Hot Plasmids: Fall 2025

By Multiple Authors

Every few months we highlight some of the new plasmids, antibodies, viral preps, and more in the repository through our Hot Plasmids articles.

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Here's what you'll find in this post:

Cell-surface proteomics for neurons and astrocytes

By Mike Lacy

Cell-cell interactions underlie many kinds of tissue function, but these connections are exquisitely important in the brain. To better understand how astrocytes and neurons interact, the labs of Baljit Khakh and colleagues mapped their cell-surface proteomes (Wu et al., 2025).

The team expressed extracellularly-anchored horseradish peroxidase (HRP) in striatal astrocytes and neurons to label surface proteins with a membrane-impermeable biotin substrate (Figure 1). Biotinylated proteins were isolated, identified by mass spectrometry, and classified by source cell based on single-cell RNA-seq data. In addition to unique proteins on each cell type, the cell-surface shared proteome of astrocytes and neurons (CS SPAN) featured extracellular matrix proteins, cell adhesion molecules, transporters, ion channels, GPCRs, and more. 

Two schematics. The first panel shows cell-surface protein labeling by HRP: A cartoon shows an HRP expressing cell and two nearby neurons with branching cell bodies intertwined in a complex way; a zoomed in view of the extracellular space and three cell membranes with various unique proteins in each, including the HFP on one; in a Proximity Labeling step, HRP catalyzes BxxP to biotin radical, decorating nearby proteins on all cell surfaces with an attached biotin. The second panel shows identification of the cell-surface shared proteome of astrocytes and neurons: The biotinylated proteins are fed into LC-MS/MS analysis and m/z peaks can be identified corresponding to the proteins illustrated above; three sets of data points are illustrated in a circular cloud, Astrocyte CSPs, Neuron CSPs, and the CS SPAN between them.

Figure 1: Workflow for cell-surface protein labeling and identification. Reproduced from Wu et al. (2025) under CC BY license.

These datasets (in healthy mice and a Huntington's disease model) will be valuable resources for future studies of the molecular bases of astrocyte-neuron interactions. Plus, the tools used here (also available as AAV Packaged on Request) will be useful for related studies in other brain regions, cell types, and tissues.

Find cell-surface HRP plasmids here!

 

Unveiling the mysteries of the mitochondria with MitoTRACER

By Alyssa Shepard

As the culturally-proclaimed powerhouse of the cell, mitochondria play a vital role in maintaining cellular function. Mitochondria can also lend their power to other cells when required, through mitochondrial transfer. In the two decades since this transfer was first proposed, researchers have shown that these transplanted mitochondria can exert their powers for better or for worse. To better understand this transfer, the Simon Grelet Lab developed MitoTRACER, a retroviral-based reporter system that permanently labels the cells receiving mitochondria (Hoover et al., 2025).

MitoTRACER relies on a Cre-lox switch to turn recipient cells from red to green fluorescence (Figure 2). Donor cells express iCre with a mitochondrial anchor and a TEV cleavage site. Recipient cells express DsRed within a lox-STOP-lox sequence, followed by the EGFP, and the TEV protease. Once the recipient cells take up the Cre-tagged mitochondria, Cre is released, translocates to the nuclease, and excises the DsRed-STOP to trigger expression of EGFP.

MitoTRACER begins with a co-culture of neurons and recipient cells. Neurons contain a DNA construct of NLS-iCre-TEV site-OMP25 anchor sequence. The cancer cell contains DNA construct LoxP-DsRed-STOP-loxP-EGFP and TEV protease. The cancer cell is red fluorescent. Next is the transfer of mitochondria, tagged with the anchor-TEV site-iCre-NLS, from the neuron to the cancer cell. Once the tagged mitochondria is in the cancer cell, TEV cleaves off NLS-iCre, which is translocated to the nuclease, where iCre excises DsRed through recombination of the loxP sites. The final step shows the fluorescence switch to EGFP, and the now green cancer cell DNA contains EGFP, TEV protease, and the transferred mitochondria.

Figure 2: Schematic of the MitoTRACER system. NLS = nuclear localization signal; TEVp = TEV protease. Created with BioRender.com.

Using this system, the team tracked the delivery of mitochondria from nerve cells to cancer cells in both breast cancer and melanoma models, showing that this transfer increases the metabolic and metastatic capacity of cancer cells. This is certainly just the beginning for MitoTRACER, as it is a diverse tool that can be used in many different systems, both in vitro and in vivo.

Find MitoTRACER plasmids here!

 

 

Red calcium indicators PinkyCaMP and FRCaMPi

By Mike Lacy

Many popular genetically encoded calcium indicators (GECIs) are available, but red GECIs have been limited compared to other colors. Two recent developments add to this part of the spectrum: PinkyCaMP from the Olivia Masseck Lab (Fink & Imai et al., 2024) and FRCaMPi from the Kiryl Piatkevich Lab (Zhou, Zhu, Eom, Fang, et al., 2025). These new sensors use quite different designs, leading to unique advantages.

While most red GECIs have been derived from just a few parent fluorescent proteins, PinkyCaMP is the first based on mScarlet. Compared to RCaMP3 and jRGECO1a, PinkyCaMP had better brightness, signal-to-noise ratio, photostability, and signal response upon Ca2+ binding. Most importantly, it doesn’t display the problematic photoswitching upon blue illumination that plagues other red GECIs, so the team could multiplex PinkyCaMP alongside green fluorescent and optogenetic tools.

FRCaMPi uses an inverted topology of FRCaMP (itself based on mApple, which means it likely has the blue-light photoswitching issue). Although similar in brightness to jRGECO1a and FRCaMP, FRCaMPi had better dynamic range and sensitivity, in part because its binding affinity is much closer to the Ca2+ concentration in resting neurons. Their soma-targeted variant SomaFRCaMPi also performed substantially better than other soma-localized red GECIs, enabling better spatial resolution for neuronal populations in vivo in both mouse and zebrafish brains.

Panel A shows a fluorescence micrograph of neurons with their cell bodies aligned in a layer and neuropils extending across the field of view. Panel B shows two sets of fluorescence micrographs for the two sensors. In all three brain regions, SomaFRCaMPi labels cell bodies more clearly resolvable, with minimal neuropil fluorescence compared with FRCaMPi images.

Figure 3: PinkyCaMP and FRCaMPi in use. A) Confocal image of CA2 neurons in a mouse brain slice expressing PinkyCaMP; scale bar 50 µm. Reproduced from Fink & Imai et al. (2024) under CC BY-NC-ND license. B) Confocal images showing fore-, mid-, and hindbrain regions of live zebrafish larvae expressing FRCaMPi or SomaFRCaMPi in neurons; scale bars 50 µm. Reproduced from Zhou, Zhu, Eom, Fang, et al. (2025) under CC BY license.

Both groups demonstrated their sensors in a variety of neuronal imaging applications, including confocal and widefield imaging, two-photon microscopy, and fiber photometry. Plus, both designs offer promising templates for future improvements.

Find PinkyCaMP plasmids and FRCaMPi plasmids!

  • Fink, R., Imai, S., et al. (2024). PinkyCaMP a mScarlet-based calcium sensor with exceptional brightness, photostability, and multiplexing capabilities. bioRxiv 2024.12.16.628673. https://doi.org/10.1101/2024.12.16.628673
  • Zhou, S., Zhu, Q., Eom, M., Fang, S., et al. (2025). A sensitive soma-localized red fluorescent calcium indicator for in vivo imaging of neuronal populations at single-cell resolution. PLoS Biol. 23(4): e3003048. https://doi.org/10.1371/journal.pbio.3003048

 

Micropeptide killswitch for biomolecular condensates

By Emily P. Bentley

Biomolecular condensates are membraneless liquid "droplets" that can concentrate and sequester specific macromolecules to serve cellular functions. Along with collaborators, the Denes Hnisz Lab previously discovered that disruption of the nucleolus — the largest biomolecular condensate in human cells — causes a rare malformation syndrome (Mensah & Niskanen et al., 2023). Now, they have adapted the 17-residue peptide that caused nucleolar disruption into a general "killswitch" for other biomolecular condensates (Zhang et al., 2025).

This new tool offers a way to selectively perturb any kind of condensate. The killswitch can be genetically fused to a protein of interest or targeted to a GFP fusion protein using an anti-GFP nanobody (Figure 4). Once incorporated into a condensate, the killswitch disrupts its unique microenvironment, immobilizing the components and altering the composition and dynamics. The researchers demonstrated this perturbation interrupted the functions of several endogenous or pathological condensates, including oncogenic transcription, proliferation of leukemia cells, and assembly of adenovirus particles (Zhang et al., 2025).

See figure caption for description.

Figure 4: Schematic of the killswitch-nanobody system. A cell expressing the protein of interest fused to GFP forms fluorescent biomolecular condensates. A GFP-nanobody fused to the killswitch (GFP-nb–KS) is delivered using a vector that also expresses mCherry to mark transfected cells. The nanobody recruits the killswitch to condensates, disrupting their dynamics and composition. Reproduced from Zhang et al. (2025) under CC BY license.

With 143 plasmids deposited from this paper, a large menu of tool and control constructs is available to choose from!

Find plasmids to probe condensate microenvironments here!

 

AAV-engineered adipocytes suppress tumor progression in cancer models

By Brian O'Neill

The Nadav Ahituv Lab and collaborators have found a way to make adipocytes fight cancer. In this method, called adipose manipulation transplantation (AMT), CRISPR-modified adipocytes (fat cells) are transplanted as a mass that starves the cancer of essential nutrients and alters the tumor microenvironment (Nguyen et al., 2025).

The team used AAV9 to deliver CRISPRa components to adipose cells to activate genes involved in converting white adipose tissue (WAT) cells to brown or browning adipose tissue (BAT) — a type of fat tissue that is able to waste energy by metabolizing glucose to dissipate heat. Of the genes they tested, activating UCP1 had the most potent effect, increasing oxygen consumption and upregulating other genes normally expressed in BAT. When donor-derived CRISPRa-AAV-treated WAT cells were transplanted into the vicinity of any one of five(!) different cancer types, the tumor size was greatly diminished, and tumor hypoxia and angiogenesis were reduced. This seemed to be due to the adipose cells utilizing glucose to the exclusion and detriment of the cancer cells. 

Illustration of experiment workflow and genetic constructs. Panel A: xenograft of cancer cells are injected into a mouse; after 6–8 weeks CRISPRa-AAV adipose organoid is injected next to the tumor; after 3 weeks the tumor is extracted and tumor volume, growth, metabolic genes, hypoxia, and angiogenesis are found decreased. Panel B shows two DNA constructs: rtTA-gRNA-AAV contains U6 promoter followed by a gRNA and CMV promoter followed by rtTA-T2A-mCherry. TRE-dCas9-VP64-AAV contains TRE (with Tet+rtTA bound) and mP followed by dCas9-VP64.

Figure 5: Implantation of engineered adipocytes suppresses tumor progression in cancer models. A) Experimental procedure for xenograft experiments. B) Constructs for tet-inducible CRISPRa-AAV engineering. Adapted from Nguyen et al. (2025) under CC BY license.

The paper includes other great feats of materials engineering as well as extensive validation of the cell and gene therapy, so please check it out!

Find AAV-CRISPRa plasmids here!

 

Knocking-down barriers to biotech education: Affordable, low-tech CRISPR/Cas9 experiments

By Ashley Waldron

CRISPR/Cas9 has revolutionized biotechnology — partly because of its relative simplicity as a gene editing system. Despite that simplicity, its accessibility outside of well-equipped laboratories remains limited. Members of the Stanley Qi Lab set out to address this limitation by developing CRISPRkit, an inexpensive system for CRISPR experiments in classroom settings without specialized equipment (Collins & Lau et al., 2024).

The method uses CRISPR interference (CRISPRi) to regulate gene expression of colorful, easily visible chromoproteins in a cell-free transcription-translation system (Figure 6). This approach eliminates the need for expensive reagents and equipment like incubators, micropipettes, and plate readers. Instead, students can use inoculation loops for liquid transfer, incubate at room temperature, and image with smartphones. The Qi lab also developed an algorithm called CRISPectra so that students can easily quantify their results. 

Illustration of components and workflow for CRISPRkit experiments, as described in the caption and text.

Figure 6: CRISPRkit uses a cell-free system to carry out transcription and translation of chromoprotein and gRNA plasmids. Nuclease-dead Cas9 (dCas9) protein is supplied separately. Results can be analyzed using either "high-tech" or "low-tech" equipment. Reproduced from Collins & Lau et al. (2024) under CC BY-NC-ND license

In addition to chromoproteins, the researchers developed a version of the kit that uses melanin production, allowing students to explore cell metabolism. Plasmid components of CRISPRkit are now available through Addgene. And educators and users can visit the Qi lab's website crisprkit.org to request complete kits or find protocols and other resources.

Find CRISPRkit plasmids here!

  • Collins, M., Lau, M. B., et al. (2024). A frugal CRISPR kit for equitable and accessible education in gene editing and synthetic biology. Nature Communications, 15(1), 6563. https://doi.org/10.1038/s41467-024-50767-2 

 

 

Topics: Hot Plasmids

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