Mammalian oocytes store proteins for the early embryo on cytoplasmic lattices.

Mammalian oocytes are filled with poorly understood structures called cytoplasmic lattices. First discovered in the 1960s and speculated to correspond to mammalian yolk, ribosomal arrays, or intermediate filaments, their function has remained enigmatic to date. Here, we show that cytoplasmic lattices are sites where oocytes store essential proteins for early embryonic development. Using super-resolution light microscopy and cryoelectron tomography, we show that cytoplasmic lattices are composed of filaments with a high surface area, which contain PADI6 and subcortical maternal complex proteins. The lattices associate with many proteins critical for embryonic development, including proteins that control epigenetic reprogramming of the preimplantation embryo. Loss of cytoplasmic lattices by knocking out PADI6 or the subcortical maternal complex prevents the accumulation of these proteins and results in early embryonic arrest. Our work suggests that cytoplasmic lattices enrich maternally provided proteins to prevent their premature degradation and cellular activity, thereby enabling early mammalian development.

inSPIRE: An Open-Source Tool for Increased Mass Spectrometry Identification Rates Using Prosit Spectral Prediction.

Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase peptide spectrum match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example, when dealing with nonspecific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large-scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides.

iBench: A ground truth approach for advanced validation of mass spectrometry identification method.

The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source. The proof-of-concept application to tryptic proteome digestions, immunopeptidomes, and synthetic peptide libraries dissected the impact that noncanonical peptides could have on the identification of canonical peptides by Mascot search with rescoring via Percolator (Mascot+Percolator).

Database search engines and target database features impinge upon the identification of post-translationally cis-spliced peptides in HLA class I immunopeptidomes.

Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines - that is, Mascot, Mascot+Percolator, and PEAKS DB - as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods' performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated.

ER-aminopeptidase 1 determines the processing and presentation of an immunotherapy-relevant melanoma epitope.

Dissecting the different steps of the processing and presentation of tumor-associated antigens is a key aspect of immunotherapies enabling to tackle the immune response evasion attempts of cancer cells. The immunodominant glycoprotein gp100209-217 epitope, which is liberated from the melanoma differentiation antigen gp100PMEL17 , is part of immunotherapy trials. By analyzing different human melanoma cell lines, we here demonstrate that a pool of N-terminal extended peptides sharing the common minimal epitope is generated by melanoma proteasome subtypes. In vitro and in cellulo experiments indicate that ER-resident aminopeptidase 1 (ERAP1)-but not ERAP2-defines the processing of this peptide pool thereby modulating the T-cell recognition of melanoma cells. By combining the outcomes of our studies and others, we can sketch the complex processing and endogenous presentation pathway of the gp100209-217 -containing epitope/peptides, which are produced by proteasomes and are translocated to the vesicular compartment through different pathways, where the precursor peptides that reach the endoplasmic reticulum are further processed by ERAP1. The latter step enhances the activation of epitope-specific T lymphocytes, which might be a target to improve the efficiency of anti-melanoma immunotherapy.

Proteolytic dynamics of human 20S thymoproteasome.

An efficient immunosurveillance of CD8+ T cells in the periphery depends on positive/negative selection of thymocytes and thus on the dynamics of antigen degradation and epitope production by thymoproteasome and immunoproteasome in the thymus. Although studies in mouse systems have shown how thymoproteasome activity differs from that of immunoproteasome and strongly impacts the T cell repertoire, the proteolytic dynamics and the regulation of human thymoproteasome are unknown. By combining biochemical and computational modeling approaches, we show here that human 20S thymoproteasome and immunoproteasome differ not only in the proteolytic activity of the catalytic sites but also in the peptide transport. These differences impinge upon the quantity of peptide products rather than where the substrates are cleaved. The comparison of the two human 20S proteasome isoforms depicts different processing of antigens that are associated to tumors and autoimmune diseases.

Post-Translational Peptide Splicing and T Cell Responses.

CD8+ T cell specificity depends on the recognition of MHC class I-epitope complexes at the cell surface. These epitopes are mainly produced via degradation of proteins by the proteasome, generating fragments of the original sequence. However, it is now clear that proteasomes can produce a significant portion of epitopes by reshuffling the antigen sequence, thus expanding the potential antigenic repertoire. MHC class I-restricted spliced epitopes have been described in tumors and infections, suggesting an unpredicted relevance of these peculiar peptides. We review current knowledge about proteasome-catalyzed peptide splicing (PCPS), the emerging rules governing this process, and the potential implications for our understanding and therapeutic use of CD8+ T cells, as well as mechanisms generating other non-canonical antigenic epitopes targeted by the T cell response.

PEITH(Θ): perfecting experiments with information theory in Python with GPU support.

Motivation: Different experiments provide differing levels of information about a biological system. This makes it difficult, a priori, to select one of them beyond mere speculation and/or belief, especially when resources are limited. With the increasing diversity of experimental approaches and general advances in quantitative systems biology, methods that inform us about the information content that a given experiment carries about the question we want to answer, become crucial. Results: PEITH(Θ) is a general purpose, Python framework for experimental design in systems biology. PEITH(Θ) uses Bayesian inference and information theory in order to derive which experiments are most informative in order to estimate all model parameters and/or perform model predictions. Availability and implementation: https://github.com/MichaelPHStumpf/Peitho. Contact: m.stumpf@imperial.ac.uk or juliane.liepe@mpibpc.mpg.de.

Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection.

The hematopoietic stem cell (HSC) niche provides essential microenvironmental cues for the production and maintenance of HSCs within the bone marrow. During inflammation, hematopoietic dynamics are perturbed, but it is not known whether changes to the HSC-niche interaction occur as a result. We visualize HSCs directly in vivo, enabling detailed analysis of the 3D niche dynamics and migration patterns in murine bone marrow following Trichinella spiralis infection. Spatial statistical analysis of these HSC trajectories reveals two distinct modes of HSC behavior: (a) a pattern of revisiting previously explored space and (b) a pattern of exploring new space. Whereas HSCs from control donors predominantly follow pattern (a), those from infected mice adopt both strategies. Using detailed computational analyses of cell migration tracks and life-history theory, we show that the increased motility of HSCs following infection can, perhaps counterintuitively, enable mice to cope better in deteriorating HSC-niche microenvironments following infection. Stem Cells 2017;35:2292-2304.

CD8(+) T cells of Listeria monocytogenes-infected mice recognize both linear and spliced proteasome products.

CD8(+) T cells responding to infection recognize pathogen-derived epitopes presented by MHC class-I molecules. While most of such epitopes are generated by proteasome-mediated antigen cleavage, analysis of tumor antigen processing has revealed that epitopes may also derive from proteasome-catalyzed peptide splicing (PCPS). To determine whether PCPS contributes to epitope processing during infection, we analyzed the fragments produced by purified proteasomes from a Listeria monocytogenes polypeptide. Mass spectrometry identified a known H-2K(b) -presented linear epitope (LLO296-304 ) in the digests, as well as four spliced peptides that were trimmed by ERAP into peptides with in silico predicted H-2K(b) binding affinity. These spliced peptides, which displayed sequence similarity with LLO296-304 , bound to H-2K(b) molecules in cellular assays and one of the peptides was recognized by CD8(+) T cells of infected mice. This spliced epitope differed by one amino acid from LLO296-304 and double staining with LLO296-304 - and spliced peptide-folded MHC multimers showed that LLO296-304 and its spliced variant were recognized by the same CD8(+) T cells. Thus, PCPS multiplies the variety of peptides that is processed from an antigen and leads to the production of epitope variants that can be recognized by cross-reacting pathogen-specific CD8(+) T cells. Such mechanism may reduce the chances for pathogen immune evasion.

Information theory and signal transduction systems: from molecular information processing to network inference.

Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design.

The T210M Substitution in the HLA-a*02:01 gp100 Epitope Strongly Affects Overall Proteasomal Cleavage Site Usage and Antigen Processing.

MHC class I-restricted epitopes, which carry a tumor-specific mutation resulting in improved MHC binding affinity, are preferred T cell receptor targets in innovative adoptive T cell therapies. However, T cell therapy requires efficient generation of the selected epitope. How such mutations may affect proteasome-mediated antigen processing has so far not been studied. Therefore, we analyzed by in vitro experiments the effect on antigen processing and recognition of a T210M exchange, which previously had been introduced into the melanoma gp100209-217 tumor epitope to improve the HLA-A*02:01 binding and its immunogenicity. A quantitative analysis of the main steps of antigen processing shows that the T210M exchange affects proteasomal cleavage site usage within the mutgp100201-230 polypeptide, leading to the generation of an unique set of cleavage products. The T210M substitution qualitatively affects the proteasome-catalyzed generation of spliced and non-spliced peptides predicted to bind HLA-A or -B complexes. The T210M substitution also induces an enhanced production of the mutgp100209-217 epitope and its N-terminally extended peptides. The T210M exchange revealed no effect on ERAP1-mediated N-terminal trimming of the precursor peptides. However, mutant N-terminally extended peptides exhibited significantly increased HLA-A*02:01 binding affinity and elicited CD8(+) T cell stimulation in vitro similar to the wtgp100209-217 epitope. Thus, our experiments demonstrate that amino acid exchanges within an epitope can result in the generation of an altered peptide pool with new antigenic peptides and in a wider CD8(+) T cell response also towards N-terminally extended versions of the minimal epitope.

Proteasome isoforms exhibit only quantitative differences in cleavage and epitope generation.

Immunoproteasomes are considered to be optimised to process Ags and to alter the peptide repertoire by generating a qualitatively different set of MHC class I epitopes. Whether the immunoproteasome at the biochemical level, influence the quality rather than the quantity of the immuno-genic peptide pool is still unclear. Here, we quantified the cleavage-site usage by human standard- and immunoproteasomes, and proteasomes from immuno-subunit-deficient mice, as well as the peptides generated from model polypeptides. We show in this study that the different proteasome isoforms can exert significant quantitative differences in the cleavage-site usage and MHC class I restricted epitope production. However, independent of the proteasome isoform and substrates studied, no evidence was obtained for the abolishment of the specific cleavage-site usage, or for differences in the quality of the peptides generated. Thus, we conclude that the observed differences in MHC class I restricted Ag presentation between standard- and immunoproteasomes are due to quantitative differences in the proteasome-generated antigenic peptides.

Inference of random walk models to describe leukocyte migration.

While the majority of cells in an organism are static and remain relatively immobile in their tissue, migrating cells occur commonly during developmental processes and are crucial for a functioning immune response. The mode of migration has been described in terms of various types of random walks. To understand the details of the migratory behaviour we rely on mathematical models and their calibration to experimental data. Here we propose an approximate Bayesian inference scheme to calibrate a class of random walk models characterized by a specific, parametric particle re-orientation mechanism to observed trajectory data. We elaborate the concept of transition matrices (TMs) to detect random walk patterns and determine a statistic to quantify these TM to make them applicable for inference schemes. We apply the developed pipeline to in vivo trajectory data of macrophages and neutrophils, extracted from zebrafish that had undergone tail transection. We find that macrophage and neutrophils exhibit very distinct biased persistent random walk patterns, where the strengths of the persistence and bias are spatio-temporally regulated. Furthermore, the movement of macrophages is far less persistent than that of neutrophils in response to wounding.

Maximizing the information content of experiments in systems biology.

Our understanding of most biological systems is in its infancy. Learning their structure and intricacies is fraught with challenges, and often side-stepped in favour of studying the function of different gene products in isolation from their physiological context. Constructing and inferring global mathematical models from experimental data is, however, central to systems biology. Different experimental setups provide different insights into such systems. Here we show how we can combine concepts from Bayesian inference and information theory in order to identify experiments that maximize the information content of the resulting data. This approach allows us to incorporate preliminary information; it is global and not constrained to some local neighbourhood in parameter space and it readily yields information on parameter robustness and confidence. Here we develop the theoretical framework and apply it to a range of exemplary problems that highlight how we can improve experimental investigations into the structure and dynamics of biological systems and their behavior.

Protein degradation by human 20S proteasomes elucidates the interplay between peptide hydrolysis and splicing.

If and how proteasomes catalyze not only peptide hydrolysis but also peptide splicing is an open question that has divided the scientific community. The debate has so far been based on immunopeptidomics, in vitro digestions of synthetic polypeptides as well as ex vivo and in vivo experiments, which could only indirectly describe proteasome-catalyzed peptide splicing of full-length proteins. Here we develop a workflow-and cognate software - to analyze proteasome-generated non-spliced and spliced peptides produced from entire proteins and apply it to in vitro digestions of 15 proteins, including well-known intrinsically disordered proteins such as human tau and α-Synuclein. The results confirm that 20S proteasomes produce a sizeable variety of cis-spliced peptides, whereas trans-spliced peptides are a minority. Both peptide hydrolysis and splicing produce peptides with well-defined characteristics, which hint toward an intricate regulation of both catalytic activities. At protein level, both non-spliced and spliced peptides are not randomly localized within protein sequences, but rather concentrated in hotspots of peptide products, in part driven by protein sequence motifs and proteasomal preferences. At sequence level, the different peptide sequence preference of peptide hydrolysis and peptide splicing suggests a competition between the two catalytic activities of 20S proteasomes during protein degradation.

The maintenance of oocytes in the mammalian ovary involves extreme protein longevity.

Women are born with all of their oocytes. The oocyte proteome must be maintained with minimal damage throughout the woman's reproductive life, and hence for decades. Here we report that oocyte and ovarian proteostasis involves extreme protein longevity. Mouse ovaries had more extremely long-lived proteins than other tissues, including brain. These long-lived proteins had diverse functions, including in mitochondria, the cytoskeleton, chromatin and proteostasis. The stable proteins resided not only in oocytes but also in long-lived ovarian somatic cells. Our data suggest that mammals increase protein longevity and enhance proteostasis by chaperones and cellular antioxidants to maintain the female germline for long periods. Indeed, protein aggregation in oocytes did not increase with age and proteasome activity did not decay. However, increasing protein longevity cannot fully block female germline senescence. Large-scale proteome profiling of ~8,890 proteins revealed a decline in many long-lived proteins of the proteostasis network in the aging ovary, accompanied by massive proteome remodeling, which eventually leads to female fertility decline.

P38 and JNK have opposing effects on persistence of in vivo leukocyte migration in zebrafish.

The recruitment and migration of macrophages and neutrophils is an important process during the early stages of the innate immune system in response to acute injury. Transgenic pu.1:EGFP zebrafish permit the acquisition of leukocyte migration trajectories during inflammation. Currently, these high-quality live-imaging data are mainly analysed using general statistics, for example, cell velocity. Here, we present a spatio-temporal analysis of the cell dynamics using transition matrices, which provide information of the type of cell migration. We find evidence that leukocytes exhibit types of migratory behaviour, which differ from previously described random walk processes. Dimethyl sulfoxide treatment decreased the level of persistence at early time points after wounding and ablated temporal dependencies observed in untreated embryos. We then use pharmacological inhibition of p38 and c-Jun N-terminal kinase mitogen-activated protein kinases to determine their effects on in vivo leukocyte migration patterns and discuss how they modify the characteristics of the cell migration process. In particular, we find that their respective inhibition leads to decreased and increased levels of persistent motion in leukocytes following wounding. This example shows the high level of information content, which can be gained from live-imaging data if appropriate statistical tools are used.

InvitroSPI and a large database of proteasome-generated spliced and non-spliced peptides.

Noncanonical epitopes presented by Human Leucocyte Antigen class I (HLA-I) complexes to CD8+ T cells attracted the spotlight in the research of novel immunotherapies against cancer, infection and autoimmunity. Proteasomes, which are the main producers of HLA-I-bound antigenic peptides, can catalyze both peptide hydrolysis and peptide splicing. The prediction of proteasome-generated spliced peptides is an objective that still requires a reliable (and large) database of non-spliced and spliced peptides produced by these proteases. Here, we present an extended database of proteasome-generated spliced and non-spliced peptides, which was obtained by analyzing in vitro digestions of 80 unique synthetic polypeptide substrates, measured by different mass spectrometers. Peptides were identified through invitroSPI method, which was validated through in silico and in vitro strategies. The peptide product database contains 16,631 unique peptide products (5,493 non-spliced, 6,453 cis-spliced and 4,685 trans-spliced peptide products), and a substrate sequence variety that is a valuable source for predictors of proteasome-catalyzed peptide hydrolysis and splicing. Potential artefacts and skewed results due to different identification and analysis strategies are discussed.

GPU accelerated biochemical network simulation.

MOTIVATION: Mathematical modelling is central to systems and synthetic biology. Using simulations to calculate statistics or to explore parameter space is a common means for analysing these models and can be computationally intensive. However, in many cases, the simulations are easily parallelizable. Graphics processing units (GPUs) are capable of efficiently running highly parallel programs and outperform CPUs in terms of raw computing power. Despite their computational advantages, their adoption by the systems biology community is relatively slow, since differences in hardware architecture between GPUs and CPUs complicate the porting of existing code. RESULTS: We present a Python package, cuda-sim, that provides highly parallelized algorithms for the repeated simulation of biochemical network models on NVIDIA CUDA GPUs. Algorithms are implemented for the three popular types of model formalisms: the LSODA algorithm for ODE integration, the Euler-Maruyama algorithm for SDE simulation and the Gillespie algorithm for MJP simulation. No knowledge of GPU computing is required from the user. Models can be specified in SBML format or provided as CUDA code. For running a large number of simulations in parallel, up to 360-fold decrease in simulation runtime is attained when compared to single CPU implementations. AVAILABILITY: http://cuda-sim.sourceforge.net/