scholarly journals A quantitative view of strategies to engineer cell-selective ligand binding

2020 ◽  
Author(s):  
Zhixin Cyrillus Tan ◽  
Brian Orcutt-Jahns ◽  
Aaron S. Meyer
Keyword(s):  
Specific Binding ◽  
Quantitative Model ◽  
Design Guidelines ◽  
Target Cells ◽  
List Type ◽  
Binding Model ◽  
Selective Ligand ◽  
Unique Cell ◽  
Development Literature ◽  
Enhanced Selectivity

AbstractA critical property of many therapies is their selective binding to specific target populations. Exceptional specificity can arise from high-affinity binding to unique cell surface targets. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multi-valent molecules, but these create a combinatorial explosion of design possibilities. Therefore, guiding strategies for developing cell-specific binding are critical to employ these tools. Here, we extend a multi-valent binding model to multi-ligand and multi-receptor interactions. Using this model, we explore a series of mechanisms to engineer cell selectivity, including mixtures of molecules, affinity adjustments, and valency changes. Each of these strategies maximizes selectivity in distinct cases, leading to synergistic improvements when used in combination. Finally, we identify situations in which selectivity cannot be derived through passive binding alone to highlight areas in need of new developments. In total, this work uses a quantitative model to unify a comprehensive set of design guidelines for engineering cell-specific therapies.Summary pointsAffinity, valency, and other alterations to target cell binding provide enhanced selectivity in specific situations.Evidence for the effectiveness and limitations of each strategy are abundant within the drug development literature.Combining strategies can offer enhanced selectivity.A simple, multivalent ligand-receptor binding model can help to direct therapeutic engineering.

scholarly journals A quantitative view of strategies to engineer cell-selective ligand binding

2021 ◽  
Author(s):  
Zhixin Cyrillus Tan ◽  
Brian T Orcutt-Jahns ◽  
Aaron S Meyer
Keyword(s):  
Specific Binding ◽  
Cell Types ◽  
Target Cells ◽  
Binding Model ◽  
Combinatorial Explosion ◽  
Model Driven ◽  
Target Populations ◽  
Proposed Model ◽  
Selective Ligand ◽  
Receptor Interactions

Abstract A critical property of many therapies is their selective binding to target populations. Exceptional specificity can arise from high-affinity binding to surface targets expressed exclusively on target cell types. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding strategies for developing cell-specific binding are critical to employ these tools. Here, we employ a uniquely general multivalent binding model to dissect multi-ligand and multi-receptor interactions. This model allows us to analyze and explore a series of mechanisms to engineer cell selectivity, including mixtures of molecules, affinity adjustments, valency changes, multi-specific molecules and ligand competition. Each of these strategies can optimize selectivity in distinct cases, leading to enhanced selectivity when employed together. The proposed model, therefore, provides a comprehensive toolkit for the model-driven design of selectively binding therapies.

scholarly journals Supercoiled DNA and non-equilibrium formation of protein complexes: A quantitative model of the nucleoprotein ParBS partition complex

2021 ◽  
Vol 17 (4) ◽  
pp. e1008869
Author(s):  
Jean-Charles Walter ◽  
Thibaut Lepage ◽  
Jérôme Dorignac ◽  
Frédéric Geniet ◽  
Andrea Parmeggiani ◽  
...  
Keyword(s):  
Protein Complexes ◽  
Specific Binding ◽  
Super Resolution ◽  
Quantitative Model ◽  
Exact Nature ◽  
Cluster Assembly ◽  
Binding Model ◽  
Supercoiled Dna ◽  
Bacterial Dna ◽  
Non Equilibrium

ParABS, the most widespread bacterial DNA segregation system, is composed of a centromeric sequence, parS, and two proteins, the ParA ATPase and the ParB DNA binding proteins. Hundreds of ParB proteins assemble dynamically to form nucleoprotein parS-anchored complexes that serve as substrates for ParA molecules to catalyze positioning and segregation events. The exact nature of this ParBS complex has remained elusive, what we address here by revisiting the Stochastic Binding model (SBM) introduced to explain the non-specific binding profile of ParB in the vicinity of parS. In the SBM, DNA loops stochastically bring loci inside a sharp cluster of ParB. However, previous SBM versions did not include the negative supercoiling of bacterial DNA, leading to use unphysically small DNA persistences to explain the ParB binding profiles. In addition, recent super-resolution microscopy experiments have revealed a ParB cluster that is significantly smaller than previous estimations and suggest that it results from a liquid-liquid like phase separation. Here, by simulating the folding of long (≥ 30 kb) supercoiled DNA molecules calibrated with realistic DNA parameters and by considering different possibilities for the physics of the ParB cluster assembly, we show that the SBM can quantitatively explain the ChIP-seq ParB binding profiles without any fitting parameter, aside from the supercoiling density of DNA, which, remarkably, is in accord with independent measurements. We also predict that ParB assembly results from a non-equilibrium, stationary balance between an influx of produced proteins and an outflux of excess proteins, i.e., ParB clusters behave like liquid-like protein condensates with unconventional “leaky” boundaries.

scholarly journals 894 The bispecific innate cell engagers AFM13 (CD30/CD16A) and AFM24 (EGFR/CD16A) increase the fraction of tumor target-responsive NK cells and boost serial killing

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A938-A938
Author(s):  
Chiara Zambarda ◽  
Karolin Guldevall ◽  
Chiara Zambarda ◽  
Karolin Guldevall ◽  
Christian Breunig ◽  
...  
Keyword(s):  
Nk Cells ◽  
Single Cell ◽  
Tumor Cells ◽  
Cell Biology ◽  
Nk Cell ◽  
Biological Evaluation ◽  
Target Cells ◽  
List Type ◽  
Tumor Target ◽  
Serial Killing

BackgroundThe use of bispecific natural killer (NK) cell engagers has emerged as a successful strategy for immune cell activation and killing of tumor cells through antibody-dependent cellular cytotoxicity (ADCC). Among these, tetravalent, bispecific innate cell engagers (ICE®) with specificity for the activating receptor CD16A selectively triggering innate responses from NK cells or macrophages represent the most clinically advanced concept. The CD30/CD16A specific ICE® AFM13, has shown efficacy in patients with CD30+ lymphomas as monotherapy1 and combination therapy with check-point inhibitors2 and most recently in combination with adoptive NK cell therapy.3 The EGFR/CD16A specific ICE® AFM24, targeting a variety of solid tumors like colorectal, or lung cancer with a unique mode of action independent of EGFR signaling inhibition, is currently evaluated in an ongoing Ph1/2a clinical study.MethodsWe used a microchip-based screening with single cell resolution4 to elucidate the dynamic responses of individual NK cells towards tumor target cells upon treatment with AFM13 or AFM24.ResultsWe found that AFM13 and AFM24 mediated potent activation of NK cells, leading to increased responsive cytotoxic NK cells and significantly increased the number of NK cells that exerted engagement with multiple target cells rendering these NK cells serial killers. Strikingly, bispecific ICE® molecules triggered stronger cytotoxic responses compared to monoclonal antibodies. One suggested strategy to boost killing by NK cells is to use molecular inhibitors or protein constructs that prevent shedding of CD16.5 However, previous results have shown that this can lead to impaired detachment from target cells, reducing the capacity for an individual NK cell to form serial contacts to target cells.6 We observed that the elevated NK cell killing induced by ICE® molecules was largely conserved when cells were treated with the shedding inhibitor Batimastat. Analysis of the functional dynamics of NK cells revealed that inhibition of CD16 shedding prevented NK cell detachment from target cells, resulting in cell cluster formation. This might strongly impact targeting of distant tumor cells by an individual NK cell thus limiting its anti-tumoral activity.ConclusionsIn conclusion, we show that both AFM13 and AFM24 increase the fraction of tumor-target responsive NK cells and boost serial killing of target cells by individual NK cells. Based on these data, ICE® molecules can be characterized as potent anti-tumoral agents leveraging the enormous potential of NK cells while maintaining crucial features of NK cell biology.AcknowledgementsWe thank members of the Önfelt lab for their valuable help and feedback.ReferencesSawas A, Elgedawe H, Vlad G, Lipschitz M, Chen P-H, Rodig SJ, et al. Clinical and biological evaluation of the novel CD30/CD16A tetravalent bispecific antibody (AFM13) in relapsed or refractory CD30-positive lymphoma with cutaneous presentation: a biomarker phase Ib/IIa study (NCT03192202). Blood 2018;132(Supplement 1):2908–2908.Bartlett NL, Herrera AF, Domingo-Domenech E, Mehta A, Forero-Torres A, Garcia-Sanz R, et al. A phase 1b study of AFM13 in combination with pembrolizumab in patients with relapsed or refractory Hodgkin lymphoma. Blood 2020. Blood 2020;136(21):2401–2409.Kerbauy LN, Marin ND, Kaplan M, Banerjee PP, Berrien-Elliott MM, Becker-Hapak M, et al. Combining AFM13, a bispecific CD30/CD16 antibody, with cytokine-activated blood and cord blood–derived NK cells facilitates CAR-like responses against CD30 + malignancies. Clin Cancer Res Epub 2021.Guldevall K, Brandt L, Forslund E, Olofsson K, Frisk TW, Olofsson PE, et al. Microchip screening platform for single cell assessment of NK cell cytotoxicity. Front Immunol 2016;7:119.Romee R, Foley B, Lenvik T, Wang Y, Zhang B, Ankarlo D, et al. NK cell CD16 surface expression and function is regulated by a disintegrin and metalloprotease-17 (ADAM17). Blood 2013;121(18):3599–608.Srpan K, Ambrose A, Karampatzakis A, Saeed M, Cartwright ANR, Guldevall K, et al. Shedding of CD16 disassembles the NK cell immune synapse and boosts serial engagement of target cells. J Cell Biol 2018;217(9):3267–83.Ethics ApprovalThis work was performed with NK cells from healthy anonymous blood donors, which requires no ethical permit according to local regulations.

scholarly journals Multi-omics profiling of U2AF1 mutants dissects pathogenic mechanisms affecting RNA granules in myeloid malignancies

2021 ◽  
Author(s):  
Giulia Biancon ◽  
Poorval Joshi ◽  
Joshua T Zimmer ◽  
Torben Hunck ◽  
Yimeng Gao ◽  
...  
Keyword(s):  
Rna Binding ◽  
Specific Binding ◽  
Aberrant Splicing ◽  
Binding Model ◽  
Full Spectrum ◽  
Myeloid Malignancies ◽  
Rna Granules ◽  
Rna Biology ◽  
Site Recognition

AbstractSomatic mutations in splicing factors are of significant interest in myeloid malignancies and other cancers. U2AF1, together with U2AF2, is essential for 3’ splice site recognition. U2AF1 mutations result in aberrant splicing, but the molecular mechanism and the full spectrum of consequences on RNA biology have not been fully elucidated to date. We performed multi-omics profiling of in vivo RNA binding, splicing and turnover for U2AF1 S34F and Q157R mutants. We dissected specific binding signals of U2AF1 and U2AF2 and showed that U2AF1 mutations individually alter U2AF1-RNA binding, resulting in defective U2AF2 recruitment. We demonstrated a complex relationship between differential binding and splicing, expanding upon the currently accepted loss-of-binding model. Finally, we observed that U2AF1 mutations increase the formation of stress granules in both cell lines and primary acute myeloid leukemia samples. Our results uncover U2AF1 mutation-dependent pathogenic RNA mechanisms and provide the basis for developing targeted therapeutic strategies.

scholarly journals Fast sorting of CD4+ T cells from whole blood using glass microbubbles

TECHNOLOGY ◽  
2015 ◽  
Vol 03 (01) ◽  
pp. 38-44 ◽  
Author(s):  
Chia-Hsien Hsu ◽  
Chihchen Chen ◽  
Daniel Irimia ◽  
Mehmet Toner
Keyword(s):  
T Cells ◽  
T Lymphocyte ◽  
Whole Blood ◽  
Specific Binding ◽  
Target Cells ◽  
Cd4 Cells ◽  
Specific Antibodies ◽  
Resource Limited ◽  
Aids Diagnosis ◽  
Better Than

The isolation of CD4 positive T lymphocyte (CD4+) from peripheral blood is important for monitoring patients after HIV infection. Here, we demonstrate a fast isolation strategy for CD4+ cells that involves mixing blood and glass microbubbles. After the specific binding of target cells to the microbubbles carrying specific antibodies on their surface, target cells will spontaneously float to the top of the blood vial and can be quickly separated. Using this strategy, we demonstrate that the isolation of CD4+ cells in less than 5 minutes and with better than 90% efficiency. This strategy for cell isolation based on buoyancy and glass microbubbles is quick and inexpensive, minimizes blood handling, does not require magnetic fields, or centrifugation equipment, and could lead to new, efficient strategies for AIDS diagnosis in resource-limited areas.

Targeted molecular imaging of prostate cancer using tumor endothelium homing Arg-Arg-Leu peptides

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 14582-14582 ◽  
Author(s):  
D. O. Henry ◽  
S. C. Chen ◽  
M. K. Wong
Keyword(s):  
Prostate Cancer ◽  
Near Infrared ◽  
Tumor Imaging ◽  
Specific Binding ◽  
Time Lapse ◽  
Human Prostate ◽  
Animal Imaging ◽  
Tumor Endothelium ◽  
Unique Cell

14582 Background: Tumor endothelial cells express a specific and unique cell surface signature. We have previously reported on the discovery of tumor endothelial cell (TDEC) binding peptides that possess the amino acid sequence Arg-Arg-Leu (RRL). We now show specific binding of this synthetic peptide to both surgically resected and experimental human prostate adenocarcinoma tumors thereby allowing for tumor imaging. Methods and Results: Cryosections from human lung, colon, renal, breast and prostate cancers were immunohistochemically processed to reveal the relationship of RRL-peptide staining in relation to Factor VIII labeled tumor vasculature. The RRL-peptide tightly co-localizes onto tumor endothelium within human prostate adenocarcinomas, and did not stain the tumor cells proper. Alexa 680, 800 are two near-infrared dyes that can be conjugated to RRL peptide and which emit at a wavelength unquenched by biologic tissue, thus permitting whole animal imaging. Intravenous administration of RRL-peptide-Alexa chimera to human PC3 prostate tumor bearing mice or TRAMP (transgenic prostate cancer) mice results in the fluorescent visualization of tumors within the intact animal through the prolonged intra-tumor retention of the RRL-dye complex as compared to controls. Direct time-lapse intravital microscopy of such tumors show real-time tumor vascular binding of the RRL peptide. Whole animal imaging revealed the tumor and did not show an appreciable image signal at any other site or organ. Conclusion: The RRL peptide homes to prostate vasculature and is useful for the specific detection of experimental prostate tumors in vivo. Further development of the RRL-peptide into a drug delivery and imaging agent is underway. No significant financial relationships to disclose.

scholarly journals Tissue-specific transcription factor target identification in the Caenorhabditis elegans epidermis using targeted DamID

2020 ◽  
Author(s):  
Dimitris Katsanos ◽  
Michalis Barkoulas
Keyword(s):  
Transcription Factor ◽  
Cell Differentiation ◽  
Single Molecule ◽  
Regulatory Networks ◽  
Specific Binding ◽  
Wnt Signalling ◽  
Specific Gene ◽  
List Type ◽  
Tissue Specific ◽  
Transcription Factor Target

SummaryTranscription factors are key orchestrators of development in multicellular animals and display complex patterns of expression, as well as tissue-specific binding to targets. However, our ability to map transcription factor-target interactions in specific tissues of intact animals remains limited. We introduce here targeted DamID (TaDa) as a method to identify transcription factor targets with tissue-specific resolution in C. elegans. We focus on the epidermis as a paradigm and demonstrate that TaDa circumvents problems with Dam-associated toxicity and allows reproducible identification of putative targets. Using a combination of TaDa and single-molecule FISH (smFISH), we refine the positions of LIN-22 and NHR-25 within the epidermal gene network. We reveal direct links between these two factors and the cell differentiation programme, as well as the Wnt signalling pathway. Our results illustrate how TaDa and smFISH can be used to dissect the architecture of tissue-specific gene regulatory networks.HighlightsTaDa circumvents Dam-associated toxicity by keeping levels of Dam expression low.TaDa allows the recovery of tissue-specific methylation profiles representing TF binding.Methylation signal is enriched in regulatory regions of the genome.LIN-22 and NHR-25 targets reveal a link to cell differentiation and Wnt signalling.

scholarly journals Resolving single-cell heterogeneity from hundreds of thousands of cells through sequential hybrid clustering and NMF

2019 ◽  
Author(s):  
Meenakshi Venkatasubramanian ◽  
Kashish Chetal ◽  
Gowtham Atluri ◽  
Nathan Salomonis
Keyword(s):  
Single Cell ◽  
Gene Selection ◽  
Cell Types ◽  
Large Datasets ◽  
Detection Methods ◽  
Cell Populations ◽  
List Type ◽  
Hybrid Clustering ◽  
Benchmark Datasets ◽  
Unique Cell

ABSTRACTThe rapid proliferation of single-cell RNA-Sequencing (scRNA-Seq) technologies has spurred the development of diverse computational approaches to detect transcriptionally coherent populations. While the complexity of the algorithms for detecting heterogeneity have increased, most existing algorithms require significant user-tuning, are heavily reliant on dimensionality reduction techniques and are not scalable to ultra-large datasets. We previously described a multi-step algorithm, Iterative Clustering and Guide-gene selection (ICGS), which applies intra-gene correlation and hybrid clustering to uniquely resolve novel transcriptionally coherent cell populations from an intuitive graphical user interface. Here, we describe a new iteration of ICGS that outperforms state-of-the-art scRNA-Seq detection workflows when applied to well-established benchmarks. This approach combines multiple complementary subtype detection methods (HOPACH, sparse-NMF, cluster “fitness”, SVM) to resolve rare and common cell-states, while minimizing differences due to donor or batch effects. Using data from the Human Cell Atlas, we show that the PageRank algorithm effectively down samples ultra-large scRNA-Seq datasets, without losing extremely rare or transcriptionally similar distinct cell-types and while recovering novel transcriptionally unique cell populations. We believe this new approach holds tremendous promise in reproducibly resolving hidden cell populations in complex datasets.HighlightsICGS2 outperforms alternative approaches in small and ultra-large benchmark datasetsIntegrates multiple solutions for cell-type detection with supervised refinementScales effectively to resolve rare cell-states from ultra-large datasets using PageRank sampling with a low memory footprintIntegrated into AltAnalyze to enable sophisticated and automated downstream analysis

Gene therapy vectors for targeting the heart

2021 ◽  
Author(s):  
Moataz Dowaidar
Keyword(s):  
Targeted Delivery ◽  
Specific Binding ◽  
Target Cells ◽  
Biological Targets ◽  
Drug Delivery Vehicles ◽  
Therapeutic Drugs ◽  
Gene Therapy Vectors ◽  
Delivery Vehicles ◽  
Selective Delivery ◽  
Targeted Medicine

The delivery of therapeutic drugs to the heart continues to be a challenge. Developing precise strategies to target the heart is equally as important as discovering new therapeutic medications. To grow this sector, a program that focuses on targeted delivery to the heart, as well as efforts to improve cardiac selectivity and retention of therapeutic medications, may be required. Targeted medicine distribution is one of the most important and unresolved issues in pharmacology. Viruses, on the other hand, have evolved unique and extremely accurate tropisms toward their biological targets through the usage of specific binding proteins. The inclusion of these viral proteins into the plasma membrane of EVs should improve the efficiency with which EVs transport drugs to target cells. Understanding the structure, content, and mechanisms of exosome–cell interactions and uptake might also help with the creation of bioengineered exosomes and other EVs that might be used as targeted drug delivery vehicles. In addition to establishing the optimal vector for each therapeutic ingredient, effective clinical translation of cardiac medicines requires minimally invasive yet highly selective delivery techniques.

scholarly journals A quantitative binding model for the Apl protein, the dual purpose recombination-directionality factor and lysis-lysogeny regulator of bacteriophage 186

2020 ◽  
Vol 48 (16) ◽  
pp. 8914-8926
Author(s):  
Erin E Cutts ◽  
J Barry Egan ◽  
Ian B Dodd ◽  
Keith E Shearwin
Keyword(s):  
Binding Sites ◽  
Specific Binding ◽  
Attachment Site ◽  
Binding Energies ◽  
Sequence Specificity ◽  
Binding Studies ◽  
Binding Model ◽  
Specific Binding Sites

Abstract The Apl protein of bacteriophage 186 functions both as an excisionase and as a transcriptional regulator; binding to the phage attachment site (att), and also between the major early phage promoters (pR-pL). Like other recombination directionality factors (RDFs), Apl binding sites are direct repeats spaced one DNA helix turn apart. Here, we use in vitro binding studies with purified Apl and pR-pL DNA to show that Apl binds to multiple sites with high cooperativity, bends the DNA and spreads from specific binding sites into adjacent non-specific DNA; features that are shared with other RDFs. By analysing Apl's repression of pR and pL, and the effect of operator mutants in vivo with a simple mathematical model, we were able to extract estimates of binding energies for single specific and non-specific sites and for Apl cooperativity, revealing that Apl monomers bind to DNA with low sequence specificity but with strong cooperativity between immediate neighbours. This model fit was then independently validated with in vitro data. The model we employed here is a simple but powerful tool that enabled better understanding of the balance between binding affinity and cooperativity required for RDF function. A modelling approach such as this is broadly applicable to other systems.

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