Antibody homotypic interactions are encoded by germline light chain complementarity determining region 2.

The utilization of avidity to drive and tune functional responses is fundamental to antibody biology and often underlies the mechanisms of action of monoclonal antibody drugs. There is increasing evidence that antibodies leverage homotypic interactions to enhance avidity, often through weak transient interfaces whereby self-association is coupled with target binding. Here, we comprehensively map the Fab­Fab interfaces of antibodies targeting DR5 and 4-1BB that utilize homotypic interaction to promote receptor activation and demonstrate that both antibodies have similar self-association determinants primarily encoded within a germline light chain complementarity determining region 2 (CDRL2). We further show that these determinants can be grafted onto antibodies of distinct target specificity to substantially enhance their activity. An expanded characterization of all unique germline CDRL2 sequences reveals additional self-association sequence determinants encoded in the human germline repertoire. Our results suggest that this phenomenon is unique to CDRL2, and is correlated with the less frequent antigen interaction and lower somatic hypermutation associated with this loop. This work reveals a previously unknown avidity mechanism in antibody native biology that can be exploited for the engineering of biotherapeutics.

In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales.

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

Previously reported placebo-response-associated variants do not predict patient outcomes in inflammatory disease Phase III trial placebo arms.

In clinical trials, a placebo response refers to improvement in disease symptoms arising from the psychological effect of receiving a treatment rather than the actual treatment under investigation. Previous research has reported genomic variation associated with the likelihood of observing a placebo response, but these studies have been limited in scope and have not been validated. Here, we analyzed whole-genome sequencing data from 784 patients undergoing placebo treatment in Phase III Asthma or Rheumatoid Arthritis trials to assess the impact of previously reported variation on patient outcomes in the placebo arms and to identify novel variants associated with the placebo response. Contrary to expectations based on previous reports, we did not observe any statistically significant associations between genomic variants and placebo treatment outcome. Our findings suggest that the biological origin of the placebo response is complex and likely to be variable between disease areas.

Engineered sigma factors increase full-length antibody expression in Escherichia coli.

Escherichia coli (E. coli) is a promising platform for expression of full-length antibodies owing to its several advantages as a production host (fast growth, well characterized genetics, low manufacturing cost), however, low titers from shake flask (typically < 5 mg/L) has limited its use for production of research-grade material in antibody discovery programs. In this work, we used global transcriptional machinery engineering (gTME) with high throughput screening to increase the expression of full-length antibodies in E. coli. A library of E. coli mutants carrying mutations in the global sigma factor RpoD were generated and screened using the Bacterial Antibody Display (BAD) method for enhanced expression. RpoD mutants were isolated that resulted in full-length antibody titers of up to 130.7 ±â€¯6.6 mg/L of shake flask culture with chaperone co-expression. These results could be useful for production of several antibodies quickly in shake flasks for characterization (e.g. antigen binding, biological function) during the early discovery phase.

BCL2 mutations do not confer adverse prognosis in follicular lymphoma patients treated with rituximab.

BCL2 mutations have been suggested to confer an adverse prognosis to follicular lymphoma (FL) patients, but their prognostic value has not been assessed in patients treated with a rituximab-containing regimen. Here we evaluated the prognostic value of BCL2 mutations in a large prospective cohort of 252 patients with FL treated with immunochemotherapy in the PRIMA randomized trial. Using a DNA-targeted sequencing approach, we detected amino acid altering mutations in 135 patients (54%) and showed that these mutations were probably mediated by the over-activation of AICDA (activation-induced cytidine deaminase) in the context of the t(14;18) translocation. The BCL2 variants identified in PRIMA patients affected the BH1, BH2, and BH3 functional motifs at a lower frequency than the N-terminus and flexible loop domain, with mostly conservative aminoacid changes. With a median follow-up of 6.7 years, we did not observe any impact of BCL2 mutations either on overall survival or progression-free survival.

The unique N terminus of the UbcH10 E2 enzyme controls the threshold for APC activation and enhances checkpoint regulation of the APC.

In vitro, the anaphase-promoting complex (APC) E3 ligase functions with E2 ubiquitin-conjugating enzymes of the E2-C and Ubc4/5 families to ubiquitinate substrates. However, only the use of the E2-C family, notably UbcH10, is genetically well validated. Here, we biochemically demonstrate preferential use of UbcH10 by the APC, specified by the E2 core domain. Importantly, an additional E2-E3 interaction mediated by the N-terminal extension of UbcH10 regulates APC activity. Mutating the highly conserved N terminus increases substrate ubiquitination and the number of substrate lysines targeted, allows ubiquitination of APC substrates lacking their destruction boxes, increases resistance to the APC inhibitors Emi1 and BubR1 in vitro, and bypasses the spindle checkpoint in vivo. Fusion of the UbcH10 N terminus to UbcH5 restricts ubiquitination activity but does not direct specific interactions with the APC. Thus, UbcH10 combines a specific E2-E3 interface and regulation via its N-terminal extension to limit APC activity for substrate selection and checkpoint control.

Visualization of protein sequence features using JavaScript and SVG with pViz.js.

UNLABELLED: pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. AVAILABILITY AND IMPLEMENTATION: pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A.

Evolutionarily conserved paired immunoglobulin-like receptor α (PILRα) domain mediates its interaction with diverse sialylated ligands.

Paired immunoglobulin-like receptor (PILR) α is an inhibitory receptor that recognizes several ligands, including mouse CD99, PILR-associating neural protein, and Herpes simplex virus-1 glycoprotein B. The physiological function(s) of interactions between PILRα and its cellular ligands are not well understood, as are the molecular determinants of PILRα/ligand interactions. To address these uncertainties, we sought to identify additional PILRα ligands and further define the molecular basis for PILRα/ligand interactions. Here, we identify two novel PILRα binding partners, neuronal differentiation and proliferation factor-1 (NPDC1), and collectin-12 (COLEC12). We find that sialylated O-glycans on these novel PILRα ligands, and on known PILRα ligands, are compulsory for PILRα binding. Sialylation-dependent ligand recognition is also a property of SIGLEC1, a member of the sialic acid-binding Ig-like lectins. SIGLEC1 Ig domain shares ∼22% sequence identity with PILRα, an identity that includes a conserved arginine localized to position 97 in mouse and human SIGLEC1, position 133 in mouse PILRα and position 126 in human PILRα. We observe that PILRα/ligand interactions require conserved PILRα Arg-133 (mouse) and Arg-126 (human), in correspondence with a previously reported requirement for SIGLEC1 Arg-197 in SIGLEC1/ligand interactions. Homology modeling identifies striking similarities between PILRα and SIGLEC1 ligand binding pockets as well as at least one set of distinctive interactions in the galactoxyl-binding site. Binding studies suggest that PILRα recognizes a complex ligand domain involving both sialic acid and protein motif(s). Thus, PILRα is evolved to engage multiple ligands with common molecular determinants to modulate myeloid cell functions in anatomical settings where PILRα ligands are expressed.

Assessment of computational methods for predicting the effects of missense mutations in human cancers.

BACKGROUND: Recent advances in sequencing technologies have greatly increased the identification of mutations in cancer genomes. However, it remains a significant challenge to identify cancer-driving mutations, since most observed missense changes are neutral passenger mutations. Various computational methods have been developed to predict the effects of amino acid substitutions on protein function and classify mutations as deleterious or benign. These include approaches that rely on evolutionary conservation, structural constraints, or physicochemical attributes of amino acid substitutions. Here we review existing methods and further examine eight tools: SIFT, PolyPhen2, Condel, CHASM, mCluster, logRE, SNAP, and MutationAssessor, with respect to their coverage, accuracy, availability and dependence on other tools. RESULTS: Single nucleotide polymorphisms with high minor allele frequencies were used as a negative (neutral) set for testing, and recurrent mutations from the COSMIC database as well as novel recurrent somatic mutations identified in very recent cancer studies were used as positive (non-neutral) sets. Conservation-based methods generally had moderately high accuracy in distinguishing neutral from deleterious mutations, whereas the performance of machine learning based predictors with comprehensive feature spaces varied between assessments using different positive sets. MutationAssessor consistently provided the highest accuracies. For certain combinations metapredictors slightly improved the performance of included individual methods, but did not outperform MutationAssessor as stand-alone tool. CONCLUSIONS: Our independent assessment of existing tools reveals various performance disparities. Cancer-trained methods did not improve upon more general predictors. No method or combination of methods exceeds 81% accuracy, indicating there is still significant room for improvement for driver mutation prediction, and perhaps more sophisticated feature integration is needed to develop a more robust tool.

A whole genome sequencing study of moderate to severe asthma identifies a lung function locus associated with asthma risk.

Genome-wide association studies (GWAS) have identified many common variant loci associated with asthma susceptibility, but few studies investigate the genetics underlying moderate-to-severe asthma risk. Here, we present a whole-genome sequencing study comparing 3181 moderate-to-severe asthma patients to 3590 non-asthma controls. We demonstrate that asthma risk is genetically correlated with lung function measures and that this component of asthma risk is orthogonal to the eosinophil genetics that also contribute to disease susceptibility. We find that polygenic scores for reduced lung function are associated with younger asthma age of onset. Genome-wide, seven previously reported common asthma variant loci and one previously reported lung function locus, near THSD4, reach significance. We replicate association of the lung function locus in a recently published GWAS of moderate-to-severe asthma patients. We additionally replicate the association of a previously reported rare (minor allele frequency < 1%) coding variant in IL33 and show significant enrichment of rare variant burden in genes from common variant allergic disease loci. Our findings highlight the contribution of lung function genetics to moderate-to-severe asthma risk, and provide initial rare variant support for associations with moderate-to-severe asthma risk at several candidate genes from common variant loci.

Effects of charge on antibody tissue distribution and pharmacokinetics.

Antibody pharmacokinetics and pharmacodynamics are often governed by biological processes such as binding to antigens and other cognate receptors. Emphasis must also be placed, however, on fundamental physicochemical properties that define antibodies as complex macromolecules, including shape, size, hydrophobicity, and charge. Electrostatic interactions between anionic cell membranes and the predominantly positive surface charge of most antibodies can influence blood concentration and tissue disposition kinetics in a manner that is independent of antigen recognition. In this context, the deliberate modification of antibodies by chemical means has been exploited as a valuable preclinical research tool to investigate the relationship between net molecular charge and biological disposition. Findings from these exploratory investigations may be summarized as follows: (I) shifts in isoelectric point of approximately one pI unit or more can produce measurable changes in tissue distribution and kinetics, (II) increases in net positive charge generally result in increased tissue retention and increased blood clearance, and (III) decreases in net positive charge generally result in decreased tissue retention and increased whole body clearance. Understanding electrostatic interactions between antibodies and biological matrices holds relevance in biotechnology, especially with regard to the development of immunoconjugates. The guiding principles and knowledge gained from preclinical evaluation of chemically modified antibodies will be discussed and placed in the context of therapeutic antibodies that are currently marketed or under development, with a particular emphasis on pharmacokinetic and disposition properties.

Enabling genome-wide association testing with multiple diseases and no healthy controls.

MOTIVATION: While large-scale whole genome sequencing is feasible the high costs compel investigators to focus on disease subjects. As a result large sequencing datasets of samples with different diseases are often readily available, but not healthy controls to contrast them with. While it is possible to perform an association study using only diseases, the associations could be driven by a disease acting as a control and not the focal disease. METHODS: We developed a genotype-on-phenotype reverse regression with a Bayesian spike and slab prior to enable association testing in datasets with multiple diseases. This method, referred to as revreg, flagged associations (both common and rare) that were driven by diseases that were not of primary interest. RESULTS: Based on simulations, revreg had 80% power to detect an odds ratio of 1.74 for common variants (3500 samples total) and 3.73 for rare variants (14,000 samples total), with minimal type I error. For common variants, we tested this method on 3657 whole genome sequenced samples aimed at discovering variants associated with disease risk of Chronic Obstructive Pulmonary Disease using three other diseases as controls. We demonstrated detection of six highly significant associations likely due to Age-Related Macular Degeneration. In an exome dataset of 8836 samples aimed at characterizing rare variants associated with disease risk of Asthma, using five other diseases as controls, we detected and removed genic regions due to AMD (C3, CFH, CFHR5, CFI, and DNMT3A) and RA (KRTAP13-4).

Analysis of protein-altering variants in telomerase genes and their association with MUC5B common variant status in patients with idiopathic pulmonary fibrosis: a candidate gene sequencing study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) risk has a strong genetic component. Studies have implicated variations at several loci, including TERT, surfactant genes, and a single nucleotide polymorphism at chr11p15 (rs35705950) in the intergenic region between TOLLIP and MUC5B. Patients with IPF who have risk alleles at rs35705950 have longer survival from the time of IPF diagnosis than do patients homozygous for the non-risk allele, whereas patients with shorter telomeres have shorter survival times. We aimed to assess whether rare protein-altering variants in genes regulating telomere length are enriched in patients with IPF homozygous for the non-risk alleles at rs35705950. METHODS: Between Nov 1, 2014, and Nov 1, 2016, we assessed blood samples from patients aged 40 years or older and of European ancestry with sporadic IPF from three international phase 3 clinical trials (INSPIRE, CAPACITY, ASCEND), one phase 2 study (RIFF), and US-based observational studies (Vanderbilt Clinical Interstitial Lung Disease Registry and the UCSF Interstitial Lung Disease Clinic registry cohorts) at the Broad Institute (Cambridge, MA, USA) and Human Longevity (San Diego, CA, USA). We also assessed blood samples from non-IPF controls in several clinical trials. We did whole-genome sequencing to assess telomere length and identify rare protein-altering variants, stratified by rs35705950 genotype. We also assessed rare functional variation in TERT exons and compared telomere length and disease progression across genotypes. FINDINGS: We assessed samples from 1510 patients with IPF and 1874 non-IPF controls. 30 (3%) of 1046 patients with an rs35705950 risk allele had a rare protein-altering variant in TERT compared with 34 (7%) of 464 non-risk allele carriers (odds ratio 0·40 [95% CI 0·24-0·66], p=0·00039). Subsequent analyses identified enrichment of rare protein-altering variants in PARN and RTEL1, and rare variation in TERC in patients with IPF compared with controls. We expanded our study population to provide a more accurate estimation of rare variant frequency in these four loci, and to calculate telomere length. The proportion of patients with at least one rare variant in TERT, PARN, TERC, or RTEL1 was higher in patients with IPF than in controls (149 [9%] of 1739 patients vs 205 [2%] of 8645 controls, p=2·44 × 10-8). Patients with IPF who had a variant in any of the four identified telomerase component genes had telomeres that were 3·69-16·10% shorter than patients without a variant in any of the four genes and had an earlier mean age of disease onset than patients without one or more variants (65·1 years [SD 7·8] vs 67·1 years [7·9], p=0·004). In the placebo arms of clinical trials, shorter telomeres were significantly associated with faster disease progression (1·7% predicted forced vital capacity per kb per year, p=0·002). Pirfenidone had treatment benefit regardless of telomere length (p=4·24 × 10-8 for telomere length lower than the median, p=0·0044 for telomere length greater than the median). INTERPRETATION: Rare protein-altering variants in TERT, PARN, TERC, and RTEL1 are enriched in patients with IPF compared with controls, and, in the case of TERT, particularly in individuals without a risk allele at the rs35705950 locus. This suggests that multiple genetic factors contribute to sporadic IPF, which might implicate distinct mechanisms of pathogenesis and disease progression. FUNDING: Genentech, National Institutes of Health, Francis Family Foundation, Pulmonary Fibrosis Foundation, Nina Ireland Program for Lung Health, US Department of Veterans Affairs.

Computational approach to site-directed ligand discovery.

A computational approach, Systematic Conformational Search & Induced Fit (SCI&FI), to site-directed ligand discovery (Tethering) is presented. SCI&FI has the ability to predict the binding site, binding mode, and bound dynamics of small molecule fragments covalently tethered to a protein. The SCI&FI method was engineered with the ability to model induced fit conformational changes of the protein because of the binding of the tether. SCI&FI generates comprehensive picture of the binding preferences of the tether to the protein by elucidating potential binding sites of the tether and by describing regions of receptor space capable of conformational change because of the binding of the tether. The SCI&FI method provides a complementary approach to experimental tethering. Initial validation of the SCI&FI method is reported by predicting the 3D structure of two Interleukin-2 and an Interleukin-4 tethered-protein systems.

A comprehensive transcriptional portrait of human cancer cell lines.

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

Structural basis for the dual recognition of helical cytokines IL-34 and CSF-1 by CSF-1R.

Lacking any discernible sequence similarity, interleukin-34 (IL-34) and colony stimulating factor 1 (CSF-1) signal through a common receptor CSF-1R on cells of mononuclear phagocyte lineage. Here, the crystal structure of dimeric IL-34 reveals a helical cytokine fold homologous to CSF-1, and we further show that the complex architecture of IL-34 bound to the N-terminal immunoglobulin domains of CSF-1R is similar to the CSF-1/CSF-1R assembly. However, unique conformational adaptations in the receptor domain geometry and intermolecular interface explain the cross-reactivity of CSF-1R for two such distantly related ligands. The docking adaptations of the IL-34 and CSF-1 quaternary complexes, when compared to the stem cell factor assembly, draw a common evolutionary theme for transmembrane signaling. In addition, the structure of IL-34 engaged by a Fab fragment reveals the mechanism of a neutralizing antibody that can help deconvolute IL-34 from CSF-1 biology, with implications for therapeutic intervention in diseases with myeloid pathogenic mechanisms.

Unison: an integrated platform for computational biology discovery.

This paper describes the design and applications of Unison, a comprehensive and integrated warehouse of protein sequences, diverse precomputed predictions, and other biological data. Unison provides a practical solution to the burden of preparing data for computational discovery projects, enables holistic feature-based mining queries regarding protein composition and functions, and provides a foundation for the development of new tools. Unison is available for immediate use online via direct database connections and a web interface. In addition, the database schema, command line tools, web interface, and non-proprietary precomputed predictions are released under the Academic Free License and available for download at http://unison-db.org/. This project has resulted in a system that significantly reduces several practical impediments to the initiation of computational biology discovery projects.

Bi-directional SIFT predicts a subset of activating mutations.

Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant) algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT) is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.