Progress toward Proteome-Wide Photo-Cross-Linking to Enable Residue-Level Visualization of Protein Structures and Networks In Vivo.

Cross-linking mass spectrometry (XL-MS) is emerging as a method at the crossroads of structural and cellular biology, uniquely capable of identifying protein-protein interactions with residue-level resolution and on the proteome-wide scale. With the development of cross-linkers that can form linkages inside cells and easily cleave during fragmentation on the mass spectrometer (MS-cleavable cross-links), it has become increasingly facile to identify contacts between any two proteins in complex samples, including in live cells or tissues. Photo-cross-linkers possess the advantages of high temporal resolution and high reactivity, thereby engaging all residue-types (rather than just lysine); nevertheless, photo-cross-linkers have not enjoyed widespread use and are yet to be employed for proteome-wide studies because their products are challenging to identify. Here, we demonstrate the synthesis and application of two heterobifunctional photo-cross-linkers that feature diazirines and N-hydroxy-succinimidyl carbamate groups, the latter of which unveil doubly fissile MS-cleavable linkages upon acyl transfer to protein targets. Moreover, these cross-linkers demonstrate high water-solubility and cell-permeability. Using these compounds, we demonstrate the feasibility of proteome-wide photo-cross-linking in cellulo. These studies elucidate a small portion of Escherichia coli's interaction network, albeit with residue-level resolution. With further optimization, these methods will enable the detection of protein quinary interaction networks in their native environment at residue-level resolution, and we expect that they will prove useful toward the effort to explore the molecular sociology of the cell.

Early Selection of the Amino Acid Alphabet Was Adaptively Shaped by Biophysical Constraints of Foldability.

Whereas modern proteins rely on a quasi-universal repertoire of 20 canonical amino acids (AAs), numerous lines of evidence suggest that ancient proteins relied on a limited alphabet of 10 "early" AAs and that the 10 "late" AAs were products of biosynthetic pathways. However, many nonproteinogenic AAs were also prebiotically available, which begs two fundamental questions: Why do we have the current modern amino acid alphabet and would proteins be able to fold into globular structures as well if different amino acids comprised the genetic code? Here, we experimentally evaluate the solubility and secondary structure propensities of several prebiotically relevant amino acids in the context of synthetic combinatorial 25-mer peptide libraries. The most prebiotically abundant linear aliphatic and basic residues were incorporated along with or in place of other early amino acids to explore these alternative sequence spaces. The results show that foldability was likely a critical factor in the selection of the canonical alphabet. Unbranched aliphatic amino acids were purged from the proteinogenic alphabet despite their high prebiotic abundance because they generate polypeptides that are oversolubilized and have low packing efficiency. Surprisingly, we find that the inclusion of a short-chain basic amino acid also decreases polypeptides' secondary structure potential, for which we suggest a biophysical model. Our results support the view that, despite lacking basic residues, the early canonical alphabet was remarkably adaptive at supporting protein folding and explain why basic residues were only incorporated at a later stage of protein evolution.

Nucleosome recognition and DNA distortion by the Chd1 remodeler in a nucleotide-free state.

Chromatin remodelers are ATP-dependent enzymes that reorganize nucleosomes within all eukaryotic genomes. Here we report a complex of the Chd1 remodeler bound to a nucleosome in a nucleotide-free state, determined by cryo-EM to 2.3 Å resolution. The remodeler stimulates the nucleosome to absorb an additional nucleotide on each strand at two different locations: on the tracking strand within the ATPase binding site and on the guide strand one helical turn from the ATPase motor. Remarkably, the additional nucleotide on the tracking strand is associated with a local transformation toward an A-form geometry, explaining how sequential ratcheting of each DNA strand occurs. The structure also reveals a histone-binding motif, ChEx, which can block opposing remodelers on the nucleosome and may allow Chd1 to participate in histone reorganization during transcription.

SurA is a cryptically grooved chaperone that expands unfolded outer membrane proteins.

The periplasmic chaperone network ensures the biogenesis of bacterial outer membrane proteins (OMPs) and has recently been identified as a promising target for antibiotics. SurA is the most important member of this network, both due to its genetic interaction with the ß-barrel assembly machinery complex as well as its ability to prevent unfolded OMP (uOMP) aggregation. Using only binding energy, the mechanism by which SurA carries out these two functions is not well-understood. Here, we use a combination of photo-crosslinking, mass spectrometry, solution scattering, and molecular modeling techniques to elucidate the key structural features that define how SurA solubilizes uOMPs. Our experimental data support a model in which SurA binds uOMPs in a groove formed between the core and P1 domains. This binding event results in a drastic expansion of the rest of the uOMP, which has many biological implications. Using these experimental data as restraints, we adopted an integrative modeling approach to create a sparse ensemble of models of a SurA•uOMP complex. We validated key structural features of the SurA•uOMP ensemble using independent scattering and chemical crosslinking data. Our data suggest that SurA utilizes three distinct binding modes to interact with uOMPs and that more than one SurA can bind a uOMP at a time. This work demonstrates that SurA operates in a distinct fashion compared to other chaperones in the OMP biogenesis network.

Multivariate data analysis of growth medium trends affecting antibody glycosylation.

Use of multivariate data analysis for the manufacturing of biologics has been increasing due to more widespread use of data-generating process analytical technologies (PAT) promoted by the US FDA. To generate a large dataset on which to apply these principles, we used an in-house model CHO DG44 cell line cultured in automated micro bioreactors alongside PAT with four commercial growth media focusing on antibody quality through N-glycosylation profiles. Using univariate analyses, we determined that different media resulted in diverse amounts of terminal galactosylation, high mannose glycoforms, and aglycosylation. Due to the amount of in-process data generated by PAT instrumentation, multivariate data analysis was necessary to ascertain which variables best modeled our glycan profile findings. Our principal component analysis revealed components that represent the development of glycoforms into terminally galacotosylated forms (G1F and G2F), and another that encompasses maturation out of high mannose glycoforms. The partial least squares model additionally incorporated metabolic values to link these processes to glycan outcomes, especially involving the consumption of glutamine. Overall, these approaches indicated a tradeoff between cellular productivity and product quality in terms of the glycosylation. This work illustrates the use of multivariate analytical approaches that can be applied to complex bioprocessing problems for identifying potential solutions.

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System.

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using Chinese hamster ovary (CHO) cells, culture and process conditions must be optimized to maximize antibody titers and achieve target quality profiles. Typically, this optimization uses automated microscale bioreactors (15 mL) to screen multiple process conditions in parallel. Optimization criteria include culture performance and the critical quality attributes (CQAs) of the monoclonal antibody (mAb) product, which may impact its efficacy and safety. Culture performance metrics include cell growth and nutrient consumption, while the CQAs include the mAb's N-glycosylation and aggregation profiles, charge variants, and molecular weight. This detailed protocol describes how to purify and subsequently analyze HCCF samples produced by an automated microbioreactor system to gain valuable performance metrics and outputs. First, an automated protein A fast protein liquid chromatography (FPLC) method is used to purify the mAb from harvested cell culture samples. Once concentrated, the glycan profiles are analyzed by mass spectrometry using a specific platform (refer to the Table of Materials). Antibody molecular weights and aggregation profiles are determined using size exclusion chromatography-multiple angle light scattering (SEC-MALS), while charge variants are analyzed using microchip capillary zone electrophoresis (mCZE). In addition to the culture performance metrics captured during the bioreactor process (i.e., culture viability, cell counts, and common metabolites including glutamine, glucose, lactate, and ammonia), spent media is analyzed to identify limiting nutrients to improve the feeding strategies and overall process design. Therefore, a detailed protocol for the absolute quantification of amino acids by liquid chromatography-mass spectrometry (LC-MS) of spent media is also described. The methods used in this protocol take advantage of high-throughput platforms that are compatible for large numbers of small-volume samples.

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells.

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts, media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE's with a higher number of variables and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

The role of mass spectrometry in the characterization of biologic protein products.

INTRODUCTION: Mass spectrometry (MS) is widely used in the characterization of biomolecules including peptide and protein therapeutics. These biotechnology products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Advances in MS instrumentation and techniques have enhanced protein characterization capabilities and supported an increased development of biopharmaceutical products. Areas covered: This review describes recent developments in MS-based biotherapeutic analysis including sequence determination, post-translational modifications (PTMs) and higher order structure (HOS) analysis along with improvements in ionization and dissociation methods. An outlook of emerging applications of MS in the lifecycle of product development such as comparability, biosimilarity and quality control practices is also presented. Expert commentary: MS-based methods have established their utility in the analysis of new biotechnology products and their lifecycle appropriate implementation. In the future, MS will likely continue to grow as one of the leading protein identification and characterization techniques in the biopharmaceutical industry landscape.

A Retrospective Evaluation of the Use of Mass Spectrometry in FDA Biologics License Applications.

The characterization sections of biologics license applications (BLAs) approved by the United States Food and Drug Administration (FDA) between 2000 and 2015 were investigated to examine the extent of the use of mass spectrometry. Mass spectrometry was found to be integral to the characterization of these biotherapeutics. Of the 80 electronically submitted monoclonal antibody and protein biotherapeutic BLAs included in this study, 79 were found to use mass spectrometric workflows for protein or impurity characterization. To further examine how MS is being used in successful BLAs, the applications were filtered based on the type and number of quality attributes characterized, the mass spectrometric workflows used (peptide mapping, intact mass analysis, and cleaved glycan analysis), the methods used to introduce the proteins into the gas phase (ESI, MALDI, or LC-ESI), and the specific types of instrumentation used. Analyses were conducted over a time course based on the FDA BLA approval to determine if any trends in utilization could be observed over time. Additionally, the different classes of protein-based biotherapeutics among the approved BLAs were clustered to determine if any trends could be attributed to the specific type of biotherapeutic. Graphical Abstract ᅟ.