A multidisciplinary approach is key
The vast majority of biological processes occur at the molecular level with DNA-binding proteins at their core. This is where diseases arise and most drugs act. Therefore, elucidating the molecular mechanisms at play is crucial.
In biology, it is key to apply a multidisciplinary approach to answer biological questions. The broad range of available life science tools provides diverse information on the investigated biological systems. Many methods are used in an attempt to approximate and extract the molecular functionality. However, these tools give either detailed structural or functional information — but rarely both.
Lack of direct observation results in ambiguity
Current life science tools give either detailed structural or functional information — but rarely both
As the current life science tools do not allow for observation of the molecular processes in real-time they are often unable to reveal the crucial mechanistic details of individual proteins at play.
What is the missing link in your toolbox?
- Cell imaging & localization give either dynamic information at low genomic resolution (e.g. fluorescence) or static information at high genomic resolution (e.g. ChIP) and misses experimental control.
- Bulk functional assays lose detailed information by averaging.
- Structural methods lack dynamic information.
This lack of direct observation of the underlying dynamic processes often results in ambiguity in the obtained results.
In turn, this frequently leads to low acceptance rates in top journals or longer submission times, as reviewers will often ask for additional control experiments. While the elimination of ambiguity might still not be guaranteed, the time to publication can drag out considerably. Submitting to Nature Structural & Molecular Biology takes on average 119 days, and publishing in Nature is almost double – 226 days .
Are you aware of these acceptance rates [2-5]?
This considerably prolongs the time to publication and can drag out projects for months or even years. Consequently, this increases the chance of falling behind and could negatively impact projects and funding. Also, with the remaining ambiguity in a study, there is a chance that your conclusions need to be reconsidered in the future.
What has been your experience regarding this? For example,
Add the missing link to fully understand the molecular mechanism
Dynamic single-molecule for direct, indisputable proof of the molecular mechanisms
Long times to publish and high rejection rates are hard consequences, often resulting from the lack of observation of molecular mechanisms while they happen. Today, scientists still spend time and resources on performing numerous methods to try to understand a dynamic process, accepting ambiguity as the standard – but it’s not. Dynamic single-molecule (DSM) methods add the missing link by enabling you to observe the molecular mechanism of DNA-binding proteins in action. Getting direct, indisputable proof of the molecular mechanisms eliminates the ambiguity resulting in a higher impact study with a short time to publication.
The C-Trap® is the only dynamic single-molecule microscope that allows you to obtain direct evidence of how the molecular mechanisms and dynamic processes of proteins on DNA work. Its unique Nobel Prize-winning technology enables –within the same experiment– to:
- Directly visualize the dynamics of individual proteins in real-time.
- Control and observe the stepwise assembly of the biological complex.
- Modulate the molecular system to test the model under different conditions.
- Nature Journal Metrics (2020), accessed 16 December 2021, https://www.nature.com/nature-portfolio/about/journal-metrics.
- eLife Journal Metrics (2021), accessed 16 December 2021, https://reviewer.elifesciences.org/author-guide/journal-metrics.
- PNAS Article and Journal Metrics (2020), accessed 16 December 2021, https://www.pnas.org/page/about/metrics.
- Journal Guide – The EMBO Journal, accessed 16 December 2021, https://www.journalguide.com/journals/the-embo-journal.
- Science Journal Metrics (2020), accessed 16 December 2021, https://www.science.org/content/page/journal-metrics.