Nature Protocols

Nuclei isolation from myelin-rich adult mouse brain regions remains challenging for single-nucleus RNA sequencing because myelin and debris can reduce nuclei quality. We describe an optimized protocol for mouse hippocampi and cerebella using tube-and-pestle homogenization and low-volume sucrose-gradient pelleting with a standard benchtop centrifuge, with optional magnetic enrichment of nuclei to reduce debris/non-nuclear carryover. Under the tested conditions, the workflow produces intact, debris-reduced nuclei and supports downstream 10x Genomics Flex and PARSE WT library preparation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/716374v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@ccbd87org.highwire.dtl.DTLVardef@1aef4bcorg.highwire.dtl.DTLVardef@14569a8org.highwire.dtl.DTLVardef@1bc261_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBenchtop sucrose-gradient pelleting enables rapid nuclei purification from myelin-rich adult mouse brain C_LIO_LIScales across tissue inputs (e.g., hippocampus [~]15-20 mg; cerebellum [~]50-70 mg) without ultracentrifugation or 15 mL gradients C_LIO_LIMagnetic enrichment as the recommended final cleanup step further reduces myelin/debris carryover and is compatible with 10x Flex and PARSE WT workflows. C_LI

MOTIVATIONLongitudinal molecular studies of the mouse brain are limited by the need for terminal tissue collection. This prevents analysis of preexisting molecular states and their evolution within the same individual. We developed a stereotactic microbiopsy technique that enables minimally invasive sampling of defined brain regions in vivo. The method preserves survival while yielding material suitable for RNA and nuclei isolation. It provides a practical solution for linking baseline molecular states to subsequent behavioural, pharmacological, or disease-related outcomes. SUMMARYThis study presents a stereotactic microbiopsy technique for sampling defined brain regions in living mice, enabling transcriptomic and epigenomic analyses without sacrificing the animal. The method will allow pre-intervention tissue collection, making it possible to separate preexisting molecular differences from experience- or treatment-induced changes. We show that microbiopsies yield sufficient, high-quality RNA and chromatin for sequencing, with minimal tissue damage that largely resolves over time. The procedure uses standard stereotactic equipment and achieves reproducible spatial precision when the syringe is stabilised. This approach provides a practical framework for within-subject molecular comparisons, reducing animal use and enabling longitudinal profiling of the living mouse brain. It establishes a foundation for investigating how baseline molecular states influence later physiological or behavioural outcomes.

SummaryThe combination of target capture metagenomics and long-read sequencing represents a powerful approach for the characterisation of rare microbial taxa and their functional genes. However, standard Nanopore library preparations are incompatible with established capture protocols. A possible workaround is the preparation of Illumina libraries prior to ONT sequencing. Currently, this hybrid approach is hindered by a lack of specialised demultiplexing software capable of handling residual adapter fragments; Nanopores higher error rates and positional variability. Here, we present deluxpore: a Nextflow pipeline that demultiplexes Nanopore reads from Illumina dual-indexed libraries (NEBNext and Nextera) using BLAST alignment and Levenshtein distance matching. Extensive benchmarking across 18 replicates validates the viability and precision of this hybrid indexing approach. Benchmarking demonstrates that accurate demultiplexing requires minimum Q20 data quality and strategic index selection. Unique index-to-sample designs achieved 91.7% sample recovery at Q20 versus 46.1% for combinatorial approaches. We also identified high-crosstalk index pairs within NEBNext Primer Set A and provide an optimized 8-sample configuration achieving ~95% accuracy at Q20. deluxpore enables reliable, automated demultiplexing for hybrid capture-long-read sequencing workflows. Availability and implementationdeluxpore is implemented in Nextflow, Python, and Bash under the GNU GPL v3.0. Source code, documentation, and benchmarking workflows are available at https://github.com/compgenomicslab/deluxpore and https://github.com/compgenomicslab/deluxpore-benchmarking.

Peptergent is a novel class of amphipathic peptides that enable detergent-free extraction and purification of membrane proteins (MPs). These designed peptides self-assemble around hydrophobic transmembrane regions of proteins, forming stable, water-soluble assemblies that can be isolated directly from biological membranes. By doing so, Peptergent bypass the limitations imposed by traditional detergents, which often destabilize proteins and restrict downstream analyses. Since detergents are completely avoided, Peptergent-isolated MPs are directly amenable to structural and mass spectrometry (MS) analysis, thereby addressing their persistent underrepresentation in proteomic datasets and improving their accessibility for drug-screening strategies. Here, we describe a streamlined protocol for isolating MPs with the Peptergent PDET-1, followed by exchange into His-tagged Peptidiscs for Ni-NTA-based affinity purification. The method comprises membrane isolation, peptide preparation, protein extraction, clarification, and exchange of MPs from Peptergent to Peptidiscs. Application of this workflow yields enriched membrane proteomes compatible with downstream LC-MS/MS analysis, with improved recovery of hydrophobic and multi-pass membrane proteins. Key featuresO_LIDirect extraction and solubilization of membrane proteins in Peptergents C_LIO_LIExchange into His-tagged Peptidiscs enabling affinity purification of MPs C_LIO_LI100% detergent-free workflow compatible with LC-MS/MS analysis C_LIO_LIApplicable to cultured cells and tissue-derived membrane fractions C_LI In BriefWe describe a Peptergent-based workflow for isolating membrane proteins directly from membrane preparations. Proteins are extracted with the Peptergent peptide scaffold (PDET-1) and transferred into His-tagged Peptidisc (HD-43). The water-soluble membrane proteins are enriched by Ni-NTA affinity purification and prepared for bottom-up mass spectrometry, yielding enriched membrane proteomes and dried peptide samples ready for LC-MS analysis Graphical Overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/711971v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@af3241org.highwire.dtl.DTLVardef@c6a94org.highwire.dtl.DTLVardef@129322aorg.highwire.dtl.DTLVardef@19c7c9d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Transposon insertion sequencing (TIS) encompasses methods such as Transposon Directed Insertion sequencing (TraDIS) and Transposon-Sequencing (Tn-Seq); these methods are widely uses for genome scale screens of essential and conditionally essential genes. Early limitations centred on mutant generation, today the biggest factor is sequencing and data generation and the costs associated. Here, we present and evaluate four methods TIS sequencing library generation protocols compatible with Illumina whole genome sequencing (WGS) workflows to maximise sequence efficiency and minimise turnaround times and costs. Using E.coli BW25113 transposon mutagenesis libraries generated with Tn5 and mariner (Himar1) transposons, we compare the methods in terms of reagent cost, workflow complexity, and target enrichments for the recovery of unique insertion sites and essential genes identified. All methods generated TIS data suitable for gene essentiality analysis. Illumina Flex based protocols were 4-6 tomes cheaper than the traditional Illumina Nextera based approach with similar or superior Transposon-Chromosome (Tn-Chr) junction enrichment. Across all methods, sequencing depth and mutant library density were the dominant factor in useful biological insight. Subsampling demonstrated that for a good quality mutant library, five million reads were sufficient to identify essential genes in E.coli. Whereas deeper sequencing reduced the statistical power and included contaminating background noise, seen primarily with Tn5. We conclude that an Illumina Flex based approach, especially when integrating with routine WGS, provides an excellent balance of speed, cost and data quality. Assuming five million reads and a robust Illumina Flex approach, a TIS library can be sequenced for around {pound}40.

MotivationGene-body coverage bias differs across scRNA-seq protocols and can influence downstream analyses, yet coverage is often assessed using bulk-level summaries that obscure cell-to-cell variability. ResultsCellCov provides gene-body coverage profiling at single-cell resolution, enabling exploration of coverage heterogeneity across both cells and features. The accompanying workflow supports flexible grouping and robust aggregation of profiles by user-provided annotations, allowing principled comparison of coverage bias across sequencing protocols. We demonstrate its use on public datasets from several full-length scRNA-seq chemistries. AvailabilityCellCov source code and documentation are available at https://github.com/ziegenhain-lab/CellCov Contactchristoph.ziegenhain@ki.se Supplementary informationSupplementary data are available at Bioinformatics online

MotivationThe transition toward "atlas-scale" single cell research has resulted in datasets comprising millions of cells across hundreds of samples, creating significant challenges for data management, computational efficiency, and reproducibility. While numerous methods are available for individual steps in single cell data processing, the highly complex nature of the analysis makes it challenging to maintain a clear record of every tool and parameter used. This makes final results difficult to reproduce, highlighting the need for a unified workflow that integrates multiple steps into a cohesive framework. Resultsscprocess is a Snakemake pipeline designed to streamline and automate the complex steps involved in processing single cell RNA sequencing data. Specifically optimized for data generated using the 10x Genomics technology, it provides a comprehensive solution that transforms raw sequencing files into standardized outputs suitable for a variety of downstream tasks. The pipeline is built to support the analysis of datasets comprising multiple (e.g. 100+) samples via a simple CLI, allowing researchers to efficiently explore their datasets while ensuring reproducibility and scalability in their workflows. Availability and implementationscprocess can be installed via GitHub (https://github.com/marusakod/scprocess) under the MIT license. Documentation, including setup instructions and tutorials on example datasets is available at https://marusakod.github.io/scprocess/.

The expanding scope of laboratory automation increasingly demands systems that can be tailored to specific experimental constraints, including footprint, timing, cost, and control. While open-source software has improved protocol flexibility, liquid-handling hardware itself remains largely closed, limiting the ability of academic and startup laboratories to build instruments around biological requirements rather than vendor defaults. Here, we present a fully open-source, purpose-built liquid-handling robot assembled from commercially available components and developed entirely in a research setting. The platform integrates open hardware, electronics, and a Python-based control stack compatible with PyLabRobot, exposing low-level motion dynamics and liquid-handling behaviors directly to experiment code. We validate the system using a high-throughput turbidostat workflow that requires rapid, closed-loop measurement and actuation to maintain microbial cultures at defined density setpoints. The robot sustains stable steady-state growth across approximately 200 cultures with heterogeneous growth dynamics. A replica build completed by two lab members in approximately one week confirms that the platform can be reproduced from its bill of materials and assembly guide. Its compact footprint and use of off-the-shelf components make it suitable for rapid, parallel deployment in settings such as public health emergencies or by distributed laboratories. Together, these results demonstrate that industry-class liquid handlers can be custom-built for specific experimental goals, establishing a blueprint for open, purpose-driven hardware development across research and industrial automation contexts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/709168v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1b2cb4eorg.highwire.dtl.DTLVardef@1418e8dorg.highwire.dtl.DTLVardef@f60618org.highwire.dtl.DTLVardef@a3d3b_HPS_FORMAT_FIGEXP M_FIG Open Liquid Handler (OLH) Design Goals. Left: Design goals for a purpose-built platform for time-sensitive, closed-loop biological workflows, emphasizing high-accuracy dosing (low variability liquid handling), rapid integrated measurement (plate deck and isolated workspace), customizable deck and peripheral options, compact footprint with high throughput, containment via an enclosed wet workspace for biosafety and sterility, and a replicable build using off-the-shelf OEM components with open design files. Right: Open Liquid Handler design and physical implementation, with aerial and front views highlighting the enclosed cabinet and the working envelope over a compact deck. C_FIG

Short-read Illumina sequencing of 10x Genomics single-nucleus multiome libraries captures only the 3 end of RNA transcripts, losing transcription start site (TSS) information. Here we demonstrate nanopore sequencing of 10x multiome libraries, which enables the profiling of full length transcripts. We show concordance with common short-read sequencing based workflows including successful genetic demultiplexing of nanopore data despite its higher error rate. We compare TSS identified using nanopore sequencing of multiome cDNA to those identified using a short-read 5 assay, and provide an optimized approach for the preprocessing of nanopore reads prior to TSS identification. We find that nanopore sequencing of multiome cDNA captures a median of 63% of the TSS detected by the 5 assay.

13C-metabolic flux analysis (13C-MFA) is a crucial technique that experimentally determines metabolic flux distribution. Although precision of each flux strongly depends on tracer labeling pattern, its optimization remains challenging. We developed an integrated platform, OpenMebius2, a graphical user interface (GUI)-based software for 13C-MFA that includes a tracer labeling pattern suggestion function to support subsequent experiments. The proposed function leverages metabolic flux distributions and their 95 % confidence intervals obtained using low-cost 13C-labeled substrates to evaluate hypothetical parallel labeling scenarios and predict improvements in flux estimation precision. Availability and implementationThis software runs on Linux, macOS, and Windows. The source code and binary files are available at https://github.com/metabolic-engineering/OpenMebius2 under the PolyForm Noncommercial License 1.0.0.

This protocol enables rapid CRISPR-Cas9 genome editing in Saccharomyces cerevisiae by replacing restriction/ligation guide cloning with PCR-based protospacer installation and seamless plasmid recircularization. It describes in silico HDR donor and SgRNA design, install guide sequences into cas9 plasmid by PCR and seamless assembly, plasmid cloning and sequence verification in E. coli, and LiAc/PEG co-transformation of yeast with Cas9-sgRNA plasmid plus HDR donor. The workflow selects yeast colonies on G418 and confirms edits by PCR and sequencing.

We present an isotropic 7.72 {micro}m/voxel post-mortem human brain dataset acquired using Hierarchical Phase-Contrast Tomography (HiP-CT) at the ESRF Extremely Brilliant Source, beamline BM18. This fills a critical gap between whole-brain MRI at 100 {micro}m resolution and serial-section histological reconstructions at 20 {micro}m or finer. HiP-CT contrast, derived from X-ray phase shifts, enables rich 3D visualisation of complex neuroanatomy including white-matter bundles, microvasculature, and sub-nuclei. We provide open-source workflows for online data exploration, subvolume download, segmentation, and reintegration of analyses into the full dataset. We demonstrate the potential of this resource by tracing vasculature over long distances, segmenting nuclei, and extracting whitematter orientations with 3D structure-tensor analysis. High-resolution human brain datasets are transformative for quantitative neuroanatomy, circuit mapping, and validation of clinical imaging; this openly available resource is a critical step for global access to next-generation multiscale brain imaging.

Lentiviral transduction of HEK293-derived expression cells provides a robust and scalable approach for large-scale protein production for structural and biochemical studies. Building on our previously reported platform, we introduce an improved workflow that decouples cell enrichment from target protein expression by enabling constitutive antibiotic selection of transduced cells prior to induction. The key advance is the use of orthogonal antibiotic-resistance cassettes to stringently enrich transduced cells, eliminate non-transduced cells, improve population homogeneity, and enable multi-vector co-selection for heteromeric assemblies and complexes. We provide two complementary transfer-vector suites. pHR-AB-CMV-TetO2 delivers maximal expression and supports inducible control in TetR-expressing lines while driving strong constitutive expression in non-TetR lines. pHR-AIO-AB ("all-in-one") encodes the transactivator, resistance marker, and gene of interest on a single construct to enable tightly controlled doxycycline-inducible expression in standard HEK293 lines, and is readily adaptable to other mammalian cell types. Both suites are available with puromycin, blasticidin, hygromycin, or zeocin markers, enabling straightforward co-infection and orthogonal multi-antibiotic selection of stable populations expressing multiple transgenes. They are well suited to demanding targets such as membrane proteins and multi-subunit assemblies. The protocol details the step-by-step generation of highly enriched, inducible HEK293 populations within 3-4 weeks.

Computational toxicology increasingly relies on evidence, high-throughput screening, predictive (Q)SAR, adverse outcome pathways (AOPs), physiologically based kinetic (PBK/PBPK) models, and exposure databases to support integrated approaches to testing and assessment (IATA). Yet the practical workflow remains fragmented across heterogeneous tools, data formats, and licensing regimes. Large language models (LLMs) can lower the interface barrier, but free-text interaction alone is insufficient for regulatory-grade science: it is difficult to audit, difficult to reproduce, and prone to overconfident errors. Here we introduce ToxMCP, a collection of Model Context Protocol (MCP) servers designed as a guardrailed, federated integration layer for reproducible computational toxicology. ToxMCP wraps toxicology-relevant capabilities, including chemical identity and regulatory context (EPA CompTox), rapid ADMET profiling (ADMETlab 3.0), mechanistic pathway retrieval and structuring (AOP knowledge services), quantitative read-across workflows (OECD QSAR Toolbox), and mechanistic PBPK simulation (Open Systems Pharmacology Suite), as typed tools with explicit inputs/outputs, provenance bundles, and policy hooks (e.g., applicability domain checks, critical-action confirmation, and role-based access control). We demonstrate how natural-language risk questions can be compiled into auditable tool invocations, returning mechanistic metrics such as tissue AUC/Cmax, sensitivity curves, and conservative points of departure. We further outline an evaluation protocol for measuring computational reproducibility, task throughput, and scientific utility across multi-tool toxicology tasks. ToxMCP reframes LLMs for toxicology from conversational summarizers into accountable orchestrators of established scientific kernels, enabling faster iteration while preserving the evidentiary structure expected in regulatory and academic settings. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/703989v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1b8ccceorg.highwire.dtl.DTLVardef@18e0703org.highwire.dtl.DTLVardef@16e87feorg.highwire.dtl.DTLVardef@1a24f13_HPS_FORMAT_FIGEXP M_FIG C_FIG

Rigorous experimental design, including formal power analysis, is a cornerstone of reproducible RNA sequencing (RNA-seq) research. The design of RNA-seq experiments requires computing the minimum sample number required to identify an effect of a particular size at a predefined significance level. Ideally, the statistical test used for the analysis of experimental data should match the test used for sample size determination; however, few tools use the assumptions of the popular differential expression testing framework DESeq2, and most opt for simulation-based rather than analytical approaches. Grounded in the DESeq2 model framework, we derive sample size requirements for both single-cell and bulk RNA-seq experiments delivered as a web-based tool for power analysis, DEPower, available at https://poweranalysis-fb.streamlit.app/ that makes rigorous RNA-seq study design accessible to all researchers.

Extrachromosomal arrays are unique chromosome-like structures created from DNA injected into the C. elegans germline. Arrays are easy to create and allow for high expression of multiple transgenes. They are, however, unstable unless integrated into a chromosome. Current methods for integration, such as X-rays and CRISPR, damage DNA and are low-efficiency. Here, we demonstrate that the viral integrase PhiC31, which mediates a non-mutagenic recombination between short attB and attP sequences, can be used for extremely efficient and targeted integration of arrays. In this method, a transgene, a selectable marker, and attP sites are injected into the gonad of a strain that (1) has an attB site in its genome, and (2) expresses PhiC31 in its germline. F1 extrachromosomal arrays are cloned, grown for multiple generations with selection, and then screened for homozygous array integrations. The procedure is simple, requires less time than screening for extrachromosomal arrays, and arrays can be screened for transgene function after stable integration. Arrays that transmit are integrated by PhiC31 with 50-95% efficiency, allowing for the isolation of many unique integrants from a single injection. Arrays can also be integrated at fluorescent landing pads and arbitrary sites in the genome. Using nanopore sequencing, we show that three new integrated arrays are between 1.6 and 18 megabases in length, assemble with large repeats, and can contain hundreds of copies of injected transgenes. We have built a collection of strains and plasmids to enable array integration at multiple sites in the genome using various selections. PhiC1-mediated Integration of Arrays of Transgenes (PhiAT) will allow C. elegans researchers to shift from using unstable extrachromosomal arrays to directly integrating arrays.

Efficient protein synthesis in eukaryotic cells typically requires a 5' cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here we describe a cell-free protocol to quantitatively assess IRES-mediated translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of IRES activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency. Key featuresO_LIStringent in vitro workflow from DNA template preparation through RNA synthesis and protein synthesis to reporter readout, including quality controls. C_LIO_LIEvaluation of IRES-driven translation suitable for testing combinations of IRES and CDS. C_LIO_LItranslation analysis without radioactive labeling. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/716985v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@417649org.highwire.dtl.DTLVardef@1bcd186org.highwire.dtl.DTLVardef@15fecb3org.highwire.dtl.DTLVardef@acdf8d_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractPipeline for the production and evaluation of IRES-firefly luciferase constructs using wheat germ extract. (1-4) Preparation: IRES-firefly luciferase constructs are amplified in E. coli and isolated from bacterial cells. Plasmids are linearized to prepare for in vitro transcription. (5-6) Transcript synthesis and verification: In vitro transcription is followed by electrophoretic validation to confirm integrity and correct molecular weight. (7-8) Translation and detection: Translation is executed in wheat germ extract and quantified by measuring reporter activity in a luminometer.

The empty drops in single-cell sequencing experiments are an underexplored resource. As such, they present a substrate to ask questions orthogonal to standard single-cell sequencing workflows, calibrate statistical models using simple internal controls, and detect technical outliers which would be otherwise challenging to distinguish from real biology. In this case study, we report a relatively simple procedure to detect sequencing artifacts and make recommendations to reduce the risk of erroneous quantifications. In addition, we report the surprising abundance and co-expression of mRNA coding for neuropeptide-related genes in the empty drops, possibly reflecting underlying physiology.

Building a high-fidelity computational model of the whole human brain will require preservation of the ultrastructure at the level of the entire organ, post-mortem. For such a model to reflect as closely as possible the brain in the living state, artifacts that arise during both the agonal phase and the postmortem interval will need to be minimized. This is potentially feasible if a terminally-ill patient donates their brain for research following physician-assisted death. In this paper, we modify a protocol for aldehyde-stabilized cryopreservation to make it compatible with physician-assisted death. We use pigs as a model, which resemble humans in cardiovascular and brain anatomy. Aldehyde-stabilized cryopreservation was designed to provide superior structural preservation of brains of any size, across all anatomical scales, compatible with diverse analytical assays and long-term storage without ultrastructural degradation. We demonstrate, with light microscopy and volume electron microscopy, that our brain preservation protocol results in connectomically traceable whole brains and propose an economically feasible storage modality that is expected to maintain stability of ultrastructure and macromolecules in the brain even for thousands of years. Most importantly, we establish that 14 min is the approximate length of the perfusability window--the time after the cardiac arrest during which blood washout needs to be initiated so that the brain ultrastructure is preserved.

Cellular lipids shape health and disease through specific protein interactions, yet lipid-protein networks remain poorly defined. Despite rapid advances in functional lipid probes, the field still lacks a practical, dedicated protocol for conducting lipid-protein interaction studies. We describe detailed methods for determining lipid interactomes from cells using multifunctionalized lipid derivatives. We provide protocols that detail 1) how to treat cells with lipid derivatives and perform photochemistry to obtain lipid-protein conjugates; 2) how to perform click chemistry with a fluorophore and observe lipid-protein conjugates by in-gel fluorescence; 3) how to perform click chemistry with azide beads and prepare lipid-protein conjugates for proteomic analysis. We provide context on important parameters for each step and include guidelines for controls, as well as suggestions for troubleshooting based on common problems encountered during the preparation of this protocol. This protocol enables mapping lipid interactomes across diverse biological systems. The entire workflow from cell treatment to complete proteomic sample preparation requires [~]15 hours over four days, depending on the type of experimental readout (in-gel fluorescence or proteomics), and the usage of pause points. Practitioners are expected to be familiar with standard biochemical techniques, such as sterile sample handling and tissue culture and gel electrophoresis. Additional skills are needed for mass spectrometric analysis, and collaboration with a proteomics core facility is recommended. The described procedures uniquely enable the identification of the protein interactors (the interactome) of select lipid species, providing for a major shift in the characterization of the biological roles of lipids in cellular systems.