Barcoded sequencing workflow for high throughput digitization of hybridoma antibody variable domain sequences

Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning

Tailored enzymes are crucial for the transition to a sustainable bioeconomy. However, enzyme engineering is laborious and failure-prone due to its reliance on serendipity. The efficiency and success rates of engineering campaigns may be improved by applying machine learning to map the sequence-activity landscape based on small experimental data sets. Yet, it often proves challenging to reliably model large sequence spaces while keeping the experimental effort tractable. To address this challenge, we present an integrated pipeline combining large-scale screening with active machine learning, which we applied to engineer an artificial metalloenzyme (ArM) catalyzing a new-to-nature hydroamination reaction. Combining lab automation and next-generation sequencing, we acquired sequence-activity data for several thousand ArM variants. We then used Gaussian process regression to model the activity landscape and guide further screening rounds. Critical characteristics of our pipeline include the cost-effective generation of information-rich data sets, the integration of an explorative round to improve the model's performance, and the inclusion of experimental noise. Our approach led to an order-of-magnitude boost in the hit rate while making efficient use of experimental resources. Search strategies like this should find broad utility in enzyme engineering and accelerate the development of novel biocatalysts.

Genotyped functional screening of soluble Fab clones enables in-depth analysis of mutation effects

Monoclonal antibodies (mAbs) and their fragments are widely used in therapeutics, diagnostics and basic research. Although display methods such as phage display offer high-throughput, affinities of individual antibodies need to be accurately measured in soluble format. We have developed a screening platform capable of providing genotyped functional data from a total of 9216 soluble, individual antigen binding fragment (Fab) clones by employing next-generation sequencing (NGS) with hierarchical indexing. Full-length, paired variable domain sequences (VL-VH) are linked to functional screening data, enabling in-depth analysis of mutation effects. The platform was applied to four phage display-selected scFv/Fab screening projects and one site-saturation VH affinity maturation project. Genotyped functional screening simultaneously enabled the identification of affinity improving mutations in the VH domain of Fab 49A3 recognizing Dengue virus non-structural protein 1 (NS1) serotype 2 and informed on VH residue positions which cannot be changed from wild-type without decreasing the affinity. Genotype-based identification revealed to us the extent of intraclonal signal variance inherent to single point screening data, a phenomenon often overlooked in the field. Moreover, genotyped screening eliminated the redundant selection of identical genotypes for further study and provided a new analysis tool to evaluate the success of phage display selections and remaining clonal diversity in the screened repertoires.

Multiplexed volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and ssEM on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (green fluorescent protein, glial fibrillary acidic protein, calbindin, parvalbumin, voltage-gated potassium channel subfamily A member 2, vesicular glutamate transporter 1, postsynaptic density protein 95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with spectral unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure with superimposition of the multiple fluorescence channels. Using this approach we could document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

A Two-Step Golden Gate Cloning Procedure for the Generation of Natively Paired YSD Fab Libraries

In vitro antibody display libraries have emerged as powerful tools for a streamlined discovery of novel antibody binders. While in vivo antibody repertoires are matured and selected as a specific pair of variable heavy and light chains (VH and VL) with optimal specificity and affinity, during the recombinant generation of in vitro libraries, the native sequence pairing is not maintained. Here we describe a cloning method that combines the flexibility and versatility of in vitro antibody display with the advantages of natively paired VH-VL antibodies. In this regard, VH-VL amplicons are cloned via a two-step Golden Gate cloning procedure, allowing the display of Fab fragments on yeast cells.

Characterization of Variable Region Genes and Discovery of Key Recognition Sites in the Complementarity Determining Regions of the Anti-Thiacloprid Monoclonal Antibody

Sequence-defined recombinant antibodies (rAbs) have emerged as alternatives to hybridoma-secreted monoclonal antibodies (mAbs) for performing immunoassays. However, the polyploidy nature of hybridomas often leads to the coexistence of aberrant or non-specific functional variable region (VR) gene transcripts, which complicates the identification of correct VR sequences. Herein, we introduced the use of LC-MS/MS combined with next-generation sequencing to characterize VR sequences in an anti-thiacloprid mAb, which was produced by a hybridoma with genetic antibody diversity. The certainty of VR sequences was verified by the functional analysis based on the recombinant antibody (rAb) expressed by HEK293 mammalian cells. The performance of the rAb was similar to that of the parental mAb, with IC50 values of 0.73 and 0.46 μg/L as measured by ELISAs. Moreover, molecular docking analysis revealed that Ser52 (H-CDR2), Trp98, and Trp93 (L-CDR3) residues in the complementarity determining regions (CDRs) of the identified VR sequences predominantly contributed to thiacloprid-specific recognition through hydrogen bonds and the CH-π interaction. Through single-site-directed alanine mutagenesis, we found that Trp98 and Trp93 (L-CDR3) showed high affinity to thiacloprid, while Ser52 (H-CDR2) had an auxiliary effect on the specific binding. This study presents an efficient and reliable way to determine the key recognition sites of hapten-specific mAbs, facilitating the improvement of antibody properties.

Dynamics of heavy chain junctional length biases in antibody repertoires

Antibody variable domain sequence diversity is generated by recombination of germline segments. The third complementarity-determining region of the heavy chain (CDR H3) is the region of highest sequence diversity and is formed by the joining of heavy chain V_H, D_H and J_H germline segments combined with random nucleotide trimming and additions between these segments. We show that CDR H3 and junctional segment length distributions are biased in human antibody repertoires as a function of V_H, V_L and J_H germline segment utilization. Most length biases are apparent in the naive and antigen experienced B cell compartments but not in nonproductive recombination products, indicating B cell selection as a major driver of these biases. Our findings reveal biases in the antibody CDR H3 diversity landscape shaped by V_H, V_L, and J_H germline segment use during naive and antigen-experienced repertoire selection.

Sankar et al. investigate the junctional length biases (determining antibody binding potential) as a function of germline gene usage in antibody repertoires. They show that CDR H3 and junction length are biased by V_H, V_L, and J_H germline segment usage and these biases are apparent in both naive and antigen-experienced repertoires but not in non-productive repertoires.

Nanoscale integration of single cell biologics discovery processes using optofluidic manipulation and monitoring

The new and rapid advancement in the complexity of biologics drug discovery has been driven by a deeper understanding of biological systems combined with innovative new therapeutic modalities, paving the way to breakthrough therapies for previously intractable diseases. These exciting times in biomedical innovation require the development of novel technologies to facilitate the sophisticated, multifaceted, high-paced workflows necessary to support modern large molecule drug discovery. A high-level aspiration is a true integration of "lab-on-a-chip" methods that vastly miniaturize cellulmical experiments could transform the speed, cost, and success of multiple workstreams in biologics development. Several microscale bioprocess technologies have been established that incrementally address these needs, yet each is inflexibly designed for a very specific process thus limiting an integrated holistic application. A more fully integrated nanoscale approach that incorporates manipulation, culture, analytics, and traceable digital record keeping of thousands of single cells in a relevant nanoenvironment would be a transformative technology capable of keeping pace with today's rapid and complex drug discovery demands. The recent advent of optical manipulation of cells using light-induced electrokinetics with micro- and nanoscale cell culture is poised to revolutionize both fundamental and applied biological research. In this review, we summarize the current state of the art for optical manipulation techniques and discuss emerging biological applications of this technology. In particular, we focus on promising prospects for drug discovery workflows, including antibody discovery, bioassay development, antibody engineering, and cell line development, which are enabled by the automation and industrialization of an integrated optoelectronic single-cell manipulation and culture platform. Continued development of such platforms will be well positioned to overcome many of the challenges currently associated with fragmented, low-throughput bioprocess workflows in biopharma and life science research.

Massively parallel single-cell B-cell receptor sequencing enables rapid discovery of diverse antigen-reactive antibodies

Obtaining full-length antibody heavy- and light-chain variable regions from individual B cells at scale remains a challenging problem. Here we use high-throughput single-cell B-cell receptor sequencing (scBCR-seq) to obtain accurately paired full-length variable regions in a massively parallel fashion. We sequenced more than 250,000 B cells from rat, mouse and human repertoires to characterize their lineages and expansion. In addition, we immunized rats with chicken ovalbumin and profiled antigen-reactive B cells from lymph nodes of immunized animals. The scBCR-seq data recovered 81% (n = 56/69) of B-cell lineages identified from hybridomas generated from the same set of B cells subjected to scBCR-seq. Importantly, scBCR-seq identified an additional 710 candidate lineages not recovered as hybridomas. We synthesized, expressed and tested 93 clones from the identified lineages and found that 99% (n = 92/93) of the clones were antigen-reactive. Our results establish scBCR-seq as a powerful tool for antibody discovery.

Immune repertoire mining for rapid affinity optimization of mouse monoclonal antibodies

Traditional hybridoma and B cell cloning antibody discovery platforms have inherent limits in immune repertoire sampling depth. One consequence is that monoclonal antibody (mAb) leads often lack the necessary affinity for therapeutic applications, thus requiring labor-intensive and time-consuming affinity in vitro engineering optimization steps. Here, we show that high-affinity variants of mouse-derived mAbs can be rapidly obtained by testing of somatic sequence variants obtained by deep sequencing of antibody variable regions in immune repertories from immunized mice, even with a relatively sparse sampling of sequence variants from large sequence datasets. Affinity improvements can be achieved for mAbs with a wide range of affinities. The optimized antibody variants derived from immune repertoire mining have no detectable in vitro off-target binding and have in vivo clearance comparable to the parental mAbs, essential properties in therapeutic antibody leads. As generation of antibody variants in vitro is replaced by mining of variants generated in vivo, the procedure can be applied to rapidly identify affinity-optimized mAb variants.

High-throughput retrieval of physical DNA for NGS-identifiable clones in phage display library

In antibody discovery, in-depth analysis of an antibody library and high-throughput retrieval of clones in the library are crucial to identifying and exploiting rare clones with different properties. However, existing methods have technical limitations, such as low process throughput from the laborious cloning process and waste of the phenotypic screening capacity from unnecessary repetitive tests on the dominant clones. To overcome the limitations, we developed a new high-throughput platform for the identification and retrieval of clones in the library, TrueRepertoire™. This new platform provides highly accurate sequences of the clones with linkage information between heavy and light chains of the antibody fragment. Additionally, the physical DNA of clones can be retrieved in high throughput based on the sequence information. We validated the high accuracy of the sequences and demonstrated that there is no platform-specific bias. Moreover, the applicability of TrueRepertoire™ was demonstrated by a phage-displayed single-chain variable fragment library targeting human hepatocyte growth factor protein.

A toolbox of IgG subclass-switched recombinant monoclonal antibodies for enhanced multiplex immunolabeling of brain

Generating recombinant monoclonal antibodies (R-mAbs) from mAb-producing hybridomas offers numerous advantages that increase the effectiveness, reproducibility, and transparent reporting of research. We report here the generation of a novel resource in the form of a library of recombinant R-mAbs validated for neuroscience research. We cloned immunoglobulin G (IgG) variable domains from cryopreserved hybridoma cells and input them into an integrated pipeline for expression and validation of functional R-mAbs. To improve efficiency over standard protocols, we eliminated aberrant Sp2/0-Ag14 hybridoma-derived variable light transcripts using restriction enzyme treatment. Further, we engineered a plasmid backbone that allows for switching of the IgG subclasses without altering target binding specificity to generate R-mAbs useful in simultaneous multiplex labeling experiments not previously possible. The method was also employed to rescue IgG variable sequences and generate functional R-mAbs from a non-viable cryopreserved hybridoma. All R-mAb sequences and plasmids will be archived and disseminated from open source suppliers.

The immune system fights off disease-causing microbes using antibodies: Y-shaped proteins that each bind to a specific foreign molecule. Indeed, these proteins bind so tightly and so specifically that they can pick out a single target in a complex mixture of different molecules. This property also makes them useful in research. For example, neurobiologists can use antibodies to mark target proteins in thin sections of brain tissue. This reveals their position inside brain cells, helping to link the structure of the brain to the roles the different parts of this structure perform.

To use antibodies in this way, scientists need to be able to produce them in large quantities without losing their target specificity. The most common way to do this is with cells called hybridomas. A hybridoma is a hybrid of an antibody-producing immune cell and a cancer cell, and it has properties of both. From the immune cell, it inherits the genes to make a specific type of antibody. From the cancer cell, it inherits the ability to go on dividing forever. In theory, hybridomas should be immortal antibody factories, but they have some limitations. They are expensive to keep alive, hard to transport between labs, and their genes can be unstable. Problems can creep into their genetic code, halting their growth or changing the targets their antibodies recognize. When this happens, scientists can lose vital research tools.

Instead of keeping the immune cells alive, an alternative approach is to make recombinant antibodies. Rather than store the whole cell, this approach just stores the parts of the genes that encode antibody target-specificity. Andrews et al. set out to convert a valuable toolbox of neuroscience antibodies into recombinant form. This involved copying the antibody genes from a large library of preserved hybridoma cells. However, many hybridomas also carry genes that produce non-functional antibodies. A step in the process removed these DNA sequences, ensuring that only working antibodies made it into the final library. Using frozen cells made it possible to recover antibody genes from hybridoma cells that could no longer grow.

The recombinant DNA sequences provide a permanent record of useful antibodies. Not only does this prevent the loss of research tools, it is also much more shareable than living cells. Modifications to the DNA sequences in the library allow for the use of many antibodies at once. This could help when studying the interactions between different molecules in the brain. Toolkits like these could also make it easier to collaborate, and to reproduce data gathered by different researchers around the world.