Project description:The analysis of single cell proteomes has recently become a viable complement to transcript and genomics studies. Proteins are the main driver of cellular functionality and mRNA levels are often an unreliable proxy of such. Therefore, the global analysis of the proteome is essential to study cellular identities. Both multiplexed and label-free mass spectrometry-based approaches with single cell resolution have lately attributed surprising heterogeneity to believed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lacks behind. Here, we introduce the proteoCHIP, a universal option for single cell proteomics sample preparation at surprising sensitivity and throughput. The automated processing using a commercial system combining single cell isolation and picoliter dispensing, the cellenONE®, allows to reduce final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error prone manual sample handling and overcoming evaporation. With this specialized workflow we achieved around 1,000 protein groups per analytical run at remarkable reporter ion signal to noise while reducing or eliminating the carrier proteome. We identified close to 2,000 protein groups across 158 multiplexed single cells from two highly similar human cell types and clustered them based on their proteome. In-depth investigation of regulated proteins readily identified one of the main drivers for tumorigenicity in this cell type. Our workflow is compatible with all labeling reagents, can be easily adapted to custom workflows and is a viable option for label-free sample preparation. The specialized proteoCHIP design allows for the direct injection of label-free single cells via a standard autosampler resulting in the recovery of 30% more protein groups compared to samples transferred to PEG coated vials. We therefore are confident that our versatile, sensitive, and automated sample preparation workflow will be easily adoptable by non-specialized groups and will drive biological applications of single cell proteomics.
Project description:Recent advances in stem cell technology have led to the development of three-dimensional (3D) culture systems called organoids, which have fueled hopes to bring about the next generation of more physiologically relevant high throughput screens (HTS). However, the adaptation of established organoid protocols for HTS applications has so far been elusive. Here, we present a fully scalable, HTS-compatible workflow for the automated generation, maintenance, whole mount staining, clearing, and optical analysis of human neural organoids generated from neural precursor cells in a standard 96-well format. By combining organoid generation and analysis steps in an automated fashion, we can perform quantitative whole-organoid high content imaging with single cell resolution. The resulting organoids are highly homogeneous with regard to their morphology, size, global gene expression, cellular composition, and structure. Calcium imaging suggests organoid-wide synchronized functional coupling. The scalability of our approach has the potential to form the basis for 3D tissue-based screening in a variety of applications including drug development, toxicology studies, and disease modeling.
Project description:Although tandem mass tag (TMT)-based isobaric labeling has become a powerful technique for multiplexed protein quantitation, it has not been easy to automate the workflow for widespread adoption. This is because preparation of TMT labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction and alkylation to tryptic digestion, desalting, labeling with TMT reagents and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic especially with large-scale studies such as clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for automated proteomics workflows for TMT-labeling experiments with manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using the automated platform and a conventional manual protocol. Single shot LC-MS/MS analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiencies of tryptic digestion, alkylation and TMT labeling were similar both in manual and automated process. In addition, comparison of quantitation accuracy and precision showed similar performance in automated workflow compared to manual sample preparation. Overall, we demonstrated that the automated platform performs at a level similar to manual process in TMT-based proteomics. We expect that the automated workflow will increasingly replace manual work and be applied to large-scale TMT-baed studies providing robust results and high sample throughput.
Project description:Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies but protein extraction and subsequent sample processing steps have shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows and analysis pipelines yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for Automated Sonication-free Acid-assisted Proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens achieving similar proteome coverage as established methods using time in equipment-heavy sonication-based methods at reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.
Project description:Single cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables and reagents for sample processing and separations, which limits accessibility of SCP to a small number of specialized laboratories. Commercial platforms have become available for SCP cell isolation and sample preparation, but the high cost of these platforms and the technical expertise required for their operation place them out of reach of many interested laboratories. Here, we assessed the new HP D100 Single Cell Dispenser for label-free SCP. The low-cost instrument proved highly accurate and reproducible for dispensing reagents in the 200 nL to 2 µL range. We used the HP D100 to isolate and prepare single cells for SCP within 384-well PCR plates. When the well plates were immediately centrifuged following cell dispensing and again after reagent dispensing, we found that ~97% of wells that were identified in the instrument software as containing a single cell indeed provided proteome coverage expected of a single cell. The D100 Single Cell Dispenser combined with one-step sample processing provides a very rapid easy-to-use workflow for SCP with no reduction in proteome coverage relative to a nanowell-based workflow. The commercial well plates also facilitate autosampling with commercial instrumentation. Single cell samples were analyzed using home-packed 30-µm-i.d. nanoLC columns as well as commercially available 50-µm-i.d. columns. The commercial columns led to identification of ~35% fewer identified proteins. However, combined with the well plate-based preparation platform the presented workflow provides fully commercial and relatively low cost alternative for SCP sample preparations and separations, which should greatly broaden accessibility of SCP to other laboratories.
Project description:Advances in several key technologies, including MHC peptidomics, has helped fuel our understanding of basic immune regulatory mechanisms and identify T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. This multi-step analytical process remains challenging, and throughput and reproducibility are paramount for rapidly characterizing multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines, can be enriched in a semi-automated fashion on reusable, dry-storage, customized antibody cartridges. TOMAHAQ, a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation.
Project description:Transcription factor binding locations by ChIP followed by high throughput sequencing. To build and validate an automated Chromatin Immunoprecipitation and high throughput Illumina sequencing pipeline