Biology subjects

Lund, S.

Publications and source records attributed to Lund, S..

4 recordsLinked to original sources

bioRxiv2023

Highly parallelized construction of DNA from low-cost oligonucleotide mixtures using Data-optimized Assembly Design and Golden Gate

Commercially synthesized genes are typically made using variations of homology-based cloning techniques, including polymerase cycling assembly from chemically synthesized microarray-derived oligonucleotides. Here we apply Data-optimized Assembly Design to the synthesis of hundreds of codon-optimized genes in both constitutive and inducible vectors using Golden Gate Assembly. Starting from oligonucleotide pools, we synthesize genes in three simple steps: 1) Amplification of parts belonging to individual assemblies in parallel from a single pool; 2) Golden Gate Assembly of parts for each construct; and 3) Transformation. We construct genes from receiving DNA to sequence confirmed isolates in as little as 4 days. By leveraging the ligation fidelity afforded by T4 DNA ligase, we expect to be able to construct a larger breadth of sequences not currently supported by homology-based methods which require stability of extensive single-stranded DNA overhangs.

synthetic biology↗

bioRxiv2023

Computational design of N-linked glycans for high throughput epitope profiling

Efficient identification of epitopes is crucial for drug discovery and design as it enables the selection of optimal epitopes, expansion of lead antibody diversity, and verification of binding interface. Although high resolution low throughput methods like X-ray crystallography can determine epitopes or protein-protein interactions accurately, they are time-consuming and can only be applied to a limited number of complexes. To overcome these limitations, we have developed a rapid computational method that incorporates N-linked glycans to mask epitopes or protein interaction surfaces, thereby providing an atomistic mapping of these regions. Using human coagulation factor IXa (fIXa) as a model system, we could rapidly and reliably delineate epitopes through the insertion of N-linked glycans that efficiently disrupt binding in a site-selective manner. To validate the efficacy of our method, we conducted ELISA experiments and high-throughput yeast surface display assays. Furthermore, X-ray crystallography was employed to verify the results, thereby recapitulating through the method of N-linked glycans an atomistic resolution mapping of the epitope.

bioengineering↗

bioRxiv2023

Non-specificity fingerprints for clinical stage antibodies in solution

Monoclonal antibodies (mAbs) have successfully been developed for the treatment of a wide range of diseases. The clinical success of mAbs, does not solely rely on optimal potency and safety, but also require good biophysical properties to ensure high developability potential. In particular, non-specific interactions are a key developability measure to monitor during discovery. Despite an increased focus on the detection of non-specific interactions, their physicochemical origins remain poorly understood. Here, we employ solution-based microfluidic technologies to characterise a set of clinical stage mAbs and their interactions with commonly used non-specificity ligands to generate non-specificity fingerprints, providing quantitative data on the underlying physical chemistry. Furthermore, the solution-based analysis enables us to evaluate the contribution of avidity in non-specific binding by mAbs. Based on our findings, we propose a quantitative solution-based non-specificity score, which can be exploited in the development of biological therapeutics and more widely in protein engineering.

biophysics↗

bioRxiv2019

A Latent Variable Model for Evaluation of Disparate Ratings of Stem Cell Colonies by Two Experts

The visual inspection of pluripotent stem cell colonies by microscopy is widely used as a primary method to assess the quality of the preparations and degree of pluripotency. The lack of ground truth and the possible inconsistency of evaluations from multiple experts within and between stem cell laboratories are sources of uncertainty about the state of the cells, the reproducibility of preparations, and the efficiency of expansion protocols. To examine how to evaluate the level of confidence one has in disparate rating from experts, we explored a statistical method for assessing the differences in ratings of pluripotent stem cells by two different experts. Two experts rated phase contrast microscope images of human embryonic stem cell (hESC) colonies on a scale of 1 (poor) to 5 (maximum pluripotency character) but agreed with one another only 48% of the time. To assess whether experts used similar criteria to rate colonies, we developed custom image feature algorithms based on the stated visual criteria provided by the experts for selection of colonies. These features, plus others, were then used to develop pluripotency scoring algorithms trained to reflect ratings of both experts. We treated expert ratings as inexact indicators of a continuous pluripotency score and considered the inconsistency between expert ratings in developing our models. The model suggests that the two experts use somewhat different scales for discriminating between colony quality. Covariance analysis indicated that both experts use features that are not included in the model. Two image features, colony perimeter and a feature based on texture, were the most important for both experts for predicting the ratings. Interestingly, colony perimeter was not one of the expert-provided criteria for rating colonies, showing that this modeling approach allowed identification of features that the experts were not aware they were using. A linear model based on both experts identified each experts top-rated colonies as well as, or better than, the ratings of the other expert, as indicated by receiver operator characteristic curve analysis. By providing an understanding of the differences and similarities in disparate sets of expert ratings, this analysis helps to establish confidence in the ratings and the criteria for ratings, even when the experts disagree.

bioinformatics↗