Development and evaluation of a micro- and nanoscale proteomic sample preparation method

Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics

Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.

Comprehensive Proteome Profiling of a Xanthomonas campestris pv. Campestris B100 Culture Grown in Minimal Medium with a Specific Focus on Nutrient Consumption and Xanthan Biosynthesis

Xanthan, a bacterial polysaccharide, is widespread in industrial applications, particularly as a food additive. However, little is known about the process of xanthan synthesis on the proteome level, even though Xanthomonas campestris is frequently used for xanthan fermentation. A label-free LC-MS/MS method was employed to study the protein changes during xanthan fermentation in minimal medium. According to the reference database, 2416 proteins were identified, representing 54.75 % of the proteome. The study examined changes in protein abundances concerning the growth phase and xanthan productivity. Throughout the experiment, changes in nitrate concentration appeared to affect the abundance of most proteins involved in nitrogen metabolism, except Gdh and GlnA. Proteins involved in sugar nucleotide metabolism stay unchanged across all growth phases. Apart from GumD, GumB, and GumC, the gum proteins showed no significant changes throughout the experiment. GumD, the first enzyme in the assembly of the xanthan-repeating unit, peaked during the early stationary phase but decreased during the late stationary phase. GumB and GumC, which are involved in exporting xanthan, increased significantly during the stationary phase. This study suggests that a potential bottleneck for xanthan productivity does not reside in the abundance of proteins directly involved in the synthesis pathways.

Recruitment of BAG2 to DNAJ-PKAc scaffolds promotes cell survival and resistance to drug-induced apoptosis in fibrolamellar carcinoma

The DNAJ-PKAc fusion kinase is a defining feature of fibrolamellar carcinoma (FLC). FLC tumors are notoriously resistant to standard chemotherapies, with aberrant kinase activity assumed to be a contributing factor. By combining proximity proteomics, biochemical analyses, and live-cell photoactivation microscopy, we demonstrate that DNAJ-PKAc is not constrained by A-kinase anchoring proteins. Consequently, the fusion kinase phosphorylates a unique array of substrates, including proteins involved in translation and the anti-apoptotic factor Bcl-2-associated athanogene 2 (BAG2), a co-chaperone recruited to the fusion kinase through association with Hsp70. Tissue samples from patients with FLC exhibit increased levels of BAG2 in primary and metastatic tumors. Furthermore, drug studies implicate the DNAJ-PKAc/Hsp70/BAG2 axis in potentiating chemotherapeutic resistance. We find that the Bcl-2 inhibitor navitoclax enhances sensitivity to etoposide-induced apoptosis in cells expressing DNAJ-PKAc. Thus, our work indicates BAG2 as a marker for advanced FLC and a chemotherapeutic resistance factor in DNAJ-PKAc signaling scaffolds.

Systems biology of industrial oxytetracycline production in Streptomyces rimosus: the secrets of a mutagenized hyperproducer

BACKGROUND

Oxytetracycline which is derived from Streptomyces rimosus, inhibits a wide range of bacteria and is industrially important. The underlying biosynthetic processes are complex and hinder rational engineering, so industrial manufacturing currently relies on classical mutants for production. While the biochemistry underlying oxytetracycline synthesis is known to involve polyketide synthase, hyperproducing strains of S. rimosus have not been extensively studied, limiting our knowledge on fundamental mechanisms that drive production.

RESULTS

In this study, a multiomics analysis of S. rimosus is performed and wild-type and hyperproducing strains are compared. Insights into the metabolic and regulatory networks driving oxytetracycline formation were obtained. The overproducer exhibited increased acetyl-CoA and malonyl CoA supply, upregulated oxytetracycline biosynthesis, reduced competing byproduct formation, and streamlined morphology. These features were used to synthesize bhimamycin, an antibiotic, and a novel microbial chassis strain was created. A cluster deletion derivative showed enhanced bhimamycin production.

CONCLUSIONS

This study suggests that the precursor supply should be globally increased to further increase the expression of the oxytetracycline cluster while maintaining the natural cluster sequence. The mutagenized hyperproducer S. rimosus HP126 exhibited numerous mutations, including large genomic rearrangements, due to natural genetic instability, and single nucleotide changes. More complex mutations were found than those typically observed in mutagenized bacteria, impacting gene expression, and complicating rational engineering. Overall, the approach revealed key traits influencing oxytetracycline production in S. rimosus, suggesting that similar studies for other antibiotics could uncover general mechanisms to improve production.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

STAT3/LKB1 controls metastatic prostate cancer by regulating mTORC1/CREB pathway

Prostate cancer (PCa) is a common and fatal type of cancer in men. Metastatic PCa (mPCa) is a major factor contributing to its lethality, although the mechanisms remain poorly understood. PTEN is one of the most frequently deleted genes in mPCa. Here we show a frequent genomic co-deletion of PTEN and STAT3 in liquid biopsies of patients with mPCa. Loss of Stat3 in a Pten-null mouse prostate model leads to a reduction of LKB1/pAMPK with simultaneous activation of mTOR/CREB, resulting in metastatic disease. However, constitutive activation of Stat3 led to high LKB1/pAMPK levels and suppressed mTORC1/CREB pathway, preventing mPCa development. Metformin, one of the most widely prescribed therapeutics against type 2 diabetes, inhibits mTORC1 in liver and requires LKB1 to mediate glucose homeostasis. We find that metformin treatment of STAT3/AR-expressing PCa xenografts resulted in significantly reduced tumor growth accompanied by diminished mTORC1/CREB, AR and PSA levels. PCa xenografts with deletion of STAT3/AR nearly completely abrogated mTORC1/CREB inhibition mediated by metformin. Moreover, metformin treatment of PCa patients with high Gleason grade and type 2 diabetes resulted in undetectable mTORC1 levels and upregulated STAT3 expression. Furthermore, PCa patients with high CREB expression have worse clinical outcomes and a significantly increased risk of PCa relapse and metastatic recurrence. In summary, we have shown that STAT3 controls mPCa via LKB1/pAMPK/mTORC1/CREB signaling, which we have identified as a promising novel downstream target for the treatment of lethal mPCa.

Dataset on the proteomic response during ferroptosis induction via tamoxifen induced GPX4 KO in mouse embryonic fibroblasts

Ferroptosis is a type of programmed cell death distinct from apoptosis and necroptosis that plays an essential role in pathophysiological conditions such as neurodegenerative diseases and tumorigenesis. Massive lipid oxidation in an iron-dependent manner is a hallmark of ferroptosis.This modality of cell death is also characterized by perturbation of several metabolic pathways, predominantly fatty acid metabolism, thiol metabolism, iron homeostasis and the mevalonate pathway. We aimed to acquire data from different timepoints of ferroptotic death in order to get information about the primary and delayed phases of the ferroptotic response. For this purpose, we used model Pfa1 cells, which are 4-OH-TAM-inducible Gpx4^-/- mouse immortalized fibroblasts [1]. GPX4 is one of the main intracellular ferroptosis regulators and inhibiting it is a classic approach to induce ferroptosis. Measuring protein fold changes at different ferroptotic stages and in nontreated Pfa1 cells could give useful information on the activation of genes involved in ferroptosis and non-genomic protein regulation during ferroptotic progression. Bottom-up proteomic data were acquired from samples obtained 24 and 48 hours after genetic induction of ferroptosis. Chromato-mass spectra were registered in DDA mode and are suitable for further label-free quantification. These data might be a valuable proteome basis for further investigation of ferroptosis and complement other available omics.

Advances in Mass Spectrometry-Based Single Cell Analysis

Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.

ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been 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 expensive sonicators, resulting in 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.

SpinTip: A Simple, Robust, and Versatile Preanalytical Method for Microscale Suspension Cell Proteomics

Sample loss and contamination are critical preanalytical pitfalls in microscale proteomic applications of nonadhering cells. Common assays and workflows are not easily adoptable to microscale sample sizes of suspension cells due to inadvertent sample loss. This impedes preanalytical experimental manipulation of limited suspension cell samples for microscale proteomics applications, such as encountered for primary human materials. Here, we describe and test a simple manual batch technique for single-step 100-fold concentration of scarce numbers of diluted suspension cells (down to 5000 cells) by volume reduction, facilitating microscale experiments with suspension cells. Pipette tips with heat-sealed orifices (SpinTips) are manufactured within 1 min and serve as versatile microcentrifugation vessels from which supernatant can be aspirated with minimal cell loss. A residual volume of approximately 3 μL can be achieved without visualization of the cell pellet. The results show that SpinTips enable the concentration, medium exchange, washing, and culture of highly limited amounts of suspension cells for functional manipulation and microscale proteomics and are readily incorporated into standard workflows. The application is illustrated by profiling ex vivo responses of primary acute myeloid leukemia (AML) cells from one AML patient to daunorubicin (DNR) to a depth of 3462 quantified proteins with excellent repeatability.

Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting

Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.

In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm

Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 μm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 μm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.

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.

Synthetic Soil Aggregates: Bioprinted Habitats for High-Throughput Microbial Metaphenomics

The dynamics of microbial processes are difficult to study in natural soil, owing to the small spatial scales on which microorganisms operate and to the opacity and chemical complexity of the soil habitat. To circumvent these challenges, we have created a 3D-bioprinted habitat that mimics aspects of natural soil aggregates while providing a chemically defined and translucent alternative culturing method for soil microorganisms. Our Synthetic Soil Aggregates (SSAs) retain the porosity, permeability, and patchy resource distribution of natural soil aggregates—parameters that are expected to influence emergent microbial community interactions. We demonstrate the printability and viability of several different microorganisms within SSAs and show how the SSAs can be integrated into a multi-omics workflow for single SSA resolution genomics, metabolomics, proteomics, lipidomics, and biogeochemical assays. We study the impact of the structured habitat on the distribution of a model co-culture microbial community and find that it is significantly different from the spatial organization of the same community in liquid culture, indicating a potential for SSAs to reproduce naturally occurring emergent community phenotypes. The SSAs have the potential as a tool to help researchers quantify microbial scale processes in situ and achieve high-resolution data from the interplay between environmental properties and microbial ecology.

Analysis of Gum proteins involved in xanthan biosynthesis throughout multiple cell fractions in a "single-tube"

Xanthomonas is a phytopathogenic bacterium and of industrial interest due to its capability to produce xanthan, used as a thickener and emulsifier in the food and non-food industry. Until now, proteome analyses of Xcc lacking a detailed view on the proteins involved in xanthan biosynthesis. The proteins involved in the biosynthesis of this polysaccharide are located near, in or at the cell membrane. This study aims to establish a robust and rapid protocol for a comprehensive proteome analysis of Xcc strains, without the need to isolate different cell fractions. Therefore, a method for the analysis of the whole cell proteome was compared to the isolation of specific fractions regarding the total number of identified proteins, the overlap, and the differences between the approaches. The whole cell proteome analysis with extended peptide separation methods resulted in more than 3254 identified proteins covering 73.1% of the whole proteome. The protocol was used to study xanthan production in a label-free quantification approach. Expression profiles of 8 Gum proteins were compared between the stationary and logarithmic growth phase. Differential expression levels within the operon structure indicate a complex regulatory mechanism for xanthan biosynthesis. Data are available via ProteomeXchange with identifier PXD027261. SIGNIFICANCE: Bacteria are metabolite factories with a wide variety of natural products. Thus, proteome analyses play a crucial role to understand the biological processes within a cell behind the biosynthesis of those metabolites. Proteins involved in the biosynthesis of secreted products are often organised on, in or around the membrane allowing metabolite channelling. Experiments targeting those biosynthesis pathways on protein level often require the analysis of multiple cell fractions like cytosolic, inner, and outer membrane. This is time consuming and demands different protocols. The protocol presented here is a rapid and robust solution to study biosynthetic pathways of biological or biotechnological interest in a single approach on protein level, where gene products are partitioned across multiple cell fractions. The use of a single method also simplifies the comparison of different experiments, for example, production vs. nonproduction conditions.

Proteomics: Concepts and applications in human medicine

Proteomics is the complete evaluation of the function and structure of proteins to understand an organism’s nature. Mass spectrometry is an essential tool that is used for profiling proteins in the cell. However, biomarker discovery remains the major challenge of proteomics because of their complexity and dynamicity. Therefore, combining the proteomics approach with genomics and bioinformatics will provide an understanding of the information of biological systems and their disease alteration. However, most studies have investigated a small part of the proteins in the blood. This review highlights the types of proteomics, the available proteomic techniques, and their applications in different research fields.

KiRNet: Kinase-centered network propagation of pharmacological screen results

The ever-increasing size and scale of biological information have popularized network-based approaches as a means to interpret these data. We develop a network propagation method that integrates kinase-inhibitor-focused functional screens with known protein-protein interactions (PPIs). This method, dubbed KiRNet, uses an a priori edge-weighting strategy based on node degree to establish a pipeline from a kinase inhibitor screen to the generation of a predictive PPI subnetwork. We apply KiRNet to uncover molecular regulators of mesenchymal cancer cells driven by overexpression of Frizzled 2 (FZD2). KiRNet produces a network model consisting of 166 high-value proteins. These proteins exhibit FZD2-dependent differential phosphorylation, and genetic knockdown studies validate their role in maintaining a mesenchymal cell state. Finally, analysis of clinical data shows that mesenchymal tumors exhibit significantly higher average expression of the 166 corresponding genes than epithelial tumors for nine different cancer types.

Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Coenzyme Q10 Biosynthesis Established in the Non-Ubiquinone Containing Corynebacterium glutamicum by Metabolic Engineering

Coenzyme Q₁₀ (CoQ10) serves as an electron carrier in aerobic respiration and has become an interesting target for biotechnological production due to its antioxidative effect and benefits in supplementation to patients with various diseases. For the microbial production, so far only bacteria have been used that naturally synthesize CoQ10 or a related CoQ species. Since the whole pathway involves many enzymatic steps and has not been fully elucidated yet, the set of genes required for transfer of CoQ10 synthesis to a bacterium not naturally synthesizing CoQ species remained unknown. Here, we established CoQ10 biosynthesis in the non-ubiquinone-containing Gram-positive Corynebacterium glutamicum by metabolic engineering. CoQ10 biosynthesis involves prenylation and, thus, requires farnesyl diphosphate as precursor. A carotenoid-deficient strain was engineered to synthesize an increased supply of the precursor molecule farnesyl diphosphate. Increased farnesyl diphosphate supply was demonstrated indirectly by increased conversion to amorpha-4,11-diene. To provide the first CoQ10 precursor decaprenyl diphosphate (DPP) from farnesyl diphosphate, DPP synthase gene ddsA from Paracoccus denitrificans was expressed. Improved supply of the second CoQ10 precursor, para-hydroxybenzoate (pHBA), resulted from metabolic engineering of the shikimate pathway. Prenylation of pHBA with DPP and subsequent decarboxylation, hydroxylation, and methylation reactions to yield CoQ10 was achieved by expression of ubi genes from Escherichia coli. CoQ10 biosynthesis was demonstrated in shake-flask cultivation and verified by liquid chromatography mass spectrometry analysis. To the best of our knowledge, this is the first report of CoQ10 production in a non-ubiquinone-containing bacterium.

Recent technical progress in sample preparation and liquid-phase separation-mass spectrometry for proteomic analysis of mass-limited samples

Mass spectrometry (MS)-based proteomics has enabled the identification and quantification of thousands of proteins from complex proteomes in a single experiment. However, its performance for mass-limited proteome samples (e.g., single cells and tissue samples from laser capture microdissection) is still not satisfying. The development of novel proteomic methodologies with better overall sensitivity is vital. During the last several years, substantial technical progress has been achieved for the preparation and liquid-phase separation-MS characterization of mass-limited proteome samples. In this review, we summarize recent technological progress of sample preparation, liquid chromatography (LC)-MS, capillary zone electrophoresis (CZE)-MS and MS instrumentation for bottom-up proteomics of trace biological samples, highlight some exciting applications of the novel techniques for single-cell proteomics, and provide a very brief perspective about the field at the end.

Microproteomic sample preparation

Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).

An antibody-free LC-MS/MS method for the quantification of intact insulin-like growth factors 1 and 2 in human plasma

Insulin-like growth factors 1 and 2 (IGF-1 and IGF-2) are important biomarkers in research and diagnosis of growth disorders. Quantitative analysis is performed using various ligand-binding assays or enzymatic digestion LC-MS/MS methods, whose widespread adoption is hampered by time-consuming sample preparation procedures. We present a simple and fast antibody-free LC-MS/MS method for the quantification of intact IGF-1 and IGF-2 in human plasma. The method requires 50 μL of plasma and uses fully ¹⁵N-labelled IGF-1 as internal standard. It features trifluoroethanol (TFE)-based IGF/IGF-binding protein complex dissociation and a two-step selective protein precipitation workflow, using 5% acetic acid in 80/20 acetone/acetonitrile (precipitation 1) and ice-cold ethanol (precipitation 2). Detection of intact IGF-1 and IGF-2 is performed by means of a Waters XEVO TQ-S triple quadrupole mass spectrometer in positive electrospray ionisation (ESI+) mode. Lower limits of quantification were 5.9 ng/mL for IGF-1 and 8.4 ng/mL for IGF-2. Intra-assay imprecision was below 4.5% and inter-assay imprecision was below 5.8% for both analytes. An excellent correlation was found between nominal and measured concentrations of the WHO reference standard for IGF-1. Comparison with the IDS-iSYS IGF-1 immunoassay showed good correlation (R² > 0.97), although a significant bias was observed with the immunoassay giving substantially higher concentrations. The LC-MS/MS method described here allows for reliable and simultaneous quantification of IGF-1 and IGF-2 in plasma, without the need for enzymatic digestion. The method can be readily implemented in clinical mass spectrometry laboratories and has the potential to be adapted for the analysis of different similarly sized peptide hormones.

The expression of the acarbose biosynthesis gene cluster in Actinoplanes sp. SE50/110 is dependent on the growth phase

BACKGROUND

Actinoplanes sp. SE50/110 is the natural producer of the diabetes mellitus drug acarbose, which is highly produced during the growth phase and ceases during the stationary phase. In previous works, the growth-dependency of acarbose formation was assumed to be caused by a decreasing transcription of the acarbose biosynthesis genes during transition and stationary growth phase.

RESULTS

In this study, transcriptomic data using RNA-seq and state-of-the-art proteomic data from seven time points of controlled bioreactor cultivations were used to analyze expression dynamics during growth of Actinoplanes sp. SE50/110. A hierarchical cluster analysis revealed co-regulated genes, which display similar transcription dynamics over the cultivation time. Aside from an expected metabolic switch from primary to secondary metabolism during transition phase, we observed a continuously decreasing transcript abundance of all acarbose biosynthetic genes from the early growth phase until stationary phase, with the strongest decrease for the monocistronically transcribed genes acbA, acbB, acbD and acbE. Our data confirm a similar trend for acb gene transcription and acarbose formation rate. Surprisingly, the proteome dynamics does not follow the respective transcription for all acb genes. This suggests different protein stabilities or post-transcriptional regulation of the Acb proteins, which in turn could indicate bottlenecks in the acarbose biosynthesis. Furthermore, several genes are co-expressed with the acb gene cluster over the course of the cultivation, including eleven transcriptional regulators (e.g. ACSP50_0424), two sigma factors (ACSP50_0644, ACSP50_6006) and further genes, which have not previously been in focus of acarbose research in Actinoplanes sp. SE50/110.

CONCLUSION

In conclusion, we have demonstrated, that a genome wide transcriptome and proteome analysis in a high temporal resolution is well suited to study the acarbose biosynthesis and the transcriptional and post-transcriptional regulation thereof.

Isolation and Characterization of Shewanella Phage Thanatos Infecting and Lysing Shewanella oneidensis and Promoting Nascent Biofilm Formation

Species of the genus Shewanella are widespread in nature in various habitats, however, little is known about phages affecting Shewanella sp. Here, we report the isolation of phages from diverse freshwater environments that infect and lyse strains of Shewanella oneidensis and other Shewanella sp. Sequence analysis and microscopic imaging strongly indicate that these phages form a so far unclassified genus, now named Shewanella phage Thanatos, which can be positioned within the subfamily of Tevenvirinae (Duplodnaviria; Heunggongvirae; Uroviricota; Caudoviricetes; Caudovirales; Myoviridae; Tevenvirinae). We characterized one member of this group in more detail using S. oneidensis MR-1 as a host. Shewanella phage Thanatos-1 possesses a prolate icosahedral capsule of about 110 nm in height and 70 nm in width and a tail of about 95 nm in length. The dsDNA genome exhibits a GC content of about 34.5%, has a size of 160.6 kbp and encodes about 206 proteins (92 with an annotated putative function) and two tRNAs. Out of those 206, MS analyses identified about 155 phage proteins in PEG-precipitated samples of infected cells. Phage attachment likely requires the outer lipopolysaccharide of S. oneidensis, narrowing the phage's host range. Under the applied conditions, about 20 novel phage particles per cell were produced after a latent period of approximately 40 min, which are stable at a pH range from 4 to 12 and resist temperatures up to 55°C for at least 24 h. Addition of Thanatos to S. oneidensis results in partial dissolution of established biofilms, however, early exposure of planktonic cells to Thanatos significantly enhances biofilm formation. Taken together, we identified a novel genus of Myophages affecting S. oneidensis communities in different ways.

A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis

Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis, and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Herein we describe a MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent acquisition (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total workup took less than a day. We observed a moderate trend towards lower protein identification in long-term stored samples (>15 years), but clustering into distinct proteomic subtypes was independent of archival time. Our results underscore the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and they prove the feasibility of analyzing large tissue cohorts in a robust, timely, and streamlined manner. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Pharmacoproteomics Identifies Kinase Pathways that Drive the Epithelial-Mesenchymal Transition and Drug Resistance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a complex and deadly disease lacking druggable genetic mutations. The limited efficacy of systemic treatments for advanced HCC implies that predictive biomarkers and drug targets are urgently needed. Most HCC drugs target protein kinases, indicating that kinase-dependent signaling networks drive HCC progression. To identify HCC signaling networks that determine responses to kinase inhibitors (KIs), we apply a pharmacoproteomics approach integrating kinome activity in 17 HCC cell lines with their responses to 299 KIs, resulting in a comprehensive dataset of pathway-based drug response signatures. By profiling patient HCC samples, we identify signatures of clinical HCC drug responses in individual tumors. Our analyses reveal kinase networks promoting the epithelial-mesenchymal transition (EMT) and drug resistance, including a FZD2-AXL-NUAK1/2 signaling module, whose inhibition reverses the EMT and sensitizes HCC cells to drugs. Our approach identifies cancer drug targets and molecular signatures of drug response for personalized oncology.

Spatial proteome profiling by immunohistochemistry-based laser capture microdissection and data-independent acquisition proteomics

Understanding the tumor heterogeneity through spatially resolved proteome profiling is important for biomedical research and clinical application. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Conventionally, tissue sections are stained with hematoxylin and eosin (H&E) for cell-type identification before LCM. However, it generally requires experienced pathologists to distinguish different cell types, which limits the application of LCM to broad cancer research field. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was marked by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance as H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT were achieved by combining with data independent acquisition proteomics. More than 3500 proteins were identified from only 0.2 mm² and 12 μm thickness of hepatocellular carcinoma (HCC) tissue section. Furthermore, using 5 mm² and 12 μm thickness of HCC tissue section, 6660 and 6052 protein groups were quantified from cancer cells and cancer-associated fibroblasts (CAFs) by the IHC-SISPROT workflow. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is a sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues.

Simple Method to Quantify Protein Abundances from 1000 Cells

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

Gestational Age-Dependent Abundance of Human Placental Transporters as Determined by Quantitative Targeted Proteomics

Some women take medication during pregnancy to address a variety of clinical conditions. Because of ethical and logistical concerns, it is impossible to determine fetal drug exposure, and therefore fetal risk, during pregnancy. Hence, alternative approaches need to be developed to predict maternal-fetal drug exposure throughout pregnancy. To do so, we previously developed and verified a maternal-fetal physiologically based pharmacokinetic model, which can predict fetal exposure to drugs that passively cross the placenta. However, many drugs are actively transported by the placenta (e.g., human immunodeficiency virus protease inhibitors). To extend our maternal-fetal physiologically based pharmacokinetic model to these actively transported drugs, we determined the gestational age–dependent changes in the protein abundance of placental transporters. Total cellular membrane fractions from first trimester (T1; n = 15), second trimester (T2; n = 19), and term (n = 15) human placentae obtained from uncomplicated pregnancies were isolated by ultracentrifugation. Transporter protein abundance was determined by targeted quantitative proteomics using liquid chromatography tandem mass specrometry. We observed that breast cancer resistance protein and P-glycoprotein abundance significantly decreased from T1 to term by 55% and 69%, respectively (per gram of tissue). Organic anion–transporting polypeptide (OATP) 2B1 abundance significantly decreased from T1 to T2 by 32%. In contrast, organic cation transporter (OCT) 3 and organic anion transporter 4 abundance significantly increased with gestational age (2-fold from T1 to term, 1.6-fold from T2 to term). Serotonin transporter and norepinephrine transporter did not change with gestational age. The abundance of bile salt export pump, multidrug resistance-associated protein 1-5, Na⁺-taurocholate cotransporting polypeptide, OATP1B1, OATP1B3, OCTN1-2, concentrative nucleoside transporter 1-3, equilibrative nucleoside transporter 2, and multidrug and toxin extrusion 1 could not be quantified. These data can be incorporated into our maternal-fetal physiologically based pharmacokinetic model to predict fetal exposure to drugs that are actively transported across the placenta.

Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1β and IL-17 upregulation in alcoholic hepatitis mice

Extracellular vesicles (EVs) have been growingly recognized as biomarkers and mediators of alcoholic liver disease (ALD) in human and mice. Here we characterized hepatocyte-derived EVs (HC-EVs) and their cargo for their biological functions in a novel murine model that closely resembles liver pathology observed in patients with alcoholic hepatitis (AH), the most severe spectrum of ALD. The numbers of circulating EVs and HC-EVs were significantly increased by 10-fold in AH mice compared with control mice. The miRNA (miR)-seq analysis detected 20 upregulated and 4 downregulated miRNAs (P < 0.001-0.05) in AH-HC-EVs. Treatment of murine primary hepatic stellate cells (HSCs) with AH-HC-EVs induced α-SMA (P < 0.05) and Col1a1 (P < 0.001). Smad7 and Nr1d2 genes, which were downregulated in HSCs from the AH mice, were predicted targets of 20 miRs upregulated in AH-HC-EVs. Among them were miR-27a and miR-181 which upon transfection in HSCs, indeed repressed Nr1d2, the quiescent HSC marker. AH-HC-EVs were also enriched with organelle proteins and mitochondrial DNA (10-fold, P < 0.05) and upregulated IL-1β and IL-17 production by hepatic macrophages (HMs) from AH mice in a TLR9-dependent manner. These results demonstrate HC-EV release is intensified in AH and suggest that AH-HC-EVs orchestrate liver fibrogenesis by directly targeting the quiescent HSC transcripts via a unique set of miRNAs and by amplifying HSC activation via DAMP-based induction of profibrogenic IL-1β and IL-17 by HMs. KEY MESSAGES: • Circulating EVs and HC-EVs were increased in AH mice compared with control mice • AH-HC-EVs were enriched in miRNAs, organelle proteins, and mitochondrial DNA • AH-HC-EVs increased cytokine production by AH-HMs in a TLR9-dependent manner.

MaxQuant Software for Ion Mobility Enhanced Shotgun Proteomics

Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range. Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

NanoTPOT: Enhanced Sample Preparation for Quantitative Nanoproteomic Analysis

With the ever-growing need for protein-level understanding in pathological research, proteomics researchers thrive to examine detailed proteome dynamics using crucial, yet often limited, primary and clinical samples. Aside from mass spectrometer instrumentation advancement, a single-tube-based high-throughput sample processing workflow is imperative to ensure sensitive, quantitative, and reproducible protein analysis for these increasingly sophisticated studies. Leveraging the benefits of an acid-cleavable detergent, RapiGest SF Surfactant (Waters Corporation), we developed and optimized a nanoproteomic workflow that we termed Nanogram TMT Processing in One Tube (NanoTPOT). Through the assessment of proteolytic digestion, tandem mass tag (TMT) labeling, online and offline fractionation strategies, our optimized workflow effectively eliminated the need for sample desalting and enabled compatible sample processing for mass spectrometry analysis. We further applied the NanoTPOT workflow to examine cellular response to stress caused by dithiothreitol in HeLa cells, where we identified and quantified 6935 and 5474 proteins in TMT 10-plex experiments with one microgram of lysate protein and 2000 sorted HeLa cells (roughly half microgram lysate protein) in each channel, respectively. Our workflow has been proven to be an effective alternative for current nanoproteomic sample processing to minimize sample loss in biological and clinical applications.

STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up-regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging, and PSA level. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.

Kinobead/LC-MS Phosphokinome Profiling Enables Rapid Analyses of Kinase-Dependent Cell Signaling Networks

Kinase-catalyzed protein phosphorylation is fundamental to eukaryotic signal transduction, regulating most cellular processes. Kinases are frequently dysregulated in cancer, inflammation, and degenerative diseases, and because they can be inhibited with small molecules, they became important drug targets. Accordingly, analytical approaches that determine kinase activation states are critically important to understand kinase-dependent signal transduction and to identify novel drug targets and predictive biomarkers. Multiplexed inhibitor beads (MIBs or kinobeads) efficiently enrich kinases from cell lysates for liquid chromatography-mass spectrometry (LC-MS) analysis. When combined with phosphopeptide enrichment, kinobead/LC-MS can also quantify the phosphorylation state of kinases, which determines their activation state. However, an efficient kinobead/LC-MS kinase phospho-profiling protocol that allows routine analyses of cell lines and tissues has not yet been developed. Here, we present a facile workflow that quantifies the global phosphorylation state of kinases with unprecedented sensitivity. We also found that our kinobead/LC-MS protocol can measure changes in kinase complex composition and show how these changes can indicate kinase activity. We demonstrate the utility of our approach in specifying kinase signaling pathways that control the acute steroidogenic response in Leydig cells; this analysis establishes the first comprehensive framework for the post-translational control of steroid biosynthesis.

Comprehensive Proteomics Analysis of Stressed Human Islets Identifies GDF15 as a Target for Type 1 Diabetes Intervention

Type 1 diabetes (T1D) results from the progressive loss of β cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between pro- and anti-apoptotic proteins. To identify proteins involved in this process, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1β and interferon-γ, leading to the identification of 11,324 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the treatment. We found that GDF15 translation was blocked during inflammation, and it was depleted in islets from individuals with T1D. The addition of exogenous GDF15 inhibited interleukin-1β+interferon-γ-induced apoptosis of human islets. Administration of GDF15 reduced by 53% the incidence of diabetes in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for T1D therapy.

Sample Preparation by Easy Extraction and Digestion (SPEED) - A Universal, Rapid, and Detergent-free Protocol for Proteomics Based on Acid Extraction

The main challenge of bottom-up proteomic sample preparation is to extract proteomes in a manner that enables efficient protein digestion for subsequent mass spectrometric analysis. Today's sample preparation strategies are commonly conceptualized around the removal of detergents, which are essential for extraction but strongly interfere with digestion and LC-MS. These multi-step preparations contribute to a lack of reproducibility as they are prone to losses, biases and contaminations, while being time-consuming and labor-intensive. We report a detergent-free method, named Sample Preparation by Easy Extraction and Digestion (SPEED), which consists of three mandatory steps, acidification, neutralization and digestion. SPEED is a universal method for peptide generation from various sources and is easily applicable even for lysis-resistant sample types as pure trifluoroacetic acid (TFA) is used for highly efficient protein extraction by complete sample dissolution. The protocol is highly reproducible, virtually loss-less, enables very rapid sample processing and is superior to the detergent/chaotropic agent-based methods FASP, ISD-Urea and SP3 for quantitative proteomics. SPEED holds the potential to dramatically simplify and standardize sample preparation while improving the depth of proteome coverage especially for challenging samples.

The Long Noncoding RNA Paupar Modulates PAX6 Regulatory Activities to Promote Alpha Cell Development and Function

Many studies have highlighted the role of dysregulated glucagon secretion in the etiology of hyperglycemia and diabetes. Accordingly, understanding the mechanisms underlying pancreatic islet α cell development and function has important implications for the discovery of new therapies for diabetes. In this study, comparative transcriptome analyses between embryonic mouse pancreas and adult mouse islets identified several pancreatic lncRNAs that lie in close proximity to essential pancreatic transcription factors, including the Pax6-associated lncRNA Paupar. We demonstrate that Paupar is enriched in glucagon-producing α cells where it promotes the alternative splicing of Pax6 to an isoform required for activation of essential α cell genes. Consistently, deletion of Paupar in mice resulted in dysregulation of PAX6 α cell target genes and corresponding α cell dysfunction, including blunted glucagon secretion. These findings illustrate a distinct mechanism by which a pancreatic lncRNA can coordinate glucose homeostasis by cell-specific regulation of a broadly expressed transcription factor.

Miniaturized sample preparation on a digital microfluidics device for sensitive bottom-up microproteomics of mammalian cells using magnetic beads and mass spectrometry-compatible surfactants

While LC-MS-based proteomics with high nanograms to micrograms of total protein has become routine, the analysis of samples derived from low cell numbers is challenged by factors such as sample losses, or difficulties encountered with the manual manipulation of small liquid volumes. Digital microfluidics (DMF) is an emerging technique for miniaturized and automated droplet manipulation, which has been proposed as a promising tool for proteomic sample preparation. However, proteome analysis of samples prepared on-chip by DMF has previously been unfeasible, due to incompatibility with down-stream LC-MS instrumentation. To overcome these limitations, we here developed protocols for bottom-up LC-MS based proteomics sample preparation of as little as 100 mammalian cells on a commercially available digital microfluidics device. To this end, we developed effective cell lysis conditions optimized for DMF, as well as detergent-buffer systems compatible with downstream proteolytic digestion on DMF chips and subsequent LC-MS analysis. A major step was the introduction of the single-pot, solid-phase-enhanced sample preparation (SP3) approach on-chip, which allowed the removal of salts and anti-fouling polymeric detergents, thus rendering sample preparation by DMF compatible with LC-MS-based proteome analysis. Application of DMF-SP3 to the proteome analysis of Jurkat T cells led to the identification of up to 2500 proteins from approximately 500 cells, and up to 1200 proteins from approximately 100 cells on an Orbitrap mass spectrometer, emphasizing the high compatibility of DMF-SP3 with low protein input and minute volumes handled by DMF. Taken together, we demonstrate the first sample preparation workflow for proteomics on a DMF chip device reported so far, allowing the sensitive analysis of limited biological material.

Proteome analysis of tissues by mass spectrometry

Tissues and biofluids are important sources of information used for the detection of diseases and decisions on patient therapies. There are several accepted methods for preservation of tissues, among which the most popular are fresh-frozen and formalin-fixed paraffin embedded methods. Depending on the preservation method and the amount of sample available, various specific protocols are available for tissue processing for subsequent proteomic analysis. Protocols are tailored to answer various biological questions, and as such vary in lysis and digestion conditions, as well as duration. The existence of diverse tissue-sample protocols has led to confusion in how to choose the best protocol for a given tissue and made it difficult to compare results across sample types. Here, we summarize procedures used for tissue processing for subsequent bottom-up proteomic analysis. Furthermore, we compare protocols for their variations in the composition of lysis buffers, digestion procedures, and purification steps. For example, reports have shown that lysis buffer composition plays an important role in the profile of extracted proteins: the most common are tris(hydroxymethyl)aminomethane, radioimmunoprecipitation assay, and ammonium bicarbonate buffers. Although, trypsin is the most commonly used enzyme for proteolysis, in some protocols it is supplemented with Lys-C and/or chymotrypsin, which will often lead to an increase in proteome coverage. Data show that the selection of the lysis procedure might need to be tissue-specific to produce distinct protocols for individual tissue types. Finally, selection of the procedures is also influenced by the amount of sample available, which range from biopsies or the size of a few dozen of mm² obtained with laser capture microdissection to much larger amounts that weight several milligrams.

The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes

Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.

Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts

High-grade serous carcinoma has a poor prognosis, owing primarily to its early dissemination throughout the abdominal cavity. Genomic and proteomic approaches have provided snapshots of the proteogenomics of ovarian cancer1,2, but a systematic examination of both the tumour and stromal compartments is critical in understanding ovarian cancer metastasis. Here we develop a label-free proteomic workflow to analyse as few as 5,000 formalin-fixed, paraffin-embedded cells microdissected from each compartment. The tumour proteome was stable during progression from in situ lesions to metastatic disease; however, the metastasis-associated stroma was characterized by a highly conserved proteomic signature, prominently including the methyltransferase nicotinamide N-methyltransferase (NNMT) and several of the proteins that it regulates. Stromal NNMT expression was necessary and sufficient for functional aspects of the cancer-associated fibroblast (CAF) phenotype, including the expression of CAF markers and the secretion of cytokines and oncogenic extracellular matrix. Stromal NNMT expression supported ovarian cancer migration, proliferation and in vivo growth and metastasis. Expression of NNMT in CAFs led to depletion of S-adenosyl methionine and reduction in histone methylation associated with widespread gene expression changes in the tumour stroma. This work supports the use of ultra-low-input proteomics to identify candidate drivers of disease phenotypes. NNMT is a central, metabolic regulator of CAF differentiation and cancer progression in the stroma that may be therapeutically targeted.

Development of a Sensitive, Scalable Method for Spatial, Cell-Type-Resolved Proteomics of the Human Brain

While nearly comprehensive proteome coverage can be achieved from bulk tissue or cultured cells, the data usually lacks spatial resolution. As a result, tissue based proteomics averages protein abundance across multiple cell types and/or localizations. With proteomics platforms lacking sensitivity and throughput to undertake deep single-cell proteome studies in order to resolve spatial or cell type dependent protein expression gradients within tissue, proteome analysis has been combined with sorting techniques to enrich for certain cell populations. However, the spatial resolution and context is lost after cell sorting. Here, we report an optimized method for the proteomic analysis of neurons isolated from post-mortem human brain by laser capture microdissection (LCM). We tested combinations of sample collection methods, lysis buffers and digestion methods to maximize the number of identifications and quantitative performance, identifying 1500 proteins from 60 000 μm² of 10 μm thick cerebellar molecular layer with excellent reproducibility. To demonstrate the ability of our workflow to resolve cell type specific proteomes within human brain tissue, we isolated sets of individual Betz and Purkinje cells. Both neuronal cell types are involved in motor coordination and were found to express highly specific proteomes to a depth of 2800 to 3600 proteins.

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

Identification of Hybrid Insulin Peptides (HIPs) in Mouse and Human Islets by Mass Spectrometry

We recently discovered hybrid insulin peptides (HIPs) as a novel class of post-translationally modified peptides in murine-derived beta cell tumors, and we demonstrated that these molecules are autoantigens in type 1 diabetes (T1D). A HIP consists of an insulin fragment linked to another secretory granule peptide via a peptide bond. We verified that autoreactive CD4 T cells in both mouse and human autoimmune diabetes recognize these modified peptides. Here, we use mass spectrometric analyses to confirm the presence of HIPs in both mouse and human pancreatic islets. We also present criteria for the confident identification of these peptides. This work supports the hypothesis that HIPs are autoantigens in human T1D and provides a foundation for future efforts to interrogate this previously unknown component of the beta cell proteome.