Perforin-2 is a pore-forming effector of endocytic escape in cross-presenting dendritic cells.

During initiation of antiviral and antitumor T cell-mediated immune responses, dendritic cells (DCs) cross-present exogenous antigens on major histocompatibility complex (MHC) class I molecules. Cross-presentation relies on the unusual "leakiness" of endocytic compartments in DCs, whereby internalized proteins escape into the cytosol for proteasome-mediated generation of MHC I-binding peptides. Given that type 1 conventional DCs excel at cross-presentation, we searched for cell type-specific effectors of endocytic escape. We devised an assay suitable for genetic screening and identified a pore-forming protein, perforin-2 (Mpeg1), as a dedicated effector exclusive to cross-presenting cells. Perforin-2 was recruited to antigen-containing compartments, where it underwent maturation, releasing its pore-forming domain. Mpeg1-/- mice failed to efficiently prime CD8+ T cells to cell-associated antigens, revealing an important role for perforin-2 in cytosolic entry of antigens during cross-presentation.

Accurate Label-Free Quantification by directLFQ to Compare Unlimited Numbers of Proteomes.

Recent advances in mass spectrometry-based proteomics enable the acquisition of increasingly large datasets within relatively short times, which exposes bottlenecks in the bioinformatics pipeline. Although peptide identification is already scalable, most label-free quantification (LFQ) algorithms scale quadratic or cubic with the sample numbers, which may even preclude the analysis of large-scale data. Here we introduce directLFQ, a ratio-based approach for sample normalization and the calculation of protein intensities. It estimates quantities via aligning samples and ion traces by shifting them on top of each other in logarithmic space. Importantly, directLFQ scales linearly with the number of samples, allowing analyses of large studies to finish in minutes instead of days or months. We quantify 10,000 proteomes in 10 min and 100,000 proteomes in less than 2 h, a 1000-fold faster than some implementations of the popular LFQ algorithm MaxLFQ. In-depth characterization of directLFQ reveals excellent normalization properties and benchmark results, comparing favorably to MaxLFQ for both data-dependent acquisition and data-independent acquisition. In addition, directLFQ provides normalized peptide intensity estimates for peptide-level comparisons. It is an important part of an overall quantitative proteomic pipeline that also needs to include high sensitive statistical analysis leading to proteoform resolution. Available as an open-source Python package and a graphical user interface with a one-click installer, it can be used in the AlphaPept ecosystem as well as downstream of most common computational proteomics pipelines.

A practical guide to interpreting and generating bottom-up proteomics data visualizations.

Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data figures in this review on GitHub (https://github.com/MannLabs/ProteomicsVisualization).

3'-NADP and 3'-NAADP, Two Metabolites Formed by the Bacterial Type III Effector AvrRxo1.

An arsenal of effector proteins is injected by bacterial pathogens into the host cell or its vicinity to increase virulence. The commonly used top-down approaches inferring the toxic mechanism of individual effector proteins from the host's phenotype are often impeded by multiple targets of different effectors as well as by their pleiotropic effects. Here we describe our bottom-up approach, showing that the bacterial type III effector AvrRxo1 of plant pathogens is an authentic phosphotransferase that produces two novel metabolites by phosphorylating nicotinamide/nicotinic acid adenine dinucleotide at the adenosine 3'-hydroxyl group. Both products of AvrRxo1, 3'-NADP and 3'-nicotinic acid adenine dinucleotide phosphate (3'-NAADP), are substantially different from the ubiquitous co-enzyme 2'-NADP and the calcium mobilizer 2'-NAADP. Interestingly, 3'-NADP and 3'-NAADP have previously been used as inhibitors or signaling molecules but were regarded as "artificial" compounds so far. Our findings now necessitate a shift in thinking about the biological importance of 3'-phosphorylated NAD derivatives.

Time-resolved cell culture assay analyser (TReCCA Analyser) for the analysis of on-line data: data integration--sensor correction--time-resolved IC50 determination.

Time-resolved cell culture assays circumvent the need to set arbitrary end-points and reveal the dynamics of quality controlled experiments. However, they lead to the generation of large data sets, which can represent a complexity barrier to their use. We therefore developed the Time-Resolved Cell Culture Assay (TReCCA) Analyser program to perform standard cell assay analyses efficiently and make sophisticated in-depth analyses easily available. The functions of the program include data normalising and averaging, as well as smoothing and slope calculation, pin-pointing exact change time points. A time-resolved IC50/EC50 calculation provides a better understanding of drug toxicity over time and a more accurate drug to drug comparison. Finally the logarithmic sensor recalibration function, for sensors with an exponential calibration curve, homogenises the sensor output and enables the detection of low-scale changes. To illustrate the capabilities of the TReCCA Analyser, we performed on-line monitoring of dissolved oxygen in the culture media of the breast cancer cell line MCF-7 treated with different concentrations of the anti-cancer drug Cisplatin. The TReCCA Analyser is freely available at www.uni-heidelberg.de/fakultaeten/biowissenschaften/ipmb/biologie/woelfl/Research.html. By introducing the program, we hope to encourage more systematic use of time-resolved assays and lead researchers to fully exploit their data.

Creating functional engineered variants of the single-module non-ribosomal peptide synthetase IndC by T domain exchange.

Non-ribosomal peptide synthetases (NRPSs) are enzymes that catalyze ribosome-independent production of small peptides, most of which are bioactive. NRPSs act as peptide assembly lines where individual, often interconnected modules each incorporate a specific amino acid into the nascent chain. The modules themselves consist of several domains that function in the activation, modification and condensation of the substrate. NRPSs are evidently modular, yet experimental proof of the ability to engineer desired permutations of domains and modules is still sought. Here, we use a synthetic-biology approach to create a small library of engineered NRPSs, in which the domain responsible for carrying the activated amino acid (T domain) is exchanged with natural or synthetic T domains. As a model system, we employ the single-module NRPS IndC from Photorhabdus luminescens that produces the blue pigment indigoidine. As chassis we use Escherichia coli. We demonstrate that heterologous T domain exchange is possible, even for T domains derived from different organisms. Interestingly, substitution of the native T domain with a synthetic one enhanced indigoidine production. Moreover, we show that selection of appropriate inter-domain linker regions is critical for functionality. Taken together, our results extend the engineering avenues for NRPSs, as they point out the possibility of combining domain sequences coming from different pathways, organisms or from conservation criteria. Moreover, our data suggest that NRPSs can be rationally engineered to control the level of production of the corresponding peptides. This could have important implications for industrial and medical applications.