Reliable interpretability of biology-inspired deep neural networks

Abstract 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

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 Employing Mass Spectrometry

Exploration of a highly glycosylated non-covalent protein comples by mass spectreometry is a challenging task due to isobarisicy of the majority of glycoforms. Integration of data from multiple structural levels (released glycan-glycopeptide-protein subunit-protein complex) by means of computational algorithms permits unraveling the hidden diversity of the human chorionic gonadotropin heterodimer, constituting the base for the study of complex glycosylated protein assemblies.<br /

Simultaneous monitoring of monoclonal antibody variants by strong cation-exchange chromatography hyphenated to mass spectrometry to assess biosimilar-ity of rituximab-based biotherapeutics

The increasing importance of biosimilars in the biopharmaceutical market leads to high demands for enhanced protein characterization methods. Different manufacturing processes can lead to a significant variability of biotherapeutics arising from chemical and enzymatic post translational modifications (PTMs), resulting in the co-existence of a plethora of proteoforms with different physicochemical properties. Thus, biosimilarity to the originator product must be proven rigorously. Among these PTMs, N-terminal pyroglutamate formation, C-terminal lysine clipping, glycosylation, glycation, and deamidation lead to differences in the net charge of the protein, resulting in charge variants (CV). To unravel the heterogeneity of these proteoforms, Strong Cat-ion eXchange (SCX) High-Performance Liquid Chromatography (HPLC) is routinely used. However, the use of non-volatile salts makes the technique incompatible for hyphenation to mass spectrometry (MS). Recently, an approach employing volatile salts and a pH gradient was applied for CV analysis, opening the era of SCX-HPLC-MS approaches. Here, we apply an already established SCX-HPLC-MS approach by Füssl et al. to characterize two Rituximab-based biotherapeutics, the originator MabThera® and its Indian copy product Reditux™. The study assessed molecular differences between the two drug products and constitutes the basis for biosimilarity characterization using a fast SCX-HPLC-MS approach

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

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

Glycoproteomics of a single protein: revealing hundreds of thousands of Myozyme® glycoforms by hybrid HPLC-MS approaches

Characterisation of highly glycosylated biopharmaceuticals by mass spectrometry is challenging because of the huge chemical space of co-existent glycoforms, i.e. heterogenous glycoprotein variants. Here, we report the use of an array of HPLC-MS-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 (SAX)-HPLC-MS 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. The large set of interdepend data acquired at different structural levels was integrated using a set of bioinformatics tools and allowed the annotation of intact glycoforms unraveling more than 1,000,000 different intact glycoform structures. Finally, for the first time, we sought to validate the intact glycoform annotations by integrating experimental data on the enzymatically dissected proteoforms revealing the strengths but also intrinsic limitations of this approach for fully characterising 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