Extracellular vesicles secreted by 3D tumor organoids are enriched for immune regulatory signaling biomolecules compared to conventional 2D glioblastoma cell systems.

Background: Newer 3D culturing approaches are a promising way to better mimic the in vivo tumor microenvironment and to study the interactions between the heterogeneous cell populations of glioblastoma multiforme. Like many other tumors, glioblastoma uses extracellular vesicles as an intercellular communication system to prepare surrounding tissue for invasive tumor growth. However, little is known about the effects of 3D culture on extracellular vesicles. The aim of this study was to comprehensively characterize extracellular vesicles in 3D organoid models and compare them to conventional 2D cell culture systems. Methods: Primary glioblastoma cells were cultured as 2D and 3D organoid models. Extracellular vesicles were obtained by precipitation and immunoaffinity, with the latter allowing targeted isolation of the CD9/CD63/CD81 vesicle subpopulation. Comprehensive vesicle characterization was performed and miRNA expression profiles were generated by smallRNA-sequencing. In silico analysis of differentially regulated miRNAs was performed to identify mRNA targets and corresponding signaling pathways. The tumor cell media and extracellular vesicle proteome were analyzed by high-resolution mass spectrometry. Results: We observed an increased concentration of extracellular vesicles in 3D organoid cultures. Differential gene expression analysis further revealed the regulation of twelve miRNAs in 3D tumor organoid cultures (with nine miRNAs down and three miRNAs upregulated). MiR-23a-3p, known to be involved in glioblastoma invasion, was significantly increased in 3D. MiR-7-5p, which counteracts glioblastoma malignancy, was significantly decreased. Moreover, we identified four miRNAs (miR-323a-3p, miR-382-5p, miR-370-3p, miR-134-5p) located within the DLK1-DIO3 domain, a cancer-associated genomic region, suggesting a possible importance of this region in glioblastoma progression. Overrepresentation analysis identified alterations of extracellular vesicle cargo in 3D organoids, including representation of several miRNA targets and proteins primarily implicated in the immune response. Conclusion: Our results show that 3D glioblastoma organoid models secrete extracellular vesicles with an altered cargo compared to corresponding conventional 2D cultures. Extracellular vesicles from 3D cultures were found to contain signaling molecules associated with the immune regulatory signaling pathways and as such could potentially change the surrounding microenvironment towards tumor progression and immunosuppressive conditions. These findings suggest the use of 3D glioblastoma models for further clinical biomarker studies as well as investigation of new therapeutic options.

Convergent evolution of plant pattern recognition receptors sensing cysteine-rich patterns from three microbial kingdoms.

The Arabidopsis thaliana Receptor-Like Protein RLP30 contributes to immunity against the fungal pathogen Sclerotinia sclerotiorum. Here we identify the RLP30-ligand as a small cysteine-rich protein (SCP) that occurs in many fungi and oomycetes and is also recognized by the Nicotiana benthamiana RLP RE02. However, RLP30 and RE02 share little sequence similarity and respond to different parts of the native/folded protein. Moreover, some Brassicaceae other than Arabidopsis also respond to a linear SCP peptide instead of the folded protein, suggesting that SCP is an eminent immune target that led to the convergent evolution of distinct immune receptors in plants. Surprisingly, RLP30 shows a second ligand specificity for a SCP-nonhomologous protein secreted by bacterial Pseudomonads. RLP30 expression in N. tabacum results in quantitatively lower susceptibility to bacterial, fungal and oomycete pathogens, thus demonstrating that detection of immunogenic patterns by Arabidopsis RLP30 is involved in defense against pathogens from three microbial kingdoms.

Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes.

Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.

Apocarotenoids are allosteric effectors of a dimeric plant glycosyltransferase involved in defense and lignin formation.

Glycosyltransferases are nature's versatile tools to tailor the functionalities of proteins, carbohydrates, lipids, and small molecules by transferring sugars. Prominent substrates are hydroxycoumarins such as scopoletin, which serve as natural plant protection agents. Similarly, C13-apocarotenoids, which are oxidative degradation products of carotenoids/xanthophylls, protect plants by repelling pests and attracting pest predators. We show that C13-apocarotenoids interact with the plant glycosyltransferase NbUGT72AY1 and induce conformational changes in the enzyme catalytic center ultimately reducing its inherent UDP-α-d-glucose glucohydrolase activity and increasing its catalytic activity for productive hydroxycoumarin substrates. By contrast, C13-apocarotenoids show no effect on the catalytic activity toward monolignol lignin precursors, which are competitive substrates. In vivo studies in tobacco plants (Nicotiana benthamiana) confirmed increased glycosylation activity upon apocarotenoid supplementation. Thus, hydroxycoumarins and apocarotenoids represent specialized damage-associated molecular patterns, as they each provide precise information about the plant compartments damaged by pathogen attack. The molecular basis for the C13-apocarotenoid-mediated interplay of two plant protective mechanisms and their function as allosteric enhancers opens up potential applications of the natural products in agriculture and pharmaceutical industry.

Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum.

Microbes that can recycle one-carbon (C1) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO2 and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model acetogen Clostridium autoethanogenum grown autotrophically on three gas mixtures (CO, CO+H2, or CO+CO2+H2). We detect the prioritization of proteome allocation for C1 fixation and the significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are likely relevant in vivo for CO oxidation, H2 metabolism, and ethanol production. The integration of proteomic and metabolic flux data demonstrated that enzymes catalyze high fluxes with high concentrations and high in vivo catalytic rates. We show that flux adjustments were dominantly accompanied by changing enzyme catalytic rates rather than concentrations. IMPORTANCE Acetogen bacteria are important for maintaining biosustainability as they can recycle gaseous C1 waste feedstocks (e.g., industrial waste gases and syngas from gasified biomass or municipal solid waste) into fuels and chemicals. Notably, the acetogen Clostridium autoethanogenum is being used as a cell factory in industrial-scale gas fermentation. Here, we perform reliable absolute proteome quantification for the first time in an acetogen. This is important as our work advances both rational metabolic engineering of acetogen cell factories and accurate in silico reconstruction of their phenotypes. Furthermore, this absolute proteomics data set serves as a reference toward a better systems-level understanding of the ancient metabolism of acetogens.

Systematic analysis of migration factors by MigExpress identifies essential cell migration control genes in non-small cell lung cancer.

Cell migration is an essential process in health and in disease, including cancer metastasis. A comprehensive inventory of migration factors is nonetheless lacking-in part due to the difficulty in assessing migration using high-throughput technologies. Hence, there are currently very few screens that systematically reveal factors controlling cell migration. Here, we introduce MigExpress as a platform for the 'identification of Migration control genes by differential Expression'. MigExpress exploits the combination of in-depth molecular profiling and the robust quantitative analysis of migration capacity in a broad panel of samples and identifies migration-associated genes by their differential expression in slow- versus fast-migrating cells. We applied MigExpress to investigate non-small cell lung cancer (NSCLC), which is the most frequent cause of cancer mortality mainly due to metastasis. In 54 NSCLC cell lines, we comprehensively determined mRNA and protein expression. Correlating the transcriptome and proteome profiles with the quantified migration properties led to the discovery and validation of FLNC, DSE, CPA4, TUBB6, and BICC1 as migration control factors in NSCLC cells, which were also negatively correlated with patient survival. Notably, FLNC was the least expressed filamin in NSCLC, but the only one controlling cell migration and correlating with patient survival and metastatic disease stage. In our study, we present MigExpress as a new method for the systematic analysis of migration factors and provide a comprehensive resource of transcriptomic and proteomic data of NSCLC cell lines related to cell migration.

mTORC1 and mTORC2 Converge on the Arp2/3 Complex to Promote KrasG12D-Induced Acinar-to-Ductal Metaplasia and Early Pancreatic Carcinogenesis.

BACKGROUND & AIMS: Oncogenic KrasG12D induces neoplastic transformation of pancreatic acinar cells through acinar-to-ductal metaplasia (ADM), an actin-based morphogenetic process, and drives pancreatic ductal adenocarcinoma (PDAC). mTOR (mechanistic target of rapamycin kinase) complex 1 (mTORC1) and 2 (mTORC2) contain Rptor and Rictor, respectively, and are activated downstream of KrasG12D, thereby contributing to PDAC. Yet, whether and how mTORC1 and mTORC2 impact on ADM and the identity of the actin nucleator(s) mediating such actin rearrangements remain unknown. METHODS: A mouse model of inflammation-accelerated KrasG12D-driven early pancreatic carcinogenesis was used. Rptor, Rictor, and Arpc4 (actin-related protein 2/3 complex subunit 4) were conditionally ablated in acinar cells to deactivate the function of mTORC1, mTORC2 and the actin-related protein (Arp) 2/3 complex, respectively. RESULTS: We found that mTORC1 and mTORC2 are markedly activated in human and mouse ADM lesions, and cooperate to promote KrasG12D-driven ADM in mice and in vitro. They use the Arp2/3 complex as a common downstream effector to induce the remodeling the actin cytoskeleton leading to ADM. In particular, mTORC1 regulates the translation of Rac1 (Rac family small GTPase 1) and the Arp2/3-complex subunit Arp3, whereas mTORC2 activates the Arp2/3 complex by promoting Akt/Rac1 signaling. Consistently, genetic ablation of the Arp2/3 complex prevents KrasG12D-driven ADM in vivo. In acinar cells, the Arp2/3 complex and its actin-nucleation activity mediated the formation of a basolateral actin cortex, which is indispensable for ADM and pre-neoplastic transformation. CONCLUSIONS: Here, we show that mTORC1 and mTORC2 attain a dual, yet nonredundant regulatory role in ADM and early pancreatic carcinogenesis by promoting Arp2/3 complex function. The role of Arp2/3 complex as a common effector of mTORC1 and mTORC2 fills the gap between oncogenic signals and actin dynamics underlying PDAC initiation.

Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing.

As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.

Tiered approach for the identification of Mal d 1 reduced, well tolerated apple genotypes.

A rising proportion of the world population suffers from food-related allergies, including incompatibilities to apples. Although several allergenic proteins have been found in apples, the most important proteins that cause allergic reactions to apples in Central-Northern Europe, and North America are the Mal d 1 proteins, which are homologues of the birch pollen allergen Bet v 1. As the demand for hypoallergenic fruits is constantly increasing, we selected apple genotypes with a low total content of Mal d 1 by enzyme-linked immunosorbent assay analysis from segregating populations and tested the tolerability of these fruits through a human provocation study. This tiered approach, which exploited the natural diversity of apples, led to the identification of fruits, which were tolerated by allergic patients. In addition, we found a significant correlation (coefficient >0.76) between the total Mal d 1 content and flavan-3-ol amount and show that the isoform composition of the Mal d 1 proteins, which was determined by LC-MS/MS has a decisive effect on the tolerability of apple genotypes. The approach presented can be applied to other types of fruit and to other allergenic proteins. Therefore, the strategy can be used to reduce the allergen content of other plant foods, thereby improving food safety for allergy subjects.

Identification of Isopeptides Between Human Tissue Transglutaminase and Wheat, Rye, and Barley Gluten Peptides.

Celiac disease (CD) is a chronic immune-mediated enteropathy of the small intestine, which is triggered by the ingestion of storage proteins (gluten) from wheat, rye, and barley in genetically predisposed individuals. Human tissue transglutaminase (TG2) plays a central role in the pathogenesis of CD, because it is responsible for specific gluten peptide deamidation and covalent crosslinking, resulting in the formation of Nε-(γ-glutamyl)-lysine isopeptide bonds. The resulting TG2-gluten peptide complexes are assumed to cause the secretion of anti-TG2 autoantibodies, but the underlying mechanisms are only partly known. To gain more insight into the structures of these complexes, the aim of our study was to identify TG2-gluten isopeptides. With the use of discovery-driven as well as targeted nanoscale liquid chromatography tandem mass spectrometry, we detected 29 TG2-gluten isopeptides in total, involving seven selected TG2 lysine residues (K205, K265, K429, K468, K590, K600, K677). Several gluten peptides carried known B-cell epitopes and/or T-cell epitopes, either intact 9-mer core regions or partial sequences, as well as sequences bearing striking similarities to already known epitopes. These novel insights into the molecular structures of TG2-gluten peptide complexes may help clarify their physiological relevance in the initiation of CD autoimmunity and the role of anti-TG2 autoantibodies.

Cathepsin S Alterations Induce a Tumor-Promoting Immune Microenvironment in Follicular Lymphoma.

Tumor cells orchestrate their microenvironment. Here, we provide biochemical, structural, functional, and clinical evidence that Cathepsin S (CTSS) alterations induce a tumor-promoting immune microenvironment in follicular lymphoma (FL). We found CTSS mutations at Y132 in 6% of FL (19/305). Another 13% (37/286) had CTSS amplification, which was associated with higher CTSS expression. CTSS Y132 mutations lead to accelerated autocatalytic conversion from an enzymatically inactive profrom to active CTSS and increased substrate cleavage, including CD74, which regulates major histocompatibility complex class II (MHC class II)-restricted antigen presentation. Lymphoma cells with hyperactive CTSS more efficiently activated antigen-specific CD4+ T cells in vitro. Tumors with hyperactive CTSS showed increased CD4+ T cell infiltration and proinflammatory cytokine perturbation in a mouse model and in human FLs. In mice, this CTSS-induced immune microenvironment promoted tumor growth. Clinically, patients with CTSS-hyperactive FL had better treatment outcomes with standard immunochemotherapies, indicating that these immunosuppressive regimens target both the lymphoma cells and the tumor-promoting immune microenvironment.

Comprehensive Detection of Isopeptides between Human Tissue Transglutaminase and Gluten Peptides.

Celiac disease (CD) is a chronic inflammation of the small intestine triggered by the ingestion of gluten in genetically predisposed individuals. Tissue transglutaminase (TG2) is a key factor in CD pathogenesis, because it catalyzes both the deamidation of specific glutamine residues and the formation of covalent Nε-(γ-glutamyl)-lysine isopeptide crosslinks resulting in TG2-gluten peptide complexes. These complexes are thought to activate B cells causing the secretion of anti-TG2 autoantibodies that serve as diagnostic markers for CD, although their pathogenic role remains unclear. To gain more insight into the molecular structures of TG2-gluten peptide complexes, we used different proteomics software tools that enable the comprehensive identification of isopeptides. Thus, 34 different isopeptides involving 20 TG2 lysine residues were identified in a model system, only six of which were previously known. Additionally, 36 isopeptides of TG2-TG2 multimers were detected. Experiments with different TG2-gluten peptide molar ratios revealed the most preferred lysine residues involved in isopeptide crosslinking. Expanding the model system to three gluten peptides with more glutamine residues allowed the localization of the preferred glutamine crosslinking sites. These new insights into the structure of TG2-gluten peptide complexes may help clarify the role of extracellular TG2 in CD autoimmunity and in other inflammatory diseases.

Analyzing bioactive effects of the minor hop compound xanthohumol C on human breast cancer cells using quantitative proteomics.

Minor prenylated hop compounds have been attracting increasing attention due to their promising anticarcinogenic properties. Even after intensive purification from natural raw extracts, allocating certain activities to single compounds or complex interactions of the main compound with remaining impurities in very low concentration is difficult. In this study, dose-dependent antiproliferative and cytotoxic effects of the promising xanthohumol (XN) analogue xanthohumol C (XNC) were evaluated and compared to XN and a XN-enriched hop extract (XF). It was demonstrated that the cell growth inhibition of human breast cancer cell line (MCF-7) significantly increases after being treated with XNC compared to XN and XF. Based on label-free data-dependent acquisition proteomics, physiological influences on the proteome of MCF-7 cells were analyzed. Different modes of action between XNC and XN treated MCF-7 cells could be postulated. XNC causes ER stress and seems to be involved in cell-cell adhesion, whereas XN influences cell cycles and DNA replication as well as type I interferon signaling pathway. The results demonstrate the utility of using quantitative proteomics for bioactivity screenings of minor hop compounds and underscore the importance of isolating highly pure compounds into their distinct forms to analyze their different and possibly synergistic activities and modes of action.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial.

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.

Consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is a prerequisite for functional analysis of biological processes. Data-independent acquisition (DIA) is a bottom-up mass spectrometry approach that provides complete information on precursor and fragment ions. However, owing to the convoluted structure of DIA data sets, confident, systematic identification and quantification of peptidoforms has remained challenging. Here, we present inference of peptidoforms (IPF), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by the DIA method SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. IPF reduced false site-localization by more than sevenfold compared with previous approaches, while recovering 85.4% of the true signals. Using IPF, we quantified peptidoforms in DIA data acquired from >200 samples of blood plasma of a human twin cohort and assessed the contribution of heritable, environmental and longitudinal effects on their PTMs.

Statistical approach to protein quantification.

A major goal in proteomics is the comprehensive and accurate description of a proteome. This task includes not only the identification of proteins in a sample, but also the accurate quantification of their abundance. Although mass spectrometry typically provides information on peptide identity and abundance in a sample, it does not directly measure the concentration of the corresponding proteins. Specifically, most mass-spectrometry-based approaches (e.g. shotgun proteomics or selected reaction monitoring) allow one to quantify peptides using chromatographic peak intensities or spectral counting information. Ultimately, based on these measurements, one wants to infer the concentrations of the corresponding proteins. Inferring properties of the proteins based on experimental peptide evidence is often a complex problem because of the ambiguity of peptide assignments and different chemical properties of the peptides that affect the observed concentrations. We present SCAMPI, a novel generic and statistically sound framework for computing protein abundance scores based on quantified peptides. In contrast to most previous approaches, our model explicitly includes information from shared peptides to improve protein quantitation, especially in eukaryotes with many homologous sequences. The model accounts for uncertainty in the input data, leading to statistical prediction intervals for the protein scores. Furthermore, peptides with extreme abundances can be reassessed and classified as either regular data points or actual outliers. We used the proposed model with several datasets and compared its performance to that of other, previously used approaches for protein quantification in bottom-up mass spectrometry.

Probing intein-catalyzed thioester formation by unnatural amino acid substitutions in the active site.

Inteins are single-turnover catalysts that splice themselves out of a precursor polypeptide chain. For most inteins, the first step of protein splicing is the formation of a thioester through an N-S acyl shift at the upstream splice junction. However, the mechanism by which this reaction is achieved and the impact of mutations in and close to the active site remain unclear on the atomic level. To investigate these questions, we have further explored a split variant of the Ssp DnaB intein by introducing substitutions with unnatural amino acids within the short synthetic N-terminal fragment. A previously reported collapse of the oxythiazolidine anion intermediate into a thiazoline ring was found to be specificially dependent on the methyl side chain of the flanking Ala(-1). The stereoisomer d-Ala and the constitutional isomers ß-Ala and sarcosine did not lead to this side reaction but rather supported splicing. Substitution of the catalytic Cys1 with homocysteine strongly inhibited protein splicing; however, thioester formation was not impaired. These results argue against the requirement of a base to deprotonate the catalytic thiol group prior to the N-S acyl shift, because it should be misaligned for optimal proton abstraction. A previously described mutant intein evolved for more general splicing in different sequence contexts could even rather efficiently splice with this homocysteine. Our findings show the large impact of some subtle structural changes on the protein splicing pathway, but also the remarkable tolerance toward other changes. Such insights will also be important for the biotechnological exploitation of inteins.

Semisynthesis of proteins using split inteins.

Protein splicing is an autocatalytic reaction in which an internal protein domain, the intein, excises itself out of a precursor protein and concomitantly links the two flanking sequences, the exteins, with a native peptide bond. In split inteins, the intein domain is divided into two parts that undergo fragment association followed by protein splicing in trans. Thus, the extein sequences joined in the process originate from two separate molecules. The specificity and sequence promiscuity of split inteins make this approach a generally useful tool for the preparation of semisynthetic proteins. To this end, the recombinant part of the protein of interest is expressed as a fusion protein with one split intein fragment. The synthetic part is extended by the other, complementary fragment of the split intein. A recently introduced split intein, in which the N-terminal fragment consists of only 11 native amino acids, has greatly facilitated preparation of the synthetic part by solid-phase peptide synthesis. This intein enables the chemoenzymatic synthesis of N-terminally modified semisynthetic proteins. The reaction can be performed under native conditions and at protein and peptide concentrations in the low micromolar range. In contrast to chemical ligation procedures like native chemical ligation and expressed protein ligation, the incorporation of a thioester group and an aminoterminal cysteine into the two polypeptides to be linked is not necessary. We discuss properties of useful inteins, design rules for split inteins and intein insertion sites and we describe selected examples in detail.

Interaction studies and alanine scanning analysis of a semi-synthetic split intein reveal thiazoline ring formation from an intermediate of the protein splicing reaction.

We recently reported an artificially split intein based on the Ssp DnaB mini-intein that consists of a synthetic N-terminal intein fragment (Int(N)) and a recombinant C-terminal part (Int(C)), which are 11 and 143 amino acids in length, respectively. This intein holds great promise for the preparation of semi-synthetic proteins by protein trans-splicing. In this work we synthesized a set of Int(N) peptide variants to investigate their structure-function relationship with regard to fragment association and promotion of protein trans-splicing. A further truncation of the Int(N) sequence below 11 amino acids resulted in loss of activity, whereas C-terminal extensions were tolerated. Alanine scanning analysis identified three essential hydrophobic residues, whereas substitutions at other positions were tolerated. We developed assays to monitor association of Int(N) with an Int(C) mutant blocked in protein splicing by native PAGE and fluorescence anisotropy. The kinetic parameters of intein complex formation were K(d) = 1.1 mum, k(on) = 16.8 m(-1) s(-1), and k(off) = 1.8 x 10(-5) s(-1) for the native Int(N11) sequence. Intriguingly, a G(-1)A substitution, previously known to significantly impair protein splicing, was revealed to result in thiazoline ring formation involving the catalytic Cys-1, likely by aberrant dehydration of a oxythiazolidine intermediate. This finding provides experimental evidence for the postulated intermediate during the initial N/S acyl shift and underlines the delicate spatial and temporal alignment required in the intein active site to prevent side reactions of the protein-splicing pathway.