Biotechnology Journal

Multi-stage continuous bioprocessing can increase volumetric productivity, operational consistency, and process throughput, but its design is complicated by coupling among dilution rate, reactor volume, feed allocation, and cellular physiology. Here, we present ContiDesigner, available at https://chemnettools.anc.univie.ac.at/ContiDesigner/, a mechanistic steady-state framework and interactive web tool for the system-level design of continuous fermentation cascades. Comparing one- and two-stage configurations at equal total reactor volume and outlet flow, ContiDesigner reveals how internal flow and reactor volume allocation shape space-time yield and identifies productivity-maximizing operating conditions. Compared with one-stage processes, two-stage cascades favor lower over-all dilution rates, thereby preserving residence time in the production stage. The first-stage dilution rate approaches the corresponding one-stage productivity optimum, but the cascade optimum occurs earlier, reflecting a system-level compromise between biomass generation and production-stage residence time. However, two-stage operation outperforms optimized one-stage operation only when non-growth-associated production in the second stage is sufficiently strong, whereas increasing growth coupling favors one-stage operation. Two case studies demonstrate both the potential and limits of process intensification. An optimized two-stage design is predicted to achieve a more than 1.5 fold increase in space-time yield for poly-R-3-hydroxybutyrate (PHB) production compared with a published experimental five-stage cascade, whereas the lactic acid case study identifies conditions under which staging offers no advantage. ContiDesigner translates these design principles into an accessible workflow to explore feasible operating regions and prioritize cascade designs for experimental evaluation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/743657v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@ef58faorg.highwire.dtl.DTLVardef@1ba88a4org.highwire.dtl.DTLVardef@160edd3org.highwire.dtl.DTLVardef@9dda34_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIContiDesigner enables system-level design of continuous fermentation cascades C_LIO_LIHigh stage-one dilution supports biomass generation C_LIO_LILow stage-two dilution preserves productive residence time C_LIO_LIYet two-stage cascades favor lower overall dilution than one-stage systems C_LIO_LITwo-stage advantage requires strong non-growth-associated production in stage two C_LI

Given the current global environmental challenges, waste biomass is an attractive renewable resource for circular economies. Gasification of biomass yields syngas (CO, CO2, and H2) that is a suitable feedstock for gas fermentation in biomanufacturing of fuels and chemicals using acetogen microbes. While it is generally known that syngas composition influences both acetogen growth and process performance, we are lacking a consistent dataset quantifying these effects under controlled fermentation conditions. Here, we mapped the metabolic response of the model-acetogen Clostridium autoethanogenum to seven synthetic syngas mixtures during exponential batch growth in bioreactor fermentations. Notably, distinct gas compositions resulted in different fermentation profiles, affecting both growth and metabolite production. Maximum specific growth rates ranged within 0.05 0.13 h-1, with slower growth for low-CO mixtures. While acetate and ethanol production yields varied between 20-133 and 76-353 mmol per gram dry cell weight, respectively, minor production of 2,3-butanediol was detected. All syngas mixtures supported co-utilization of CO and H2, though gas uptake stoichiometry only moderately correlated with syngas content. Importantly, gas uptake stoichiometry strongly influenced carbon partitioning, with higher relative H2 uptake reducing CO2 loss or even realizing CO2 fixation together with increasing carbon flow towards metabolites. Interestingly, higher syngas H2 content favored ethanol and 2,3-butanediol production, while higher H2:CO uptake ratios increased total flux through the Wood-Ljungdahl pathway rather than selectively favoring reduced by-products. Our results are valuable for a better understanding of syngas composition effects on the acetogen biocatalyst and for process engineering towards optimizing gas fermentation performance. HighlightsO_LISyngas composition affects acetogen growth, gas uptake, and carbon distribution C_LIO_LIHigher H2:CO uptake ratios increase carbon flow through the Wood-Ljungdahl pathway C_LIO_LIHigher relative H2 uptake reduces CO2 loss and increases metabolite production C_LI

BackgroundContinuous glucose monitoring (CGM) systems are used not only for retrospective assessment of the glycemic profile but also for real-time decision-making, including automated insulin delivery. Accordingly, CGM performance characterization must capture not only the agreement of individual paired values but also the systems ability to reproduce the direction, rate, amplitude, and shape of glucose concentration change. Summary metrics, most notably MARD, cannot establish whether an observed deviation reflects an error in the formation of the test profile itself, a constant sensor offset, amplitude compression, a change in response rate, temporal misalignment, or hysteresis. ObjectiveTo adapt a programmable flow-based in vitro platform for the separate assessment of the experimentally delivered glucose profile and the dynamic response of CGM systems, and to propose a set of metrics that decomposes dynamic error into its components. MethodsGLU profiles were generated by programmable mixing of solutions at a constant total flow rate of 2 mL/min. Actual GLU concentration was independently measured with a SUPER GL2 glucose analyzer. Four static levels, three repeats of a 5.5[->]12.0[->]5.5 mmol/L profile, three repeats of a 6.0[->]3.0[->]6.0 mmol/L hypoglycemic profile, three 5.0[->]15.0[->]5.0 mmol/L profiles at different rates, one complex 4[->]18[->]3[->]12[->]5.5 mmol/L profile, and two proof-of-concept sensor experiments at 100- and 200-min transitions were investigated. Dynamic response was characterized by bias, MAE, RMSE, MARD, amplitude transfer coefficient K_A, rate transfer coefficients K_up and K_down, normalized shape RMSE, residual shift, and hysteresis loop area. ResultsAt the static levels, measured GLU exceeded the programmed value by 0.234-0.780 mmol/L. In the repeated 5.5[->]12.0[->]5.5 profiles, the ratio of actual to programmed rate was 0.978-1.083 on the rising phase and 0.987-1.157 on the falling phase, while the amplitude transfer coefficient was 0.967-1.066. In the hypoglycemic profile, minimum GLU was 2.55- 2.96 mmol/L, and time below 3.0 mmol/L was 15.2-72.6 min. The measured rates of 0.0519, 0.1045, and 0.2027 mmol/L/min preserved the intended ratio of approximately 1:2:4. In the complex profile, the programmed plateau of 18 mmol/L was not reached: mean measured GLU was 16.20 mmol/L. For CGM-A, K_A was 0.682 and 0.650, and K_up/K_down were 0.666/0.730 and 0.634/0.626; the corresponding values for CGM-B were 1.228 and 1.128, and 1.564/1.328 and 1.276/1.145. Hysteresis loop area differed 5- to 10-fold between the two sensor responses, exceeding an order of magnitude at the 100-min transition. ConclusionThe programmed concentration should be treated as a control setpoint, rather than as a reference measurement. The "programmed trajectory -- measured glucose -- CGM output" cascade first allows quantitative assessment of the agreement between the programmed and actually realized profile and only then separate characterization of sensor response. Decomposition of dynamic error into amplitude, rate, shape, and hysteresis components reveals differences that a single MARD value or correlation coefficient cannot capture.

Microbial fuel cells (MFCs) have been widely investigated as decentralized bioelectrochemical systems capable of converting organic substrates into electricity. However, their long-term autonomous operation is constrained by substrate depletion in the anode compartment, leading to metabolic starvation of electroactive biofilms and a decline in power output. Conventional MFC design treats substrate crossover through the membrane separator as a parasitic loss that reduces coulombic efficiency. In this work, we propose a conceptual inversion of this paradigm by considering controlled cathodic-to-anodic substrate crossover as a passive mechanism to sustain basal microbial metabolism during periods of substrate scarcity. A transport-reaction framework is developed to quantify the balance between membrane-mediated substrate flux and microbial maintenance demand within the anode biofilm. Based on this balance, a dimensionless maintenance crossover Damkohler number (Dam) is introduced to define three operational regimes: starvation-dominated (Dam >> 1), balanced autonomous (Dam {approx} 1), and crossover-dominated (Dam << 1). The framework integrates membrane transport theory with biofilm kinetics to evaluate the effects of separator properties, substrate gradients, and current-dependent electro-osmotic transport on system stability. Order-of-magnitude analysis indicates that achievable crossover fluxes span several orders of magnitude depending on separator characteristics, suggesting that membrane properties critically influence system behavior. This perspective reframes substrate crossover from a loss mechanism to a potential design variable, offering a conceptual tool for enhancing resilience and guiding separator selection in MFCs intended for long-duration, and low-maintenance operation. HighlightsO_LIControlled crossover can sustain microbial metabolism in MFCs C_LIO_LIIntroduces maintenance crossover Damkohler number (Dam) C_LIO_LIIdentifies regimes for autonomous and starvation operation C_LIO_LILinks membrane properties to long-term system stability C_LIO_LIReframes crossover as a design variable, not only a loss C_LI

In liquid fermentation of filamentous fungi such as Aspergillus oryzae, increased broth viscosity and biomass adhesion to bioreactor surfaces remain major challenges. We previously developed a hyphal dispersion mutant lacking two hyphal adhesion factors, namely cell wall -1,3-glucan (AG) and biofilm galactosaminogalactan (GAG) (AG{Delta}-GAG{Delta} strain). The culture broth of the AG{Delta}-GAG{Delta} strain has low viscosity, which improves mixing and enzyme production. However, mycelia still extensively attach to bioreactor walls and downstream equipment, which impairs mixing and reduces product recovery. The hydrophobin RolA, a surface-active protein of A. oryzae, densely coats conidia and hyphae and contributes to cell surface hydrophobicity. In this study, we disrupted the rolA gene in AG{Delta}-GAG{Delta} (AG{Delta}-GAG{Delta}-{Delta}rolA strain) and evaluated the effects of this disruption on hyphal adhesion to the walls of culture vessels, enzyme production, and bioreactor performance. At the flask scale, the adhesion to glass surfaces was significantly reduced and recombinant enzyme activity was increased by 10%. Improved culture recovery at the end of fermentation further increased total enzyme yield. In a lab-scale stirred-tank bioreactor, both growth and enzyme production were increased. Scaling-up to a 200-L bioreactor showed reduced agitation power consumption while improving hydrodynamic properties. Fermentation of AG{Delta}-GAG{Delta}-{Delta}rolA was successfully scaled up to a 3000-L bioreactor; consistent enzyme activity and improved flow circulation in the bioreactors were confirmed by computational fluid dynamics analysis. Overall, the AG{Delta}-GAG{Delta}-{Delta}rolA strain has increased enzyme production and scalability, supporting its suitability for industrial applications.

Extracellular vesicles (EVs) facilitate intercellular communication by transferring diverse bioactive molecules from donor to recipient cells. However, EVs released by distinct cellular lineages become difficult to distinguish when mixed in multicellular experimental models, limiting the analysis of how cell-cell interactions affect EV-associated molecular profiles. To address this, EV-Tracer, a CD63-based dual-fluorescence tracing and capture system for detecting, isolating, and profiling lineage-associated EV fractions, was developed. Achilles or mScarlet was inserted into the small extracellular loop of CD63, enabling tracer-specific EV detection by digital counting, antibody-based isolation, and live-cell visualisation. Exploratory EV RNA sequencing suggested that physical cell-cell contact was associated with distinct EV RNA profiles, including interferon-related signals, which were supported by targeted cellular and EV-associated RNA analyses. EV-Tracer provides a practical framework for investigating lineage-associated EV dynamics and molecular signals in mixed-cell systems.

Copper is an essential redox-active micronutrient, but agricultural soils are increasingly contaminated by copper from mining, industrial discharge, and intensive agrochemical use, pushing concentrations beyond levels plants can tolerate. Excess copper triggers Fenton-like reactive oxygen species (ROS) generation, mitochondrial dysfunction, and impaired growth. Existing mitigation strategies, such as soil amendments, phytoremediation, antioxidants, and different chelators, have been explored to reduce copper toxicity, but their effectiveness can be limited by immobilization, poor specificity, and environmental persistence. The present work introduces a nanoparticle-based strategy for the direct sequestration of excess copper coupled with protection against the oxidative damage caused by copper stress. Here, we report MPA-iron oxide nanoparticles (MIONPs), sequentially functionalized with chitosan, glutathione, and 3-mercaptopropionic acid, designed to simultaneously scavenge ROS, restore redox homeostasis, and chelate copper via surface thiol groups. MIONPs showed a significant increase in copper binding capacity over bare iron oxide nanoparticles (BIONPs) and, in copper-stressed Solanum lycopersicum seedlings, significantly improved germination and root/shoot growth, reduced intracellular ROS, restored mitochondrial membrane potential, and preserved nuclear integrity. This integrated design establishes MIONPs as a promising, dual-function nanoplatform for sustainable copper stress management in agriculture.

The increasing world population necessitates new sustainable nutrient sources, making microalgae like Chlorella sorokiniana interesting due to its rich nutrient profile and sustainable cultivation methods. With genetic optimization tools like CRISPR/Cas9, microalgae as a nutrient source can be improved even further. However, degradation of the rigid cell wall of microalgae, and thereby developing protoplasts, is often necessary prior to transformation, but monitoring protoplast development in spherical, single-celled organisms like C. sorokiniana is challenging using bright-field microscopy. Carbotrace 480 and 630 were tested as fluorescent markers of the cell wall of a C. sorokiniana mutant for protoplast detection, and Carbotrace 480 was successfully used to distinguish protoplast from normal cells in a cell suspension. The enzymes Driselase, Glucanex, Snailase, and Saczyme were tested in different combinations to degrade the cell wall of the mutant, with Snailase as the most effective yielding ~60 % protoplasts. This study provides a quick and easy tool for monitoring protoplast development in the microalgae C. sorokiniana, the first step to improve C. sorokiniana as a sustainable nutrient source using genetic optimization tools like CRISPR/Cas9.

Fed-batch production in Chinese hamster ovary cells is usually optimised empirically, yet the intracellular mechanisms that determine whether cells sustain productivity or enter terminal decline remain poorly resolved. Here, we combine longitudinal proteomics and intracellular metabolomics across differential ambr250 fed-batch processes to define the metabolic programmes associated with CHO cell viability and antibody production. Across media/feed combinations and an intensified seeding regime, culture progression followed a conserved trajectory from proliferation to metabolic transition and terminal stress. The high-stress state was characterised by a switch toward mitochondrial and peroxisomal fatty acid {beta}-oxidation, lipid remodelling, oxidative burden and activation of ferroptosis-associated pathways. Enriched feed conditions delayed this transition through enhanced redox and glutathione-linked defence, but did not proportionally increase antibody titre, revealing a trade-off in which cellular resources are diverted from recombinant protein production toward survival. These data identify fatty acid metabolism and ferroptosis as key constraints on late-stage CHO fed-batch performance and provide a mechanistic framework for rational feed design and host-cell engineering.

Human iPSC-derived brain organoids are revolutionizing tools to study layers biology, synergize disease modeling, and accelerate therapeutic discoveries that overcome obstacles in monolayer cell culture or animal models. The neurovascular unit including vasculature and microglia is critical for brain development, maintenance of synaptic plasticity and neural activity, and the high metabolic demands of long-term culture. We present a methodology to incorporate these important components during organoid generation and discuss potential approach, aiming consistent production of vascularized organoids for longitudinal study. We also demonstrate that this vascularized organoid is a versatile platform to model brain cancer and traumatic brain injury.

Compact Cas nucleases offer advantages over the widely used SpCas9 due to their smaller size, which enables more efficient delivery for in vivo applications. Among these, the phage-encoded Cas{Phi}2 (Cas12j2) is highly promising due to its relaxed PAM requirement (5-TTN-3) and compact size (757 aa); however, its translational potential is limited by low editing activity. To enhance the efficacy of Cas{Phi}2, we optimized the previously reported EPICA system, developing EPICA.2, a eukaryotic directed evolution platform to improve nucleases with nearly undetectable activity. EPICA.2 integrates additional yeast evolution rounds to enrich for active variants along with a low background mammalian reporter system that improves detection and selection of enhanced variants. Finally, we set up a long-read sequencing protocol which uses unique molecular identifiers (UMIs) to reduce sequencing errors, enabling accurate identification of the mutation combinations in each evolved variant. Among the most frequent variants, we obtained evoCas{Phi}2, which contains six activity-boosting mutations with a synergistic effect not predictable by rational engineering. Overall, evoCas{Phi}2 showed up to 70-fold increased activity in human cells compared to wild-type and outperformed variants generated through rational approaches, highlighting the potential of EPICA.2 as a powerful strategy to evolve genome editing tools with low native activity.

Cell confluency is a major determinant of cell-cell communication, protein interactions, access to nutrients, and signalling dynamics, thereby significantly impacting biological outcomes. Lung cancer cells like A549 are widely used as screening models for scientific studies wherein their growth in vitro progress from non-confluent to confluent growth. In this study, we investigated the transcriptomic adaptations associated with the transition of A549 cells from baseline non-confluent to confluent growth. Comparative transcriptomic analysis between confluent and cells at baseline identified 815 upregulated and 671 downregulated transcripts. Pathway enrichment analysis of deregulated transcripts in confluent cells revealed enhanced cholesterol and sterol biosynthetic pathways, along with suppression of chromosomal segregation and mitotic pathways. At confluency, an increased expression of glucose transporters (SLC2, SLC60, and SL37 families) and glycolytic pathways, and a decrease in amino acid transporters (SLC1, SLC7, SLC38, and SLC36) and amino acid metabolic pathways is observed. A reduced one-carbon metabolic signature (SHMT2, DHFR, and MTHFD2) and enhanced fatty acid precursor synthesis (HMGCLL1, ALDH6A1, and AASS) were also observed at confluency. 1H NMR profiling of culture media revealed higher glucose and glutamine utilisation with lactate accumulation during culture maturation. Collectively, the data suggest transcriptome-level rewiring in A549 cells with preferential biosynthesis of lipids and sterols at confluency and underscore the importance of considering culture maturity in cancer biology, metabolism, and therapeutic studies.

Induced pluripotent stem cells (iPSCs) hold great promise for both allogeneic and autologous cellular therapies. However, broad application and clinical translation is hindered by fragmented, complex and time-intensive workflows, resulting in high manufacturing costs, poor standardization and increased risk of genomic aberrations in derived iPSCs. In this study we developed a standardizable, automatable and time- efficient process for the derivation of monoclonal iPSC lines straight from skin including a comprehensive and cascaded OC strategy. We generated monoclonal iPSC lines derived from human skin punch biopsies of ten donors (age 49-81) via mRNA-based reprogramming that subsequently underwent comprehensive and thorough characterization of phenotypic and genetic properties. The use of a combined mechanical and enzymatic fibroblast isolation protocol and a transient non-integrative reprogramming technology allowed us to obtain 78 monoclonal iPSC lines, ready for banking, molecular characterization and further differentiation within seven weeks from initial sample processing to passage four iPSC lines. The phenotypical characterization via flow cytometry-based pluripotency marker expression and 2D-directed differentiation into the three germ layers showed low intra- and inter-donor variability over all generated lines. A combination of SNP array based CNV analysis followed by whole exome sequencing proved to be the most efficient approach for assessment of genomic integrity. Proof-of-concept experiments for closed system processing revealed that a substantial part of the most error-prone and technically demanding steps can be transferred to semi- automated, closed systems. In conclusion, the described protocol allows for time- efficient, standardizable and automatable generation of high-quality monoclonal iPSC lines from human skin punch biopsies within seven weeks, thus moving the field of autologous iPSC manufacturing one step further towards cost-efficient clinical implementation.

Development of candidate countermeasures against human pathogens frequently includes nonhuman animal experimentation. Preclinical animal pathogen exposure studies are conducted to model diseases and accumulate preliminary and hypothetically translatable data to inform and justify the design of clinical trial evaluation of countermeasure safety and efficacy. In addition to frequent ethical critiques, challenges associated with animal experimentation include considerable resources needed to achieve statistical power and robustness, replicability and reproducibility concerns, potentially compromised objectivity through lack of blinding, fundamental species-specific biological differences, and risk of unpredictable pathogen adaptation to the experimental animal. Recent U.S. and U.K. government initiatives aim to reduce animal experimentation by complementing or potentially replacing them with new approach methodologies (NAMs), i.e., increasingly sophisticated in silico, in chemico, and in vitro approaches. We piloted development of one type of NAM, organ-on-chips (OOCs), in the highly challenging environment of a maximum (biosafety level 4) containment laboratory. Using a Risk Group 4 virus, Nipah virus (NiV), and two types of lung OOCs seeded with human or porcine cells, we demonstrated the recapitulation of key features of NiV lung infection, including viral infection, replication, and translocation, that are associated with proinflammatory cytokine secretion, immune cell recruitment, and disruption of the air-liquid interface barrier. We reproduced the known anti-NiV activity of remdesivir and evaluated that of another potential antiviral, zotatifin. Our results pave the way for similar applications of advanced microphysiological systems for modeling infections caused by high-consequence viruses.

Hydrogels have emerged as attractive vaccine delivery platforms because they enable controlled modulation of antigen availability. However, how different hydrogel environments affect the release and functionality of mRNA-loaded lipid nanoparticles (mRNA-LNPs) remains poorly understood. Here, we investigated the release, stability, cellular uptake, and transfection capability of LNPs released from four hydrogel systems representing distinct crosslinking mechanisms: covalently crosslinked poly(ethylene glycol) (PEG), ionically crosslinked alginate, thermoresponsive Poloxamer 407 (P407), and protein-based Matrigel/collagen hydrogels. All hydrogels enabled release of LNPs over days, with kinetics strongly depending on hydrogel composition and polymer concentration. LNPs were quantitatively recovered from all hydrogel types, except from Matrigel/collagen where incomplete matrix dissolution was the limiting step. Lower polymer concentrations generally accelerated nanoparticle release. PEG offered greatest tunability of release kinetics; at the same time the recovery of the LNP-incorporated fluorescent dye DiI was reduced to about 80 %, indicating partial dye leakage. Alginate hydrogels exhibited recovery of DiI below 50 % and broader particle size distributions after release, while P407 hydrogels largely preserved LNP characteristics. Although quantitative recovery from Matrigel/collagen hydrogels was limited, released LNPs remained readily available for cellular uptake. Notably, LNPs released from low- and intermediate-concentration Matrigel/collagen hydrogels achieved approximately 80-90 % of the eGFP expression compared to mRNA-LNP that were not embedded into a hydrogel. Importantly, cellular uptake and transfection experiments demonstrated that all investigated hydrogels released biologically active mRNA-LNPs capable of mediating protein expression. Moreover, our findings show that hydrogel composition is a critical determinant of mRNA-LNP release, stability, and functional delivery. This work provides design principles for the development of hydrogel-based mRNA delivery systems aimed at sustained antigen availability and prolonged vaccine responses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/741169v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@138d9eforg.highwire.dtl.DTLVardef@16c0edaorg.highwire.dtl.DTLVardef@1432dd1org.highwire.dtl.DTLVardef@17511b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

While in vivo synthesis of biologic therapeutics has been broadly successful, it is limited by biological constraints of the cells and by the complexity, time, and cost of implementing the pipeline from discovery through manufacturing. Cell-free expression systems (CFES), which use cellular transcription and translation machinery to express proteins in vitro, offer a promising alternative approach that could improve robustness and modularity in that pipeline. However, current benchmark CFES productivity is well below the theoretical capacity of the input nucleotides and amino acids. Efforts to address this issue are hindered by limited understanding of the extent of enzymatic activity in CFES beyond gene expression, as previous work has shown that metabolic enzymes in cell-free lysates cause substantial background metabolic activity that influences protein expression. Here, we hypothesized that the inflection point of protein expression is a critical timescale for CFES metabolism. We performed metabolomics characterization of CFES reactions, finding significant metabolic changes at the inflection point. Driven by these findings, we sought to identify supplements that could be added to the cell-free reaction to avoid metabolic limitations. We found that amino acid supplementation increased expression productivity and lifetime only when added after the inflection point, and actually hurt expression when added before the inflection point. We found similar supplementation timing impacts for some other metabolites as well. These findings show that endogenous metabolism and supplementation timing are deeply interconnected and are critical considerations in CFES optimization, and that metabolomics-informed fed-batch supplementation is a potentially valuable strategy to improve reaction productivity.

An important step toward clinical implementation of (epi-)genomic assays on liquid biopsies is their validation on identical samples within and across laboratories. For these validation studies, there is a need for cell-free DNA (cfDNA) samples with defined tumor fractions and (epi-)genomic aberrations. However, the amount of circulating cfDNA isolated from patient samples is often limited, especially in pediatric cases. Additionally, patient samples contain a high degree of variability in cfDNA yield and tumor fraction. Several commercial artificial cfDNA products are available for validation studies, however their use is restricted to specific assays, aberrations and/or tumor entities. Alternatively, artificial cfDNA samples can be produced by fragmenting genomic DNA to mimic highly fragmented cfDNA derived from both tumor and healthy blood, followed by mixing artificial tumoral and healthy cfDNA at defined fractions. In this study, we compared native cfDNA with artificial cfDNA generated by three different fragmentation methods, including sonication and two enzymatic digestions using micrococcal nuclease and double-stranded deoxyribonuclease (dsDNase). We assessed fragment length profiles, end motifs and nucleosome occupancy patterns from shallow whole-genome sequencing data, as well as coverage profiles from targeted panel sequencing, together with a small-scale mixing experiment of tumor and healthy cell derived artificial cfDNA. Although sonication remains a convenient high-throughput approach to generate artificial cfDNA for certain downstream applications, enzymatic fragmentation, particularly the dsDNase-based method, more faithfully reproduced native cfDNA characteristics.

Isotopic Metabolic Flux Analysis (I-MFA) is a standard approach for estimating intracellular metabolic fluxes. I-MFA infers fluxes by comparing simulated and measured metabolite isotopologue distributions (MIDs) of metabolites from isotope labeling experiments. MIDs represent fractional abundances that strictly sum to one for any given metabolite, thus they are inherently compositional data. However, state-of-the-art estimation approaches rely on calculating standard Euclidean distances between MIDs in a non-compositional paradigm, introducing a systemic bias. To resolve this, our study proposes compositional I-MFA. We demonstrate how to construct a meaningful orthonormal basis for MIDs via ordered sequential binary partitioning, which can be used to perform isometric log-ratio (ILR) transformation. As a minimal change to existing I-MFA workflows, we suggest estimating fluxes by minimizing Euclidean distances between ILR-transformed MIDs. We validated this framework against traditional methods using both a toy model and a biologically realistic model, evaluating point estimates, sensitivity across varied true fluxes, and confidence intervals. In the two examples, compositional I-MFA consistently outperformed traditional approaches, reducing mean squared error of flux point estimates by an average of 42.6% and substantially narrowing confidence intervals. We conclude that compositional data analysis significantly improves I-MFA and can be implemented as a simple drop-in replacement for current pipelines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/742769v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1a53aa4org.highwire.dtl.DTLVardef@ad225aorg.highwire.dtl.DTLVardef@aa430eorg.highwire.dtl.DTLVardef@1880ca_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINew compositional data approach improves metabolic flux estimation. C_LIO_LIThis data transformation requires minimal changes to existing workflows. C_LIO_LIThe new method reduced MSE of flux estimates by 42.6% in two examples tested. C_LIO_LIThe confidence intervals of the estimated fluxes were substantially narrowed. C_LIO_LIEstimation accuracy remained robust across a wide range of metabolic fluxes. C_LI

Endothelial cells (ECs) derived from human induced pluripotent stem cells (hiPSCs) are increasingly used to model vascular diseases and test therapeutic strategies. However, the efficiency and reproducibility of differentiation can vary depending on the culture medium and its supplemented factors and stages. Here, we directly compared two defined media, APEL and BPEL, for iPSC-to-ECs differentiation. iPSCs were differentiated over 10 days with sequential growth factor induction, followed by magnetic-activated cell sorting or flow cytometry for CD31+ cells. Both media produced ECs with similar morphology and marker expression, including CD31 and VE-cadherin. Functional assays demonstrated comparable tube formation, indicating equivalent endothelial functionality. Cost analysis indicated that APEL had a higher total reagent cost but generated a higher total cell yield, resulting in a comparable cost per 10 total cells, whereas BPEL was more cost-efficient for producing CD31/VE-cadherin endothelial-specific cells. Our results suggest that APEL and BPEL media are equally effective for generating iPSC-derived ECs, providing flexibility in method selection for vascular disease modeling and drug discovery applications.

Actinomycin D (Act D) is a global transcriptional inhibitor widely used in research and clinical practice; however, its effects on RNA-binding protein (RBP) dynamics remain poorly understood. Analysis of an RNA-seq dataset from Act D-treated HeLa cells revealed a compensatory stress response enriched in RNA metabolism, processing, and translation. Here, we investigated the effects of Act D on the subcellular localization of RBPs using HuR as a model mRNA stabilizing RBP. Short-term Act D treatment markedly increased cytoplasmic HuR localization in HCT116 and HeLa cells where the protein is known to be active. Analysis of known pathways regulating HuR nucleocytoplasmic translocation did not fully explain this redistribution, suggesting alternative mechanisms. To identify proteins proximal to HuR following Act D treatment, we performed TurboID labeling followed by LC-MS/MS in HCT116 cells. Several proteins involved in RNA regulation were identified. Probabilistic modeling highlighted FUS, an RBP with established roles in phase-separated granule dynamics, as a candidate proximal protein. The Act D-dependent interaction between HuR and FUS was interrogated using molecular dynamics simulations and validated with proximity ligation assays. Furthermore, increased cytoplasmic localization of RBPs following Act D treatment was accompanied by formation of granular structures that were relatively fluid and could be disrupted by hypotonic shock. Collectively, our findings demonstrate that Act D induces cytoplasmic redistribution of multiple RBPs and their sequestration into dynamic granular structures, revealing a previously unrecognized cellular response to transcriptional inhibition. Graphical AbstractAct D induced cytoplasmic re-localization of HuR along with FUS and other RBPs in dynamic, hypotonic shock-sensitive granular structures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/745449v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@515322org.highwire.dtl.DTLVardef@128f0d5org.highwire.dtl.DTLVardef@db4302org.highwire.dtl.DTLVardef@10c4a2e_HPS_FORMAT_FIGEXP M_FIG C_FIG