JAK-STAT signaling maintains homeostasis in T cells and macrophages.

Immune cells need to sustain a state of constant alertness over a lifetime. Yet, little is known about the regulatory processes that control the fluent and fragile balance that is called homeostasis. Here we demonstrate that JAK-STAT signaling, beyond its role in immune responses, is a major regulator of immune cell homeostasis. We investigated JAK-STAT-mediated transcription and chromatin accessibility across 12 mouse models, including knockouts of all STAT transcription factors and of the TYK2 kinase. Baseline JAK-STAT signaling was detected in CD8+ T cells and macrophages of unperturbed mice-but abrogated in the knockouts and in unstimulated immune cells deprived of their normal tissue context. We observed diverse gene-regulatory programs, including effects of STAT2 and IRF9 that were independent of STAT1. In summary, our large-scale dataset and integrative analysis of JAK-STAT mutant and wild-type mice uncovered a crucial role of JAK-STAT signaling in unstimulated immune cells, where it contributes to a poised epigenetic and transcriptional state and helps prepare these cells for rapid response to immune stimuli.

Reliable interpretability of biology-inspired deep neural networks.

Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where real-world concepts are encoded in hidden nodes, which can be ranked by importance and thereby interpreted. In such models trained on single-cell transcriptomes, we previously demonstrated that node-level interpretations lack robustness upon repeated training and are influenced by biases in biological knowledge. Similar studies are missing for related models. Here, we test and extend our methodology for reliable interpretability in P-NET, a biology-inspired model trained on patient mutation data. We observe variability of interpretations and susceptibility to knowledge biases, and identify the network properties that drive interpretation biases. We further present an approach to control the robustness and biases of interpretations, which leads to more specific interpretations. In summary, our study reveals the broad importance of methods to ensure robust and bias-aware interpretability in biology-inspired deep learning.

Glycoproteomics of a Single Protein: Revealing Tens of Thousands of Myozyme Glycoforms by Hybrid HPLC-MS Approaches.

Characterization of highly glycosylated biopharma-ceuticals by mass spectrometry is challenging because of the huge chemical space of coexistent glycoforms present. Here, we report the use of an array of HPLC-mass spectrometry-based approaches at different structural levels of released glycan, glycopeptide, and hitherto unexplored intact glycoforms to scrutinize the biopharmaceutical Myozyme, containing the highly complex lysosomal enzyme recombinant acid α-glucosidase. The intrinsic heterogeneity of recombinant acid α-glucosidase glycoforms was unraveled using a novel strong anion exchange HPLC-mass spectrometry approach involving a pH-gradient of volatile buffers to facilitate chromatographic separation of glycoforms based on their degree of sialylation, followed by the acquisition of native mass spectra in an Orbitrap mass spectrometer. Upon considering the structures of 60 different glycans attached to seven glycosylation sites in the intact protein, the large set of interdependent data acquired at different structural levels was integrated using a set of bioinformatic tools and allowed the annotation of intact glycoforms unraveling more than 1,000,000 putative intact glycoforms. Detectable isoforms also included several mannose-6-phosphate variants, which are essential for directing the drug toward its target, the lysosomes. Finally, for the first time, we sought to validate the intact glycoform annotations by integrating experimental data on the enzymatically dissected proteoforms, which reduced the number of glycoforms supported by experimental evidence to 42,104. The latter verification clearly revealed the strengths but also intrinsic limitations of this approach for fully characterizing such highly complex glycoproteins by mass spectrometry.

Single-cell transcriptomics and epigenomics unravel the role of monocytes in neuroblastoma bone marrow metastasis.

Metastasis is the major cause of cancer-related deaths. Neuroblastoma (NB), a childhood tumor has been molecularly defined at the primary cancer site, however, the bone marrow (BM) as the metastatic niche of NB is poorly characterized. Here we perform single-cell transcriptomic and epigenomic profiling of BM aspirates from 11 subjects spanning three major NB subtypes and compare these to five age-matched and metastasis-free BM, followed by in-depth single cell analyses of tissue diversity and cell-cell interactions, as well as functional validation. We show that cellular plasticity of NB tumor cells is conserved upon metastasis and tumor cell type composition is NB subtype-dependent. NB cells signal to the BM microenvironment, rewiring via macrophage mgration inhibitory factor and midkine signaling specifically monocytes, which exhibit M1 and M2 features, are marked by activation of pro- and anti-inflammatory programs, and express tumor-promoting factors, reminiscent of tumor-associated macrophages. The interactions and pathways characterized in our study provide the basis for therapeutic approaches that target tumor-to-microenvironment interactions.

At-line quantitative profiling of monoclonal antibody products during bioprocessing using HPLC-MS.

(1) Background: The N-glycosylation profile as well as the subunit assembly of monoclonal antibodies (mAbs) are strongly dependent on manufacturing conditions and thus need to be monitored during the bioprocess. Commonly, mAbs are characterized downstream of the fermentation process applying different analytical techniques like released glycan analysis, peptide mapping, or subunit profiling. However, these procedures are time-consuming and difficult to perform in real-time. (2) Methods: We applied a simple HPLC-MS workflow with minimal sample preparation to characterize mAb product quality at the intact protein level at different time points during fermentation. After harvest, the cell culture medium was centrifuged briefly. The supernatant containing the fermentation product was diluted and immediately subjected to HPLC-MS analysis. (3) Results: Besides the product of interest (mAb), the fermentation broth contained misassembled variants, mostly light chain and light chain dimer. The mAb's glycosylation profile changed over time showing an increase in galactosylated variants with G0F/G1F being the most abundant glycoform at all time points of fermentation. Furthermore, expressed protein species were relatively and absolutely quantified. The workflow was very robust despite analyzing a highly complex matrix. Relative standard deviations for retention times were below 0.5% for both intra and inter-day comparison, whereas relative procedural standard deviations for quantification of the different protein species ranged between 7 and 13%. (4) Conclusions: This approach allows for reliable analysis of product profiles of monoclonal antibody species including misassembled subunits and glycosylation variants directly from fermentation broth using a fast and robust HPLC-MS workflow.

Simultaneous Monitoring of Monoclonal Antibody Variants by Strong Cation-Exchange Chromatography Hyphenated to Mass Spectrometry to Assess Quality Attributes of Rituximab-Based Biotherapeutics.

Different manufacturing processes and storage conditions of biotherapeutics can lead to a significant variability in drug products arising from chemical and enzymatic post-translational modifications (PTMs), resulting in the co-existence of a plethora of proteoforms with different physicochemical properties. To unravel the heterogeneity of these proteoforms, novel approaches employing strong cation-exchange (SCX) high-performance liquid chromatography (HPLC) hyphenated to mass spectrometry (MS) using a pH gradient of volatile salts have been developed in recent years. Here, we apply an established SCX-HPLC-MS method to characterize and compare two rituximab-based biotherapeutics, the originator MabThera® and its Indian copy product Reditux™. The study assessed molecular differences between the two drug products in terms of C-terminal lysine variants, glycosylation patterns, and other basic and acidic variants. Overall, MabThera® and Reditux™ displayed differences at the molecular level. MabThera® showed a higher degree of galactosylated and sialylated glycoforms, while Reditux™ showed increased levels of oligomannose and afucosylated glycoforms. Moreover, the two drug products showed differences in terms of basic variants such as C-terminal lysine and N-terminal truncation, present in Reditux™ but not in MabThera®. This study demonstrates the capability of this fast SCX-HPLC-MS approach to compare different drug products and simultaneously assess some of their quality attributes.

Exploring the Chemical Space of Protein Glycosylation in Noncovalent Protein Complexes: An Expedition along Different Structural Levels of Human Chorionic Gonadotropin by Employing Mass Spectrometry.

Modern analytical approaches employing high-resolution mass spectrometry (MS) facilitate the generation of a vast amount of structural data of highly complex glycoproteins. Nevertheless, systematic interpretation of this data at different structural levels remains an analytical challenge. The glycoprotein utilized as a model system in this study, human chorionic gonadotropin (hCG), exists as a heterodimer composed of two heavily glycosylated subunits. In order to unravel the multitude of glycoforms of recombinant hCG (drug product Ovitrelle), we combine established techniques, such as released glycan and glycopeptide analysis, with novel approaches employing high-performance liquid chromatography-mass spectrometry (HPLC-MS) to characterize protein subunits and native MS to analyze the noncovalent hCG complex. Starting from the deconvoluted mass spectrum of dimeric hCG comprising about 50 signals, it was possible to explore the chemical space of hCG glycoforms and elucidate the complexity that hides behind just 50 signals. Systematic, stepwise integration of data obtained at the levels of released glycans, glycopeptides, and subunits using a computational annotation tool allowed us to reveal 1031 underlying glycoforms. Additionally, critical quality attributes such as sialylation and core fucosylation were compared for two batches of Ovitrelle to assess the potential product variability.

Exploring sample preparation and data evaluation strategies for enhanced identification of host cell proteins in drug products of therapeutic antibodies and Fc-fusion proteins.

Manufacturing of biopharmaceuticals involves recombinant protein expression in host cells followed by extensive purification of the target protein. Yet, host cell proteins (HCPs) may persist in the final drug product, potentially reducing its quality with respect to safety and efficacy. Consequently, residual HCPs are closely monitored during downstream processing by techniques such as enzyme-linked immunosorbent assay (ELISA) or high-performance liquid chromatography combined with tandem mass spectrometry (HPLC-MS/MS). The latter is especially attractive as it provides information with respect to protein identities. Although the applied HPLC-MS/MS methodologies are frequently optimized with respect to HCP identification, acquired data is typically analyzed using standard settings. Here, we describe an improved strategy for evaluating HPLC-MS/MS data of HCP-derived peptides, involving probabilistic protein inference and peptide detection in the absence of fragment ion spectra. This data analysis workflow was applied to data obtained for drug products of various biotherapeutics upon protein A affinity depletion. The presented data evaluation strategy enabled in-depth comparative analysis of the HCP repertoires identified in drug products of the monoclonal antibodies rituximab and bevacizumab, as well as the fusion protein etanercept. In contrast to commonly applied ELISA strategies, the here presented workflow is process-independent and may be implemented into existing HPLC-MS/MS setups for drug product characterization and process development. Graphical abstract.

A Simple Strategy to Eliminate Hexosylation Bias in the Relative Quantification of N-Glycosylation in Biopharmaceuticals.

N-glycosylation may affect the safety and efficacy of biopharmaceuticals and is thus monitored during manufacturing. Mass spectrometry of the intact protein is increasingly used to reveal co-existing glycosylation variants. However, quantification of N-glycoforms via this approach may be biased by single hexose residues as introduced by glycation or O-glycosylation. Herein, we describe a simple strategy to reveal actual N-glycoform abundances of therapeutic antibodies, involving experimental determination of glycation levels followed by computational elimination of the "hexosylation bias". We show that actual N-glycoform abundances may significantly deviate from initially determined values. Indeed, glycation may even obscure considerable differences in N-glycosylation patterns of drug product batches. Our observations may thus have implications for biopharmaceutical quality control. Moreover, we solve an instance of the problem of isobaricity, which is fundamental to mass spectrometry.

Dilute-and-shoot analysis of therapeutic monoclonal antibody variants in fermentation broth: a method capability study.

Monoclonal antibodies (mAbs) are widely applied as highly specific and efficient therapeutic agents for various medical conditions, including cancer, inflammatory and autoimmune diseases. As protein production in cellular systems inherently generates a multitude of molecular variants, manufacturing of mAbs requires stringent control in order to ensure safety and efficacy of the drugs. Moreover, monitoring of mAb variants in the course of the fermentation process may allow instant tuning of process parameters to maintain optimal cell culture conditions. Here, we describe a fast and robust workflow for the characterization of mAb variants in fermentation broth. Sample preparation is minimal in that the fermentation broth is shortly centrifuged before dilution and HPLC-MS analysis in a short 15-min gradient run. In a single analysis, N-glycosylation and truncation variants of the expressed mAb are identified at the intact protein level. Simultaneously, absolute quantification of mAb content in fermentation broth is achieved. The whole workflow features excellent robustness as well as retention time and peak area stability. Additional enzymatic removal of N-glycans enables determination of mAb glycation levels, which are subsequently considered in relative N-glycoform quantification to correct for isobaric galactosylation. Several molecular attributes of the expressed therapeutic protein may thus be continuously monitored to ensure the desired product profile. Application of the described workflow in an industrial environment may therefore substantially enhance in-process control in mAb production, as well as targeted biosimilar development.