Generating purified protein for GLP toxicology studies (GLP-Tox) represents an important and often rate limiting step in the biopharmaceutical drug development process. Toxicity testing requires large amounts of therapeutic protein (>100 g), typically produced in a single 500-2,500 L bioreactor, using the final CHO clonally derived cell line (CDCL). One approach currently used to save time is to manufacture GLP-Tox material using pools of high-producing CHO CDCLs instead of waiting for the final CDCL. Recently, we reported CHO pools producing mAb titers >7 g/L using piggyBac-mediated gene integration (PB CHO pools). In this study, we wanted to leverage high titer PB CHO pools to produce GLP-Tox material. A detailed product quality attribute (PQA) assessment was conducted comparing PB CHO pools to pooled Top4 CDCLs. Four mAbs were evaluated. First, we found that PB CHO pools expressed all four mAbs at high titers (2.8-4.4 g/L in shake flasks). Second, all four PB CHO pools were aged to 55 generations (Gen). All four PB CHO Pools were found to be suitable over 55 Gen. Finally, we performed bioreactor scale-up. PB CHO pool titers (3.7-4.8 g/L) were similar or higher than the pooled Top 4 CDCLs in 5 L bioreactors (2.4-4.1 g/L). The PQAs of protein derived from PB CHO pools were very similar to pooled Top 4 CHO CDCLs according to multiple orthogonal techniques including peptide mapping analysis. Taken together, these results demonstrate the technical feasibility of using PB CHO pools to manufacture protein for GLP-Tox. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1436-1448, 2017.

Cell culture process conditions including media components and bioreactor operation conditions have a profound impact on recombinant protein quality attributes. Considerable changes in the distribution of galactosylated glycoforms (G0F, G1F, and G2F) were observed across multiple CHO derived recombinant proteins in development at Eli Lilly and Company when switching to a new chemically defined (CD) media platform condition. In the new CD platform, significantly lower G0F percentages and higher G1F and G2F were observed. These changes were of interest as glycosylation heterogeneity can impact the effectiveness of a protein. A systematic investigation was done to understand the root cause of the change and control strategy for galactosylated glycoforms distribution. It was found that changes in asparagine concentration could result in a corresponding change in G0F, G1F, and G2F distribution. A follow-up study examined a wider range of asparagine concentration and it was found that G0F, G1F, and G2F percentage could be titrated by adjusting asparagine concentration. The observed changes in heterogeneity from changing asparagine concentration are due to resulting changes in ammonium metabolism. Further study ascertained that different integrated ammonium level during the cell culture process could control G0F, G1F, and G2F percentage distribution. A mechanism hypothesis is proposed that integrated ammonium level impacts intracellular pH, which further regulates β-1, 4 galactosyltransferase activity.

Chinese hamster ovary (CHO) cells remain the most popular host for the production of biopharmaceutical drugs, particularly monoclonal antibodies (mAbs), bispecific antibodies, and Fc-fusion proteins. Creating and characterizing the stable CHO clonally-derived cell lines (CDCLs) needed to manufacture these therapeutic proteins is a lengthy and laborious process. Therefore, CHO pools have increasingly been used to rapidly produce protein to support and enable preclinical drug development. We recently described the generation of CHO pools yielding mAb titers as high as 7.6 g/L in a 16 day bioprocess using piggyBac transposon-mediated gene integration. In this study, we wanted to understand why the piggyBac pool titers were significantly higher (2-10 fold) than the control CHO pools. Higher titers were the result of a combination of increased average gene copy number, significantly higher messenger RNA levels and the homogeneity (i.e. less diverse population distribution) of the piggyBac pools, relative to the control pools. In order to validate the use of piggyBac pools to support preclinical drug development, we then performed an in-depth product quality analysis of purified protein. The product quality of protein obtained from the piggyBac pools was very similar to the product quality profile of protein obtained from the control pools. Finally, we demonstrated the scalability of these pools from shake flasks to 36L bioreactors. Overall, these results suggest that gram quantities of therapeutic protein can be rapidly obtained from piggyBac CHO pools without significantly changing product quality attributes. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:534-540, 2017.

The study of low-abundance proteins is a challenge to discovery-based proteomics. Mass spectrometry (MS) applications, such as thermal proteome profiling (TPP), face specific challenges in the detection of the whole proteome as a consequence of the use of nondenaturing extraction buffers. TPP is a powerful method for the study of protein thermal stability, but quantitative accuracy is highly dependent on consistent detection. Therefore, TPP can be limited in its amenability to study low-abundance proteins that tend to have stochastic or poor detection by MS. To address this challenge, we incorporated an affinity-purified protein complex sample at submolar concentrations as an isobaric trigger channel into a mutant TPP (mTPP) workflow to provide reproducible detection and quantitation of the low-abundance subunits of the cleavage and polyadenylation factor (CPF) complex. The inclusion of an isobaric protein complex trigger channel increased detection an average of 40× for previously detected subunits and facilitated detection of CPF subunits that were previously below the limit of detection. Importantly, these gains in CPF detection did not cause large changes in melt temperature ( T m ) calculations for other unrelated proteins in the samples, with a high positive correlation between T m estimates in samples with and without isobaric trigger channel addition. Overall, the incorporation of an affinity-purified protein complex as an isobaric trigger channel within a tandem mass tag (TMT) multiplex for mTPP experiments is an effective and reproducible way to gather thermal profiling data on proteins that are not readily detected using the original TPP or mTPP protocols.

The CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein–ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures ( T m ) and relative melt shifts from proteomics abundance data. Here, we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impact the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and have made the R based program Inflect available for research community use through the CRAN repository [McCracken, N. Inflect: Melt Curve Fitting and Melt Shift Analysis. R package version 1.0.3 , 2021]. The Inflect outputs include melt curves for each protein which passes filtering criteria in addition to a data matrix which is directly compatible with downstream packages such as UpsetR for replicate comparisons and identification of biologically relevant changes. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared toward specific applications.

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Thermal Proteome Profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein-ligand, protein-protein, and protein-RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with advancements and improvements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is even more apparent as TPP findings have reported more subtle melt shift changes related to protein post-translational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. To benchmark InflectSSP, we have reanalyzed two publicly available datasets to demonstrate the performance of this publicly available R based program for TPP data analysis. Additionally, we report new findings following temporal treatment of human cells with the small molecule Thapsigargin which induces the unfolded protein response (UPR). InflectSSP analysis of our UPR study revealed highly reproducible target engagement over time while simultaneously providing new insights into the dynamics of UPR induction.

The use of CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impacts the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and will make the R based program Inflect available for research community use. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared towards specific applications.