Antibacterial effect of Cu2O/TiO2 photocatalytic composite on Pseudomonas marginalis pv. marginalis.

Cu2O/TiO2 visible-light photocatalytic composite was successfully synthesized by supercritical solvothermal route. Cu2O/TiO2 presented excellent bacterial inactivation activity for Pseudomonas marginalis pv. marginalis, which was related to the concentration of bacteria and the antibacterial time. The highest sterilization ratio reached up to 100% when the bacteria was treated with 80 µg/mL of Cu2O/TiO2 photocatalytic composite for 80 min, which could be further proved by the damage of integrity and shrink of the cell membrane in transmission electron microscopy (TEM) image. When the bacterial concentration was 1 × 105 CFU/mL, the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC) were determined as 16 and 32 µg/mL by agar dilution, respectively. Meanwhile, the production of reactive oxygen species (ROS), glutathione reductase (GR) and glutathione (GSH) of Pseudomonas marginalis pv. marginalis treated by Cu2O/TiO2 were determined by DCFH-DA, DTNB and kinetic method, respectively, to evaluate the anti-oxidation capacity of bacteria cell. The enzyme activity of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) in bacteria treated with Cu2O/TiO2 were measured to further confirm the overproduction of ROS. Cu2O/TiO2 was demonstrated as the excellent visible-light photocatalyst for efficiently killing Pseudomonas marginalis pv. marginalis with the low dosage. Finally, the Cu2O/TiO2 composite photocatalytic material was applied to cucumber seedlings based on field experimental, and its inhibitory effect in practical application was judged by measuring the morphology, enzyme activity and resistance index of cucumber plants. It is of great significance to the practical application as a suitable and powerful antibacterial agent for Pseudomonas marginalis pv. marginalis and other bacteria.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: II: carcass merit traits.

BACKGROUND: Genome wide association studies (GWAS) were conducted on 7,853,211 imputed whole genome sequence variants in a population of 3354 to 3984 animals from multiple beef cattle breeds for five carcass merit traits including hot carcass weight (HCW), average backfat thickness (AFAT), rib eye area (REA), lean meat yield (LMY) and carcass marbling score (CMAR). Based on the GWAS results, genetic architectures of the carcass merit traits in beef cattle were elucidated. RESULTS: The distributions of DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants conformed to a scaled inverse chi-squared distribution to a greater extent. At a threshold of P-value < 10-5, 51, 33, 46, 40, and 38 lead DNA variants on multiple chromosomes were significantly associated with HCW, AFAT, REA, LMY, and CMAR, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on HCW, AFAT, REA, and LMY were found on chromosome 6. On average, missense variants, 3'UTR variants, 5'UTR variants, and other regulatory region variants exhibited larger allele substitution effects on the traits in comparison to other functional classes. The amounts of additive genetic variance explained per DNA variant were smaller for intergenic and intron variants on all the traits whereas synonymous variants, missense variants, 3'UTR variants, 5'UTR variants, downstream and upstream gene variants, and other regulatory region variants captured a greater amount of additive genetic variance per sequence variant for one or more carcass merit traits investigated. In total, 26 enriched cellular and molecular functions were identified with lipid metabolisms, small molecular biochemistry, and carbohydrate metabolism being the most significant for the carcass merit traits. CONCLUSIONS: The GWAS results have shown that the carcass merit traits are controlled by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory, synonymous, and missense functional classes have relatively larger impacts per sequence variant on the variation of carcass merit traits. The genetic architecture as revealed by the GWAS will improve our understanding on genetic controls of carcass merit traits in beef cattle.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits.

BACKGROUND: Genome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle. RESULTS: The DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits. CONCLUSIONS: RFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.

Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle.

BACKGROUND: Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations. METHODS: Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb. RESULTS: Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals. CONCLUSIONS: Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.

Genome-wide association and genomic prediction of breeding values for fatty acid composition in subcutaneous adipose and longissimus lumborum muscle of beef cattle.

BACKGROUND: Identification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and also allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management. In this study, 81 and 83 fatty acid traits were measured in subcutaneous adipose (SQ) and longissimus lumborum muscle (LL), respectively, from 1366 purebred and crossbred beef steers and heifers that were genotyped on the Illumina BovineSNP50 Beadchip. The objective was to conduct genome-wide association studies (GWAS) for the fatty acid traits and to evaluate the accuracy of genomic prediction for fatty acid composition using genomic best linear unbiased prediction (GBLUP) and Bayesian methods. RESULTS: In total, 302 and 360 significant SNPs spanning all autosomal chromosomes were identified to be associated with fatty acid composition in SQ and LL tissues, respectively. Proportions of total genetic variance explained by individual significant SNPs ranged from 0.03 to 11.06% in SQ, and from 0.005 to 24.28% in the LL muscle. Markers with relatively large effects were located near fatty acid synthase (FASN), stearoyl-CoA desaturase (SCD), and thyroid hormone responsive (THRSP) genes. For the majority of the fatty acid traits studied, the accuracy of genomic prediction was relatively low (<0.40). Relatively high accuracies (> = 0.50) were achieved for 10:0, 12:0, 14:0, 15:0, 16:0, 9c-14:1, 12c-16:1, 13c-18:1, and health index (HI) in LL, and for 12:0, 14:0, 15:0, 10 t,12c-18:2, and 11 t,13c + 11c,13 t-18:2 in SQ. The Bayesian method performed similarly as GBLUP for most of the traits but substantially better for traits that were affected by SNPs of large effects as identified by GWAS. CONCLUSIONS: Fatty acid composition in beef is influenced by a few host genes with major effects and many genes of smaller effects. With the current training population size and marker density, genomic prediction has the potential to predict the breeding values of fatty acid composition in beef cattle at a moderate to relatively high accuracy for fatty acids that have moderate to high heritability.

Multi-population genomic prediction using a multi-task Bayesian learning model.

BACKGROUND: Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. RESULTS: A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an increase of accuracy between 0 and 0.07 in the Ayrshire validation set when 28,206 SNPs were used, while the simple data pooling method resulted in a reduction of accuracy for all traits except for protein percentage. When 246,668 SNPs were used, the accuracy achieved from the multi-task model increased by 0 to 0.03, while using the pooling method resulted in a reduction of accuracy by 0.01 to 0.09. In the Holstein population, the three methods had similar performance. CONCLUSIONS: Results in this study suggest that the proposed multi-task Bayesian learning model for multi-population genomic prediction is effective and has the potential to improve the accuracy of genomic prediction.

Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids.

The objectives of this study were to evaluate fixed risk factors associated with PWM and to estimate genetic parameters for PWM. A total of 927 birth records from a mixed population of purebred and crossbred Boer and Spanish goats born between 2016 and 2023 at the International Goat Research Center (IGRC) were used for this study. Four binary traits were studied: D0-3 (death within 3 days after birth), D4-60 (death between 4 and 60 days), D61-90 (death between 61 and 90 days), and D0-90 (death within 90 days). Logistic regression models were used to evaluate the risk factors associated with PWM traits. Bayesian threshold models and Gibbs sampling were used to estimate the genetic parameters. Birth weight, season, litter size, sex, dam age, breed, and heterosis were found to be significantly associated with at least one of the PWM traits. Heritability estimates were 0.263, 0.124, 0.080, and 0.207, for D0-3, D4-60, D61-90, and D0-90, respectively. The genetic correlations between the studied traits ranged from 0.892 (D0-3 and D0-90) to 0.999 (D0-3 and D61-90). These results suggest that PWM in goats is influenced by both non-genetic and genetic factors and can be reduced by management, genetic selection, and crossbreeding approaches.

Discovery and Characterization of a Bicyclic Peptide (Bicycle) Binder to Thymic Stromal Lymphopoietin.

Thymic stromal lymphopoietin (TSLP) is an epithelial-derived pro-inflammatory cytokine involved in the development of asthma and other atopic diseases. We used Bicycle Therapeutics' proprietary phage display platform to identify bicyclic peptides (Bicycles) with high affinity for TSLP, a target that is difficult to drug with conventional small molecules due to the extended protein-protein interactions it forms with both receptors. The hit series was shown to bind to TSLP in a hotspot, that is also used by IL-7Rα. Guided by the first X-ray crystal structure of a small peptide binding to TSLP and the identification of key metabolites, we were able to improve the proteolytic stability of this series in lung S9 fractions without sacrificing binding affinity. This resulted in the potent Bicycle 46 with nanomolar affinity to TSLP (KD = 13 nM), low plasma clearance of 6.4 mL/min/kg, and an effective half-life of 46 min after intravenous dosing to rats.

Structure-Guided Chemical Optimization of Bicyclic Peptide (Bicycle) Inhibitors of Angiotensin-Converting Enzyme 2.

Angiotensin-converting enzyme 2 (ACE2) is a metalloprotease that cleaves angiotensin II, a peptide substrate involved in the regulation of hypertension. Here, we identified a series of constrained bicyclic peptides, Bicycle, inhibitors of human ACE2 by panning highly diverse bacteriophage display libraries. These were used to generate X-ray crystal structures which were used to inform the design of additional Bicycles with increased affinity and inhibition of ACE2 enzymatic activity. This novel structural class of ACE2 inhibitors is among the most potent ACE2 inhibitors yet described in vitro, representing a valuable tool to further probe ACE2 function and for potential therapeutic utility.

Multivalent bicyclic peptides are an effective antiviral modality that can potently inhibit SARS-CoV-2.

COVID-19 has stimulated the rapid development of new antibody and small molecule therapeutics to inhibit SARS-CoV-2 infection. Here we describe a third antiviral modality that combines the drug-like advantages of both. Bicycles are entropically constrained peptides stabilized by a central chemical scaffold into a bi-cyclic structure. Rapid screening of diverse bacteriophage libraries against SARS-CoV-2 Spike yielded unique Bicycle binders across the entire protein. Exploiting Bicycles' inherent chemical combinability, we converted early micromolar hits into nanomolar viral inhibitors through simple multimerization. We also show how combining Bicycles against different epitopes into a single biparatopic agent allows Spike from diverse variants of concern (VoC) to be targeted (Alpha, Beta, Delta and Omicron). Finally, we demonstrate in both male hACE2-transgenic mice and Syrian golden hamsters that both multimerized and biparatopic Bicycles reduce viraemia and prevent host inflammation. These results introduce Bicycles as a potential antiviral modality to tackle new and rapidly evolving viruses.

Probing riboswitch-ligand interactions using thiamine pyrophosphate analogues.

The Escherichia coli thiM riboswitch forms specific contacts with its natural ligand, thiamine pyrophosphate (TPP or thiamine diphosphate), allowing it to generate not only nanomolar binding affinity, but also a high degree of discrimination against similar small molecules. A range of synthetic TPP analogues have been used to probe each of the riboswitch-ligand interactions. The results show that the pyrimidine-sensing helix of thiM is exquisitely tuned to select for TPP by recognising the H-bonding donor and acceptors around its aminopyrimidine ring and also by forming π-stacking interactions that may be sensitive to the electronics of the ring. The central thiazolium ring of TPP appears to be more important for ligand recognition than previously thought. It may contribute to binding via long-range electrostatic interactions and/or by exerting an electron withdrawing effect on the pyrimidine ring, allowing its presence to be sensed indirectly and thereby allowing discrimination between thiamine (and its phosphate esters) and other aminopyrimidines found in vivo. The pyrophosphate moiety is essential for submicromolar binding affinity, but unexpectedly, it does not appear to be strictly necessary for modulation of gene expression.

Discovery of BT8009: A Nectin-4 Targeting Bicycle Toxin Conjugate for the Treatment of Cancer.

Bicycle toxin conjugates (BTCs) are a promising new class of molecules for targeted delivery of toxin payloads into tumors. Herein we describe the discovery of BT8009, a Nectin-4 targeting BTC currently under clinical evaluation. Nectin-4 is overexpressed in multiple tumor types and is a clinically validated target for selective delivery of cytotoxic payloads. A Nectin-4 targeting bicyclic peptide was identified by phage display, which showed highly selective binding for Nectin-4 but suffered from low plasma stability and poor physicochemical properties. Multiparameter chemical optimization involving introduction of non-natural amino acids resulted in a lead Bicycle that demonstrated high affinity for Nectin-4, good stability in biological matrices, and a much-improved physicochemical profile. The optimized Bicycle was conjugated to the cytotoxin Monomethyl auristatin E via a cleavable linker to give the targeted drug conjugate BT8009, which demonstrates potent anticancer activity in in vivo rodent models.

BT8009; A Nectin-4 Targeting Bicycle Toxin Conjugate for Treatment of Solid Tumors.

Multiple tumor types overexpress Nectin-4 and the antibody-drug conjugate (ADC), enfortumab vedotin (EV) shows striking efficacy in clinical trials for metastatic urothelial cancer, which expresses high levels of Nectin-4, validating Nectin-4 as a clinical target for toxin delivery in this indication. Despite excellent data in urothelial cancer, little efficacy data are reported for EV in other Nectin-4 expressing tumors and EV therapy can produce significant toxicities in many patients, frequently leading to discontinuation of treatment. Thus, additional approaches to this target with the potential to extend utility and reduce toxicity are warranted. We describe the preclinical development of BT8009, a "Bicycle Toxin Conjugate" (BTC) consisting of a Nectin-4-binding bicyclic peptide, a cleavable linker system and the cell penetrant toxin mono-methylauristatin E (MMAE). BT8009 shows significant antitumor activity in preclinical tumor models, across a variety of cancer indications and is well tolerated in preclinical safety studies. In several models, it shows superior or equivalent antitumor activity to an EV analog. As a small hydrophilic peptide-based drug BT8009 rapidly diffuses from the systemic circulation, through tissues to penetrate the tumor and target tumor cells. It is renally eliminated from the circulation, with a half-life of 1-2 hours in rat and non-human primate. These physical and PK characteristics differentiate BT8009 from ADCs and may provide benefit in terms of tumor penetration and reduced systemic exposure. BT8009 is currently in a Phase 1/2 multicenter clinical trial across the US, Canada, and Europe, enrolling patients with advanced solid tumors associated with Nectin-4 expression.

Identification of novel ligands for thiamine pyrophosphate (TPP) riboswitches.

Riboswitches are regions of mRNA to which a metabolite binds in the absence of proteins, resoulting in alteration of transcription, translation or splicing. The most widespread forms of riboswitches are those responsive to TPP (thiamine pyrophosphate) the active form of vitamin B1, thiamine. TPP-riboswitches have been found in all bacterial genomes examined, and are the only ones found in eukaryotes. In each case, the riboswitch appears to regulate the expression of a gene involved in synthesis or uptake of the vitamin. Riboswitches offer an attractive target for chemical intervention, and identification of novel ligands would allow a detailed study on structure-activity relationships, as well as potential leads for the development of antimicrobial compounds. To this end, we have developed a medium-throughput methodology for screening libraries of small molecules using biophysical methods.

Anticancer immunity induced by a synthetic tumor-targeted CD137 agonist.

BACKGROUND: In contrast to immune checkpoint inhibitors, the use of antibodies as agonists of immune costimulatory receptors as cancer therapeutics has largely failed. We sought to address this problem using a new class of modular synthetic drugs, termed tumor-targeted immune cell agonists (TICAs), based on constrained bicyclic peptides (Bicycles). METHODS: Phage libraries displaying Bicycles were panned for binders against tumor necrosis factor (TNF) superfamily receptors CD137 and OX40, and tumor antigens EphA2, Nectin-4 and programmed death ligand 1. The CD137 and OX40 Bicycles were chemically conjugated to tumor antigen Bicycles with different linkers and stoichiometric ratios of binders to obtain a library of low molecular weight TICAs (MW <8 kDa). The TICAs were evaluated in a suite of in vitro and in vivo assays to characterize their pharmacology and mechanism of action. RESULTS: Linking Bicycles against costimulatory receptors (e.g., CD137) to Bicycles against tumor antigens (e.g., EphA2) created potent agonists that activated the receptors selectively in the presence of tumor cells expressing these antigens. An EphA2/CD137 TICA (BCY12491) efficiently costimulated human peripheral blood mononuclear cells in vitro in the presence of EphA2 expressing tumor cell lines as measured by the increased secretion of interferon γ and interleukin-2. Treatment of C57/Bl6 mice transgenic for the human CD137 extracellular domain (huCD137) bearing EphA2-expressing MC38 tumors with BCY12491 resulted in the infiltration of CD8+ T cells, elimination of tumors and generation of immunological memory. BCY12491 was cleared quickly from the circulation (plasma t1/2 in mice of 1-2 hr), yet intermittent dosing proved effective. CONCLUSION: Tumor target-dependent CD137 agonism using a novel chemical approach (TICAs) afforded elimination of tumors with only intermittent dosing suggesting potential for a wide therapeutic index in humans. This work unlocks a new path to effective cancer immunotherapy via agonism of TNF superfamily receptors.

DirectMX - One-Step Reconstitution of Membrane Proteins From Crude Cell Membranes Into Salipro Nanoparticles.

Integral membrane proteins (IMPs) are central to many physiological processes and represent ∼60% of current drug targets. An intricate interplay with the lipid molecules in the cell membrane is known to influence the stability, structure and function of IMPs. Detergents are commonly used to solubilize and extract IMPs from cell membranes. However, due to the loss of the lipid environment, IMPs usually tend to be unstable and lose function in the continuous presence of detergent. To overcome this problem, various technologies have been developed, including protein engineering by mutagenesis to improve IMP stability, as well as methods to reconstitute IMPs into detergent-free entities, such as nanodiscs based on apolipoprotein A or its membrane scaffold protein (MSP) derivatives, amphipols, and styrene-maleic acid copolymer-lipid particles (SMALPs). Although significant progress has been made in this field, working with inherently unstable human IMP targets (e.g., GPCRs, ion channels and transporters) remains a challenging task. Here, we present a novel methodology, termed DirectMX (for direct membrane extraction), taking advantage of the saposin-lipoprotein (Salipro) nanoparticle technology to reconstitute fragile IMPs directly from human crude cell membranes. We demonstrate the applicability of the DirectMX methodology by the reconstitution of a human solute carrier transporter and a wild-type GPCR belonging to the human chemokine receptor (CKR) family. We envision that DirectMX bears the potential to enable studies of IMPs that so far remained inaccessible to other solubilization, stabilization or reconstitution methods.

MMAE Delivery Using the Bicycle Toxin Conjugate BT5528.

The EphA2 receptor is found at high levels in tumors and low levels in normal tissue and high EphA2 expression in biopsies is a predictor of poor outcome in patients. Drug discovery groups have therefore sought to develop EphA2-based therapies using small molecule, peptide, and nanoparticle-based approaches (1-3). However, until now only EphA2-targeting antibody-drug conjugates (ADC) have entered clinical development. For example, MEDI-547 is an EphA2-targeting ADC that displayed encouraging antitumor activity in preclinical models and progressed to phase I clinical testing in man. Here we describe the development of BT5528, a bicyclic peptide ("Bicycle") conjugated to the auristatin derivative maleimidocaproyl-monomethyl auristatin E to generate the Bicycle toxin conjugate BT5528. The report compares and contrasts the Pharmacokinetics (PK) characteristics of antibody and Bicycle-based targeting systems and discusses how the PK and payload characteristics of different delivery systems impact the efficacy-toxicity trade off which is key to the development of successful cancer therapies. We show that BT5528 gives rise to rapid update into tumors and fast renal elimination followed by persistent toxin levels in tumors without prolonged exposure of parent drug in the vasculature. This fast in, fast out kinetics gave rise to more favorable toxicology findings in rats and monkeys than were observed with MEDI-547 in preclinical and clinical studies.Graphical Abstract: http://mct.aacrjournals.org/content/molcanther/19/7/1385/F1.large.jpg.

Identification and Optimization of EphA2-Selective Bicycles for the Delivery of Cytotoxic Payloads.

Bicycles are constrained bicyclic peptides that represent a promising binding modality for use in targeted drug conjugates. A phage display screen against EphA2, a receptor tyrosine kinase highly expressed in a number of solid tumors, identified a number of Bicycle families with low nanomolar affinity. A Bicycle toxin conjugate (BTC) was generated by derivatization of one of these Bicycles with the potent cytotoxin DM1 via a cleavable linker. This BTC demonstrated potent antitumor activity in vivo but was poorly tolerated, which was hypothesized to be the result of undesired liver uptake caused by poor physicochemical properties. Chemical optimization of a second Bicycle, guided by structural biology, provided a high affinity, metabolically stable Bicycle with improved physicochemical properties. A BTC incorporating this Bicycle also demonstrated potent antitumor activity and was very well tolerated when compared to the initial BTC. Phage display selection followed by chemical optimization of Bicycles can deliver potent drug conjugates with favorable pharmaceutical properties.

An Assay for Periplasm Entry Advances the Development of Chimeric Peptide Antibiotics.

The treatment of infection by Gram-negative bacteria is increasingly challenging as resistance to existing antibiotics spreads. Constrained peptides, selected for high target specificity and affinity via library display technologies, are an emerging therapeutic modality in many disease areas and may be a fertile source of new antibiotics. Currently, the utility of constrained peptides and other large molecules as antibiotics is limited by the outer membrane (OM) barrier of Gram-negative bacteria. However, the addition of certain moieties to large molecules can confer the ability to cross the OM; these moieties function as intramolecular trans-OM "vectors". Here, we present a method to systematically assess the carrying capacity of candidate trans-OM vectors using a real-time luminescence assay ("SLALOM", Split Luciferase Assay for Live monitoring of Outer Membrane transit), reporting on periplasmic entry. We demonstrate the usefulness of our tools by constructing a 3800 Da chimeric compound composed of a constrained bicyclic peptide (Bicycle) with a periplasmic target, linked to an intramolecular peptide vector; the resulting chimera is a broad-spectrum inhibitor of pathogenic Gram-negative bacterial growth.

Evaluation of a genomic-enhanced sorting system for feeder cattle1.

This study evaluated the use of molecular breeding values (MBVs) for carcass traits to sort steers into quality grid and lean meat yield (LMY) groups. A discovery set of 2,609 animals with genotypes and carcass phenotypes was used to predict MBVs for LMY and marbling score (MBS) for 299 Angus, 181 Charolais, and 638 Kinsella Composite steers using genomic best linear unbiased prediction. Steers were sorted in silico into four MBV groups namely Quality (with MBVs greater than the mean for LMY and MBS), Lean (with MBVs greater than the mean for LMY but less than or equal to the mean for MBS), Marbling (with MBVs greater than the mean for MBS but less than or equal to the mean for LMY), and Other (with MBVs lower than the mean for LMY and MBS). Carcass phenotypes on the steers were then collected at slaughter and evaluated for consistency with the assigned MBV groups using descriptive statistics and least square analysis. Accuracy of MBV predictions was assessed by Pearson's correlation between predicted MBV and adjusted phenotype divided by the square root of trait heritability. Genomic breed compositions were predicted for all steers to correct for possible population stratification and breed effects in the test model. The number of steers that met the expected carcass outcome was counted to produce actual percentages for each MBV group. Results showed that on average, Quality and Marbling groups had greater back-fat and more marbling across the three populations while Lean group had leaner carcasses. Carcass weights were similar across MBV groups. Within MBV groups, decreases in variability were observed for most traits suggesting improvement in carcass uniformity. Greater than 70% of the steers in Quality, Lean, and Marbling groups met the Quality Grid and Y1-LMY target for Angus and Charolais but not for Kinsella composite. The accuracy of MBV prediction ranged from 0.43 to 0.59 indicating that up to 35% of the observed carcass trait variability can be predicted, which suggests utility of MBV as a marker-assisted management tool to sort feeder cattle into uniform carcass endpoint groups under similar environmental and management conditions. Further investigation is warranted to evaluate the performance of feeder cattle sorted based on MBV and managed for different carcass endpoints as well as the cost-benefit implications for feedlot operations.