Biology subjects

Lorenzen, N.

Publications and source records attributed to Lorenzen, N..

7 recordsLinked to original sources

bioRxiv2025

Decoupling liquid-liquid phase separation and opalescence from stress-induced aggregation in therapeutic mAb formulations

Liquid-liquid phase separation (LLPS) and high opalescence are two self-association phenomena commonly encountered in monoclonal antibody (mAb) formulations. Because of their impact on colloidal stability, they are commonly avoided, due to a suspected link with aggregation and reduced product shelf-life. However, the molecular underpinnings and interrelation between these phenomena remain unclear, complicating predictions of their occurrence. By combining light and X-ray scattering techniques with microscopy and advanced microfluidic setups, we here report the delicate phase behavior of a model mAb, named mAb1. This is characterized by rapid clustering and LLPS in a narrow NaCl range, above which it transitions into an opalescent state devoid of micron-sized assemblies, yet retaining a similar interaction fingerprint. Using Monte Carlo simulations, we report that the macroscopic solution state of mAb1 is controlled by a positive patch, whose degree of charge screening determines whether LLPS or opalescence will take place. Specifically, neutralization of this patch via counterion interactions diminishes intermolecular repulsion and favors the concerted action of weaker dipole-dipole/hydrophobic interactions, amounting to the creation of a new solution phase, via LLPS. Further NaCl addition distributes ions more uniformly across the surface, attenuating these attractive interactions, leading to the dismantling of droplets while preserving solution opalescence. Finally, we show that LLPS and opalescence are decoupled from stirring-induced aggregation, challenging an unequivocal relationship between these phenomena. Significance StatementTailoring formulations to maximize the stability of therapeutic antibodies is crucial for their development. This is complicated by their tendency for self-association at high concentrations, where increased opalescence and phase separation, that are thought to precede irreversible aggregation, are routinely observed. Here, we studied the molecular underpinnings of mAb opalescence versus liquid-liquid phase separation. We report the mechanisms determining the two phenomena and provide a foundation for their prediction, which may guide the rational development of mAb formulations. We further show that LLPS and opalescence can be decoupled from stress-induced aggregation. We hypothesize that excluding mAbs from the bulk solvent via LLPS may even be harnessed to enhance drug product stability.

biophysics↗

bioRxiv2025

Prediction of Antibody Non-Specificity using Protein Language Models and Biophysical Parameters

The development of therapeutic antibodies requires optimizing target binding affinity and pharmacodynamics, while ensuring high developability potential, including minimizing non-specific binding. In this study, we address this problem by predicting antibody non-specificity by two complementary approaches: (i) antibody sequence embeddings by protein language models (PLMs), and (ii) a comprehensive set of sequence-based biophysical descriptors. These models were trained on human and mouse antibody data from Boughter et al. (2020) and tested on three public datasets: Jain et al. (2017), Shehata et al. (2019) and Harvey et al. (2022). We show that non-specificity is best predicted from the heavy variable domain and heavy-chain complementary variable regions (CDRs). The top performing PLM, a heavy variable domain-based ESM 1v LogisticReg model, resulted in 10-fold cross-validation accuracy of up to 71%. Our biophysical descriptor-based analysis identified the isoelectric point as a key driver of non-specificity. Our findings underscore the importance of biophysical properties in predicting antibody non-specificity and highlight the potential of protein language models for the development of antibody-based therapeutics. To illustrate the use of our approach in the development of lead candidates with high developability potential, we show that it can be extended to therapeutic antibodies and nanobodies.

bioinformatics↗

bioRxiv2024

Biomolecular condensates sustain pH gradients at equilibrium driven by charge neutralisation

Electrochemical gradients are essential to the functioning of cells and form across membranes using active transporters. Here, we show in contrast that condensed biomolecular systems sustain significant pH gradients without any external energy input. By studying individual condensates on the micron scale using a microdroplet platform, we reveal dense phase pH shifts towards conditions of minimal electrostatic repulsion. We demonstrate that by doing so protein condensates can drive substantial alkaline and acidic gradients which are compositionally tuneable and can extend to complex architectures sustaining multiple unique pH conditions simultaneously. Through in silico characterisation of human proteomic condensate networks, we further highlight potential wide ranging electrochemical properties emerging from condensation in nature, while correlating intracellular condensate pH gradients with complex biomolecular composition. Together, the emergent nature of condensation shapes distinct pH microenvironments, thereby creating a unique regulatory mechanism to modulate biochemical activity in living systems.

biophysics↗

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↗

bioRxiv2022

Reduced representation sequencing accurately quantifies relative abundance and reveals population-level variation in Pseudo-nitzschia spp.

Certain species within the genus Pseudo-nitzschia are able to produce the neurotoxin domoic acid (DA), which can cause illness in humans, mass-mortality of marine animals, and closure of commercial and recreational shellfisheries during toxic events. Understanding and forecasting blooms of these harmful species is a primary management goal. However, accurately predicting the onset and severity of bloom events remains difficult, in part because the underlying drivers of bloom formation have not been fully resolved. Furthermore, Pseudo-nitzschia species often co-occur, and recent work suggests that the genetic composition of a Pseudo-nitzschia bloom may be a better predictor of toxicity than prevailing environmental conditions. We developed a novel next-generation sequencing assay using restriction site-associated DNA (2b-RAD) genotyping and applied it to mock Pseudo-nitzschia communities generated by mixing cultures of different species in known abundances. On average, 94% of the variance in observed species abundance was explained by the expected abundance. In addition, the false positive rate was low (0.45% on average) and unrelated to read depth, and false negatives were never observed. Application of this method to environmental DNA samples collected during natural Pseudo-nitzschia spp. bloom events in Southern California revealed that increases in DA were associated with increases in the relative abundance of P. australis. Although the absolute correlation across time-points was weak, an independent species fingerprinting assay (Automated Ribosomal Intergenic Spacer Analysis) supported this and identified other potentially toxic species. Finally, we assessed population-level genomic variation by mining SNPs from the environmental 2bRAD dataset. Consistent shifts in allele frequencies in P. pungens and P. subpacifica were detected between high and low DA years, suggesting that different intraspecific variants may be associated with prevailing environmental conditions or the presence of DA. Taken together, this method presents a potentially cost-effective and high-throughput approach for studies aiming to evaluate both population and species dynamics in mixed samples. HighlightsO_LI2bRAD method facilitates species- and population-level analysis of the same sample C_LIO_LIMethod accurately quantifies species relative abundance with low false positives C_LIO_LIConsistent shifts in allele frequencies were detected between high and low DA years C_LIO_LICertain Pseudo-nitzschia spp. populations may be more associated with DA presence C_LI

genomics↗

bioRxiv2022

Surface interaction patches link non-specific binding and phase separation of antibodies

Non-specificity is a key challenge in the successful development of therapeutic antibodies. The tendency for non-specific binding in antibodies is often difficult to reduce via judicious design and, instead, it is necessary to rely on comprehensive screening campaigns. A better understanding of the molecular origins that drive antibody non-specificity is therefore highly desirable in order to prevent non-specific off-target binding. Here, we perform a systematic analysis of the impact of surface patch properties on antibody non-specificity using a designer antibody library as a model system and DNA as a non-specificity ligand. Using an in solution microfluidics approach, we discover patches of surface hydrogen bonding to be causative of the observed non-specificity under physiological salt conditions and suggest them to be a vital addition to the molecular origins of non-specificity. Moreover, we find that a change in formulation conditions leads to DNA-induced antibody liquid-liquid phase separation as a manifestation of antibody non-specificity. We show that this behaviour is driven by a cooperative electrostatic network assembly mechanism enabled by mutations that yield a positively charged surface patch. Together, our study provides a direct link between molecular binding events and macroscopic liquid-liquid phase separation. These findings highlight a delicate balance between surface interaction patches and their crucial role in conferring antibody non-specificity.

biophysics↗

bioRxiv2022

Relative enrichment - a density-based colocalization measure for single-molecule localization microscopy

Dual-color single-molecule localization microscopy (SMLM) provides unprecedented possibilities for detailed studies of colocalization of different molecular species in a cell. However, the informational richness of the data is not fully exploited by current analysis tools that often reduce colocalization to a single value. Here, we describe a new tool specifically designed for determination of co-localization in both 2D and 3D from SMLM data. The approach uses a novel function that describes the relative enrichment of one molecular species on the density distribution of a reference species. The function reframes the question of colocalization by providing a density-context relevant to multiple biological questions. Moreover, the function visualize enrichment (i.e. colocalization) directly in the images for easy interpretation. We demonstrate the approachs functionality on both simulated data and cultured neurons, and compare it to current alternative measures. The method is available in a Python function for easy and parameter-free implementation.

cell biology↗