with 3D capabilities. SIM has rapidly taken over our routine needs and has been transformative for several publications (Collins et al., Genetics, 2014; Avena et al., PLoS Genet., 2014; Zhou et al., Cell, 2014; Lake et al., eLife, 2015).
Recently, we have taken this technique to a new level by combining it with single particle averaging (SPA-SIM). A recent paper utilized this technique to map out the structure of the yeast centrosome during duplication and membrane insertion (Burns et al., eLife, 2015).