Biology subjects

Jasinski, M.

Publications and source records attributed to Jasinski, M..

10 recordsLinked to original sources

bioRxiv2026

Direct Counting of mRNA Copies Inside Individual Lipid Nanoparticles Using In Situ Lysis and Labeling

The optimization of mRNA-lipid nanoparticles (mRNA-LNPs) for therapeutic applications is limited in part by the inadequate characterization of mRNA payload heterogeneity. One current challenge is accurately measuring the number of mRNA copies within individual LNPs, where the standard method of intensity-based mRNA number determination is sensitive to fluorescent dye-dye interactions and heterogeneity of mRNA labeling. Here we present a single-particle microscopy method that combines direct counting of the mRNA copies per LNP with LNP size measurements. While confined in microwells, individual mRNA-LNPs are lysed to release their cargo and stained with a dye such that the number of mRNA molecules in each well can be directly counted using fluorescence microscopy. Since the method stains the mRNA cargo in situ, it enables characterization of LNPs formulated with therapeutic grade (e.g., unlabeled) mRNA. We applied this approach to two Onpattro(R)-based LNP formulations prepared using different formulation buffers, where the two formulations had different average mRNA copy number, particle size, and fraction of LNPs lacking mRNA. The ability to directly count the number of mRNA molecules in LNPs establishes a complimentary method to intensity-based mRNA number determination and supports the characterization and screening of clinically relevant LNP formulations.

biophysics↗

bioRxiv2025

Single-particle multi-parametric microscopy reveals structural, size, and payload heterogeneity in mRNA-loaded lipid nanoparticles

Deciphering the heterogeneity of mRNA-containing lipid nanoparticles (LNPs) is essential for understanding the relationship between their microscopic properties and therapeutic function. Here, by combining alternating laser excitation (ALEX) with Convex Lens-induced Confinement (CLiC) microscopy, we simultaneously measure size, multi-color fluorescence, mRNA payload, and Forster resonance energy transfer (FRET) of individual suspended LNPs containing labeled lipid and mRNA molecules. By varying formulation parameters, including ionizable lipids, formulation buffers, and molecular ratios, we investigated and correlated key microscopic properties for relevant vaccine formulations. While the per-particle lipid fluorescence was lower for empty versus mRNA-loaded particles for all formulations, the relative size of empty versus mRNA-loaded particles depended upon the formulation and intraparticle structure. When comparing CLiC-ALEX to cryogenic transmission electron microscopy measurements (Cryo-TEM), for the LNP formulations that display blebs, the fraction of bleb LNPs is in close agreement with the fraction of mRNA-containing LNPs. CLiC-ALEX also enabled quantification of the per-particle mRNA fluorescence and FRET signals, and thus the heterogeneity in the mRNA copy number and mRNA-LNP structural arrangements, where the results were compared with biophysical estimates based on the LNP formulations. These rigorous biophysical insights are critical to inform our understanding of structure-activity relationships and inform rational design of nanomedicines.

biophysics↗

bioRxiv2024

A key residue of the extracellular gate provides quality control contributing to ABCG substrate specificity

For G-type ATP-binding cassette (ABC) transporters, a hydrophobic "di-leucine motif" as part of a hydrophobic extracellular gate has been described to separate a large substrate-binding cavity from a smaller upper cavity and proposed to act as a valve controlling drug extrusion. Here, we show that an L704F mutation in the hydrophobic extracellular gate of Arabidopsis ABCG36/PDR8/PEN3 uncouples the export of the auxin precursor indole-3-butyric acid (IBA) from that of the defense compound camalexin (CLX). Molecular dynamics simulations reveal an increase in free energy and pulling forces for CLX at both the entrance and exit sites of ABCG36L704F, respectively, providing a mechanistic rationale for the transport discrimination of CLX. Mutagenesis of L704 to tyrosine allows export of structurally related non-ABCG36 substrates, indole-3-acetic acid (IAA) and indole, suggesting an allosteric communication between the extracellular gate and the central substrate binding pocket. In summary, our work supports the conclusion that L704 is a key residue of the extracellular gate that provides a final quality control contributing to ABCG substrate specificity.

biochemistry↗

bioRxiv2023

Identification of tumor-specific MHC ligands through improved biochemical isolation and incorporation of machine learning

Isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for TCR-T immunotherapies. However, as many targets of high tumor-specificity are only presented at low abundance on the cell surface of tumor cells, the efficient isolation of these peptides is crucial for their successful detection. Here, we demonstrate how different isolation strategies, which consider hydrophobicity and post-translational modifications, can improve the detection of MHC ligands, including cysteinylated MHC ligands from cancer germline antigens or point-mutated neoepitopes. Furthermore, we developed a novel MHC class I ligand prediction algorithm (ARDisplay-I) that outperforms the current state-of-the-art and facilitates the assignment of peptides to the correct MHC allele. The model has other applications, such as the identification of additional MHC ligands not detected from mass spectrometry or determining whether the MHC ligands can be presented on the cell surface via MHC alleles not included in the study. The implementation of these strategies can augment the development of T cell receptor-based therapies (i.a. TIL1-derived T cells, genetically engineered T cells expressing tumor recognizing receptors or TCR-mimic antibodies) by facilitating the identification of novel immunotherapy targets and by enriching the resources available in the field of computational immunology. SignificanceThis study demonstrates how the isolation of different tumor-specific MHC ligands can be optimized when considering their hydrophobicity and post-translational modification status. Additionally, we developed a novel machine-learning model for the probability prediction of the MHC ligands presentation on the cell surface. The algorithm can assign these MHC ligands to their respective MHC alleles which is essential for the design of TCR-T immunotherapies.

immunology↗

bioRxiv2023

ARDitox: platform for the prediction of TCRs potential off-target binding

Cellular immunotherapies, such as those utilizing T lymphocytes expressing native or engineered T cell receptors (TCRs), have already demonstrated therapeutic efficacy. However, some high-affinity TCRs have also proved to be fatal due to off-target immunotoxicity. This process occurs when the immune system acts against epitopes found on both tumor cells and healthy tissues. Moreover, some TCRs can be cross-reactive to epitopes with highly dissimilar sequences. To address this issue, we developed ARDitox, a novel in silico method based on computational immunology and artificial intelligence (AI) for predicting and analyzing potential off-target binding. We tested the performance of ARDitox in silico on different cases found in the literature where TCRs were used to target cancer-related antigens, as well as on a set of TCRs targeting a viral epitope. ARDitox was able to identify previously reported cross-reactive epitopes in line with the data available in the literature. In addition, we investigated a TCR targeting an HLA-A*02:01-restricted immunodominant epitope from the glioblastoma-associated antigen NLGN4X, identifying a cross-reactive ADH1A epitope that would not be detected in murine models. In conclusion, our in silico approach is a powerful tool that identifies potential off-target epitopes, complementing preclinical studies in developing safer cell therapies targeting tumor(- associated) antigens.

immunology↗

bioRxiv2022

Medicago truncatula ABCG40 is a cytokinin importer negatively regulating lateral root density and nodule number

Numerous studies suggest that cytokinin (CK) distribution plays a relevant role in shaping plant morphology in changing environments. Nonetheless, our knowledge about the involvement of short-distance CK translocation in root mineral nutrition remains scarce, and the specific role of CK transporters in root morphology has yet to be established. Therefore, the molecular identity of CK transporters should be determined to increase knowledge on root plasticity during soil fertility, as well as more frequently encountered plant nutrient deficiencies. In this work, we identified and characterized the Medicago truncatula full-size ATP-binding cassette (ABC) transporter of the G subfamily MtABCG40 as a plasma membrane CK importer. Its expression is root-specific and is induced by nitrogen deprivation and CKs. Our analyses indicate that MtABCG40 exerts a negative impact on lateral root density by decreasing lateral root initiation and enhancing primary root elongation. Moreover, we also observed that this transporter negatively influenced the nodule number. Our results suggest that MtABCG40 action affects CK signalling, which impacts the cellular response to auxin. In summary, we identified a novel ABCG-type CK transporter that regulates lateral root density and nodule number.

plant biology↗

bioRxiv2022

A key residue of plant ABC transporter modulates access path geometry and phenylpropanoid substrate selectivity

ABCG46 of the legume Medicago truncatula is an ABC-type transporter responsible for highly selective translocation of the phenylpropanoids, 4-coumarate and liquiritigenin, over the plasma membrane. To investigate molecular determinants of the observed substrate selectivity, we applied a combination of phylogenetic and biochemical analyses, AlphaFold2 structure prediction, molecular dynamics simulations, and mutagenesis. We discovered an unusually narrow transient access path to the central cavity of MtABCG46 that constitutes an initial filter responsible for the selective translocation of these phenylpropanoids through a lipid bilayer. Furthermore, we identified remote residue F562 as pivotal for maintaining the stability of this filter. The determination of individual amino acids that impact the selective transport of specialized metabolites may provide new opportunities associated with ABCGs being of interest, as a clinically relevant group of proteins.

biochemistry↗

bioRxiv2022

A phospho-switch provided by LRR receptor-like kinase, ALK1/QSK1/KIN7, prioritizes ABCG36/PEN3/PDR8 transport toward defense

Based on its proposed substrate preferences, the ABC transporter, ABCG36/PDR8/PEN3, from the model plant Arabidopsis stands at the cross-road between growth and defence. Recently, ABCG36 was shown to export a few indolic compounds, including the auxin precursor, indole-3-butyric acid (IBA), and to be implicated in the export of the major phytoalexin of Arabidopsis, camalexin, although clear-cut proof of camalexin transport activity is still lacking. Here we provide strong evidence that ABCG36 catalyses the direct, ATP-dependent export of camalexin over the plasma membrane, however, most likely in functional interplay with non-camalexin transporting ABCG isoforms. We identify the leucin-rich repeat receptor-like kinase, Auxin-induced LRR Kinase1 (ALK1/KIN7/QSK1), as a functional kinase to physically interact with and phosphorylate ABCG36. ABCG36 phosphorylation by ALK1 represses unilaterally IBA but not camalexin export leading to a prioritization of ABCG transport toward defense. As a consequence, phospho-dead mutants of ABCG36, like alk1 and abcg36 alleles, are hypersensitive toward infection with the root pathogen, F. oxysporum, caused by elevated fungal progression. Our findings indicate a novel, direct regulatory circuit between a receptor kinase and an ABC transporter determining transporter substrate specificity. It appears that growth and defense balance decisions in plants are performed on the transporter level by means of a reversible phospho-switch.

plant biology↗

bioRxiv2021

Identification of an isoflavonoid transporter required for the nodule establishment of the Rhizobium-Fabaceae symbiotic interaction

Nitrogen (N) as well as Phosphorus (P) are key nutrients determining crop productivity. Legumes have developed strategies to overcome nutrient limitation by e.g., forming a symbiotic relationship with N-fixing rhizobia and the release of P-mobilizing exudates and are thus able to grow without supply of N or P fertilizers. The legume-rhizobial symbiosis starts with root release of isoflavonoids, that act as signaling molecules perceived by compatible bacteria. Subsequently, bacteria release nod factors, which induce signaling cascades allowing the formation of functional N-fixing nodules. We report here the identification and functional characterization of a plasma membrane-localized MATE-type transporter (LaMATE2) involved in the release of genistein from white lupin roots. The LaMATE2 expression in the root is upregulated under N deficiency as well as low phosphate availability, two nutritional deficiencies that induce the release of this isoflavonoid. LaMATE2 silencing reduced genistein efflux and even more the formation of symbiotic nodules, supporting the crucial role of LaMATE2 in isoflavonoid release and nodulation. Furthermore, silencing of LaMATE2 limited the P-solubilization activity of lupin root exudates. Transport assays in yeast vesicles demonstrated that LaMATE2 acts as a proton-driven isoflavonoid transporter.

plant biology↗

bioRxiv2021

Graph neural networks and sequence embeddings enable the prediction and design of the cofactor specificity of Rossmann fold proteins

The Rossmann fold enzymes are involved in essential biochemical pathways such as nucleotide and amino acid metabolism. Their functioning relies on interaction with cofactors, small nucleoside-based compounds specifically recognized by a conserved {beta}{beta} motif shared by all Rossmann fold proteins. While Rossmann methyltransferases recognize only a single cofactor type, the S-Adenosylmethionine (SAM), the oxidoreductases, depending on the family, bind nicotinamide (NAD, NADP) or flavin-based (FAD) cofactors. In this study, we show that despite its short length, the {beta}{beta} motif unambiguously defines the specificity towards the cofactor. Following this observation, we trained two complementary deep learning models for the prediction of the cofactor specificity based on the sequence and structural features of the {beta}{beta} motif. A benchmark on two independent test sets, one containing {beta}{beta} motifs bearing no resemblance to those of the training set, and the other comprising 38 experimentally confirmed cases of rational design of the cofactor specificity, revealed the nearly perfect performance of the two methods. The Rossmann-toolbox protocols can be accessed via the webserver at https://lbs.cent.uw.edu.pl/rossmann-toolbox and are available as a Python package at https://github.com/labstructbioinf/rossmann-toolbox. Key pointsO_LIThe Rossmann fold encompasses a multitude of diverse enzymes involved in most of the essential cellular pathways C_LIO_LIProteins belonging to the Rossmann fold co-evolved with their nucleoside-based cofactors and require them for the functioning C_LIO_LIManipulating the cofactor specificity is an important step in the process of enzyme engineering C_LIO_LIWe developed an end-to-end pipeline for the prediction and design of the cofactor specificity of the Rossmann fold proteins C_LIO_LIOwing to the utilization of deep learning approaches the pipeline achieved nearly perfect accuracy C_LI

bioinformatics↗