A Universal and High-Throughput Proteomics Sample Preparation Platform

MassSpecPreppy-An end-to-end solution for automated protein concentration determination and flexible sample digestion for proteomics applications

In proteomics, fast, efficient, and highly reproducible sample preparation is of utmost importance, particularly in view of fast scanning mass spectrometers enabling analyses of large sample series. To address this need, we have developed the web application MassSpecPreppy that operates on the open science OT-2 liquid handling robot from Opentrons. This platform can prepare up to 96 samples at once, performing tasks like BCA protein concentration determination, sample digestion with normalization, reduction/alkylation and peptide elution into vials or loading specified peptide amounts onto Evotips in an automated and flexible manner. The performance of the developed workflows using MassSpecPreppy was compared with standard manual sample preparation workflows. The BCA assay experiments revealed an average recovery of 101.3% (SD: ± 7.82%) for the MassSpecPreppy workflow, while the manual workflow had a recovery of 96.3% (SD: ± 9.73%). The species mix used in the evaluation experiments showed that 94.5% of protein groups for OT-2 digestion and 95% for manual digestion passed the significance thresholds with comparable peptide level coefficient of variations. These results demonstrate that MassSpecPreppy is a versatile and scalable platform for automated sample preparation, producing injection-ready samples for proteomics research.

RapidAIM 2.0: a high-throughput assay to study functional response of human gut microbiome to xenobiotics

Aim: Our gut microbiome has its own functionalities which can be modulated by various xenobiotic and biotic components. The development and application of a high-throughput functional screening approach of individual gut microbiomes accelerates drug discovery and our understanding of microbiome-drug interactions. We previously developed the rapid assay of individual microbiome (RapidAIM), which combined an optimized culturing model with metaproteomics to study gut microbiome responses to xenobiotics. In this study, we aim to incorporate automation and multiplexing techniques into RapidAIM to develop a high-throughput protocol. Methods: To develop a 2.0 version of RapidAIM, we automated the protein analysis protocol, and introduced a tandem mass tag (TMT) multiplexing technique. To demonstrate the typical outcome of the protocol, we used RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows. Results: We describe the protocol of RapidAIM 2.0 with extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, sample processing, metaproteomics measurement, and data analysis. The analysis depth of 5,014 ± 142 protein groups per multiplexed sample was achieved. A test on five biobanking methods using RapidAIM 2.0 showed the minimal effect of sample processing on live microbiota functional responses to kestose. Conclusions: Depth and reproducibility of RapidAIM 2.0 are comparable to previous manual label-free metaproteomic analyses. In the meantime, the protocol realizes culturing and sample preparation of 320 samples in six days, opening the door to extensively understanding the effects of xenobiotic and biotic factors on our internal ecology.

Heat 'n Beat: A Universal High-Throughput End-to-End Proteomics Sample Processing Platform in under an Hour

Proteomic analysis by mass spectrometry of small (≤2 mg) solid tissue samples from diverse formats requires high throughput and comprehensive proteome coverage. We developed a nearly universal, rapid, and robust protocol for sample preparation, suitable for high-throughput projects that encompass most cell or tissue types. This end-to-end workflow extends from original sample to loading the mass spectrometer and is centered on a one-tube homogenization and digestion method called Heat 'n Beat (HnB). It is applicable to most tissues, regardless of how they were fixed or embedded. Sample preparation was divided into separate challenges. The initial sample washing and final peptide cleanup steps were adapted to three tissue sources: fresh frozen (FF), optimal cutting temperature (OCT) compound embedded (FF-OCT), and formalin-fixed paraffin embedded (FFPE). Third, for core processing, tissue disruption and lysis were decreased to a 7 min heat and homogenization treatment, and reduction, alkylation, and proteolysis were optimized into a single step. The refinements produced near doubled peptide yield when compared to our earlier method ABLE delivered a consistently high digestion efficiency of 85-90%, reported by ProteinPilot, and required only 38 min for core processing in a single tube, with the total processing time being 53-63 min. The robustness of HnB was demonstrated on six organ types, a cell line, and a cancer biopsy. Its suitability for high-throughput applications was demonstrated on a set of 1171 FF-OCT human cancer biopsies, which were processed for end-to-end completion in 92 h, producing highly consistent peptide yield and quality for over 3513 MS runs.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

Enhancing docosahexaenoic acid production in Aurantiochytrium species using atmospheric and room temperature plasma mutagenesis and comprehensive multi-omics analysis

Aurantiochytrium sp. belongs to marine heterotrophic single-cell protist, which is an important decomposer in marine ecosystem. Aurantiochytrium sp. has gained notoriety because of its ability to accumulate high-value docosahexaenoic acid (DHA), but the key factors of DHA synthesis were unclear at present. In this study, Atmospheric and Room Temperature Plasma technology was applied to the mutagenic breeding of Aurantiochytrium sp., and transcriptomics and proteomics were adopted to analyze the DHA-biosynthesis mechanism. According to the growth and DHA accumulation profiles, the mutant strain Aurantiochytrium sp. R2A35 was selected. The DHA content in total lipids was greatly improved from 49.39 % of the wild strain R2 to 63.69 % of the mutant strain. Moreover, the DHA content in the biomass of Aurantiochytrium sp. R2A35 as 39.72 % was the highest DHA productivity reported so far. The differentially expressed genes distinguished from transcriptome and the TMT-identified differential proteins distinguished from proteome confirmed that the expression of acetyl-CoA carboxylase and ketoacyl reductase was up-regulated by 4.78-fold and 6.95-fold, respectively and the fatty acid synthase was concurrently down-regulated by 2.79-fold, so that more precursor was transported to the polyketide synthase pathway, thereby increasing the DHA yield in Aurantiochytrium sp. R2A35. This research would provide reference for the DHA metabolism process and contribute to the understanding of the decomposer - Aurantiochytrium sp. in marine ecosystems.

Methotrexate-based PROTACs as DHFR-specific chemical probes

Methotrexate (MTX) is a tight-binding dihydrofolate reductase (DHFR) inhibitor, used as both an antineoplastic and immunosuppressant therapeutic. MTX, like folate undergoes folylpolyglutamate synthetase-mediated γ-glutamylation, which affects cellular retention and target specificity. Mechanisms of MTX resistance in cancers include a decrease in MTX poly-γ-glutamylation and an upregulation of DHFR. Here, we report a series of potent MTX-based proteolysis targeting chimeras (PROTACs) to investigate DHFR degradation pharmacology and one-carbon biochemistry. These on-target, cell-active PROTACs show proteasome- and E3 ligase-dependent activity, and selective degradation of DHFR in multiple cancer cell lines. By comparison, treatment with MTX increases cellular DHFR protein expression. Importantly, these PROTACs produced distinct, less-lethal phenotypes compared to MTX. The chemical probe set described here should complement conventional DHFR inhibitors and serve as useful tools for studying one-carbon biochemistry and dissecting complex polypharmacology of MTX and related drugs. Such compounds may also serve as leads for potential autoimmune and antineoplastic therapeutics.

Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run.

High-Throughput Screening to Advance In Vitro Toxicology: Accomplishments, Challenges, and Future Directions

Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.

Reaping the benefits of liquid handlers for high-throughput gene expression profiling in a marine model invertebrate

BACKGROUND

Modern high-throughput technologies enable the processing of a large number of samples simultaneously, while also providing rapid and accurate procedures. In recent years, automated liquid handling workstations have emerged as an established technology for reproducible sample preparation. They offer flexibility, making them suitable for an expanding range of applications. Commonly, such approaches are well-developed for experimental procedures primarily designed for cell-line processing and xenobiotics testing. Conversely, little attention is focused on the application of automated liquid handlers in the analysis of whole organisms, which often involves time-consuming laboratory procedures.

RESULTS

Here, we present a fully automated workflow for all steps, from RNA extraction to real-time PCR processing, for gene expression quantification in the ascidian marine model Ciona robusta. For procedure validation, we compared the results obtained with the liquid handler with those of the classical manual procedure. The outcome revealed comparable results, demonstrating a remarkable time saving particularly in the initial steps of sample processing.

CONCLUSIONS

This work expands the possible application fields of this technology to whole-body organisms, mitigating issues that can arise from manual procedures. By minimizing errors, avoiding cross-contamination, decreasing hands-on time and streamlining the procedure, it could be employed for large-scale screening investigations.

Automation to Enable High-Throughput Chemical Proteomics

Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

In vivo quantitative high-throughput screening for drug discovery and comparative toxicology

Quantitative high-throughput screening (qHTS) pharmacologically evaluates chemical libraries for therapeutic uses, toxicological risk and, increasingly, for academic probe discovery. Phenotypic high-throughput screening assays interrogate molecular pathways, often relying on cell culture systems, historically less focused on multicellular organisms. Caenorhabditis elegans has served as a eukaryotic model organism for human biology by virtue of genetic conservation and experimental tractability. Here, a paradigm enabling C. elegans qHTS using 384-well microtiter plate laser-scanning cytometry is described, in which GFP-expressing organisms revealing phenotype-modifying structure-activity relationships guide subsequent life-stage and proteomic analyses, and Escherichia coli bacterial ghosts, a non-replicating nutrient source, allow compound exposures over two life cycles, mitigating bacterial overgrowth complications. We demonstrate the method with libraries of anti-infective agents, or substances of toxicological concern. Each was tested in seven-point titration to assess the feasibility of nematode-based in vivo qHTS, and examples of follow-up strategies were provided to study organism-based chemotype selectivity and subsequent network perturbations with a physiological impact. We anticipate that this qHTS approach will enable analysis of C. elegans orthologous phenotypes of human pathologies to facilitate drug library profiling for a range of therapeutic indications.

Separation methods in single-cell proteomics: RPLC or CE?

Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.

Proteomic Analysis of Adenovirus 5 by UHPLC-MS/MS: Development of a Robust and Reproducible Sample Preparation Workflow

Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses double-stranded DNA. These proteins are the main components and key players in initial stages of infection by the virus particles, so their heterogeneity and content must be evaluated to ensure product and process consistency. Peptide mapping can provide detailed information on these proteins, e.g., their amino acid sequences and post-translational modifications (PTMs), which is crucial for the development and optimization of the manufacturing processes. However, sample preparation remains the main bottleneck for successful proteomic analysis of the viral proteins (VPs) of AdVs due to their low concentrations and vast stoichiometric ranges. To address this problem, we have developed a fast and efficient protocol for preparing samples for proteomic analysis of VPs of AdV5 that requires no cleaning step prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach enabled identification of 92% of amino acids in AdV5 VPs on average and quantification of 53 PTMs in a single LC-MS/MS experiment using trypsin protease. The data obtained demonstrate the method's potential utility for supporting the development of novel AdV-based gene therapy products (GTPs).

Integrated and High-Throughput Approach for Sensitive Analysis of Tyrosine Phosphoproteome

Tyrosine phosphorylation (pTyr) regulates various signaling pathways under normal and cancerous states. Due to their low abundance and transient and dynamic natures, systematic profiling of pTyr sites is challenging. Antibody and engineered binding domain-based approaches have been well applied to pTyr peptide enrichment. However, traditional methods have the disadvantage of a long sample preparation process, which makes them unsuitable for processing limited amount of samples, especially in a high-throughput manner. In this study we developed a 96-well microplate-based approach to integrate all the sample preparation steps starting from cell culture to MS-compatible pTyr peptide enrichment in three consecutive 96-well microplates. By assembling an engineered SH2 domain onto a microplate, nonspecific adsorption of phosphopeptides is greatly reduced, which allows us to remove the Ti-IMAC purification and three C18 desalting steps (after digestion, pTyr enrichment, and Ti-IMAC purification) and, therefore, greatly simplifies the entire pTyr peptide enrichment workflow, especially when processing a large number of samples. Starting with 96-well microplate-cultured, pervanadate-stimulated cells, our approach could enrich 21% more pTyr sites than the traditional serial pTyr enrichment approach and showed good sensitivity and reproducibility in the range of 200 ng to 200 μg peptides. Importantly, we applied this approach to profile tyrosine kinase inhibitor-mediated EGFR signaling pathway and could well differentiate the distinct response of different pTyr sites. Collectively, the integrated 96-well microplate-based approach is valuable for profiling pTyr sites from limited biological samples and in a high-throughput manner.

Infrared Laser Ablation Microsampling for Small Volume Proteomics

Infrared (IR) laser ablation was used to remove localized tissue regions from which proteins were extracted and processed with a low volume sample preparation workflow for bottom-up proteomics by liquid chromatography tandem mass spectrometry (LC-MS/MS). A polytetrafluoroethylene (PTFE) coated glass slide with 2 mm diameter microwells was used to capture ablated rat brain tissue for in situ protein digestion with submicroliter solution volumes. The resulting peptides were analyzed with LC-MS/MS for protein identification and label-free quantification. The method was used to identify an average of 600, 1350, and 1900 proteins from ablation areas of 0.01, 0.04, and 0.1 mm², respectively, from a 50 μm thick rat brain tissue section. Differential proteomics of 0.01 mm² regions captured from cerebral cortex and corpus callosum was accomplished to demonstrate the capabilities of the approach.