Can antibodies be "vegan"? A guide through the maze of today's antibody generation methods.

There is no doubt that today's life sciences would look very different without the availability of millions of research antibody products. Nevertheless, the use of antibody reagents that are poorly characterized has led to the publication of false or misleading results. The use of laboratory animals to produce research antibodies has also been criticized. Surprisingly, both problems can be addressed with the same technology. This review charts today's maze of different antibody formats and the various methods for antibody production and their interconnections, ultimately concluding that sequence-defined recombinant antibodies offer a clear path to both improved quality of experimental data and reduced use of animals.

High-throughput homogenous assay for the direct detection of Listeria monocytogenes DNA.

The Amplified Luminescent Proximity Homogenous Assay-linked Immunosorbent Assay (AlphaLISA) is known for detecting various protein targets; however, its ability to detect nucleic acid sequences is not well established. Here, the capabilities of the AlphaLISA technology were expanded to include direct detection of DNA (aka: oligo-Alpha) and was applied to the detection of Listeria monocytogenes. Parameters were defined that allowed the newly developed oligo-Alpha to differentiate L. monocytogenes from other Listeria species through the use of only a single nucleotide polymorphism within the 16S rDNA region. Investigations into the applicability of this assay with different matrices demonstrated its utility in both milk and juice. One remarkable feature of the oligo-Alpha is that greater sensitivity could be achieved through the use of multiple acceptor oligos compared to only a single acceptor oligo, even when only a single donor oligo was employed. Additional acceptor oligos were easily incorporated into the assay and a tenfold change in the detection limit was readily achieved, with detection limits of 250 attomole of target being recorded. In summary, replacement of antibodies with oligonucleotides allows us to take advantage of genotypic difference(s), which both expands its repertoire of biological markers and furthers its use as a diagnostic tool.

The genetics of resilience and its relationships with egg production traits and antibody traits in chickens.

BACKGROUND: Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to its initial state before exposure to a disturbance. Resilient livestock are desired because of their improved health and increased economic profit. Genetic improvement of resilience may also lead to trade-offs with production traits. Recently, resilience indicators based on longitudinal data have been suggested, but they need further evaluation to determine whether they are indeed predictive of improved resilience, such as disease resilience. This study investigated different resilience indicators based on deviations between expected and observed egg production (EP) by exploring their genetic parameters, their possible trade-offs with production traits, and their relationships with antibody traits in chickens. METHODS: Egg production in a nucleus breeding herd environment based on 1-week-, 2-week-, or 3-week-intervals of two purebred chicken lines, a white egg-laying (33,825 chickens) and a brown egg-laying line (34,397 chickens), were used to determine deviations between observed EP and expected average batch EP, and between observed EP and expected individual EP. These deviations were used to calculate three types of resilience indicators for two life periods of each individual: natural logarithm-transformed variance (ln(variance)), skewness, and lag-one autocorrelation (autocorrelation) of deviations from 25 to 83 weeks of age and from 83 weeks of age to end of life. Then, we estimated their genetic correlations with EP traits and with two antibody traits. RESULTS: The most promising resilience indicators were those based on 1-week-intervals, as they had the highest heritability estimates (0.02-0.12) and high genetic correlations (above 0.60) with the same resilience indicators based on longer intervals. The three types of resilience indicators differed genetically from each other, which indicates that they possibly capture different aspects of resilience. Genetic correlations of the resilience indicator traits based on 1-week-intervals with EP traits were favorable or zero, which means that trade-off effects were marginal. The resilience indicator traits based on 1-week-intervals also showed no genetic correlations with the antibody traits, which suggests that they are not informative for improved immunity or vice versa in the nucleus environment. CONCLUSIONS: This paper gives direction towards the evaluation and implementation of resilience indicators, i.e. to further investigate resilience indicator traits based on 1-week-intervals, in breeding programs for selecting genetically more resilient layer chickens.

Single-sequence protein structure prediction by integrating protein language models.

Protein structure prediction has been greatly improved by deep learning in the past few years. However, the most successful methods rely on multiple sequence alignment (MSA) of the sequence homologs of the protein under prediction. In nature, a protein folds in the absence of its sequence homologs and thus, a MSA-free structure prediction method is desired. Here, we develop a single-sequence-based protein structure prediction method RaptorX-Single by integrating several protein language models and a structure generation module and then study its advantage over MSA-based methods. Our experimental results indicate that in addition to running much faster than MSA-based methods such as AlphaFold2, RaptorX-Single outperforms AlphaFold2 and other MSA-free methods in predicting the structure of antibodies (after fine-tuning on antibody data), proteins of very few sequence homologs, and single mutation effects. By comparing different protein language models, our results show that not only the scale but also the training data of protein language models will impact the performance. RaptorX-Single also compares favorably to MSA-based AlphaFold2 when the protein under prediction has a large number of sequence homologs.

Bringing to Light the Importance of the miRNA Methylome in Colorectal Cancer Prognosis Through Electrochemical Bioplatforms.

This work reports the first electrochemical bioplatforms developed for the determination of the total contents of either target miRNA or methylated target miRNA. The bioplatforms are based on the hybridization of the target miRNA with a synthetic biotinylated DNA probe, the capture of the formed DNA/miRNA heterohybrids on the surface of magnetic microcarriers, and their recognition with an antibody selective to these heterohybrids or to the N6-methyladenosine (m6A) epimark. The determination of the total or methylated target miRNA was accomplished by labeling such secondary antibodies with the horseradish peroxidase (HRP) enzyme. In both cases, amperometric transduction was performed on the surface of disposable electrodes after capturing the resulting HRP-tagged magnetic bioconjugates. Because of their increasing relevance in colorectal cancer (CRC) diagnosis and prognosis, miRNA let-7a and m6A methylation were selected. The proposed electrochemical bioplatforms showed attractive analytical and operational characteristics for the determination of the total and m6A-methylated target miRNA in less than 75 min. These bioplatforms, innovative in design and application, were applied to the analysis of total RNA samples extracted from cultured cancer cells with different metastatic profiles and from paired healthy and tumor tissues of patients diagnosed with CRC at different stages. The obtained results demonstrated, for the first time using electrochemical platforms, the potential of interrogating the target miRNA methylation level to discriminate the metastatic capacities of cancer cells and to identify tumor tissues and, in a pioneering way, the potential of the m6A methylation in miRNA let-7a to serve as a prognostic biomarker for CRC.

Complement activation and cellular inflammation in Fabry disease patients despite enzyme replacement therapy.

Defective α-galactosidase A (AGAL/GLA) due to missense or nonsense mutations in the GLA gene results in accumulation of the glycosphingolipids globotriaosylceramide (Gb3) and its deacylated derivate globotriaosylsphingosine (lyso-Gb3) in cells and body fluids. The aberrant glycosphingolipid metabolism leads to a progressive lysosomal storage disorder, i. e. Fabry disease (FD), characterized by chronic inflammation leading to multiorgan damage. Enzyme replacement therapy (ERT) with agalsidase-alfa or -beta is one of the main treatment options facilitating cellular Gb3 clearance. Proteome studies have shown changes in complement proteins during ERT. However, the direct activation of the complement system during FD has not been explored. Here, we demonstrate strong activation of the complement system in 17 classical male FD patients with either missense or nonsense mutations before and after ERT as evidenced by high C3a and C5a serum levels. In contrast to the strong reduction of lyso-Gb3 under ERT, C3a and C5a markedly increased in FD patients with nonsense mutations, most of whom developed anti-drug antibodies (ADA), whereas FD patients with missense mutations, which were ADA-negative, showed heterogenous C3a and C5a serum levels under treatment. In addition to the complement activation, we found increased IL-6, IL-10 and TGF-ß1 serum levels in FD patients. This increase was most prominent in patients with missense mutations under ERT, most of whom developed mild nephropathy with decreased estimated glomerular filtration rate. Together, our findings demonstrate strong complement activation in FD independent of ERT therapy, especially in males with nonsense mutations and the development of ADAs. In addition, our data suggest kidney cell-associated production of cytokines, which have a strong potential to drive renal damage. Thus, chronic inflammation as a driver of organ damage in FD seems to proceed despite ERT and may prove useful as a target to cope with progressive organ damage.

Production of antibodies and antibody fragments containing non-natural amino acids in Escherichia coli.

Therapeutic bioconjugates are emerging as an essential tool to combat human disease. Site-specific conjugation technologies are widely recognized as the optimal approach for producing homogeneous drug products. Non-natural amino acid (nnAA) incorporation allows the introduction of bioconjugation handles at genetically defined locations. Escherichia coli (E. coli) is a facile host for therapeutic nnAA protein synthesis because it can stably replicate plasmids encoding genes for product and nnAA incorporation. Here, we demonstrate that by engineering E. coli to incorporate high levels of nnAAs, it is feasible to produce nnAA-containing antibody fragments and full-length immunoglobulin Gs (IgGs) in the cytoplasm of E. coli. Using high-density fermentation, it was possible to produce both of these types of molecules with site-specifically incorporated nnAAs at titers > 1 g/L. We anticipate this strategy will help simplify the production and manufacture of promising antibody therapeutics.

Structures of AT8 and PHF1 phosphomimetic tau: Insights into the posttranslational modification code of tau aggregation.

The microtubule-associated protein tau aggregates into amyloid fibrils in Alzheimer's disease and other neurodegenerative diseases. In these tauopathies, tau is hyperphosphorylated, suggesting that this posttranslational modification (PTM) may induce tau aggregation. Tau is also phosphorylated in normal developing brains. To investigate how tau phosphorylation induces amyloid fibrils, here we report the atomic structures of two phosphomimetic full-length tau fibrils assembled without anionic cofactors. We mutated key Ser and Thr residues to Glu in two regions of the protein. One construct contains three Glu mutations at the epitope of the anti-phospho-tau antibody AT8 (AT8-3E tau), whereas the other construct contains four Glu mutations at the epitope of the antibody PHF1 (PHF1-4E tau). Solid-state NMR data show that both phosphomimetic tau mutants form homogeneous fibrils with a single set of chemical shifts. The AT8-3E tau rigid core extends from the R3 repeat to the C terminus, whereas the PHF1-4E tau rigid core spans R2, R3, and R4 repeats. Cryoelectron microscopy data show that AT8-3E tau forms a triangular multi-layered core, whereas PHF1-4E tau forms a triple-stranded core. Interestingly, a construct combining all seven Glu mutations exhibits the same conformation as PHF1-4E tau. Scalar-coupled NMR data additionally reveal the dynamics and shape of the fuzzy coat surrounding the rigid cores. These results demonstrate that specific PTMs induce structurally specific tau aggregates, and the phosphorylation code of tau contains redundancy.

Antibody production relies on the tRNA inosine wobble modification to meet biased codon demand.

Antibodies are produced at high rates to provide immunoprotection, which puts pressure on the B cell translational machinery. Here, we identified a pattern of codon usage conserved across antibody genes. One feature thereof is the hyperutilization of codons that lack genome-encoded Watson-Crick transfer RNAs (tRNAs), instead relying on the posttranscriptional tRNA modification inosine (I34), which expands the decoding capacity of specific tRNAs through wobbling. Antibody-secreting cells had increased I34 levels and were more reliant on I34 for protein production than naïve B cells. Furthermore, antibody I34-dependent codon usage may influence B cell passage through regulatory checkpoints. Our work elucidates the interface between the tRNA pool and protein production in the immune system and has implications for the design and selection of antibodies for vaccines and therapeutics.

Current advancements in B-cell receptor sequencing fast-track the development of synthetic antibodies.

Synthetic antibodies (Abs) are a class of engineered proteins designed to mimic the functions of natural Abs. These are produced entirely in vitro, eliminating the need for an immune response. As such, synthetic Abs have transformed the traditional methods of raising Abs. Likewise, deep sequencing technologies have revolutionized genomics and molecular biology. These enable the rapid and cost-effective sequencing of DNA and RNA molecules. They have allowed for accurate and inexpensive analysis of entire genomes and transcriptomes. Notably, via deep sequencing it is now possible to sequence a person's entire B-cell receptor immune repertoire, termed BCR sequencing. This procedure allows for big data explorations of natural Abs associated with an immune response. Importantly, the identified sequences have the ability to improve the design and engineering of synthetic Abs by offering an initial sequence framework for downstream optimizations. Additionally, machine learning algorithms can be introduced to leverage the vast amount of BCR sequencing datasets to rapidly identify patterns hidden in big data to effectively make in silico predictions of antigen selective synthetic Abs. Thus, the convergence of BCR sequencing, machine learning, and synthetic Ab development has effectively promoted a new era in Ab therapeutics. The combination of these technologies is driving rapid advances in precision medicine, diagnostics, and personalized treatments.

Advancing Antibody Engineering through Synthetic Evolution and Machine Learning.

Abs are versatile molecules with the potential to achieve exceptional binding to target Ags, while also possessing biophysical properties suitable for therapeutic drug development. Protein display and directed evolution systems have transformed synthetic Ab discovery, engineering, and optimization, vastly expanding the number of Ab clones able to be experimentally screened for binding. Moreover, the burgeoning integration of high-throughput screening, deep sequencing, and machine learning has further augmented in vitro Ab optimization, promising to accelerate the design process and massively expand the Ab sequence space interrogated. In this Brief Review, we discuss the experimental and computational tools employed in synthetic Ab engineering and optimization. We also explore the therapeutic challenges posed by developing Abs for infectious diseases, and the prospects for leveraging machine learning-guided protein engineering to prospectively design Abs resistant to viral escape.

Recent advances in antibody glycoengineering for the gain of functions.

Glycans play important roles in antibody functions, and antibody glycoengineering has long been an important research field. Here, we summarize the significant strategies of antibody glycoengineering, including expressed antibody glycoengineering in mammalian cell expression systems, chemo-enzymatic antibody glycoengineering, and yeast expression system-based antibody engineering, as well as the applications of glycoengineering in antibody-drug conjugates. These advances in antibody glycoengineering will provide a comprehensive understanding and inspire us to develop more advanced techniques to achieve glycoengineered antibodies.

VarEPS-Influ:an risk evaluation system of occurred and virtual variations of influenza virus genomes.

Influenza viruses undergo frequent genomic mutations, leading to potential cross-species transmission, phenotypic changes, and challenges in diagnostic reagents and vaccines. Accurately evaluating and predicting the risk of such variations remain significant challenges. To address this, we developed the VarEPS-Influ database, an influenza virus variations risk evaluation system (VarEPS-Influ). This database employs a 'multi-dimensional evaluation of mutations' strategy, utilizing various tools to assess the physical and chemical properties, primary, secondary, and tertiary structures, receptor affinity, antibody binding capacity, antigen epitopes, and other aspects of the variation's impact. Additionally, we consider space-time distribution, host species distribution, pedigree analysis, and frequency of mutations to provide a comprehensive risk evaluation of mutations and viruses. The VarEPS-Influ database evaluates both observed variations and virtual variations (variations that have not yet occurred), thereby addressing the time-lag issue in risk predictions. Our current one-stop evaluation system for influenza virus genomic variation integrates 1065290 sequences from 224 927 Influenza A, B and C isolates retrieved from public resources. Researchers can freely access the data at https://nmdc.cn/influvar/.

The Patent and Literature Antibody Database (PLAbDab): an evolving reference set of functionally diverse, literature-annotated antibody sequences and structures.

Antibodies are key proteins of the adaptive immune system, and there exists a large body of academic literature and patents dedicated to their study and concomitant conversion into therapeutics, diagnostics, or reagents. These documents often contain extensive functional characterisations of the sets of antibodies they describe. However, leveraging these heterogeneous reports, for example to offer insights into the properties of query antibodies of interest, is currently challenging as there is no central repository through which this wide corpus can be mined by sequence or structure. Here, we present PLAbDab (the Patent and Literature Antibody Database), a self-updating repository containing over 150,000 paired antibody sequences and 3D structural models, of which over 65 000 are unique. We describe the methods used to extract, filter, pair, and model the antibodies in PLAbDab, and showcase how PLAbDab can be searched by sequence, structure, or keyword. PLAbDab uses include annotating query antibodies with potential antigen information from similar entries, analysing structural models of existing antibodies to identify modifications that could improve their properties, and facilitating the compilation of bespoke datasets of antibody sequences/structures that bind to a specific antigen. PLAbDab is freely available via Github (https://github.com/oxpig/PLAbDab) and as a searchable webserver (https://opig.stats.ox.ac.uk/webapps/plabdab/).

BG4 antibody can recognize telomeric G-quadruplexes harboring destabilizing base modifications and lesions.

BG4 is a single-chain variable fragment antibody shown to bind various G-quadruplex (GQ) topologies with high affinity and specificity, and to detect GQ in cells, including GQ structures formed within telomeric TTAGGG repeats. Here, we used ELISA and single-molecule pull-down (SiMPull) detection to test how various lengths and GQ destabilizing base modifications in telomeric DNA constructs alter BG4 binding. We observed high-affinity BG4 binding to telomeric GQ independent of telomere length, although three telomeric repeat constructs that cannot form stable intramolecular GQ showed reduced affinity. A single guanine substitution with 8-aza-7-deaza-G, T, A, or C reduced affinity to varying degrees depending on the location and base type, whereas two G substitutions in the telomeric construct dramatically reduced or abolished binding. Substitution with damaged bases 8-oxoguanine and O6-methylguanine failed to prevent BG4 binding although affinity was reduced depending on lesion location. SiMPull combined with FRET revealed that BG4 binding promotes folding of telomeric GQ harboring a G to T substitution or 8-oxoguanine. Atomic force microscopy revealed that BG4 binds telomeric GQ with a 1:1 stoichiometry. Collectively, our data suggest that BG4 can recognize partially folded telomeric GQ structures and promote telomeric GQ stability.

Epstein-Barr Virus and Human Endogenous Retrovirus in Japanese Patients with Autoimmune Demyelinating Disorders.

Multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocytes glycoprotein-antibody disease (MOGAD) are distinct autoimmune demyelinating disorders characterized by varying clinical and pathological characteristics. While the precise origins of these diseases remain elusive, a combination of genetic and environmental factors, including viral elements, have been suggested as potential contributors to their development. Our goal was to assess the occurrence of antibodies against pathogenic peptides associated with Epstein-Barr virus (EBV) and the human endogenous retrovirus-W (HERV-W) in serum samples obtained from Japanese individuals diagnosed with MS, NMOSD, and MOGAD and to make comparisons with a group of healthy controls (HCs). We conducted a retrospective analysis involving 114 Japanese participants, comprising individuals with MS (34), NMOSD (20), MOGAD (20), and HCs (40). These individuals were tested using a peptide-based enzyme-linked immunosorbent assay. A marked increase in antibody response against EBV nuclear antigen 1 (EBNA1)386-405 was observed in the serum of MS and MOGAD patients, as compared to HCs. Notably, we observed a correlation between antibodies against EBNA1386-405 and HERV-W486-504 peptides in a subset of the antibody-positive MS patients. These findings emphasize the involvement of EBV in the pathogenesis of MS and potentially MOGAD, suggesting its role in the reactivation of HERV-W.

Fast clonal family inference from large-scale B cell repertoire sequencing data.

Advances in high-throughput sequencing technologies have facilitated the large-scale characterization of B cell receptor (BCR) repertoires. However, the vast amount and high diversity of the BCR sequences pose challenges for efficient and biologically meaningful analysis. Here, we introduce fastBCR, an efficient computational approach for inferring B cell clonal families from massive BCR heavy chain sequences. We demonstrate that fastBCR substantially reduces the running time while ensuring high accuracy on simulated datasets with diverse numbers of B cell lineages and varying mutation rates. We apply fastBCR to real BCR sequencing data from peripheral blood samples of COVID-19 patients, showing that the inferred clonal families display disease-associated features, as well as corresponding antigen-binding specificity and affinity. Overall, our results demonstrate the advantages of fastBCR for analyzing BCR repertoire data, which will facilitate the identification of disease-associated antibodies and improve our understanding of the B cell immune response.

Rare antibody phage isolation and discrimination (RAPID) biopanning enables identification of high-affinity antibodies against challenging targets.

In vitro biopanning platforms using synthetic phage display antibody libraries have enabled the identification of antibodies against antigens that were once thought to be beyond the scope of immunization. Applying these methods against challenging targets remains a critical challenge. Here, we present a new biopanning pipeline, RAPID (Rare Antibody Phage Isolation and Discrimination), for the identification of rare high-affinity antibodies against challenging targets. RAPID biopanning uses fluorescent labeled phage displayed fragment antigen-binding (Fab) antibody libraries for the isolation of high-affinity binders with fluorescent activated sorting. Subsequently, discriminatory hit screening is performed with a biolayer interferometry (BLI) method, BIAS (Biolayer Interferometry Antibody Screen), where candidate binders are ranked and prioritized according to their estimated kinetic off rates. Previously reported antibodies were used to develop the methodology, and the RAPID biopanning pipeline was applied to three challenging targets (CHIP, Gαq, and CS3D), enabling the identification of high-affinity antibodies.

Benchmarking TriadAb using targets from the second antibody modeling assessment.

Computational modeling and design of antibodies has become an integral part of today's research and development in antibody therapeutics. Here we describe the Triad Antibody Homology Modeling (TriadAb) package, a functionality of the Triad protein design platform that predicts the structure of any heavy and light chain sequences of an antibody Fv domain using template-based modeling. To gauge the performance of TriadAb, we benchmarked against the results of the Second Antibody Modeling Assessment (AMA-II). On average, TriadAb produced main-chain carbonyl root-mean-square deviations between models and experimentally determined structures at 1.10 Å, 1.45 Å, 1.41 Å, 3.04 Å, 1.47 Å, 1.27 Å, 1.63 Å in the framework and the six complementarity-determining regions (H1, H2, H3, L1, L2, L3), respectively. The inaugural results are comparable to those reported in AMA-II, corroborating with our internal bench-based experiences that models generated using TriadAb are sufficiently accurate and useful for antibody engineering using the sequence design capabilities provided by Triad.

Insights into next generation sequencing guided antibody selection strategies.

Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random colony picking and Sanger sequencing, which has limitations. Next-generation sequencing (NGS) offers a cost-effective solution with increased read depth, allowing a comprehensive understanding of diversity. Our study establishes NGS guidelines for antibody drug discovery, demonstrating its advantages in expanding the number of unique HCDR3 clusters, broadening the number of high affinity antibodies, expanding the total number of antibodies recognizing different epitopes, and improving lead prioritization. Surprisingly, our investigation into the correlation between NGS-derived frequencies of CDRs and affinity revealed a lack of association, although this limitation could be moderately mitigated by leveraging NGS clustering, enrichment and/or relative abundance across different regions to enhance lead prioritization. This study highlights NGS benefits, offering insights, recommendations, and the most effective approach to leverage NGS in therapeutic antibody discovery.