Biology subjects

Nowak, R.

Publications and source records attributed to Nowak, R..

8 recordsLinked to original sources

bioRxiv2025

Perfusion Bioreactor Culture Incorporating Mechanical Confinement Enhances Mesenchymal Stem Cell Extracellular Vesicle Production and Wound Healing Potential

Mesenchymal stem cell extracellular vesicles (MSC EVs) have been widely studied for regenerative medicine and tissue repair applications. However, clinical translation of EV therapeutics has been hampered by low potency and lack of scalable production strategies. This work aims to develop a novel approach that exploits the mechanosensitivity of MSCs to enhance EV potency in the context of enhanced production via bioreactor culture. MSCs are well known to respond to mechanical stimuli such as substrate stiffness and shear stress, and here it is shown that exposing MSCs to another mechanoregulatory parameter, confinement, enhances the pro-angiogenic bioactivity of their EVs. This is consistent across both donor-derived primary MSCs and induced pluripotent stem cell-derived MSCs (iMSCs). The development of a 3D-printed perfusion bioreactor system that enables culture of confined MSCs under flow is also detailed here, resulting in a 67-fold increase in EV production compared to flask culture. iMSC EVs obtained downstream of this confinement-bioreactor culture induce greater vascularization and generally improve wound healing in a diabetic mouse model compared to iMSC EVs from conventional tissue culture. Overall, this work establishes the development of a scalable, bioreactor-based iMSC EV production platform that provides a solution to major translational bottlenecks of therapeutic EVs.

bioengineering↗

bioRxiv2025

Genetically-programmed Hypervesiculation of Lactiplantibacillus plantarum Increases Production of Bacterial Extracellular Vesicles with Therapeutic Efficacy in a Preclinical Inflammatory Bowel Disease Model

Inflammatory bowel diseases (IBD) affect over 6 million people globally and current treatments achieve only 10-20% rates of durable disease remission. Bacterial extracellular vesicles (BEVs) from probiotic lactic acid bacteria (LAB) are a promising novel therapeutic with mechanisms holding potential to drive increased rates of durable disease remission, including immunomodulation and intestinal epithelial tissue repair. However, translation of these cell-secreted nanovesicles is limited by long standing biomanufacturing hurdles, especially low production yields due to low biogenesis rates from cells. Here, our goal was to identify a candidate probiotic LAB that produces BEVs effective in a preclinical mouse model of IBD, and then genetically engineer the LAB for at least 10-fold increased production yields of BEVs, thereby passing a critical production threshold. We identified Lactiplantibacillus plantarum as a candidate LAB producing BEVs effective in treating acute dextran sulfate sodium (DSS)-induced murine colitis, and with greater efficacy than BEVs from probiotic Escherichia coli Nissle 1917. We then genetically engineered a hypervesiculating L. plantarum strain by inducible expression of a peptidoglycan-modifying enzyme, resulting in a 66-fold increase in BEV productivity. Finally, we confirmed hypervesiculating L. plantarum BEVs were therapeutically effective in the acute DSS mouse model of colitis and found these BEVs were superior in reducing mucosal tissue damage compared to live L. plantarum cells. These findings demonstrate that BEVs from genetically engineered hypervesiculating strain of L. plantarum are a promising preclinical therapeutic candidate for IBD that overcomes historical biomanufacturing limitations of BEV therapeutics.

bioengineering↗

bioRxiv2025

Decoding protein-peptide interactions using a large, target-agnostic yeast surface display library

Protein-peptide interactions underlie key biological processes and are commonly utilized in biomedical research and therapeutic discovery. It is often desirable to identify peptide sequence properties that confer high-affinity binding to a target protein. However, common approaches to such characterization are typically low throughput and only sample regions of sequence space near an initial hit. To overcome these challenges, we built a yeast surface displayed library representing [~]6.1 x 109 unique peptides. We then performed screens against diverse protein targets, including two antibodies, an E3 ubiquitin ligase, and an essential membrane-bound bacterial enzyme. In each case, we observed motifs that appear to drive peptide binding and we identified multiple novel, high-affinity clones. These results highlight the librarys utility as a robust and versatile tool for discovering peptide ligands and for characterizing protein-peptide binding interactions more generally. To enable further studies, we will make the library freely available upon request.

bioengineering↗

bioRxiv2024

Direct RNA Oxford Nanopore sequencing distinguishes between modifications in tRNA at the U34 position

The measurement of tRNA modifications with single transcript resolution has been feasible for only a few modifications due to the lack of available methods. This limitation does not allow to advance basic research studies on the dynamic nature of tRNA modification and its cellular function in time and space, neither to develop modern diagnostic tools for several already known tRNA-dependent human diseases. Nanopore is a well-established sequencing method that has proven to be efficient for the study of RNA. The analysis of tRNA modifications by Nanopore is still under development. We have investigated the efficacy of nanopore technology to discriminate between complex modifications of uridine 34 in tRNA, which affect the base-calling properties of neighbouring bases and are therefore difficult to accurately predict. We have developed new methods to chemically and enzymatically synthesise single modified tRNA molecules with modifications at the anticodon loop. Nanopore technology captures the features produced by uridine with and without a thiol group when present on synthetic tRNA molecules. Thus, Oxford Nanopore Technology (ONT) has great potential for developing strategies to accurately identify the modification status of the tRNA anticodon loop (ACL), which encompasses the most complex modifications on uridine-containing RNA motifs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/630739v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@4317baorg.highwire.dtl.DTLVardef@caf204org.highwire.dtl.DTLVardef@1d7249dorg.highwire.dtl.DTLVardef@1a4f8c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2021

Early cross-coronavirus reactive signatures of protective humoral immunity against COVID-19

The introduction of vaccines has inspired new hope in the battle against SARS-CoV-2. However, the emergence of viral variants, in the absence of potent antivirals, has left the world struggling with the uncertain nature of this disease. Antibodies currently represent the strongest correlate of immunity against COVID-19, thus we profiled the earliest humoral signatures in a large cohort of severe and asymptomatic COVID-19 individuals. While a SARS-CoV-2-specific immune response evolved rapidly in survivors of COVID-19, non-survivors exhibited blunted and delayed humoral immune evolution, particularly with respect to S2-specific antibody evolution. Given the conservation of S2 across {beta}-coronaviruses, we found the early development of SARS-CoV-2-specific immunity occurred in tandem with pre-existing common {beta}-coronavirus OC43 humoral immunity in survivors, which was selectively also expanded in individuals that develop paucisymptomatic infection. These data point to the importance of cross-coronavirus immunity as a correlate of protection against COVID-19.

immunology↗

bioRxiv2020

Proteomic and functional analyses of the periodic membrane skeleton in neurons

Actin, spectrin, and associated molecules form a membrane-associated periodic skeleton (MPS) in neurons. The molecular composition and functions of the MPS remain incompletely understood. Here, using co-immunoprecipitation and mass spectrometry, we identified hundreds of candidate MPS-interacting proteins that span diverse functional categories. We validated representative proteins in several of these categories, including previously unknown MPS structural components, as well as motor proteins, cell adhesion molecules, ion channels, and signaling proteins, demonstrating periodic distributions of [~]20 proteins in neurons using super-resolution imaging. Genetic perturbations of the MPS and its interacting proteins further suggested functional roles of the MPS in axon-axon and axon-dendrite interactions and in axon diameter regulation, and implicated the involvement of MPS interactions with cell adhesion molecules and non-muscle myosin in these roles. These results provide new insights into the interactome of the MPS, and suggest new functions of the MPS in neurons.

neuroscience↗

bioRxiv2019

The Low-Cost, Semi-Automated Shifter Microscope Stage Transforms Speed and Robustness of Manual Protein Crystal Harvesting

Despite the tremendous success of x-ray cryocrystallography over recent decades, the transfer of crystals from the drops where they grow to diffractometer sample mounts, remains a manual process in almost all laboratories. Here we describe the Shifter, a semi-automated microscope stage that offers an accessible and scalable approach to crystal mounting that exploits on the strengths of both humans and machines. The Shifter control software manoeuvres sample drops beneath a hole in a clear protective cover, for human mounting under a microscope. By allowing complete removal of film seals the tedium of cutting or removing the seal is eliminated. The control software also automatically captures experimental annotations for uploading to the users data repository, removing the overhead of manual documentation. The Shifter facilitates mounting rates of 100-240 crystals per hour, in a more controlled process than manual mounting, which greatly extends the lifetime of drops and thus allows for a dramatic increase in the number of crystals retrievable from any given drop, without loss of X-ray diffraction quality. In 2015 the first in a series of three Shifter devices was deployed as part of the XChem fragment screening facility at Diamond Light Source (DLS), where they have since facilitated the mounting of over 100,000 crystals. The Shifter was engineered to be simple, allowing for a low-cost device to be commercialised and thus potentially transformative as many research initiatives as possible. SynopsisA motorised X/Y microscope stage is presented that combines human fine motor control with machine automation and automated experiment documentation, to transform productivity in protein crystal harvesting.

biophysics↗

bioRxiv2018

Clustering-based optimization method of reference set selection for improved CNV callers performance

BackgroundThere are over 25 tools dedicated for the detection of Copy Number Variants (CNVs) using Whole Exome Sequencing (WES) data based on read depth analysis.\n\nThe tools reported consist of several steps, including: (i) calculation of read depth for each sequencing target, (ii) normalization, (iii) segmentation and (iv) actual CNV calling. The essential aspect of the entire process is the normalization stage, in which systematic errors and biases are removed and the reference sample set is used to increase the signal-to-noise ratio.\n\nAlthough some CNV calling tools use dedicated algorithms to obtain the optimal reference sample set, most of the advanced CNV callers do not include this feature.\n\nTo our knowledge, this work is the first attempt to assess the impact of reference sample set selection on CNV detection performance.\n\nMethodsWe used WES data from the 1000 Genomes project to evaluate the impact of various methods of reference sample set selection on CNV calling performance of three chosen state-of-the-art tools: CODEX, CNVkit and exomeCopy. Two naive solutions (all samples as reference set and random selection) as well as two clustering methods (k-means and k nearest neighbours with a variable number of clusters or group sizes) have been evaluated to discover the best performing sample selection method.\n\nResults and ConclusionsThe performed experiments have shown that the appropriate selection of the reference sample set may greatly improve the CNV detection rate. In particular, we found that smart reduction of reference sample size may significantly increase the algorithms precision while having negligible negative effect on sensitivity. We observed that a complete CNV calling process with the k-means algorithm as the selection method has significantly better time complexity than kNN-based solution.

bioinformatics↗