Resurrection of a clinical antibody: template proteogenomic de novo proteomic sequencing and reverse engineering of an anti-lymphotoxin-α antibody

A Handle on Mass Coincidence Errors in De Novo Sequencing of Antibodies by Bottom-up Proteomics

Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.

In silico λ-dynamics predicts protein binding specificities to modified RNAs

RNA modifications shape gene expression through a smorgasbord of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.

Template-Based Assembly of Proteomic Short Reads For De Novo Antibody Sequencing and Repertoire Profiling

Antibodies can target a vast molecular diversity of antigens. This is achieved by generating a complementary diversity of antibody sequences through somatic recombination and hypermutation. A full understanding of the antibody repertoire in health and disease therefore requires dedicated de novo sequencing methods. Next-generation cDNA sequencing methods have laid the foundation of our current understanding of the antibody repertoire, but these methods share one major limitation in that they target the antibody-producing B-cells, rather than the functional secreted product in bodily fluids. Mass spectrometry-based methods offer an opportunity to bridge this gap between antibody repertoire profiling and bulk serological assays, as they can access antibody sequence information straight from the secreted polypeptide products. In a step to meeting the challenge of mass spectrometry (MS)-based antibody sequencing, we present a fast and simple software tool (Stitch) to map proteomic short reads to user-defined templates with dedicated features for both monoclonal antibody sequencing and profiling of polyclonal antibody repertoires. We demonstrate the use of Stitch by fully reconstructing two monoclonal antibody sequences with >98% accuracy (including I/L assignment); sequencing a Fab from patient serum isolated by reversed-phase liquid chromatography (LC) fractionation against a high background of homologous antibody sequences; sequencing antibody light chains from the urine of multiple-myeloma patients; and profiling the IgG repertoire in sera from patients hospitalized with COVID-19. We demonstrate that Stitch assembles a comprehensive overview of the antibody sequences that are represented in the dataset and provides an important first step toward analyzing polyclonal antibodies and repertoire profiling.

Template-Assisted De Novo Sequencing of SARS-CoV-2 and Influenza Monoclonal Antibodies by Mass Spectrometry

In this study, we used multiple enzyme digestions, coupled with higher-energy collisional dissociation (HCD) and electron-transfer/higher-energy collision dissociation (EThcD) fragmentation to develop a mass-spectrometric (MS) method for determining the complete protein sequence of monoclonal antibodies (mAbs). The method was refined on an mAb of a known sequence, a SARS-CoV-1 antireceptor binding domain (RBD) spike monoclonal antibody. The data were searched using Supernovo to generate a complete template-assisted de novo sequence for this and two SARS-CoV-2 mAbs of known sequences resulting in correct sequences for the variable regions and correct distinction of Ile and Leu residues. We then used the method on a set of 25 antihemagglutinin (HA) influenza antibodies of unknown sequences and determined high confidence sequences for >99% of the complementarity determining regions (CDRs). The heavy-chain and light-chain genes were cloned and transfected into cells for recombinant expression followed by affinity purification. The recombinant mAbs displayed binding curves matching the original mAbs with specificity to the HA influenza antigen. Our findings indicate that this methodology results in almost complete antibody sequence coverage with high confidence results for CDR regions on diverse mAb sequences.

Mass Spectrometry-Based De Novo Sequencing of Monoclonal Antibodies Using Multiple Proteases and a Dual Fragmentation Scheme

Antibody sequence information is crucial to understanding the structural basis for antigen binding and enables the use of antibodies as therapeutics and research tools. Here, we demonstrate a method for direct de novo sequencing of monoclonal IgG from the purified antibody products. The method uses a panel of multiple complementary proteases to generate suitable peptides for de novo sequencing by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a bottom-up fashion. Furthermore, we apply a dual fragmentation scheme, using both stepped high-energy collision dissociation (stepped HCD) and electron-transfer high-energy collision dissociation (EThcD), on all peptide precursors. The method achieves full sequence coverage of the monoclonal antibody herceptin, with an accuracy of 99% in the variable regions. We applied the method to sequence the widely used anti-FLAG-M2 mouse monoclonal antibody, which we successfully validated by remodeling a high-resolution crystal structure of the Fab and demonstrating binding to a FLAG-tagged target protein in Western blot analysis. The method thus offers robust and reliable sequences of monoclonal antibodies.

Proteomics Pipeline for Identifying Variant Proteins in Plasmodium falciparum Parasites Isolated from Children Presenting with Malaria

Plasmodium falciparum variant antigens named erythrocyte membrane protein 1 (PfEMP1) are important targets for developing a protective immunity to malaria caused by P. falciparum. One of the major challenges in P. falciparum proteomics studies is identifying PfEMP1s at the protein level due to antigenic variation. To identify these PfEMP1s using shotgun proteomics, we developed a pipeline that searches high-resolution mass spectrometry spectra against a custom protein sequence database. A local alignment algorithm, LAX, was developed as a part of the pipeline that matches peptide sequences to the most similar PfEMP1 and calculates a weight value based on peptide's uniqueness used for PfEMP1 protein inference. The pipeline was first validated in the analysis of a laboratory strain with a known PfEMP1, then it was implemented on the analysis of parasite isolates from malaria-infected pregnant women and finally on the analysis of parasite isolates from malaria-infected children where there was an increase of PfEMP1s identified in 27 out of 31 isolates using the expanded database.

A simplified workflow for monoclonal antibody sequencing

The diversity of antibody variable regions makes cDNA sequencing challenging, and conventional monoclonal antibody cDNA amplification requires the use of degenerate primers. Here, we describe a simplified workflow for amplification of IgG antibody variable regions from hybridoma RNA by a specialized RT-PCR followed by Sanger sequencing. We perform three separate reactions for each hybridoma: one each for kappa, lambda, and heavy chain transcripts. We prime reverse transcription with a primer specific to the respective constant region and use a template-switch oligonucleotide, which creates a custom sequence at the 5’ end of the antibody cDNA. This template-switching circumvents the issue of low sequence homology and the need for degenerate primers. Instead, subsequent PCR amplification of the antibody cDNA molecules requires only two primers: one primer specific for the template-switch oligonucleotide sequence and a nested primer to the respective constant region. We successfully sequenced the variable regions of five mouse monoclonal IgG antibodies using this method, which enabled us to design chimeric mouse/human antibody expression plasmids for recombinant antibody production in mammalian cell culture expression systems. All five recombinant antibodies bind their respective antigens with high affinity, confirming that the amino acid sequences determined by our method are correct and demonstrating the high success rate of our method. Furthermore, we also designed RT-PCR primers and amplified the variable regions from RNA of cells transfected with chimeric mouse/human antibody expression plasmids, showing that our approach is also applicable to IgG antibodies of human origin. Our monoclonal antibody sequencing method is highly accurate, user-friendly, and very cost-effective.

Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies

The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3-5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material.

Engineering Translation in Mammalian Cell Factories to Increase Protein Yield: The Unexpected Use of Long Non-Coding SINEUP RNAs

Mammalian cells are an indispensable tool for the production of recombinant proteins in contexts where function depends on post-translational modifications. Among them, Chinese Hamster Ovary (CHO) cells are the primary factories for the production of therapeutic proteins, including monoclonal antibodies (MAbs). To improve expression and stability, several methodologies have been adopted, including methods based on media formulation, selective pressure and cell- or vector engineering. This review presents current approaches aimed at improving mammalian cell factories that are based on the enhancement of translation. Among well-established techniques (codon optimization and improvement of mRNA secondary structure), we describe SINEUPs, a family of antisense long non-coding RNAs that are able to increase translation of partially overlapping protein-coding mRNAs. By exploiting their modular structure, SINEUP molecules can be designed to target virtually any mRNA of interest, and thus to increase the production of secreted proteins. Thus, synthetic SINEUPs represent a new versatile tool to improve the production of secreted proteins in biomanufacturing processes.

Proteogenomics for the Comprehensive Analysis of Human Cellular and Serum Antibody Repertoires

The vast repertoire of immunoglobulins produced by the immune system is a consequence of the huge amount of antigens to which we are exposed every day. The diversity of these immunoglobulins is due to different mechanisms (including VDJ recombination, somatic hypermutation, and antigen selection). Understanding how the immune system is capable of generating this diversity and which are the molecular bases of the composition of immunoglobulins are key challenges in the immunological field. During the last decades, several techniques have emerged as promising strategies to achieve these goals, but it is their combination which appears to be the fruitful solution for increasing the knowledge about human cellular and serum antibody repertoires.In this chapter, we address the diverse strategies focused on the analysis of immunoglobulin repertoires as well as the characterization of the genomic and peptide sequences. Moreover, the advantages of combining various -omics approaches are discussed through review different published studies, showing the benefits in clinical areas.

Peptidomics of Acanthoscurria gomesiana spider venom reveals new toxins with potential antimicrobial activity

Acanthoscurria gomesiana is a Brazilian spider from the Theraphosidae family inhabiting regions of Southeastern Brazil. Potent antimicrobial peptides as gomesin and acanthoscurrin have been discovered from the spider hemolymph in previous works. Spider venoms are also recognized as sources of biologically active peptides, however the venom peptidome of A. gomesiana remained unexplored to date. In this work, a MS-based workflow was applied to the investigation of the spider venom peptidome. Data-independent and data-dependent LC-MS/MS acquisitions of intact peptides and of peptides submitted to multiple enzyme digestions, followed by automated chromatographic alignment, de novo analysis, database and homology searches with manual validations showed that the venom is composed by <165 features, with masses ranging from 0.4-15.8kDa. From digestions, 135 peptides were identified from 17 proteins, including three new mature peptides: U1-TRTX-Agm1a, U1-TRTX-Agm2a and U1-TRTX-Agm3a, containing 3, 4 and 3 disulfide bonds, respectively. The toxins U1-TRTX-Agm1a differed by only one amino acid from U1-TRTX-Ap1a from A. paulensis and U1-TRTX-Agm2a was derived from the genicutoxin-D1 precursor from A. geniculata. These toxins have potential applications as antimicrobial agents, as the peptide fraction of A. gomesiana showed activity against Escherichia coli, Enterobacter cloacae and Candida albicans strains. MS data are available via ProteomeXchange Consortium with identifier PXD003884.

BIOLOGICAL SIGNIFICANCE

Biological fluids of the Acanthoscurria gomesiana spider are sources of active molecules, as is the case of antimicrobial peptides and acylpolyamines found in the hemolymphs. The venom is also a potential source of toxins with pharmacological and biotechnological applications. However, to our knowledge no A. gomesiana venom toxin structure has been determined to date. Using a combination of high resolution mass spectrometry, transcriptomics and bioinformatics, we employed a workflow to fully sequence, determine the number of disulfide bonds of mature peptides and we found new potential antimicrobial peptides. This workflow is suitable for complete peptide toxin sequencing when handling limited amount of venom samples and can accelerate the discovery of peptides with potential biotechnological applications.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

De Novo Sequencing and Resurrection of a Human Astrovirus-Neutralizing Antibody

Monoclonal antibody (mAb) therapeutics targeting cancer, autoimmune diseases, inflammatory diseases, and infectious diseases are growing exponentially. Although numerous panels of mAbs targeting infectious disease agents have been developed, their progression into clinically useful mAbs is often hindered by the lack of sequence information and/or loss of hybridoma cells that produce them. Here we combine the power of crystallography and mass spectrometry to determine the amino acid sequence and glycosylation modification of the Fab fragment of a potent human astrovirus-neutralizing mAb. We used this information to engineer a recombinant antibody single-chain variable fragment that has the same specificity as the parent monoclonal antibody to bind to the astrovirus capsid protein. This antibody can now potentially be developed as a therapeutic and diagnostic agent.

IgRepertoireConstructor: a novel algorithm for antibody repertoire construction and immunoproteogenomics analysis

The analysis of concentrations of circulating antibodies in serum (antibody repertoire) is a fundamental, yet poorly studied, problem in immunoinformatics. The two current approaches to the analysis of antibody repertoires [next generation sequencing (NGS) and mass spectrometry (MS)] present difficult computational challenges since antibodies are not directly encoded in the germline but are extensively diversified by somatic recombination and hypermutations. Therefore, the protein database required for the interpretation of spectra from circulating antibodies is custom for each individual. Although such a database can be constructed via NGS, the reads generated by NGS are error-prone and even a single nucleotide error precludes identification of a peptide by the standard proteomics tools. Here, we present the IgRepertoireConstructor algorithm that performs error-correction of immunosequencing reads and uses mass spectra to validate the constructed antibody repertoires.

AVAILABILITY AND IMPLEMENTATION

IgRepertoireConstructor is open source and freely available as a C++ and Python program running on all Unix-compatible platforms. The source code is available from http://bioinf.spbau.ru/igtools.

CONTACT

ppevzner@ucsd.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Proteomic detection of immunoglobulin light chain variable region peptides from amyloidosis patient biopsies

Immunoglobulin light chain (LC) amyloidosis (AL) is caused by deposition of clonal LCs produced by an underlying plasma cell neoplasm. The clonotypic LC sequences are unique to each patient, and they cannot be reliably detected by either immunoassays or standard proteomic workflows that target the constant regions of LCs. We addressed this issue by developing a novel sequence template-based workflow to detect LC variable (LCV) region peptides directly from AL amyloid deposits. The workflow was implemented in a CAP/CLIA compliant clinical laboratory dedicated to proteomic subtyping of amyloid deposits extracted from either formalin-fixed paraffin-embedded tissues or subcutaneous fat aspirates. We evaluated the performance of the workflow on a validation cohort of 30 AL patients, whose amyloidogenic clone was identified using a novel proteogenomics method, and 30 controls. The recall and negative predictive values of the workflow, when identifying the gene family of the AL clone, were 93 and 98%, respectively. Application of the workflow on a clinical cohort of 500 AL amyloidosis samples highlighted a bias in the LCV gene families used by the AL clones. We also detected similarity between AL clones deposited in multiple organs of systemic AL patients. In summary, AL proteomic data sets are rich in LCV region peptides of potential clinical significance that are recoverable with advanced bioinformatics.

Evolutionary divergence in the catalytic activity of the CAM-1, ROR1 and ROR2 kinase domains

Receptor tyrosine kinase-like orphan receptors (ROR) 1 and 2 are atypical members of the receptor tyrosine kinase (RTK) family and have been associated with several human diseases. The vertebrate RORs contain an ATP binding domain that deviates from the consensus amino acid sequence, although the impact of this deviation on catalytic activity is not known and the kinase function of these receptors remains controversial. Recently, ROR2 was shown to signal through a Wnt responsive, β-catenin independent pathway and suppress a canonical Wnt/β-catenin signal. In this work we demonstrate that both ROR1 and ROR2 kinase domains are catalytically deficient while CAM-1, the C. elegans homolog of ROR, has an active tyrosine kinase domain, suggesting a divergence in the signaling processes of the ROR family during evolution. In addition, we show that substitution of the non-consensus residues from ROR1 or ROR2 into CAM-1 and MuSK markedly reduce kinase activity, while restoration of the consensus residues in ROR does not restore robust kinase function. We further demonstrate that the membrane-bound extracellular domain alone of either ROR1 or ROR2 is sufficient for suppression of canonical Wnt3a signaling, and that this domain can also enhance Wnt5a suppression of Wnt3a signaling. Based on these data, we conclude that human ROR1 and ROR2 are RTK-like pseudokinases.

Characterization of immunoglobulin by mass spectrometry with applications for the clinical laboratory

Studies monitoring immunoglobulin (Ig) antigen specificity have brought to light key Ig biomarkers for immunity, autoimmunity, cancer detection, and immune system function evaluation. A fundamentally new approach to the detection of Igs based on the primary structure of the Ig is beginning to emerge in the literature. This approach has only become feasible in light of advances in proteomics and rapid improvements in mass spectrometry (MS). Driven primarily by the development of Ig pharmaceuticals, Ig MS-based proteomic methods are revealing structural features which were previously unavailable with other characterization techniques. The task of adapting these techniques to clinical chemistry is in its infancy, but these methods have the potential to dramatically alter testing for Ig biomarkers. The purpose of this article is to review the advances that have been made in proteomic characterization of Igs by MS and the early attempts to apply these methods to clinical samples.

Sequencing-grade de novo analysis of MS/MS triplets (CID/HCD/ETD) from overlapping peptides

Full-length de novo sequencing of unknown proteins remains a challenging open problem. Traditional methods that sequence spectra individually are limited by short peptide length, incomplete peptide fragmentation, and ambiguous de novo interpretations. We address these issues by determining consensus sequences for assembled tandem mass (MS/MS) spectra from overlapping peptides (e.g., by using multiple enzymatic digests). We have combined electron-transfer dissociation (ETD) with collision-induced dissociation (CID) and higher-energy collision-induced dissociation (HCD) fragmentation methods to boost interpretation of long, highly charged peptides and take advantage of corroborating b/y/c/z ions in CID/HCD/ETD. Using these strategies, we show that triplet CID/HCD/ETD MS/MS spectra from overlapping peptides yield de novo sequences of average length 70 AA and as long as 200 AA at up to 99% sequencing accuracy.

Ubiquilin4 is an adaptor protein that recruits Ubiquilin1 to the autophagy machinery

Ubiquilins (Ubqlns)-a family of ubiquitin-binding proteins-are involved in several protein degradation pathways and have been implicated in various neurodegenerative diseases. Ubqln1 regulates autophagosome maturation during autophagy-mediated degradation. We now show that Ubqln4 mediates the interaction between Ubqln1 and the autophagy machinery by recruiting Ubqln1 to LC3. This targeting of Ubqln1 to autophagosomes requires the Ubqln4 UBL domain and the Ubqln1 UBA domain. This study identifies a new role for Ubqln4, expanding the role for Ubqlns in protein degradation.

The spectral networks paradigm in high throughput mass spectrometry

High-throughput proteomics is made possible by a combination of modern mass spectrometry instruments capable of generating many millions of tandem mass (MS(2)) spectra on a daily basis and the increasingly sophisticated associated software for their automated identification. Despite the growing accumulation of collections of identified spectra and the regular generation of MS(2) data from related peptides, the mainstream approach for peptide identification is still the nearly two decades old approach of matching one MS(2) spectrum at a time against a database of protein sequences. Moreover, database search tools overwhelmingly continue to require that users guess in advance a small set of 4-6 post-translational modifications that may be present in their data in order to avoid incurring substantial false positive and negative rates. The spectral networks paradigm for analysis of MS(2) spectra differs from the mainstream database search paradigm in three fundamental ways. First, spectral networks are based on matching spectra against other spectra instead of against protein sequences. Second, spectral networks find spectra from related peptides even before considering their possible identifications. Third, spectral networks determine consensus identifications from sets of spectra from related peptides instead of separately attempting to identify one spectrum at a time. Even though spectral networks algorithms are still in their infancy, they have already delivered the longest and most accurate de novo sequences to date, revealed a new route for the discovery of unexpected post-translational modifications and highly-modified peptides, enabled automated sequencing of cyclic non-ribosomal peptides with unknown amino acids and are now defining a novel approach for mapping the entire molecular output of biological systems that is suitable for analysis with tandem mass spectrometry. Here we review the current state of spectral networks algorithms and discuss possible future directions for automated interpretation of spectra from any class of molecules.

Phosphorylation of NLRC4 is critical for inflammasome activation

NLRC4 is a cytosolic member of the NOD-like receptor family that is expressed in innate immune cells. It senses indirectly bacterial flagellin and type III secretion systems, and responds by assembling an inflammasome complex that promotes caspase-1 activation and pyroptosis. Here we use knock-in mice expressing NLRC4 with a carboxy-terminal 3×Flag tag to identify phosphorylation of NLRC4 on a single, evolutionarily conserved residue, Ser 533, following infection of macrophages with Salmonella enterica serovar Typhimurium (also known as Salmonella typhimurium). Western blotting with a NLRC4 phospho-Ser 533 antibody confirmed that this post-translational modification occurs only in the presence of stimuli known to engage NLRC4 and not the related protein NLRP3 or AIM2. Nlrc4(-/-) macrophages reconstituted with NLRC4 mutant S533A, unlike those reconstituted with wild-type NLRC4, did not activate caspase-1 and pyroptosis in response to S. typhimurium, indicating that S533 phosphorylation is critical for NLRC4 inflammasome function. Conversely, phosphomimetic NLRC4 S533D caused rapid macrophage pyroptosis without infection. Biochemical purification of the NLRC4-phosphorylating activity and a screen of kinase inhibitors identified PRKCD (PKCδ) as a candidate NLRC4 kinase. Recombinant PKCδ phosphorylated NLRC4 S533 in vitro, immunodepletion of PKCδ from macrophage lysates blocked NLRC4 S533 phosphorylation in vitro, and Prkcd(-/-) macrophages exhibited greatly attenuated caspase-1 activation and IL-1β secretion specifically in response to S. typhimurium. Phosphorylation-defective NLRC4 S533A failed to recruit procaspase-1 and did not assemble inflammasome specks during S. typhimurium infection, so phosphorylation of NLRC4 S533 probably drives conformational changes necessary for NLRC4 inflammasome activity and host innate immunity.

In vivo depletion of lymphotoxin-alpha expressing lymphocytes inhibits xenogeneic graft-versus-host-disease

Graft-versus-host disease (GVHD) is a major barrier to successful allogeneic hematopoietic cell transplantation and is largely mediated by activated donor lymphocytes. Lymphotoxin (LT)-α is expressed by subsets of activated T and B cells, and studies in preclinical models demonstrated that targeted depletion of these cells with a mouse anti-LT-α monoclonal antibody (mAb) was efficacious in inhibiting inflammation and autoimmune disease. Here we demonstrate that LT-α is also upregulated on activated human donor lymphocytes in a xenogeneic model of GVHD and targeted depletion of these donor cells ameliorated GVHD. A depleting humanized anti-LT-α mAb, designated MLTA3698A, was generated that specifically binds to LT-α in both the soluble and membrane-bound forms, and elicits antibody-dependent cellular cytotoxicity (ADCC) activity in vitro. Using a human peripheral blood mononuclear cell transplanted SCID (Hu-SCID) mouse model of GVHD, the anti-human LT-α mAb specifically depleted activated LT-expressing human donor T and B cells, resulting in prolonged survival of the mice. A mutation in the Fc region, rendering the mAb incapable of mediating ADCC, abolished all in vitro and in vivo effects. These data support a role for using a depleting anti-LT-α antibody in treating immune diseases such as GVHD and autoimmune diseases.