Human immunoglobulin A (IgA) is the most prevalent antibody class at mucosal sites with an important role in mucosal defense. Little is known about the impact of N-glycan modifications of IgA1 and IgA2 on binding to the Fcα receptor (FcαRI), which is also heavily glycosylated at its extracellular domain. Here, we transiently expressed human epidermal growth factor receptor 2 (HER2)-binding monomeric IgA1, IgA2m(1), and IgA2m(2) variants in Nicotiana benthamiana ΔXT/FT plants lacking the enzymes responsible for generating nonhuman N-glycan structures. By coinfiltrating IgA with the respective glycan-modifying enzymes, we generated IgA carrying distinct homogenous N-glycans. We demonstrate that distinctly different N-glycan profiles did not influence antigen binding or the overall structure and integrity of the IgA antibodies but did affect their thermal stability. Using size-exclusion chromatography, differential scanning and isothermal titration calorimetry, surface plasmon resonance spectroscopy, and molecular modeling, we probed distinct IgA1 and IgA2 glycoforms for binding to four different FcαRI glycoforms and investigated the thermodynamics and kinetics of complex formation. Our results suggest that different N-glycans on the receptor significantly contribute to binding affinities for its cognate ligand. We also noted that full-length IgA and FcαRI form a mixture of 1:1 and 1:2 complexes tending toward a 1:1 stoichiometry due to different IgA tailpiece conformations that make it less likely that both binding sites are simultaneously occupied. In conclusion, N-glycans of human IgA do not affect its structure and integrity but its thermal stability, and FcαRI N-glycans significantly modulate binding affinity to IgA.

In spite of the abundance of glycoproteins in biological processes, relatively little three-dimensional structural data is available for glycan structures. Here, we study the structure and flexibility of the vast majority of mammalian oligosaccharides appearing in N- and O-glycosylated proteins using a bottom up approach. We report the conformational free-energy landscapes of all relevant glycosidic linkages as obtained from local elevation simulations and subsequent umbrella sampling. To the best of our knowledge, this represents the first complete conformational library for the construction of N- and O-glycan structures. Next, we systematically study the effect of neighboring residues, by extensively simulating all relevant trisaccharides and one tetrasaccharide. This allows for an unprecedented comparison of disaccharide linkages in large oligosaccharides. With a small number of exceptions, the conformational preferences in the larger structures are very similar as in the disaccharides. This, finally, allows us to suggest several efficient approaches to construct complete N- and O-glycans on glycoproteins, as exemplified on two relevant examples.

Surface plasmon field-enhanced fluorescence energy transfer is employed for sensitive optical readout of a reversible hairpin aptamer assay that is suitable for continuous monitoring of low-molecular-weight chemical analytes. A hairpin aptamer specific to adenosine and adenosine triphosphate with Alexa Fluor 647 fluorophore attached to its 5′ end was anchored via 3′ end thiol to a gold thin film. Molecular spacers were used to control the distance of the fluorophore from the surface in the aptamer “off” and “on” states. The specific binding of the target analyte changes the aptamer conformation, which alters the distance of the fluorophore from the gold surface and translates to variations in the detected fluorescence intensity. The plasmonically mediated fluorescence signal increases the measured signal-to-noise ratio and allows for real-time observation of the analyte binding. Theoretical as well as experimental study of the optical signal dependence on fluorophore orientation, design of spacers, and angular distribution of collected light is presented for rational design of the assay. The detected sensor signal increased by a factor as large as 23 upon switching the aptamer from the “off” to “on” state due to the hairpin opening associated with the specific capture of target analyte.

The increasing biotechnological interest in human IgE antibodies demands advanced systems which allow their proper expression. However, this is still a challenge due to the complexity of the molecule, particularly regarding the diverse N-glycosylation pattern. Here, we present the expression of recombinant IgE in wild type and glycan-engineered Nicotiana benthamiana plants and in-depth N-glycosylation analyses. Mass spectrometric profiling revealed that plant IgE has a site occupancy rate that ranges from non-occupied at glycosite 6 (GS6) to 100% occupancy at GS1 and 2. Similarly to human cell-derived IgE, plant versions carry complex N-glycans at GS1-5 and oligomannosidic structures at GS7. Computational modelling suggests that spatial position (or orientation) of glycans can impair processing or site occupancy on adjacent glycosites. IgE expressed in glycoengineered and wild type plants carry, respectively, GnGn and plant-typical GnGnXF structures at large homogeneity. This contrasts with the glycan diversity of HEK cell-derived IgE, carrying at least 20 different glycoforms. Importantly, IgE glycoengineering allows the control of its glycosylation, a so far unmet need when using well-established expression systems. This enables the elucidation of possible carbohydrate-dependent IgE functions. Targeted glycosylation of recombinant proteins may provide an advantage in therapeutic applications. Despite increasing biotechnological interest in IgE antibodies, knowledge and impact of glycosylation on this antibody class are scarce. With the ability to glyco-engineer recombinant IgE, we provide an important step towards the generation of IgE with other targeted N-glycans. This will facilitate detailed structure-function studies and may lead to the production of IgE with optimized activities.

Advancements in deep learning and availability of medical imaging data have led to the use of CNN-based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction-based tests in COVID-19 diagnosis, CT images offer an applicable supplement with their high sensitivity rates. Here, we study the classification of COVID-19 pneumonia and non-COVID-19 pneumonia in chest CT scans using efficient deep learning methods to be readily implemented by any hospital. We report our deep network framework design that encompasses Convolutional Neural Networks and bidirectional Long Short Term Memory architectures. Our study achieved high specificity (COVID-19 pneumonia: 98.3%, non-COVID-19 pneumonia: 96.2% Healthy: 89.3%) and high sensitivity (COVID-19 pneumonia: 84.0%, non-COVID-19 pneumonia: 93.9% Healthy: 94.9%) in classifying COVID-19 pneumonia, non-COVID-19 pneumonia and healthy patients. Next, we provide visual explanations for the Convolutional Neural Network predictions with gradient-weighted class activation mapping (Grad-CAM). The results provided a model explainability by showing that Ground Glass Opacities, indicators of COVID-19 pneumonia disease, were captured by our convolutional neural network. Finally, we have implemented our approach in three hospitals proving its compatibility and efficiency.

The Arabidopsis thaliana Fasciclin like arabinogalactan protein 4 (FLA4) locus is required for normal root growth in a linear genetic pathway with the FEI1 and FEI2 loci coding for receptor-like kinases. The two Fas1 domains of FLA4 are conserved among angiosperms but only the C-terminal Fas1 domain is required for genetic function. We show that at low salt deletion of the N-terminal Fas1 domain of transgenic FLA4 leads to enhanced root elongation compared to the tandem Fas1 wild type version. Modeling the hypothetical interaction between FLA4 and FEI1 we show that the predicted interaction is predominantly involving the C-terminal Fas1 domain. Relative conformational mobility between the two FLA4 Fas1 domains might regulate the interaction with the FEI receptor kinases. We therefore speculate that the FLA4 FEI complex might be a sensor for environmental conditions in the apoplast.