The human antibody sequence space and structural design of the V, J regions, and CDRH3 with Rosetta.

The human adaptive immune response enables the targeting of epitopes on pathogens with high specificity. Infection with a pathogen induces somatic hyper-mutation and B-cell selection processes that govern the shape and diversity of the antibody sequence landscape. To date, even the largest immunome repertoires of adaptive immune receptors acquired by next-generation sequencing cannot fully capture the vast antibody sequence space of a single individual, which is estimated to be at least 1012 potential sequences. Degeneracy of the genetic code means that the number of possible nucleotide triplets (64) is greater than the number of canonical amino acids (20), resulting in some amino acids being encoded by multiple triplets and different amino acids sharing the same nucleotide in 1 or 2 positions in the triplet. We hypothesize that the degeneracy of the genetic code can be used to statistically model an enlarged space of human antibody amino acid sequences, accommodating for the discrepancy between the observed and the hypothesized antibody sequence space. Facilitated by Bayesian statistics and immunome repertoire clustering, we calculated amino acid probabilities from single nucleotide frequencies to infer a human amino acid sequence space that is used to design human-like antibodies with Rosetta. We show that antibodies designed with our restraints are on average up to 16.6% more human-like in the V and J regions compared to the Rosetta designs produced without constraints. The human-likeness of the heavy-chain CDR3 region (CDRH3) could be increased for 8 of 27 antibodies compared to Rosetta designs with a similar number of mutations and could be successfully applied on Mus musculus antibodies to demonstrate humanization.

Small integral membrane protein 10 like 1 downregulation enhances differentiation of adipose progenitor cells.

Small integral membrane protein 10 like 1 (SMIM10L1) was identified by RNA sequencing as the most significantly downregulated gene in Phosphatase and Tensin Homologue (PTEN) knockdown adipose progenitor cells (APCs). PTEN is a tumor suppressor that antagonizes the growth promoting Phosphoinositide 3-kinase (PI3K)/AKT/mechanistic Target of Rapamycin (mTOR) cascade. Diseases caused by germline pathogenic variants in PTEN are summarized as PTEN Hamartoma Tumor Syndrome (PHTS). This overgrowth syndrome is associated with lipoma formation, especially in pediatric patients. The mechanisms underlying this adipose tissue dysfunction remain elusive. We observed that SMIM10L1 downregulation in APCs led to an enhanced adipocyte differentiation in two- and three-dimensional cell culture and increased expression of adipogenesis markers. Furthermore, SMIM10L1 knockdown cells showed a decreased expression of PTEN, pointing to a mutual crosstalk between PTEN and SMIM10L1. In line with these observations, SMIM10L1 knockdown cells showed increased activation of PI3K/AKT/mTOR signaling and concomitantly increased expression of the adipogenic transcription factor SREBP1. We computationally predicted an α-helical structure and membrane association of SMIM10L1. These results support a specific role for SMIM10L1 in regulating adipogenesis, potentially by increasing PI3K/AKT/mTOR signaling, which might be conducive to lipoma formation in pediatric patients with PHTS.

RosettaCM for antibodies with very long HCDR3s and low template availability.

Antibody-antigen co-crystal structures are a valuable resource for the fundamental understanding of antibody-mediated immunity. Determination of structures with antibodies in complex with their antigens, however, is a laborious task without guarantee of success. Therefore, homology modeling of antibodies and docking to their respective antigens has become a very important technique to drive antibody and vaccine design. The quality of the antibody modeling process is critical for the success of these endeavors. Here, we compare different computational protocols for predicting antibody structure from sequence in the biomolecular modeling software Rosetta-all of which use multiple existing antibody structures to guide modeling. Specifically, we compare protocols developed solely to predict antibody structure (RosettaAntibody, AbPredict) with a universal homology modeling protocol (RosettaCM). Following recent advances in homology modeling with multiple templates simultaneously, we propose that the use of multiple templates over the same antibody regions may improve modeling performance. To evaluate whether multi-template comparative modeling with RosettaCM can improve the modeling accuracy of antibodies over existing methods, this study compares the performance of the three modeling algorithms when modeling human antibodies taken from antibody-antigen co-crystal structures. In these benchmarking experiments, RosettaCM outperformed other methods when modeling antibodies with long HCDR3s and few available templates.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design.

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Rosetta design with co-evolutionary information retains protein function.

Computational protein design has the ambitious goal of crafting novel proteins that address challenges in biology and medicine. To overcome these challenges, the computational protein modeling suite Rosetta has been tailored to address various protein design tasks. Recently, statistical methods have been developed that identify correlated mutations between residues in a multiple sequence alignment of homologous proteins. These subtle inter-dependencies in the occupancy of residue positions throughout evolution are crucial for protein function, but we found that three current Rosetta design approaches fail to recover these co-evolutionary couplings. Thus, we developed the Rosetta method ResCue (residue-coupling enhanced) that leverages co-evolutionary information to favor sequences which recapitulate correlated mutations, as observed in nature. To assess the protocols via recapitulation designs, we compiled a benchmark of ten proteins each represented by two, structurally diverse states. We could demonstrate that ResCue designed sequences with an average sequence recovery rate of 70%, whereas three other protocols reached not more than 50%, on average. Our approach had higher recovery rates also for functionally important residues, which were studied in detail. This improvement has only a minor negative effect on the fitness of the designed sequences as assessed by Rosetta energy. In conclusion, our findings support the idea that informing protocols with co-evolutionary signals helps to design stable and native-like proteins that are compatible with the different conformational states required for a complex function.

Identification of a novel leptin receptor (LEPR) variant and proof of functional relevance directing treatment decisions in patients with morbid obesity.

BACKGROUND: Deficiency in the leptin-leptin receptor (LEPR) axis leads to severe, and potentially treatable, obesity in humans. To guide clinical decision-making, the functional relevance of variants in the LEPR gene needs to be carefully investigated. CASES AND METHODS: We characterized the functional impact of LEPR variants identified in two patients with severe early-onset obesity (1: compound heterozygous for the novel variant p.Tyr411del and p.Trp664Arg; 2: heterozygous for p.Arg612His) by investigating leptin-mediated signaling, leptin binding, receptor expression on cell surfaces, and receptor dimerization and activation for either wild-type and/or mutant LEPR. RESULTS: Leptin-induced STAT3-phosphorylation was blunted the novel p.Tyr411del or the p.Trp664Arg variant and mildly reduced with the p.Arg612His variant. Computational structure prediction suggested impaired leptin binding for all three LEPR variants. Experimentally, reduced leptin binding of all mutant proteins was due to diminished LEPR expression on the cell surface, with the p.Trp664Arg mutations being the most affected. Considering the heterozygosity in our patients, we assessed the heterodimerization capacity with the wild-type LEPR, which was retained for the p.Tyr411del and p.Arg612His variants. Finally, mimicking (compound) heterozygosity, we confirmed abolished STAT3-phosphorylation for the variant combination [p.Tyr411del + p.Trp664Arg] as found in patient 1, whereas it was retained for [p.Arg612His + wilde type] as found in patient 2. CONCLUSIONS: The novel p.Tyr411del mutation causes complete loss of function alone (and combined with p.Trp664Arg) and is likely the cause for the early onset obesity, qualifying the patient for pharmacologic treatment. Heterozygosity for the p.Arg612His variant, however, appears unlikely to be solely responsible for the phenotype.

PyIR: a scalable wrapper for processing billions of immunoglobulin and T cell receptor sequences using IgBLAST.

BACKGROUND: Recent advances in DNA sequencing technologies have enabled significant leaps in capacity to generate large volumes of DNA sequence data, which has spurred a rapid growth in the use of bioinformatics as a means of interrogating antibody variable gene repertoires. Common tools used for annotation of antibody sequences are often limited in functionality, modularity and usability. RESULTS: We have developed PyIR, a Python wrapper and library for IgBLAST, which offers a minimal setup CLI and API, FASTQ support, file chunking for large sequence files, JSON and Python dictionary output, and built-in sequence filtering. CONCLUSIONS: PyIR offers improved processing speed over multithreaded IgBLAST (version 1.14) when spawning more than 16 processes on a single computer system. Its customizable filtering and data encapsulation allow it to be adapted to a wide range of computing environments. The API allows for IgBLAST to be used in customized bioinformatics workflows.

Human-likeness of antibody biologics determined by back-translation and comparison with large antibody variable gene repertoires.

The antibody (Ab) germline gene rearrangement of variable (V), diversity (D), and joining (J) gene segments, as well as somatic hypermutation, give rise to the human Ab variable gene sequence repertoire. It is common to characterize single nucleotide frequencies of the variable region by alignment to species-specific wildtype germline genes. The increasing application of next-generation sequencing to immune repertoire studies has led to the compilation of increasing large adaptive immunome receptor repertoire datasets. We have developed a method that maps the sequence of a target Ab onto an immunome dataset of 326 million human Ab sequences. For this purpose, we created a position- and gene-specific scoring matrix (PGSSM) and its corresponding antibody similarity score. We characterized our PGSSM score and found that it strongly correlated with the phylogenetic distance of 181,355 Ab sequences from GenBank across 20 species. The most likely human nucleotide back-translation was obtained given only PGSSMs and the amino acid sequence of an Ab achieving a nucleotide sequence recovery of 95.9% and 97.2% for human heavy and light chains, respectively. In conclusion, the scoring of our back-translation is a valuable estimate for the similarity of an Ab sequence to the natural human repertoire. As expected, Ab therapeutic molecules developed from a human source showed a higher similarity to the repertoire than engineered Abs. Thus, the PGSSM metric introduced here can be used to engineer human-like Ab therapeutics.

Rosetta:MSF: a modular framework for multi-state computational protein design.

Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta's protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta's single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (ßα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.

Plasmodium falciparum Nucleosomes Exhibit Reduced Stability and Lost Sequence Dependent Nucleosome Positioning.

The packaging and organization of genomic DNA into chromatin represents an additional regulatory layer of gene expression, with specific nucleosome positions that restrict the accessibility of regulatory DNA elements. The mechanisms that position nucleosomes in vivo are thought to depend on the biophysical properties of the histones, sequence patterns, like phased di-nucleotide repeats and the architecture of the histone octamer that folds DNA in 1.65 tight turns. Comparative studies of human and P. falciparum histones reveal that the latter have a strongly reduced ability to recognize internal sequence dependent nucleosome positioning signals. In contrast, the nucleosomes are positioned by AT-repeat sequences flanking nucleosomes in vivo and in vitro. Further, the strong sequence variations in the plasmodium histones, compared to other mammalian histones, do not present adaptations to its AT-rich genome. Human and parasite histones bind with higher affinity to GC-rich DNA and with lower affinity to AT-rich DNA. However, the plasmodium nucleosomes are overall less stable, with increased temperature induced mobility, decreased salt stability of the histones H2A and H2B and considerable reduced binding affinity to GC-rich DNA, as compared with the human nucleosomes. In addition, we show that plasmodium histone octamers form the shortest known nucleosome repeat length (155bp) in vitro and in vivo. Our data suggest that the biochemical properties of the parasite histones are distinct from the typical characteristics of other eukaryotic histones and these properties reflect the increased accessibility of the P. falciparum genome.

Response features across the auditory midbrain reveal an organization consistent with a dual lemniscal pathway.

The central auditory system has traditionally been divided into lemniscal and nonlemniscal pathways leading from the midbrain through the thalamus to the cortex. This view has served as an organizing principle for studying, modeling, and understanding the encoding of sound within the brain. However, there is evidence that the lemniscal pathway could be further divided into at least two subpathways, each potentially coding for sound in different ways. We investigated whether such an interpretation is supported by the spatial distribution of response features in the central nucleus of the inferior colliculus (ICC), the part of the auditory midbrain assigned to the lemniscal pathway. We recorded responses to pure tone stimuli in the ICC of ketamine-xylazine-anesthetized guinea pigs and used three-dimensional brain reconstruction techniques to map the location of the recording sites. Compared with neurons in caudal-and-medial regions within an isofrequency lamina of the ICC, neurons in rostral-and-lateral regions responded with shorter first-spike latencies with less spiking jitter, shorter durations of spiking responses, a higher proportion of spikes occurring near the onset of the stimulus, lower thresholds, and larger local field potentials with shorter latencies. Further analysis revealed two distinct clusters of response features located in either the caudal-and-medial or the rostral-and-lateral parts of the isofrequency laminae of the ICC. Thus we report substantial differences in coding properties in two regions of the ICC that are consistent with the hypothesis that the lemniscal pathway is made up of at least two distinct subpathways from the midbrain up to the cortex.