HappyTools: A software for high-throughput HPLC data processing and quantitation

<div><p>High-performance liquid chromatography (HPLC) is widely used for absolute quantitation. The advent of new columns and HPLC technology has enabled higher sample throughput, and hence, larger scale studies that perform quantitation on different sample types (<i>e</i>.<i>g</i>. healthy controls <i>vs</i>. patients with rheumatoid arthritis) using HPLC are becoming feasible. However, there remains a lack of methods that can analyse the increased number of HPLC samples. To address this in part, the modular toolkit HappyTools has been developed for the high-throughput targeted quantitation of HPLC measurements. HappyTools enables the user to create an automated workflow that includes retention time (t_r) calibration, data extraction and the calculation of several quality criteria for data curation. HappyTools has been tested on a biopharmaceutical standard and previously published clinical samples. The results show comparable accuracy between HappyTools, Waters Empower and ThermoFisher Chromeleon. However, HappyTools offered superior precision and throughput when compared with Waters Empower and ThermoFisher Chromeleon. HappyTools is released under the Apache 2.0 license, both the source code and a Windows binary can be freely downloaded from <a href="https://github.com/Tarskin/HappyTools" target="_blank">https://github.com/Tarskin/HappyTools</a>.</p></div

ThermoFisher Chromeleon vs. HappyTools comparison of total IgG and ACPA-IgG.

<p>A total of 36 UHPLC measurements was used to compare the quantitation as performed by HappyTools with the original quantitation performed using ThermoFisher Chromeleon. Data points that derived from IgG are indicated by an open circle, while data points that derive from ACPA-IgG are portrayed by closed circles. The results show that both programs yield a similar result and more importantly that there is a significant (p < 0.0001) correlation between the two data sets.</p

Biopharmaceutical quantitation using Waters Empower, ThermoFisher Chromeleon and HappyTools.

<p>A set of 9 replicates of V-Tag labelled tryptic glycopeptides were used to compare the three different software tools. The results show that all methods yield comparable accuracy, while HappyTools yields superior precision. Peak 4a and peak 4b could not be quantified separately using ThermoFisher Chromeleon but was instead quantified as a singular peak. The individual values for peaks 4a and peak 4b obtained from Waters Empower and HappyTools were summed to compare with ThermoFisher Chromeleon.</p

DataSheet_1_Role of N-Glycosylation in FcγRIIIa interaction with IgG.pdf

Immunoglobulins G (IgG) and their Fc gamma receptors (FcγRs) play important roles in our immune system. The conserved N-glycan in the Fc region of IgG1 impacts interaction of IgG with FcγRs and the resulting effector functions, which has led to the design of antibody therapeutics with greatly improved antibody-dependent cell cytotoxicity (ADCC) activities. Studies have suggested that also N-glycosylation of the FcγRIII affects receptor interactions with IgG, but detailed studies of the interaction of IgG1 and FcγRIIIa with distinct N-glycans have been hindered by the natural heterogeneity in N-glycosylation. In this study, we employed comprehensive genetic engineering of the N-glycosylation capacities in mammalian cell lines to express IgG1 and FcγRIIIa with different N-glycan structures to more generally explore the role of N-glycosylation in IgG1:FcγRIIIa binding interactions. We included FcγRIIIa variants of both the 158F and 158V allotypes and investigated the key N-glycan features that affected binding affinity. Our study confirms that afucosylated IgG1 has the highest binding affinity to oligomannose FcγRIIIa, a glycan structure commonly found on Asn162 on FcγRIIIa expressed by NK cells but not monocytes or recombinantly expressed FcγRIIIa.</p

Table_1_Role of N-Glycosylation in FcγRIIIa interaction with IgG.xlsx

Immunoglobulins G (IgG) and their Fc gamma receptors (FcγRs) play important roles in our immune system. The conserved N-glycan in the Fc region of IgG1 impacts interaction of IgG with FcγRs and the resulting effector functions, which has led to the design of antibody therapeutics with greatly improved antibody-dependent cell cytotoxicity (ADCC) activities. Studies have suggested that also N-glycosylation of the FcγRIII affects receptor interactions with IgG, but detailed studies of the interaction of IgG1 and FcγRIIIa with distinct N-glycans have been hindered by the natural heterogeneity in N-glycosylation. In this study, we employed comprehensive genetic engineering of the N-glycosylation capacities in mammalian cell lines to express IgG1 and FcγRIIIa with different N-glycan structures to more generally explore the role of N-glycosylation in IgG1:FcγRIIIa binding interactions. We included FcγRIIIa variants of both the 158F and 158V allotypes and investigated the key N-glycan features that affected binding affinity. Our study confirms that afucosylated IgG1 has the highest binding affinity to oligomannose FcγRIIIa, a glycan structure commonly found on Asn162 on FcγRIIIa expressed by NK cells but not monocytes or recombinantly expressed FcγRIIIa.</p