Biology subjects

Rapp, E.

Publications and source records attributed to Rapp, E..

5 recordsLinked to original sources

bioRxiv2021

Cell-free glycoengineering of the recombinant SARS-CoV-2 spike glycoprotein

The baculovirus-insect cell expression system is readily utilized to produce viral glycoproteins for research as well as for subunit vaccines and vaccine candidates, for instance against SARS-CoV-2 infections. However, the glycoforms of recombinant proteins derived from this expression system are inherently different from mammalian cell-derived glycoforms with mainly complex-type N-glycans attached, and the impact of these differences in protein glycosylation on the immunogenicity is severely underinvestigated. This applies also to the SARS-CoV-2 spike glycoprotein, which is the antigen target of all licensed vaccines and vaccine candidates including virus like particles and subunit vaccines that are variants of the spike protein. Here, we expressed the transmembrane-deleted human {beta}-1,2 N-acetlyglucosamintransferases I and II (MGAT1{triangleup}TM and MGAT2{triangleup}TM) and the {beta}-1,4-galactosyltransferase (GalT{triangleup}TM) in E. coli to in-vitro remodel the N-glycans of a recombinant SARS-CoV-2 spike glycoprotein derived from insect cells. In a cell-free sequential one-pot reaction, fucosylated and afucosylated paucimannose-type N-glycans were converted to complex-type galactosylated N-glycans. In the future, this in-vitro glycoengineering approach can be used to efficiently generate a wide range of N-glycans on antigens considered as vaccine candidates for animal trials and preclinical testing to better characterize the impact of N-glycosylation on immunity and to improve the efficacy of protein subunit vaccines.

synthetic biology↗

bioRxiv2021

Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies of Glycopeptide Data

Glycoproteome profiling (glycoproteomics) is a powerful yet analytically challenging research tool. The complex tandem mass spectra generated from glycopeptide mixtures require sophisticated analysis pipelines for structural determination. Diverse software aiding the process have appeared, but their relative performance remains untested. Conducted through the HUPO Human Proteome Project - Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates the performance of informatics solutions for system-wide glycopeptide analysis. Mass spectrometry-based glycoproteomics datasets from human serum were shared with all teams. The relative team performance for N- and O-glycopeptide data analysis was comprehensively established and validated through orthogonal performance tests. Excitingly, several high-performance glycoproteomics informatics solutions were identified. While the study illustrated that significant informatics challenges remain, as indicated by a high discordance between annotated glycopeptides, lists of high-confidence (consensus) glycopeptides were compiled from the standardised team reports. Deep analysis of the performance data revealed key performance-associated search variables and led to recommendations for improved "high coverage" and "high accuracy" glycoproteomics search strategies. This study concludes that diverse software for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies, and specifies key variables that may guide future software developments and assist informatics decision-making in glycoproteomics.

biochemistry↗

bioRxiv2020

Estimation of Kinematics from Inertial Measurement Units Using a Combined Deep Learning and Optimization Framework

The difficulty of estimating joint kinematics remains a critical barrier toward widespread use of inertial measurement units in biomechanics. Traditional sensor-fusion filters are largely reliant on magnetometer readings, which may be disturbed in uncontrolled environments. Careful sensor-to-segment alignment and calibration strategies are also necessary, which may burden users and lead to further error in uncontrolled settings. We introduce a new framework that combines deep learning and top-down optimization to accurately predict lower extremity joint angles directly from inertial data, without relying on magnetometer readings. We trained deep neural networks on a large set of synthetic inertial data derived from a clinical marker-based motion-tracking database of hundreds of subjects. We used data augmentation techniques and an automated calibration approach to reduce error due to variability in sensor placement and limb alignment. On left-out subjects, lower extremity kinematics could be predicted with a mean ({+/-} STD) root mean squared error of less than 1.27 {degrees} ({+/-} 0.38 {degrees}) in flexion/extension, less than 2.52 {degrees} ({+/-} 0.98 {degrees}) in ad/abduction, and less than 3.34 {degrees} ({+/-} 1.02 {degrees}) internal/external rotation, across walking and running trials. Errors decreased exponentially with the amount of training data, confirming the need for large datasets when training deep neural networks. While this framework remains to be validated with true inertial measurement unit (IMU) data, the results presented here are a promising advance toward convenient estimation of gait kinematics in natural environments. Progress in this direction could enable large-scale studies and offer an unprecedented view into disease progression, patient recovery, and sports biomechanics.

bioengineering↗

bioRxiv2020

Glycosyltransferase POMGNT1 deficiency affects N-cadherin-mediated cell-cell adhesion

Defects in protein O-mannosylation lead to severe congenital muscular dystrophies known as -dystroglycanopathy. A hallmark of these diseases is the loss of the O-mannose-bound matriglycan on -dystroglycan, which leads to a reduction in cell adhesion to the extracellular matrix. Mutations in protein O-mannose {beta}1,2-N-acetylglucosaminyltransferase 1 (POMGNT1), which is crucial for the elongation of O-mannosyl glycans, are mainly associated with muscle-eye-brain (MEB) disease. In addition to defects in cell-extracellular matrix adhesion, aberrant cell-cell adhesion has occasionally been observed in response to defects in POMGNT1. However, direct molecular mechanisms are largely unknown. We used POMGNT1 knock-out HEK293T cells and fibroblasts from a MEB patient to gain a deeper insight into the molecular changes in POMGNT1 deficiency. A combination of biochemical and molecular biological techniques with proteomics, glycoproteomics and glycomics revealed that a lack of POMGNT1 activity strengthens cell-cell adhesion. We demonstrate that the altered intrinsic adhesion properties are due to an increased abundance of N-cadherin (N-Cdh). In addition, site-specific changes in the N-glycan structures in the extracellular domain of N-Cdh were detected, which positively impact on homotypic interactions. We found that in POMGNT1 deficient cells ERK1/2 and p38 signaling pathways are activated and transcriptional changes that are comparable to the epithelial-mesenchymal transition (EMT) are triggered, defining a possible molecular mechanism underlying the observed phenotype. Our study indicates that changes in cadherin-mediated cell-cell adhesion and other EMT-related processes may contribute to the complex clinical symptoms of MEB or -dystroglycanopathy in general, and suggests a previously underestimated impact of changes in O-mannosylation on N-glycosylation.

biochemistry↗

bioRxiv2020

The medaka alg2 mutant is a model for hypo-N-glycosylation-associated retinitis pigmentosa

Patients suffering from Congenital Disorders of Glycosylation (CDG) carry mutations in components of the evolutionarily highly conserved protein-glycosylation-machinery. Employing targeted genome editing, we modeled alleles in medaka fish based on a mutation described in an ALG2-index patient. The multisystemic phenotypes in our alg2 model closely resembled the patients syndromes. Molecularly, the mutation results in a reduction of the abundance of N-glycans without altering the profile of glycan structures in fish as well as in patient fibroblasts. This hypo-N-glycosylation impacted on protein abundance in two directions. We discovered a putative compensatory upregulation of the basic glycosylation and glycoprotein processing machinery highlighting the regulatory topology of the network. Conversely, proteins of the retinal phototransduction machinery were massively downregulated in the alg2 model. Those relate to the specific loss of rod photoreceptors that fail to be maintained in the alg2 mutants, a condition known as retinitis pigmentosa. Transient supply of human or medaka alg2 mRNA efficiently rescued the phenotypic spectrum and restored viability demonstrating that our alg2 model delivers key traits for the potential treatment of the disorder.

developmental biology↗