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Autophagy (Greek for “self-eating”) is a process by which cytoplasmic material, including organelles, are targeted to lysosomes for degradation. Autophagy is a dynamic process which involves autophagosome synthesis, delivery of materials to be degraded to the lysosome, and degradation of autophagic substrates inside the lysosome. Historically, methods for studying autophagy focused on counting the number of autophagosomes. This approach, however, has inherent limitations because it turns a dynamic process into a static measurement and it provides limited information about what materials or organelles are being targeted for autophagy. The development of several fluorescent autophagy reporters now allows for the measurement of autophagic flux, or the changes in autophagic activity, and are a more reliable indicator of autophagic activity. The aim of this post is to provide an overview of four autophagy biosensors currently available from Addgene.

Before I started writing for the Addgene blog, sharing Chemistry Cat memes was how I used social media as a scientist. I mean, I had a LinkedIn page and a Twitter handle, but I wasn’t using them to my professional advantage. It wasn’t until I wrote a blog post about a research paper that explored how scientists connect on Twitter that I realized 1) a lot of scientists are using social media professionally, and 2) I needed to start using Twitter.

My lab's vector of choice is AAV, with nearly every experiment requiring AAV. Before joining my lab, I had never worked with AAV, so naturally I had to package some virus for my first experiment. It was a bit intimidating, but I had my lab’s protocols and some great co-workers to help me out. Even with these tools, I found myself writing AAV production tricks into the margins of my protocol. While these tips weren’t critical to the experiment, they definitely made my life easier!  In this post, I’ll share some AAV production, purification, and titration tips, while also summarizing the basic steps and analyses needed for packaging AAV.

Genome-wide CRISPR/Cas9 screens are a high-throughput systematic approach for identifying genes involved in a biological process. These screens provide an alternative to genome-wide RNAi screens, which although highly effective, are affected by low on-target efficacy, non-specific toxicity, and off-target effects. The flaws of RNAi screens are well characterized and strategies exist to control for these faults. However, it’s still unclear if similar pitfalls exist for CRISPR screens and how best to design these screens to controls for flaws. Recently the Bassik Lab at Stanford developed a new genome-wide CRISPR knockout screen to analyze the following unanswered questions about CRISPR screen design.

Sometimes it feels like DNA and protein get all the attention.There are numerous ways to detect DNA-protein interactions or to analyze chromatin states (CHIP-seq, FAIRE-seq, Cut & Run) and to detect protein-protein interactions (yeast-two hybrid, Co-IP, BioID),  and that’s just to name a few. But what if you want to study RNA-protein interactions? The characterization of RNA-protein interactions has lagged behind, likely due to limitations of current means to detect RNA-protein interactions. To address this need, the Khavari lab at Stanford created the RNA-protein interaction detection (RaPID) method. RaPID borrows the E. coli biotin ligase BirA* from BioID and allows a researcher to identify proteins that bind an RNA motif of interest in living cells.