Though looking through a microscope can inspire, applying the technology to our own research questions can be intimidating. Like any field, optical microscopy has its own language, jargon, and conceptual framework, but is rarely taught in academic programs. To learn microscopy, most of us shadow colleagues, stream videos, read the literature, and perhaps attend a short workshop, to list a few of the ways we try to develop our skills and knowledge. This type of informal on-the-job learning is useful, yet the lack of formal education and quality control can put research integrity at risk. Without a shared base of knowledge and skills, it is possible to acquire and analyze imaging data without mastering critical fundamental concepts and practices, which can put the rigor and reproducibility of research at risk. Through these “Field notes,” we hope to fill this gap by making good practices explicit.

To develop any new skill, you need time, dedication, and patience. Microscopy is no different. You need to set reasonable goals and reasonable expectations, or you can find yourself dispirited and annoyed. If you are a beginner, a good place to start is to map out an experimental workflow, depicted visually below. Each step in the workflow requires you to make informed choices that draw on specific skills, knowledge, and experience. You don’t need to have everything in place right from the start, but this framework will identify gaps in your knowledge and training, which helps you create a learning path that is directly relevant to your research.

An experimental plan will also help you make systematic progress and minimize avoidable errors, and most importantly, you will experience much less stress. You will also manage your time better and establish realistic expectations for project deliverables. As you work through the steps, you can build in flexibility, for as when you want to follow up on unexpected and exciting findings.

The imaging experiment workflow

The experimental workflow can be as simple as notes jotted on a whiteboard, or a set of sticky notes. If you want to take it up a notch, an online shared document or site makes it easier to share progress and ideas with your supervisor and your colleagues.  If you have not used a digital platform before, you have a wealth of options. You can use a shared Word document or Excel file, or work with project management software. In the LCI, we have adopted Notion (notion.so), a platform that is free for academic users. We find its interface intuitive and accessible.

It is important to view the steps in the experimental imaging workflow as an iterative cycle, rather than a linear sequence. When we prepare samples and collect images, but do not review and analyze the data before moving onto the next set of samples, we put our research at risk. If you skip this step, you may miss issues with your sample preparation and/or image acquisition that could undermine the integrity of your data. You need to close the experimental loop to make sure that you extract the maximum information and value from all your hard work and long hours in the laboratory. By reviewing and analyzing your data after every imaging session, you will set yourself up for success.

In the next post, we’ll delve more into the considerations and decisions that are needed at each step of the imaging workflow. Until then, why not start mapping out an experimental plan and we welcome your perspectives and questions in the Comments section below.