WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows.

The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.

Comparative gut proteomics study revealing adaptive physiology of Eurasian spruce bark beetle, Ips typographus (Coleoptera: Scolytinae).

The bark beetle, Ips typographus (L.), is a major pest of Norway spruce, Picea abies (L.), causing enormous economic losses globally. The adult stage of the I. typographus has a complex life cycle (callow and sclerotized); the callow beetles feed ferociously, whereas sclerotized male beetles are more aggressive and pioneers in establishing new colonies. We conducted a comparative proteomics study to understand male and female digestion and detoxification processes in callow and sclerotized beetles. Proteome profiling was performed using high-throughput liquid chromatography-mass spectrometry. A total of >3000 proteins were identified from the bark beetle gut, and among them, 539 were differentially abundant (fold change ±2, FDR <0.05) between callow and sclerotized beetles. The differentially abundant proteins (DAPs) mainly engage with binding, catalytic activity, anatomical activity, hydrolase activity, metabolic process, and carbohydrate metabolism, and hence may be crucial for growth, digestion, detoxification, and signalling. We validated selected DAPs with RT-qPCR. Gut enzymes such as NADPH-cytochrome P450 reductase (CYC), glutathione S-transferase (GST), and esterase (EST) play a crucial role in the I. typographus for detoxification and digesting of host allelochemicals. We conducted enzyme activity assays with them and observed a positive correlation of CYC and GST activities with the proteomic results, whereas EST activity was not fully correlated. Furthermore, our investigation revealed that callow beetles had an upregulation of proteins associated with juvenile hormone (JH) biosynthesis and chitin metabolism, whereas sclerotized beetles exhibited an upregulation of proteins linked to fatty acid metabolism and the TCA cycle. These distinctive patterns of protein regulation in metabolic and functional processes are specific to each developmental stage, underscoring the adaptive responses of I. typographicus in overcoming conifer defences and facilitating their survival. Taken together, it is the first gut proteomic study comparing males and females of callow and sclerotized I. typographus, shedding light on the adaptive ecology at the molecular level. Furthermore, the information about bark beetle handling of nutritionally limiting and defence-rich spruce phloem diet can be utilized to formulate RNAi-mediated beetle management.

PLK1 as a cooperating partner for BCL2-mediated antiapoptotic program in leukemia.

The deregulation of BCL2 family proteins plays a crucial role in leukemia development. Therefore, pharmacological inhibition of this family of proteins is becoming a prevalent treatment method. However, due to the emergence of primary and acquired resistance, efficacy is compromised in clinical or preclinical settings. We developed a drug sensitivity prediction model utilizing a deep tabular learning algorithm for the assessment of venetoclax sensitivity in T-cell acute lymphoblastic leukemia (T-ALL) patient samples. Through analysis of predicted venetoclax-sensitive and resistant samples, PLK1 was identified as a cooperating partner for the BCL2-mediated antiapoptotic program. This finding was substantiated by additional data obtained through phosphoproteomics and high-throughput kinase screening. Concurrent treatment using venetoclax with PLK1-specific inhibitors and PLK1 knockdown demonstrated a greater therapeutic effect on T-ALL cell lines, patient-derived xenografts, and engrafted mice compared with using each treatment separately. Mechanistically, the attenuation of PLK1 enhanced BCL2 inhibitor sensitivity through upregulation of BCL2L13 and PMAIP1 expression. Collectively, these findings underscore the dependency of T-ALL on PLK1 and postulate a plausible regulatory mechanism.

An mTRAN-mRNA interaction mediates mitochondrial translation initiation in plants.

Plant mitochondria represent the largest group of respiring organelles on the planet. Plant mitochondrial messenger RNAs (mRNAs) lack Shine-Dalgarno-like ribosome-binding sites, so it is unknown how plant mitoribosomes recognize mRNA. We show that "mitochondrial translation factors" mTRAN1 and mTRAN2 are land plant-specific proteins, required for normal mitochondrial respiration chain biogenesis. Our studies suggest that mTRANs are noncanonical pentatricopeptide repeat (PPR)-like RNA binding proteins of the mitoribosomal "small" subunit. We identified conserved Adenosine (A)/Uridine (U)-rich motifs in the 5' regions of plant mitochondrial mRNAs. mTRAN1 binds this motif, suggesting that it is a mitoribosome homing factor to identify mRNAs. We demonstrate that mTRANs are likely required for translation of all plant mitochondrial mRNAs. Plant mitochondrial translation initiation thus appears to use a protein-mRNA interaction that is divergent from bacteria or mammalian mitochondria.

Quantification of proteomic profile changes in the hemolymph of crayfish during in vitro coagulation.

Hemolymph is the circulatory fluid that fills the body cavity of crustaceans, analogous to blood in vertebrates. Hemolymph coagulation, similar to blood clotting in vertebrates, plays a crucial role in wound healing and innate immune responses. Despite extensive studies on the clotting process in crustaceans, no comparative quantitative analysis of the protein composition of non-clotted and clotted hemolymph in any decapod has been reported. In this study, we used label-free protein quantification with high-resolution mass spectrometry to identify the proteomic profile of hemolymph in crayfish and quantify significant changes in protein abundances between non-clotted and clotted hemolymph. Our analysis identified a total of two-hundred and nineteen proteins in both hemolymph groups. Furthermore, we discussed the potential functions of the top most high and low-abundant proteins in hemolymph proteomic profile. The quantity of most of the proteins was not significantly changed during coagulation between non-clotted and clotted hemolymph, which may indicate that clotting proteins are likely pre-synthesized, allowing for a swift coagulation response to injury. Four proteins still showed abundance differences (p < 0.05, fold change>2), including C-type lectin domain-containing proteins, Laminin A chain, Tropomyosin, and Reverse transcriptase domain-containing proteins. While the first three proteins were down-regulated, the last one was up-regulated. The down-regulation of structural and cytoskeletal proteins may affect the process of hemocyte degranulation needed for coagulation, while the up-regulation of an immune-related protein might be attributed to the phagocytosis ability of viable hemocytes during coagulation.

A proteomics dataset capturing myeloid cell responses upon cellular exposure to fungicides, adjuvants and fungicide formulations.

Dendritic cells are the sentinels of the immune system, linking the innate and adaptive immune response. Myeloid and dendritic cell models have been successfully used in in vitro approaches to predict adverse outcomes such as skin sensitization. We here exposed a well-characterized human dendritic cell-like cell line to agricultural chemicals, including fungicide formulations, active ingredients, adjuvants and defined mixtures for 24 h to profile induced changes on protein levels. Cell pellets were harvested and prepared for bottom-up label-free analysis with peptide separation on an EASY-nano LC system 1200 coupled online with a QExactive HF-X mass spectrometer with data-dependent acquisition (DDA). The raw data files and processed quantitative data have been deposited to ProteomeXchange with the data identification number PXD034624 and are described here. The data in this article may serve as a resource for researchers interested in e.g. human toxicology, immunology, cell biology and pharmacology.

Adjuvants in fungicide formulations can be skin sensitizers and cause different types of cell stress responses.

New approaches based on -omics technologies can identify biomarkers and processes regulated in response to xenobiotics, and thus support toxicological risk assessments. This is vital to meet the challenges associated with "cocktail effects", i.e. combination effects of chemicals present simultaneously in a product, our environment, and/or our body. For plant protection products (PPPs), investigations largely focus on active ingredients such as herbicides and fungicides. In this study, we have analyzed agricultural chemicals, two surfactants (poly(oxy-1,2-ethanediyl), alpha-sulfo-omega-[2,4,6-tris(1-phenylethyl)phenoxy]-, ammonium salt, POL; N,N-dimethylcapramide, NND), and one preservative, 1,2-benzisothiazol-3(2 H)-one (BEN) used as adjuvants in PPPs, and further three fungicide PPPs, Proline EC 250, Shirlan, Folicur Xpert, containing the adjuvants, and other major individual constituents (fluazinam (FLU), prothioconazole (PRO), tebuconazole (TEB)) as well as defined mixtures ("mixes") thereof using several in vitro approaches. All investigated single agricultural chemicals were predicted as skin sensitizers using an in vitro transcriptomic assay based on a dendritic cell model. For selected chemicals and mixes, also skin sensitization potency was predicted. The preservative BEN induced significant changes in cytokine secretion and dendritic cell activation marker CD86 expression. The surfactant NND changed cytokine secretion only and the POL only affected CD86 expression. Proteomic analyses revealed unique response profiles for all adjuvants, an oxidative stress pattern response in BEN-treated cells, and differentially abundant proteins associated with cholesterol homeostasis in response to POL. In summary, we find responses to agricultural chemicals and products consistent with the dendritic cell model reacting to chemical exposure with oxidative stress, ER stress, effects on autophagy, and metabolic changes especially related to cholesterol homeostasis. After exposure to certain mixes, novel proteins or transcripts were differentially expressed and these were not detected for any single constituents, supporting the occurrence of cocktail effects. This indicates that all chemicals in a PPP can contribute to the toxicity profile of a PPP, including their skin sensitizing/immunotoxic properties.

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery.

In recent years, several advances have been achieved in breast cancer (BC) classification and treatment. However, overdiagnosis, overtreatment, and recurrent disease are still significant causes of complication and death. Here, we present the development of a protocol aimed at parallel transcriptome and proteome analysis of BC tissue samples using mass spectrometry, via Data Dependent and Independent Acquisitions (DDA and DIA). Protein digestion was semi-automated and performed on flowthroughs after RNA extraction. Data for 116 samples were acquired in DDA and DIA modes and processed using MaxQuant, EncyclopeDIA, or DIA-NN. DIA-NN showed an increased number of identified proteins, reproducibility, and correlation with matching RNA-seq data, therefore representing the best alternative for this setup. Gene Set Enrichment Analysis pointed towards complementary information being found between transcriptomic and proteomic data. A decision tree model, designed to predict the intrinsic subtypes based on differentially abundant proteins across different conditions, selected protein groups that recapitulate important clinical features, such as estrogen receptor status, HER2 status, proliferation, and aggressiveness. Taken together, our results indicate that the proposed protocol performed well for the application. Additionally, the relevance of the selected proteins points to the possibility of using such data as a biomarker discovery tool for personalized medicine.

Plasma proteome profiling of healthy individuals across the life span in a Sicilian cohort with long-lived individuals.

The study of healthy human aging is important for shedding light on the molecular mechanisms behind aging to promote well-being and to possibly predict and/or avoid the development of age-related disorders such as atherosclerosis and diabetes. Herein, we have employed an untargeted mass spectrometry-based approach to study age-related protein changes in a healthy Sicilian plasma cohort including long-lived individuals. This approach confirmed some of the previously known proteins correlated with age including fibulin-1, dystroglycan, and gamma-glutamyl hydrolase. Furthermore, our findings include novel proteins that correlate with age and/or with location and uric acid, which could represent a unique signature for healthy aging.

Leaf Apoplast of Field-Grown Potato Analyzed by Quantitative Proteomics and Activity-Based Protein Profiling.

Multiple biotic and abiotic stresses challenge plants growing in agricultural fields. Most molecular studies have aimed to understand plant responses to challenges under controlled conditions. However, studies on field-grown plants are scarce, limiting application of the findings in agricultural conditions. In this study, we investigated the composition of apoplastic proteomes of potato cultivar Bintje grown under field conditions, i.e., two field sites in June-August across two years and fungicide treated and untreated, using quantitative proteomics, as well as its activity using activity-based protein profiling (ABPP). Samples were clustered and some proteins showed significant intensity and activity differences, based on their field site and sampling time (June-August), indicating differential regulation of certain proteins in response to environmental or developmental factors. Peroxidases, class II chitinases, pectinesterases, and osmotins were among the proteins more abundant later in the growing season (July-August) as compared to early in the season (June). We did not detect significant differences between fungicide Shirlan treated and untreated field samples in two growing seasons. Using ABPP, we showed differential activity of serine hydrolases and ß-glycosidases under greenhouse and field conditions and across a growing season. Furthermore, the activity of serine hydrolases and ß-glycosidases, including proteins related to biotic stress tolerance, decreased as the season progressed. The generated proteomics data would facilitate further studies aiming at understanding mechanisms of molecular plant physiology in agricultural fields and help applying effective strategies to mitigate biotic and abiotic stresses.

High-Resolution Proteomic Profiling Shows Sexual Dimorphism in Zebrafish Heart-Associated Proteins.

Understanding the molecular basis of sexual dimorphism in the cardiovascular system may contribute to the improvement of the outcome in biological, pharmacological, and toxicological studies as well as on the development of sex-based drugs and therapeutic approaches. Label-free protein quantification using high-resolution mass spectrometry was applied to detect sex-based proteome differences in the heart of zebrafish Danio rerio. Out of almost 3000 unique identified proteins in the heart, 79 showed significant abundance differences between male and female fish. The functional differences were mapped using enrichment analyses. Our results suggest that a large amount of materials needed for reproduction (e.g., sugars, lipids, proteins, etc.) may impose extra pressure on blood, vessels, and heart on their way toward the ovaries. In the present study, the female's heart shows a clear sexual dimorphism by changing abundance levels of numerous proteins, which could be a way to safely overcome material-induced elevated pressures. These proteins belong to the immune system, oxidative stress response, drug metabolization, detoxification, energy, metabolism, and so on. In conclusion, we showed that sex can induce dimorphism at the molecular level in nonsexual organs such as heart and must be considered as an important factor in cardiovascular research. Data are available via ProteomeXchange with identifier PXD023506.

OmicLoupe: facilitating biological discovery by interactive exploration of multiple omic datasets and statistical comparisons.

BACKGROUND: Visual exploration of gene product behavior across multiple omic datasets can pinpoint technical limitations in data and reveal biological trends. Still, such exploration is challenging as there is a need for visualizations that are tailored for the purpose. RESULTS: The OmicLoupe software was developed to facilitate visual data exploration and provides more than 15 interactive cross-dataset visualizations for omics data. It expands visualizations to multiple datasets for quality control, statistical comparisons and overlap and correlation analyses, while allowing for rapid inspection and downloading of selected features. The usage of OmicLoupe is demonstrated in three different studies, where it allowed for detection of both technical data limitations and biological trends across different omic layers. An example is an analysis of SARS-CoV-2 infection based on two previously published studies, where OmicLoupe facilitated the identification of gene products with consistent expression changes across datasets at both the transcript and protein levels. CONCLUSIONS: OmicLoupe provides fast exploration of omics data with tailored visualizations for comparisons within and across data layers. The interactive visualizations are highly informative and are expected to be useful in various analyses of both newly generated and previously published data. OmicLoupe is available at quantitativeproteomics.org/omicloupe.

An integrated transcriptomic- and proteomic-based approach to evaluate the human skin sensitization potential of glyphosate and its commercial agrochemical formulations.

We investigated the skin sensitization hazard of glyphosate, the surfactant polyethylated tallow amine (POEA) and two commercial glyphosate-containing formulations using different omics-technologies based on a human dendritic cell (DC)-like cell line. First, the GARD™skin assay, investigating changes in the expression of 200 transcripts upon cell exposure to xenobiotics, was used for skin sensitization prediction. POEA and the formulations were classified as skin sensitizers while glyphosate alone was classified as a non-sensitizer. Interestingly, the mixture of POEA together with glyphosate displayed a similar sensitizing prediction as POEA alone, indicating that glyphosate likely does not increase the sensitizing capacity when associated with POEA. Moreover, mass spectrometry analysis identified differentially regulated protein groups and predicted molecular pathways based on a proteomic approach in response to cell exposures with glyphosate, POEA and the glyphosate-containing formulations. Based on the protein expression data, predicted pathways were linked to immunologically relevant events and regulated proteins further to cholesterol biosynthesis and homeostasis as well as to autophagy, identifying novel aspects of DC responses after exposure to xenobiotics. In summary, we here present an integrative analysis involving advanced technologies to elucidate the molecular mechanisms behind DC activation in the skin sensitization process triggered by the investigated agrochemical materials. SIGNIFICANCE: The use of glyphosate has increased worldwide, and much effort has been made to improve risk assessments and to further elucidate the mechanisms behind any potential human health hazard of this chemical and its agrochemical formulations. In this context, omics-based techniques can provide a multiparametric approach, including several biomarkers, to expand the mechanistic knowledge of xenobiotics-induced toxicity. Based on this, we performed the integration of GARD™skin and proteomic data to elucidate the skin sensitization hazard of POEA, glyphosate and its two commercial mixtures, and to investigate cellular responses more in detail on protein level. The proteomic data indicate the regulation of immune response-related pathways and proteins associated with cholesterol biosynthesis and homeostasis as well as to autophagy, identifying novel aspects of DC responses after exposure to xenobiotics. Therefore, our data show the applicability of a multiparametric integrated approach for the mechanism-based hazard evaluation of xenobiotics, eventually complementing decision making in the holistic risk assessment of chemicals regarding their allergenic potential in humans.

Proteomics of PTI and Two ETI Immune Reactions in Potato Leaves.

Plants have a variety of ways to defend themselves against pathogens. A commonly used model of the plant immune system is divided into a general response triggered by pathogen-associated molecular patterns (PAMPs), and a specific response triggered by effectors. The first type of response is known as PAMP triggered immunity (PTI), and the second is known as effector-triggered immunity (ETI). To obtain better insight into changes of protein abundance in immunity reactions, we performed a comparative proteomic analysis of a PTI and two different ETI models (relating to Phytophthora infestans) in potato. Several proteins showed higher abundance in all immune reactions, such as a protein annotated as sterol carrier protein 2 that could be interesting since Phytophthora species are sterol auxotrophs. RNA binding proteins also showed altered abundance in the different immune reactions. Furthermore, we identified some PTI-specific changes of protein abundance, such as for example, a glyoxysomal fatty acid beta-oxidation multifunctional protein and a MAR-binding protein. Interestingly, a lysine histone demethylase was decreased in PTI, and that prompted us to also analyze protein methylation in our datasets. The proteins upregulated explicitly in ETI included several catalases. Few proteins were regulated in only one of the ETI interactions. For example, histones were only downregulated in the ETI-Avr2 interaction, and a putative multiprotein bridging factor was only upregulated in the ETI-IpiO interaction. One example of a methylated protein that increased in the ETI interactions was a serine hydroxymethyltransferase.

Towards a standardized bioinformatics infrastructure for N- and O-glycomics.

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N- and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.

NormalyzerDE: Online Tool for Improved Normalization of Omics Expression Data and High-Sensitivity Differential Expression Analysis.

Technical biases are introduced in omics data sets during data generation and interfere with the ability to study biological mechanisms. Several normalization approaches have been proposed to minimize the effects of such biases, but fluctuations in the electrospray current during liquid chromatography-mass spectrometry gradients cause local and sample-specific bias not considered by most approaches. Here we introduce a software named NormalyzerDE that includes a generic retention time (RT)-segmented approach compatible with a wide range of global normalization approaches to reduce the effects of time-resolved bias. The software offers straightforward access to multiple normalization methods, allows for data set evaluation and normalization quality assessment as well as subsequent or independent differential expression analysis using the empirical Bayes Limma approach. When evaluated on two spike-in data sets the RT-segmented approaches outperformed conventional approaches by detecting more peptides (8-36%) without loss of precision. Furthermore, differential expression analysis using the Limma approach consistently increased recall (2-35%) compared to analysis of variance. The combination of RT-normalization and Limma was in one case able to distinguish 108% (2597 vs 1249) more spike-in peptides compared to traditional approaches. NormalyzerDE provides widely usable tools for performing normalization and evaluating the outcome and makes calculation of subsequent differential expression statistics straightforward. The program is available as a web server at http://quantitativeproteomics.org/normalyzerde .

Patient-Derived Xenograft Models Reveal Intratumor Heterogeneity and Temporal Stability in Neuroblastoma.

Patient-derived xenografts (PDX) and the Avatar, a single PDX mirroring an individual patient, are emerging tools in preclinical cancer research. However, the consequences of intratumor heterogeneity for PDX modeling of biomarkers, target identification, and treatment decisions remain underexplored. In this study, we undertook serial passaging and comprehensive molecular analysis of neuroblastoma orthotopic PDXs, which revealed strong intrinsic genetic, transcriptional, and phenotypic stability for more than 2 years. The PDXs showed preserved neuroblastoma-associated gene signatures that correlated with poor clinical outcome in a large cohort of patients with neuroblastoma. Furthermore, we captured spatial intratumor heterogeneity using ten PDXs from a single high-risk patient tumor. We observed diverse growth rates, transcriptional, proteomic, and phosphoproteomic profiles. PDX-derived transcriptional profiles were associated with diverse clinical characteristics in patients with high-risk neuroblastoma. These data suggest that high-risk neuroblastoma contains elements of both temporal stability and spatial intratumor heterogeneity, the latter of which complicates clinical translation of personalized PDX-Avatar studies into preclinical cancer research.Significance: These findings underpin the complexity of PDX modeling as a means to advance translational applications against neuroblastoma. Cancer Res; 78(20); 5958-69. ©2018 AACR.

In Vitro Evolution of Antibodies Inspired by In Vivo Evolution.

In vitro generation of antibodies often requires variable domain sequence evolution to adapt the protein in terms of affinity, specificity, or developability. Such antibodies, including those that are of interest for clinical development, may have their origins in a diversity of immunoglobulin germline genes. Others and we have previously shown that antibodies of different origins tend to evolve along different, preferred trajectories. Apart from substitutions within the complementary determining regions, evolution may also, in a germline gene-origin-defined manner, be focused to residues in the framework regions, and even to residues within the protein core, in many instances at a substantial distance from the antibody's antigen-binding site. Examples of such germline origin-defined patterns of evolution are described. We propose that germline gene-preferred substitution patterns offer attractive alternatives that should be considered in efforts to evolve antibodies intended for therapeutic use with respect to appropriate affinity, specificity, and product developability. We also hypothesize that such germline gene-origin-defined in vitro evolution hold potential to result in products with limited immunogenicity, as similarly evolved antibodies will be parts of conventional, in vivo-generated antibody responses and thus are likely to have been seen by the immune system in the past.

Comparative Membrane-Associated Proteomics of Three Different Immune Reactions in Potato.

Plants have evolved different types of immune reactions but large-scale proteomics about these processes are lacking, especially in the case of agriculturally important crop pathosystems. We have established a system for investigating PAMP-triggered immunity (PTI) and two different effector-triggered immunity (ETI; triggered by Avr2 or IpiO) responses in potato. The ETI responses are triggered by molecules from the agriculturally important Phytophthora infestans interaction. To perform large-scale membrane protein-based comparison of these responses, we established a method to extract proteins from subcellular compartments in leaves. In the membrane fractions that were subjected to quantitative proteomics analysis, we found that most proteins regulated during PTI were also regulated in the same way in ETI. Proteins related to photosynthesis had lower abundance, while proteins related to oxidative and biotic stress, as well as those related to general antimicrobial defense and cell wall degradation, were found to be higher in abundance. On the other hand, we identified a few proteins-for instance, an ABC transporter-like protein-that were only found in the PTI reaction. Furthermore, we also identified proteins that were regulated only in ETI interactions. These included proteins related to GTP binding and heterotrimeric G-protein signaling, as well as those related to phospholipase signaling.

Antibody Heavy Chain Variable Domains of Different Germline Gene Origins Diversify through Different Paths.

B cells produce antibodies, key effector molecules in health and disease. They mature their properties, including their affinity for antigen, through hypermutation events; processes that involve, e.g., base substitution, codon insertion and deletion, often in association with an isotype switch. Investigations of antibody evolution define modes whereby particular antibody responses are able to form, and such studies provide insight important for instance for development of efficient vaccines. Antibody evolution is also used in vitro for the design of antibodies with improved properties. To better understand the basic concepts of antibody evolution, we analyzed the mutational paths, both in terms of amino acid substitution and insertions and deletions, taken by antibodies of the IgG isotype. The analysis focused on the evolution of the heavy chain variable domain of sets of antibodies, each with an origin in 1 of 11 different germline genes representing six human heavy chain germline gene subgroups. Investigated genes were isolated from cells of human bone marrow, a major site of antibody production, and characterized by next-generation sequencing and an in-house bioinformatics pipeline. Apart from substitutions within the complementarity determining regions, multiple framework residues including those in protein cores were targets of extensive diversification. Diversity, both in terms of substitutions, and insertions and deletions, in antibodies is focused to different positions in the sequence in a germline gene-unique manner. Altogether, our findings create a framework for understanding patterns of evolution of antibodies from defined germline genes.