Dataset Information

CDR1 Composition Can Affect Nanobody Recombinant Expression Yields.

ABSTRACT: The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the available structural information indicated that four CDR1 residues bound directly to the antigen. We therefore modified the loop flexibility with the addition of an extra glycine rather than by mutating single amino acids. This approach significantly increased the nanobody yields but traded-off with moderate affinity loss. Accurate modeling coupled with atomistic molecular dynamics simulations enabled the modifications induced by the glycine insertion and the rationale behind the engineering design to be described in detail.

SUBMITTER: Orlando M

PROVIDER: S-EPMC8465892 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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CDR1 Composition Can Affect Nanobody Recombinant Expression Yields.

Orlando Marco M Fortuna Sara S Oloketuyi Sandra S Bajc Gregor G Goldenzweig Adi A de Marco Ario A

Biomolecules 20210914 9

The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the avail ...[more]

PMID: 34572576

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Project description:BackgroundInfectious diseases pose a severe worldwide threat to human and livestock health. While early diagnosis could enable prompt preventive interventions, the majority of diseases are found in rural settings where basic laboratory facilities are scarce. Under such field conditions, point-of-care immunoassays provide an appropriate solution for rapid and reliable diagnosis. The limiting steps in the development of the assay are the identification of a suitable target antigen and the selection of appropriate high affinity capture and detection antibodies. To meet these challenges, we describe the development of a Nanobody (Nb)-based antigen detection assay generated from a Nb library directed against the soluble proteome of an infectious agent. In this study, Trypanosoma congolense was chosen as a model system.Methodology/principal findingsAn alpaca was vaccinated with whole-parasite soluble proteome to generate a Nb library from which the most potent T. congolense specific Nb sandwich immunoassay (Nb474H-Nb474B) was selected. First, the Nb474-homologous sandwich ELISA (Nb474-ELISA) was shown to detect experimental infections with high Positive Predictive Value (98%), Sensitivity (87%) and Specificity (94%). Second, it was demonstrated under experimental conditions that the assay serves as test-of-cure after Berenil treatment. Finally, this assay allowed target antigen identification. The latter was independently purified through immuno-capturing from (i) T. congolense soluble proteome, (ii) T. congolense secretome preparation and (iii) sera of T. congolense infected mice. Subsequent mass spectrometry analysis identified the target as T. congolense glycosomal aldolase.Conclusions/significanceThe results show that glycosomal aldolase is a candidate biomarker for active T. congolense infections. In addition, and by proof-of-principle, the data demonstrate that the Nb strategy devised here offers a unique approach to both diagnostic development and target discovery that could be widely applied to other infectious diseases.

Project description:Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha-1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha-1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha-1), medium- (3 Mg ha-1), and high- (4.3 Mg ha-1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m-2), medium (200-300 seeds m-2), and high (> 300 seeds m-2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha-1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities.

Dataset Information

CDR1 Composition Can Affect Nanobody Recombinant Expression Yields.

Publications

CDR1 Composition Can Affect Nanobody Recombinant Expression Yields.

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