This article describes a workflow of techniques employed for testing novel candidate mediators of melanoma metastasis and their mechanism(s) of action.
Metastasis is a complex process, requiring cells to overcome barriers that are only incompletely modeled by in vitro assays. A systematic workflow was established using robust, reproducible in vivo models and standardized methods to identify novel players in melanoma metastasis. This approach allows for data inference at specific experimental stages to precisely characterize a gene’s role in metastasis. Models are established by introducing genetically modified melanoma cells via intracardiac, intradermal, or subcutaneous injections into mice, followed by monitoring with serial in vivo imaging. Once preestablished endpoints are reached, primary tumors and/or metastases-bearing organs are harvested and processed for various analyses. Tumor cells can be sorted and subjected to any of several ‘omics’ platforms, including single-cell RNA sequencing. Organs undergo imaging and immunohistopathological analyses to quantify the overall burden of metastases and map their specific anatomic location. This optimized pipeline, including standardized protocols for engraftment, monitoring, tissue harvesting, processing, and analysis, can be adopted for patient-derived, short-term cultures and established human and murine cell lines of various solid cancer types.
The high mortality associated with metastatic melanoma combined with an increasing incidence of melanoma worldwide1 (an estimated 7.86% increase by 2025) calls for new treatment approaches. Advances in target discovery hinge upon reproducible models of metastasis, a highly complex process. Throughout the steps of the metastatic cascade, melanoma cells must overcome countless barriers to achieve immune system evasion and colonization of distant tissues2. The resilience and adaptability of melanoma cells arise from a multitude of factors, including their high genetic mutational burden3 and their neural crest origin, which confer crucial phenotypic plasticity3,4,5. At each step, transcriptional programs allow metastasizing melanoma cells to switch from one state to another based on cues from the crosstalk with the microenvironment, comprising the immune system6, the extracellular milieu7,8, and the cellular architecture of physical barriers9 with which they come in contact. For example, melanoma cells escape immune surveillance by downregulating the expression of important immune-priming tumor-secreted factors6.
Studies describe a "premetastatic niche", wherein melanoma cells secrete chemokines and cytokines to prime the distant "target" organ for metastasis10. These findings raise important questions about the organ tropism of metastatic melanoma cells and the anatomic route they take to access distant tissues. After intravasation, melanoma cells are known to metastasize through lymphatics (lymphatic spread) and blood vessels (hematogenous spread)2,11. While most patients present with localized disease, a small subset of cases presents with distant metastatic disease and no lymphatic dissemination (negative lymph node involvement)11, suggesting the existence of alternative metastatic pathways for melanoma.
When they colonize a metastatic site, melanoma cells undergo epigenetic and metabolic adaptations12,13. To access and invade new compartments, melanoma cells employ proteases14 and cytoskeletal modifications11,15, which enable them to traverse to and grow in their new location. The difficulty in targeting melanoma cells resides in the complexity and number of such adaptations; thus, the field should make efforts to recreate experimentally as many steps and adaptations as possible. Despite numerous advances in in vitro assays such as organoids and 3D cultures16,17, these models only incompletely recapitulate the in vivo metastatic cascade.
Murine models have shown value by striking a balance between reproducibility, technical feasibility, and simulation of human disease. Intravascularly, orthotopically and heterotopically implanted melanoma cells from patient-derived xenografts or short-term cultures into immune-compromised or humanized mice represent the backbone of target discovery in metastatic melanoma. However, these systems often lack a crucial biological constraint on metastasis: the immune system. Syngeneic melanoma metastasis models that possess this constraint are relatively scarce in the field. These systems, developed in immunocompetent mice, including B16-F1018, the YUMM family of cell lines19, SM120, D4M321, RIM322 or more recently, the RMS23 and M1 (Mel114433), M3 (HCmel1274), M4 (B2905)24 melanoma cell lines, facilitate the investigation of the complex role of the host immune response in melanoma progression.
Here, a pipeline for melanoma metastasis target identification is presented. With increasing and larger 'omics' datasets being generated from melanoma patient cohorts, we postulate that studies holding the most clinical promise are those that stem from big data integration, leading to meticulous functional and mechanistic interrogation25,26,27,28. By using mouse models to study potential targets in the metastatic process, one can account for in vivo-specific events and tissue interactions, thus increasing the probability of clinical translation. Multiple methods to quantify metastatic burden are outlined, providing complementary data on the results of any given experiment. A protocol for single-cell isolation from tumors in various organ is described to aid the unbiased characterization of gene expression in metastatic cells, which may precede single-cell or bulk RNA sequencing.
NOTE: The animal procedures involved in the following protocol were approved by the New York University Institutional Animal Care and Use Committee (IACUC). All the procedures are conducted in facilities approved by the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC). Figure 1 depicts the general experimental approach.
1. Patient-derived melanoma short-term cultures (STCs)
Figure 1: Schematic illustrating the described workflow, from patient data integration to generation and analysis of in vivo data from mice. Abbreviations: LOF = loss of function; GOF = gain of function. Please click here to view a larger version of this figure.
2. Xenograft implantation
NOTE: The experimental procedures described here are conducted in mice that have impaired adaptive and innate immune systems, NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice; or in mice that lack adaptive immunity only, such as the T cell-deficient athymic/nude (NU/J) mice. Animals are of male sex, 8 to 10 weeks of age. Females often exhibit a high incidence of gonadal metastases upon intracardiac injection of tumor cells, which reduces their survival.
3. Staged survival surgery (SSS)
4. In vivo imaging (Figure 2A)
5. Ex vivo magnetic resonance imaging
6. Tissue processing for single-cell or bulk RNA sequencing
7. Animal tissue perfusion and preparation for immunohistological analyses
Figure 2: Examples of BLI, brightfield, ex vivo fluorescence, and H&E staining images illustrating the multipronged approach for the analysis of candidate genes' effects in melanoma metastasis. (A) BLI, (B) BF, (C) ex vivo fluorescence, and (D) H&E staining images. The images used for the purpose of illustration correspond to an experiment in which 131/6-4L melanoma cells transduced with a non-targeting control shRNA (shNTC) or an shRNA targeting FUT8 were injected into immunodeficient (NSG) mice. FUT8 silencing impaired the metastatic dissemination of melanoma cells. Scale bars and color bar = p/sec/cm2/sr × 106 (A), 100 mm (B, C), 100 µm (D). Abbreviations: BLI = bioluminescence imaging; H&E = hematoxylin and eosin; shRNA = short hairpin RNA; shNTC = non-targeting control shRNA; NSG = non-obese diabetic severe combined immunodeficiency gamma; FUT8 = fucosyltransferase 8; BF = brightfield. Please click here to view a larger version of this figure.
8. Nuclear Mitotic Apparatus Protein (NuMA) staining (Figure 3)
9. Tissue slice immunofluorescence
To identify the metastatic stage in which a particular gene candidate is required (e.g., extravasation vs. survival after seeding), one can determine tissue slice immunofluorescence at different time points to track tumor cell progression from injection to distant organ invasion, seeding, and growth. This approach allows the addition of markers for neighboring cells to capture the extravasation event and the surrounding tumor microenvironment changes33.
The following figures illustrate how the described workflow has been applied for the identification of novel drivers of melanoma metastasis. Figure 2 summarizes the results of a published study in which the effects of silencing the fucosyltransferase FUT8 in in vivo melanoma metastasis were studied26. Briefly, analysis of human patient glycomic data (obtained by lectin arrays) and transcriptomic profiling revealed increased levels of alpha-1,6-fucose associated with progression from primary to metastatic melanoma, consistent with an increase in the corresponding fucosyltransferase (FUT8).
113/6-4L melanoma cells transduced with lentiviruses carrying a FUT8 shRNA or the corresponding non-targeting control (shNTC) were introduced by ultrasound-guided intracardiac injection into immunodeficient mice (NSG), as described above (section 2.9). The mice were monitored for metastatic dissemination by in vivo BLI. The mice were euthanized at the end of the experiment, the organs were examined for ex vivo fluorescence and processed for histological analyses. In addition to H&E, NuMA staining was performed to specifically identify human cells in murine tissues. As illustrated in Figure 3, NuMA-stained sections were processed by digital imaging to quantify the metastatic burden across multiple sections and experimental groups. A similar workflow can be applied to assess the contribution of other candidate genes to melanoma metastasis.
Figure 3: NuMA-stained lung sections. (A) Left, representative images of NuMA-stained lung sections from Group I (melanoma cells infected with control lentivirus) and Group II (melanoma cells infected with a metastasis suppressor-expressing lentivirus). Scale bars = 1,000 µm. Insets display metastatic foci (middle) that can be quantified using software. Right, metastatic melanoma cells are labeled green, and the organ area is delineated by a green hatched line. NuMA-negative cells are labeled blue. Scale bars = 100 µm. (B) Example of a micrometastasis in NuMA-stained lung sections illustrates the sensitivity of the software in detecting a small number of cells. Scale bars = 100 µm. Abbreviation: NuMA = Nuclear Mitotic Apparatus Protein. Please click here to view a larger version of this figure.
Antibody | Manufacturer | Catalog No | Host species | Reactivity | Fluorophore | Dilution | Incubation time | Incubation temperature |
anti-GFP | Abcam | ab6556 | Rabbit | Mouse | unconjugate | 1:1000 | 24 hrs | 4°C |
anti-GFAP | Aves Labs | GFAP | Chicken | Mouse | unconjugate | 1:2000 | 24 hrs | 4°C |
secondary | Invitrogen | a11041 | Goat | Chicken | A568 | 1:500 | 2 hrs | Room Temperature |
secondary | Invitrogen | a32731 | Goat | Rabbit | A488 | 1:500 | 2 hrs | Room Temperature |
Table 1: Examples of Antibody and incubation conditions for brain slice immunofluorescence.
Cell Line | Type | Time to euthanasia | Sex of Mice | Genetic Background of Mice | Route of injection | # Cells Injected | Sites of metastasis | |
12-273 BM+ | Human melanoma STC | 4-5 weeks | M | NSG | Intracardiac | 100K | Brain parenchyma, leptomeninges, liver, kidney, adrenal glands | |
131/4-5B1* | Human melanoma | 4-6 weeks | M | Athymic nude or NSG | Intracardiac | 50-200K | Brain parenchyma, liver, lung | |
113/6-4L* | Human melanoma | 5-7 weeks | M | Athymic nude or NSG | Intracardiac | 50-100K | Brain parenchyma (few), liver, lung | |
WM 4265-2** | Human melanoma STC | 11 weeks | M | Athymic nude or NSG | Intracardiac | 200K | Brain parenchyma | |
WM 4257-1** | Human melanoma STC | 10-13 weeks | M | Athymic nude | Intracardiac | 100K | Brain parenchyma (few) | |
WM 4257-2** | Human melanoma STC | 10-13 weeks | M | Athymic nude | Intracardiac | 100K | Brain parenchyma | |
10-230 BM+ | Human melanoma STC | 8-9 weeks | M | Athymic nude | Intracardiac | 100K | Brain parenchyma, leptomeninges, liver (few) |
Table 2: Breakdown of results from representative in vivo experiments of various human melanoma cell lines and short-term cultures following the described protocol.
The aim of this technical report is to offer a standardized, top-to-bottom workflow for the investigation of potential actors in melanoma metastasis. As in vivo experiments can be costly and time-consuming, strategies to maximize efficiency and increase the value of the information obtained are paramount.
It is imperative to use complementary approaches throughout to crossvalidate findings within the same experiment. For example, both NuMA immunohistochemical staining and BLI are complementary methods of quantitating metastatic burden because neither is comprehensive. While BLI is an invaluable, noninvasive method of tracking tumor progression in vivo, these data are inherently of low resolution. NuMA staining allows for meticulous analysis of metastatic burden in fixed organs; however, comprehensive sectioning through the entire tissue thickness is impractical. As such, only a sample of each organ can be stained. Indeed, in the experience of the authors, BLI results are not always directly proportional to the tumor burden evident in histopathological analysis. This is in part due to the limited sensitivity of this method, particularly in the brain, because of transcranial attenuation34. In addition, these data can be affected by incomplete luciferin uptake and/or variable luciferase expression. Therefore, BLI should be interpreted in conjunction with ex vivo imaging and histopathologic studies.
Histological evaluation of tissue samples treated with generic stains, such as H&E, demands specialized anatomopathology training, is often low-throughput, and is prone to interobserver variations. The authors are currently working with bioinformatics colleagues to standardize and accelerate experimental data analysis by developing a machine learning algorithm for automated and reliable quantitation of metastatic burden as a percentage of organ tissue section in histopathologic images. These and other tools will be critical for the field, especially as the role of the metastatic microenvironment comes into focus at a finer resolution (e.g., spatial transcriptomics). Nevertheless, expert histopathological evaluation of the tissue is essential, particularly in subtypes of brain metastasis such as leptomeningeal, a biologically distinct subtype, which is easily misinterpreted as parenchymal brain metastasis via BLI alone. NuMA staining (section 8) accelerates the histopathologic assessment of metastatic burden, allowing for unbiased identification and quantitation of human cells in mouse organs. However, distinction between anatomic compartments on NuMA-stained sections, such as the brain parenchyma versus the leptomeninges, is critical to gain further biological insights.
The techniques described herein may be used to investigate the functional relevance of genes of interest to the melanoma metastatic cascade. It is critical to select a model with a reproducible phenotype that is appropriate for the study in question. For example, a gene upregulated in human patient samples of metastasis can be "knocked down" to assess if this decreases metastatic burden compared to a control group. This approach is best carried out in a model cell line or short-term culture that features both a) high expression of the gene of interest and b) generates significant metastatic burden with reliable kinetics when injected into mice, such that a decrease in metastatic capacity will be appreciable and assignable to the genetic perturbation being tested.
Also crucial in experimental design is the selected mode of injection most appropriate to the stage of metastasis under investigation. Each stage of the metastatic cascade presents distinct biological and physical barriers to melanoma cells. Investigators seeking to answer questions on the initial stages of metastasis, namely invasion and intravasation, should employ the techniques outlined in section 2 for intradermal and subcutaneous injections, respectively, followed by survival surgery (section 3). Importantly, these procedures mimic the process by which primary melanomas are resected in humans, after which a patient may or may not present with metastasis. While technically more delicate than subcutaneous injection, the intradermal route plants tumor cells in the anatomic compartment where melanomas develop in human patients. This is particularly important in studies of immune surveillance of melanoma, as the skin has a unique ecosystem of patrolling immune populations35.
However, if the hypothesis being tested centers on later stages of metastasis, such as extravasation from the arterial circulation, methods such as intracardiac, intracarotid, and retro-orbital injection are advantageous. These techniques yield metastasis on a larger scale in a much shorter time span than those involving a "primary" tumor. For studies of brain metastasis, in particular, models that reliably produce tumors in the brain parenchyma can be difficult to establish. In these cases, intracarotid and retro-orbital injection represent methods of bypassing organs with lower "barriers to entry", such as the liver and kidneys, which can cause premature mortality in mice injected via the intracardiac route.
The mouse genetic background of choice for xeno- or allograft transplantation depends on the source of cells (human, mouse) and, occasionally, on genetic modifications of the implanted cells that may elicit immune rejection. Experiments involving human xenograft models are usually conducted in mice with impaired adaptive and innate immune systems, NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice; or mice lacking adaptive immunity, such as T cell-deficient athymic/nude (NU/J) mice. Another immunodeficient model frequently used is the RAG2 knockout (KO) model, which lacks B and T cells and retains a functional natural killer cell population. These immunodeficient mouse models must be deployed strategically, as each has advantages at the expense of some drawbacks related to their intrinsic immune deficiencies. In the authors' experience, the same cell line- or patient-derived STC exhibits different organ tropism based on the route of injection (e.g., subcutaneous vs. intracardiac) and/or the recipient mouse strain (e.g., NSG vs. athymic/nude) (see Table 2).
To mitigate the experimental variability pertaining to the host in which melanoma cells are implanted (e.g., immune response, microbiota), and maximize 'on target' and reproducible findings, the following are recommended: i) increasing the number of experimental animals per group (using power calculations to reach an optimal number based on the effect size), ii) using orthogonal methods to manipulate gene candidates (i.e., CRISPR/Cas9, CRISPRi, shRNA), and 'add-back' experiments (i.e., concomitant ectopic expression of a Cas9- or shRNA-resistant cDNA of the gene of interest). These complementary techniques reduce the off-target effects possibility and/or biological and experimental variation.
While this protocol can certainly be applied for hypothesis-driven validation of candidate drivers or suppressors of metastasis, these methods may also be useful for unbiased, exploratory studies. For example, pooled CRISPR/cas9, CRISPR-KRAB-dCas9 (CRISPRi), and shRNA-based screens allow for a process of Darwinian selection to play out in vivo36. The conceptual basis for such studies is as follows: a cell with a gene knocked out that is essential to the phenotype of interest (e.g., tumor growth) will die or fail to proliferate, such that its representation in the sequenced library is diminished at the conclusion of the experiment relative to the baseline. The procedures described here may be applied for such an approach, with appropriate optimization37,38.
In regard to candidate gene selection, multiple sources can be mined. Melanoma patient transcriptomics and proteomics datasets are publicly available via the NCBI Gene Expression Omnibus (GEO)39, the European Genome-Phenome Archive40, cBioPortal41 (which hosts The Cancer Genome Atlas, or TCGA42), and other hosting sites. Reanalysis of raw data is recommended as quality control measures can vary greatly between public databases, impacting the results. When interrogating raw datasets, questions appropriate for candidate gene selection suitable for application to the workflow described here include: which genes are dysregulated in metastatic samples as compared to primary melanoma samples or to melanocytic nevi?; which genes are dysregulated in specific sites of metastasis?; is the dysregulated expression of the candidate gene associated with improved patient survival?; is this gene part of a larger gene expression program that is generally dysregulated?; are the interactors of the gene product well-characterized or unknown?; is the gene product druggable, and if so, are targeting tools available?; and very importantly, is the gene essential to all human cells, or to many tissues, such that interference with its activity in a clinical setting might prove toxic?
The appropriate strategy for the manipulation of the genes of interest depends on the hypotheses to be tested. For example, a gene upregulated in metastasis can be knocked down to assess if the corresponding mice would display decreased metastatic burden compared to a control group. This approach is best carried out in a model cell line or short-term culture, which features both: a) high expression of the gene of interest and b) generates appreciable metastatic burden when injected into mice with reproducible kinetics. Knockdown approaches include shRNA- and CRISPR/Cas9 based-methods, both of which can be engineered via lentiviral infection of melanoma cells and deployed in an inducible or constitutive fashion. One of the advantages of inducible expression (see pLKO Tet-On in the Table of Materials) is the temporal regulation of knockdown, which can be leveraged in an in vivo experiment. Thus, inducible shRNAs/sgRNAs can be used to model a "therapeutic setting" in which established tumor cells are subjected to a candidate gene knockdown. However, exposure to the inducing agent, e.g., doxycycline, may have consequences for the behavior of certain melanoma cells; as such, the inclusion of control cells transduced with a scrambled shRNA that also experience this treatment is critical.
Whereas shRNAs often yield a partial knockdown of gene expression, CRISPR/Cas9-based systems edit a gene at the DNA level, theoretically eliciting a complete "knockout" (KO). Their use presents both advantages and disadvantages. If a gene is essential for melanoma cell viability, cells with a complete KO will be negatively selected in vitro and later in vivo. Although this issue may be partially mitigated by selecting single-cell clones, melanoma cells struggle to grow from single cells, which results in unpredictable and often disparate adaptations. Thus, multiple KO clones need to be tested to control for interclonal phenotypic variations. Furthermore, in the case of patient-derived STCs especially, the number of lentiviral infections to which melanoma cells are exposed can greatly affect in vitro proliferation and in vivo metastatic behavior. Therefore, a single-vector, single-infection approach incorporating Cas9 and an sgRNA (see lentiCRISPRv2 in the Table of Materials) is recommended. Other systems make use of a "recombinase dead" Cas9 to elicit transcriptional repression (dCas9-KRAB in the Table of Materials).
A gain-of-function approach may be appropriate if a gene of interest is hypothesized to be a metastasis-promoting gene. In this case, the selection of a melanoma line yielding few metastases upon injection in mice and featuring low basal expression of the gene of interest is key. Overexpression constructs (particularly those driven by CMV promoters) often lead to supraphysiologic expression levels, which cause proteotoxic stress. Therefore, choosing lentiviral vectors that allow for the physiological expression of the gene of interest is recommended.
Once an approach has been selected, it is important to carry out the following experiments prior to the engraftment of cells. Lentiviral infection procedures vary between laboratories and will necessitate optimization for each cell line and knockdown system. However, universal considerations include a complete positive or negative selection of cells featuring gene knockdown (e.g., FACS/cell sorting for fluorescent reporters or antibiotic resistance selection, if applicable), followed by RT-qPCR and western blot with appropriate controls to demonstrate reproducible and robust knockdown or overexpression of the gene of interest. An in vitro proliferation assay should be conducted to determine if interfering with the gene of interest affects cell viability. This step is important for reliable cell characterization and for the correct interpretation of in vivo results. Here is an example of a pitfall if the experiments described are not performed: if a gene knockdown results in a drastic proliferation defect in vitro, this will confound the interpretation of decreased metastatic burden, as the specific contribution of this gene to the metastatic cascade cannot be accurately assessed. Various modalities of proliferation assays include commercially available kits, live cell-imaging systems, or traditional cell-culture-based assays, e.g., crystal violet, trypan blue exclusion.
Among the major limitations for this platform in discovering mediators in melanoma is that the proposed workflow investigates only tumor cell-intrinsic gene candidates, not genes expressed by the cells of the surrounding microenvironment at different metastatic stages, which are key modulators of tumor cell adaptation and seeding of distal organs. Another important factor to consider is differential metastatic behavior based on the engraftment route. The interlaboratory and interoperator variability intrinsic to some of the techniques presented can be addressed by standardization across the metastasis research field. Currently, the most suitable protocol for standardization is the intracardiac injection due to the ultrasound guidance and static injection devices, which reduce interoperator variability. This protocol represents one of the numerous steps in the direction of uniformity, reproducibility, and thorough documentation of methods used across laboratories working on the identification of novel mediators of melanoma metastasis.
The authors have nothing to disclose.
We thank the Division of Advanced Research Technologies (DART) at NYU Langone Health, and in particular, the Experimental Pathology Research Laboratory, Genome Technology Center, Cytometry and Cell Sorting Laboratory, Pre-Clinical Imaging Core, which are partially supported by the Perlmutter Cancer Center Support Grant NIH/NCI 5P30CA016087. We thank the NYU Interdisciplinary Melanoma Cooperative Group (PI: Dr. Iman Osman) for providing access to patient-derived melanoma short-term cultures+ (10-230BM and 12-273BM), which were obtained through IRB-approved protocols (Universal Consent study #s16-00122 and Interdisciplinary Melanoma Cooperative Group study #10362). We thank Dr. Robert Kerbel (University of Toronto) for providing 113/6-4L and 131/4-5B1 melanoma cell lines* and Dr. Meenhard Herlyn (Wistar Institute) for providing WM 4265-2, WM 4257s-1, WM 4257-2 melanoma short-term cultures**. E.H. is supported by NIH/NCI R01CA243446, P01CA206980, an American Cancer Society-Melanoma Research Alliance Team Science Award, and an NIH Melanoma SPORE (NCI P50 CA225450; PI: I.O.). Figure 1 was created with Biorender.com.
#15 Scapel Blade | WPI | 500242 | For surgical procedures |
#3 Scapel Handle | WPI | 500236 | For surgical procedures |
1 mL Tuberculin syringe, slip tip | BD | 309626 | Injections |
10 mL syringe, slip tip | BD | 301029 | Perfusion |
10% Formalin Sodium Buffered | EK Industries | 4499-20L | For perfusion/tissue fixative |
15 mL Conical | Corning | 430052 | Cell culture |
15 mL Conical Polypropylene Centrifuge Tubes | Falcon | 352196 | Cell culture |
200 Proof Ethanol | Deacon Labs | 04-355-223 | Histology |
22G – 22mm needle | BD | 305156 | Perfusion |
4-0 Vicryl Suture | Ethicon | J464G | Suture |
4% Carson's phosphate buffered paraformaldehyde | EMS | 15733-10 | For perfusion/tissue fixative |
40µm | Corning | 431750 | Tissue processing |
5-0 Absorbable Suture | Ethicon | 6542000 | Closure |
50 mL Conical | Corning | 430828 | Cell culture |
50mL Conical Polypropylene Centrifuge Tubes | Falcon | 352070 | Cell culture |
7-0 Silk suture | FST | 18020-70 | Ligature |
70µm | Corning | 431751 | Tissue processing |
Anti-fade mounting media | Vector Labs | H-1000-10 | Immunofluorescence |
Approximator applying Forceps, 10cm | WPI | 14189 | For microsurgical procedures |
Avance | Bruker | 3 HD | NMR Console |
Biospec 7030 | Bruker | 7030 | Micro MRI |
BSA | Bioreg | A941 | NuMA Staining |
Castroviejo suturing forceps, straight tips 5.5mm tying platform, 11cm | WPI | WP5025501 | For microsurgical procedures |
Coplin Staining Jar | Bel-Art | F44208-1000 | Histology |
DAPI | Sigma-Aldrich | D9542-1MG | Immunofluorescence |
dCas9-KRAB | Addgene | 110820 | Genetic manipulation |
DNase I | NEB | M0303L | Tissue processing |
DPBS | Corning | 21-030-CM | Tissue processing |
Extra Sharp Uncoated Single Edge Blade | GEM | 62-0167 | Tissue processing |
Extracellular Matrix Substrate | Corning | 354234 | Consider the Growth Factor Reduced ( as alternative |
FBS | Cytiva | SH30910.03 | Cell culture |
Fiji Image J | Fiji Image J | Software | Immunofluorescence |
Goat anti-rabbit HRP conjugated multimer | Thermo Fisher | A16104 | NuMA Staining |
Goat Serum | Gibco | PCN5000 | Immunofluorescence |
HBSS | Corning | 21-020-CV | Tissue processing |
Hematoxylin | Richard-Allan Scientific | 7231 | Histology |
Illumina III | PerkinElmer | CLS136334 | BLI Instrument |
Insulin syringe 28G – 8mm needle | BD | 329424 | Injections |
Insulin syringe 31G – 6mm needle | BD | 326730 | Injections |
Iris Forceps, 10.2cm, Full Curve, serrated | WPI | 504478 | For perfusion and surgical procedures |
Isoflurane USP | Covetrus | 11695067772 | Anesthesia |
Jewelers #7 Forceps Titanium 11 cm 0.07 x 0.01 mm Tip | WPI | WP6570 | For microsurgical procedures |
Ketamine HCl 100mg/mL | Mylan Ind. | 1049007 | Anesthesia |
lentiCRISPRv2 | Addgene | 98290 | Genetic manipulation |
Lycopersicon Esculentum (Tomato) Lectin, DyLight 649 | Invitrogen | L32472 | Vascular endothelial cells marker |
MEM non-essential amino acids X 100 | Corning | 25-025-CI | Cell culture |
Metzenbaum Scissors | WPI | 503269 | For surgical procedures |
Microinjection Unit | KOPF | 5000 | Intracardiac injections |
NaCl | Fisher | S25877 | NuMA Staining |
Needle 30G x 25mm | BD | 305128 | Intracardiac Injection |
Needle 33G x 15mm | Hamilton | 7747-01 | Intracarotid Injection |
Needle holder, Castroviejo, 14cm, with lock, 1.2mm Serrated Jaws | WPI | 14137-G | For microsurgical procedures |
NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice | The Jackson Laboratory | 005557 | Murine model |
NU/J mice | The Jackson Laboratory | 002019 | Murine model |
Nuclear Mitotic Apparatus Protein polyclonal rabbit anti-human | Abcam | 97585 | NuMA Staining |
Penicillin-Streptomycin 10000U/mL | Gibco | 15140122 | Cell culture |
Percoll | GE | 0891-01 | density separation solution |
PI Classic Surgical Gloves | Cardinal Health | 2D72PT75X | Surgery |
pLKO Tet-On | Addgene | 21915 | Genetic manipulation |
Povidone-Iodine 10% Solution | Medline | MDS093943 | Surgery |
Proparacaine Drops 0.5% | Akorn Pharma | AX0501 | Opthalmic local anesthetic |
Puralube Petrolatum Opthalmic Ointment | Dechra | 83592 | Anesthesia |
Razor Blade Double Edge Blades | EMS | 72000 | Shaving and Vibrotome Brain Slicing |
Reflex 9mm EZ Clip | Braintree | EZC- KIT | Wound closure |
RPMI 1640 | Corning | 10-040-CM | Cell culture |
Scissors, Spring 10.5cm Str, 8mm Blades | WPI | 501235 | For microsurgical procedures |
Semi-Automatic Vibrating Blade Microtome | Leica | VT1200 | Brain Slice Immunofluorescence |
Single Channel Anesthesia Vaporizer System | Kent Scientific | VetFlo-1210S | Anesthesia |
Smartbox Tabletop Chamber System and Exhaust Blower | EZ Systems | TT4000 | CO2 Euthanasia |
Sterile Fenestrated Disposable Drape | Medline | NON21002 | Surgery |
Sterile Non-Reinforced Aurora Surgical Gowns with Set-In Sleeves | Medline | DYNJP2715 | Surgery |
T25 Flask | Corning | 430639 | Cell culture |
Tris | Corning | 46-031-CM | NuMA Staining |
Triton X-100 | Sigma-Aldrich | X100-500ML | Immunofluorescence |
Troutman tying forceps, 10cm, Curved G pattern, 0.52mm tip with tying platform | WPI | WP505210 | For microsurgical procedures |
Vessel clips 10G Pressure 5x 0.8mm Jaws, 5/pkg | WPI | 15911 | For microsurgical procedures |
Visiopharm | Visiopharm | Visiopharm | NuMA Staining Quantification Software |
Xylasine 100mg/mL | Akorn Pharma | 59399-111-50 | Anesthesia |
Xylene | Fisher | X3P-1GAL | Histology |