Biology subjects

Meyer, A. S.

Publications and source records attributed to Meyer, A. S..

At least 19 recordsLinked to original sources

bioRxiv2026

3D bioprinting of engineered living materials in support slurries for complex free-standing structures

The combination of synthetic biology and additive manufacturing has driven major changes in production of biomaterials, especially through the use of three-dimensional (3D) bioprinting to create engineered living materials. However, current fabrication methods can be limited by prohibitive hardware costs and the inability to maintain structural fidelity in complex, free-form living architectures. This work demonstrates how to build a low-cost, open-source 3D bioprinting platform that can make complicated bacterial structures with complex geometry and high dimensional accuracy. A commercially available, conventional fused deposition modeling 3D printer was modified to create a bioprinting system that is simple to build. The modified bioprinter, which costs around $450, is less expensive than many commercial bioprinters. This 3D-printing technology uses slurry-based support bath methods featuring low-cost gelatin and agarose microparticles, resulting in structures with a high aspect ratio (>8:1) and feature sizes as small as 260 m. The optimization of critical printing settings, including the ability of the bioink to retract during non-print movements, resulted in a reduction of unwanted bacterial deposition by nearly two orders of magnitude. Long-term viability experiments showed that bacteria in the bioprints could survive for at least 28 days with nutrient supplementation. Additionally, 3D-printed engineered biofilms revealed that incubation conditions and extracellular matrix composition significantly impacted the mechanical properties of printed constructs, with tradeoffs between matrix production and mechanical integrity. This study showcases an accessible 3D bioprinting platform for advanced bioprinting technologies, enabling development of engineered living materials with potential applications in synthetic biology, biotechnology, and tissue engineering.

synthetic biology↗

bioRxiv2026

Systems serology of responses against tumor antigens in ovarian cancer reveal disrupted Fc-mediated immunity

High-grade serous ovarian cancer (HGSOC) represents 75% of ovarian cancer cases and 80% of deaths, with most patients relapsing despite initial treatment response. The limited effectiveness of immunotherapies in HGSOC indicates urgent need for novel therapeutic approaches. HGSOC patients produce tumor-binding autoantibodies (TBAs) with high tumor selectivity. Since effective antibody-mediated tumor cell killing requires Fc domain interactions with immune cells, we hypothesized that, although TBAs recognize tumor cells, they might still poorly elicit cell killing responses. Using a systems serology approach, we profiled TBA subclass and biophysical interactions with Fc receptors in HGSOC, comparing them to antiviral antibody responses. TBAs were consistently identified within ascites and serum and were heterogeneous in subclass composition. However, TBAs consistently lacked the capacity to bind Fc{gamma}RIIIa despite abundant interaction with Fc{gamma}RIIa and poorly elicited antibody-dependent cellular cytotoxicity, suggesting their Fc features prevent cell killing responses. Restoring Fc{gamma}RIIIa interaction may be a promising therapeutic approach in HGSOC. HighlightsO_LITBAs in ovarian carcinoma patients consistently lack interaction with Fc{gamma}RIIIa C_LIO_LIAscites- and serum-derived TBAs have heterogeneous subclass composition C_LIO_LISystems analysis shows complex serologic differences between TBAs and antiviral responses C_LIO_LIPatient-expressed TBAs demonstrate little antibody-dependent cellular cytotoxicity C_LI

cancer biology↗

bioRxiv2026

Tracing cell communication programs across conditions at single cell resolution with CCC-RISE

Cell-cell communication (CCC) mediates coordinated cellular activities that vary dynamically across time, location, and biological context. While various tools exist to infer CCC, they typically aggregate data according to pre-defined cell types, obscuring critical single-cell heterogeneity. Furthermore, because signaling pathways and cell populations operate in a coordinated manner, an integrative analytical approach is essential. To address these challenges, we developed CCC-RISE, an extension of the tensor-based method Reduction and Insight in Single-cell Exploration (RISE). CCC-RISE identifies integrative patterns of single-cell variation by deconvolving communication into interpretable modules defined by unique sender cells, receiver cells, ligands, and condition associations. We applied this framework to a COVID-19 cohort with varying disease severity and a lung transplant cohort with acute allograft dysfunction. In both contexts, CCC-RISE successfully identified disease-relevant communication programs and traced them to specific cellular subpopulations, often crossing conventional cell-type boundaries. This approach offers a robust pipeline enabling the identification of disease-relevant signaling subpopulations that are invisible to aggregate methods. HighlightsO_LICCC-RISE enables integrative analysis of cell-cell communication across multiple conditions at single-cell resolution C_LIO_LICCC-RISE deconvolves signaling patterns into modules defined by their sender cells, receiver cells, LR pairs, and experimental conditions/samples C_LIO_LIAnalysis at single-cell resolution uncovers signaling activity within and across conventional cell types C_LI

systems biology↗

bioRxiv2025

Transforming dairy waste into hydrogen fuel using alginate-encapsulated bacterial co-cultures

Dairy waste, such as whey resulting from cheese production, is produced in massive volumes worldwide and is regarded as environmentally difficult to dispose of due to its high organic content1. Harnessing the potential of this waste material to support the synthesis of valuable products such as hydrogen fuel or reduced graphene oxide, which may be utilized for conductive thin films and energy storage2,3, can reduce waste and add revenue streams for dairy farmers. Here, we demonstrate a circular bioeconomy using alginate-encapsulated co-cultures of Shewanella oneidensis together with lactic-acid-producing bacteria Klebsiella pneumoniae. These co-cultures can directly metabolize unprocessed cheese-making waste as an electron source instead of costly, environmentally high-impact lactic acid4,5. Alginate-encapsulated co-cultures fed unprocessed dairy waste showed a 2-to-3-fold higher graphene oxide reduction rate compared to S. oneidensis monocultures with no supplemental electron source. Encapsulated co-cultures were able to be recycled for more than 30 days with no measurable decrease in graphene oxide reduction efficiency, showing compatibility with future industrial scaling. Photocatalytic hydrogen generation with cadmium selenide quantum dots as the catalyst resulted in 6-fold increases in hydrogen produced by co-cultures using milk as an electron source precursor for the system in comparison to S. oneidensis monocultures without any added electron sources. Thus, dairy waste may be processed to drive the synthesis of valuable products utilizing microbial electron transfer processes, converting a significant fluvial environmental pollutant into a valuable renewable energy resource that could provide a robust alternative revenue stream for dairy farmers in a volatile industry.

microbiology↗

bioRxiv2025

Tunable light-focusing behavior of engineered bacterial microlenses with controllable shapes

Recently, engineered bacterial cells have been shown to behave as optically-active photonic devices comparable to industrially fabricated microlenses1. Bacterial cells can be encapsulated within a layer of polysilicate through surface display of the sea sponge enzyme silicatein, which mineralizes a polysilicate coating. The addition of this polysilicate layer significantly enhances the ability of these cells to guide, scatter, and focus light1. However, this previous technique was limited to creating rod-shaped microlenses, which are not ideal for all applications. Here we expand upon this technology by engineering the shapes of silicatein-displaying bacterial cells. Through the overexpression of the genes bolA2-5 and sulA6,7 or through the use of the drug A228,9, we are able to alter Escherichia coli cells from their characteristic rod-like shape to either spherical or filamentous forms. Round cells encapsulated in polysilicate were shown to scatter light more intensely and symmetrically than rod-shaped cells, while encapsulated filamentous cells were shown to guide light similarly to an optical fiber. This control over the size and shape of optically-active cells is a major advancement towards developing bio-engineered photonic devices such as nanophotonic waveguides, spherical microlens arrays, and advanced biosensors.

synthetic biology↗

bioRxiv2025

Emergent Morphologies, Slow Dynamics, and Phase Behavior in Dps:DNA assemblies

The DNA-binding protein from starved cells (Dps) compacts bacterial DNA into stress-protective condensates, but the physical ingredients that are sufficient to produce the observed morphological and dynamical phenomenology remain unclear. Here we use Dps:DNA as the motivation for a broader soft-matter question: which properties govern the co-condensation of a semiflexible polymer with a binding co-solute, and how is the resulting condensate morphology selected? We combine coarse-grained Brownian dynamics (BD) simulations, in which DNA is a semiflexible bead-spring chain and Dps a spherical particle interacting through heterotypic attraction and homotypic repulsion, with a ternary Flory-Huggins free energy evolved under conserved Cahn-Hilliard-Cook dynamics. Both frameworks show that the condensate morphology is governed jointly by the heterotypic Dps:DNA attraction and by composition: attraction drives co-condensation, while at fixed attraction the relative abundance of the two species selects between extended, network-like structures and compact, droplet-like condensates. That two independent models, sampling different concentration regimes, both show composition-controlled morphology selection indicates it is a robust feature of the co-condensation thermodynamics. The simulations further reveal slow, heterogeneous dynamics: sub-diffusive Dps motion and a stretched-exponential collapse of chain dimensions, signatures of the dynamical arrest that accompanies compaction. The framework provides general, transferable principles for protein-nucleic-acid phase separation in soft and living matter.

biophysics↗

bioRxiv2025

Genome-wide DNA bridging by H-NS reshapes the stationary phase nucleoid and transcriptional landscape

Bacterial nucleoid-associated proteins (NAPs) structure the chromosome and regulate gene expression, but how these two functions are related is unclear. H-NS is a well-studied NAP that acts as a global gene silencer capable of bridging and looping DNA in vitro. Here, using high-throughput chromosome conformation capture assays, we show that H-NS mediates genome-wide long-range DNA looping in the stationary-phase nucleoid of Escherichia coli. Chromatin immunoprecipitation assays demonstrate that high levels of H-NS are present at the base of DNA loops. Super-resolution imaging and single-particle tracking show that H-NS binds more tightly in stationary phase and compacts the nucleoid mesh. Transcriptomic analyses indicate H-NS represses gene expression more strongly in the looped nucleoid and enables higher expression of genes outside of H-NS-bound regions. Overall, our study demonstrates that H-NS bridges distal DNA regions along the genome upon nutrient limitation, causing reduced nucleoid accessibility, stronger transcriptional repression, and a shifted transcriptional landscape.

molecular biology↗

bioRxiv2025

Dps binds and protects DNA in starved Escherichia coli with minimal effect on chromosome accessibility, dynamics and organisation

Dps is the most abundant nucleoid-associated protein in starved Escherichia coli with [~]180,000 copies per cell. Dps binds DNA and oxidises iron, facilitating survival in harsh environments. Dps-DNA complexes can form crystalline structures, leading to the proposed model that Dps reorganises the starved E. coli nucleoid into a compact liquid crystal, slowing chromosome dynamics and limiting access of other proteins to DNA. In this work, we directly tested this model using live-cell super-resolution microscopy and Hi-C analysis. We found that after 96 h of starvation, Dps compacts the nucleoid and increases short-range DNA-DNA interactions, but does not affect chromosome accessibility to large protein nanocages or small restriction enzymes. We also report that chromosome dynamics and organisation are primarily impacted by the bacterial growth phase; the effect of Dps is relatively minor. Our work clarifies the role of Dps in modulating nucleoid properties, and we propose an updated model for Dps-DNA interactions in which Dps binds, protects and compacts DNA largely without influencing chromosome access, dynamics and organisation. Additionally, this work provides a general framework for assessing the impact of nucleoid-associated proteins on key aspects of chromosome function in live cells. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/673347v3_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1385efforg.highwire.dtl.DTLVardef@1e4cb76org.highwire.dtl.DTLVardef@1e9e43dorg.highwire.dtl.DTLVardef@8768f4_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Tensor-Based Integration of Time-Series Measurements Reveals Relationships Between Underlying Disease, Early Injury, and CD4+ Polarization in Liver Transplantation

For patients with end-stage liver failure, liver transplantation (LT) remains the standard-of-care, though five-year allograft survival rates remain below 80%. Liver ischemia reperfusion injuries (LIRI) arise during transplant and contribute to allograft dysfunction. While many drivers of LIRI have been well-characterized, the relationships between LIRI and later immunological signatures remain poorly understood, possibly because of limited integrated studies examining immunological signatures across the LT process. Furthermore, the role of underlying disease in LT remains poorly understood as it is unknown if later immunological signatures are universal or etiology dependent. To better examine etiology- and LIRI-driven immunological mechanisms across the LT lifetime, we collected cytokine and liver function test (LFT) measurements from LT donors and recipients at multiple pre- and post-operative timepoints. By developing a tensor-based factorization method to integrate these longitudinal measurements, we reduced the datasets to four immunological signatures that manifested across cytokines, LFTs, and time. Correlative analyses revealed associations between these integrated immunological signatures with etiology and LIRI. Later integration of allograft survival into this factorization method reduced these four signatures to two that were predictive of five-year allograft survival. Examination of these signatures prognostic of allograft survival found that CD4+ hyperpolarization towards Th1 or Th2 subtypes impaired growth factor expression and led to increased allograft loss risk. Clinical correlates revealed that donor and recipient age alongside etiology and donor liver health modulate this balance of CD4+ polarization in LT. Collectively, these results link immunological mechanisms to etiology and LIRI offering immediately actionable clinical insights alongside etiology- and donor-specific therapeutic targets for improving LT outcomes.

immunology↗

bioRxiv2025

3D-bioprinted marine bacteria for the degradation of bioplastics

The severe, long-lasting harm caused by plastic pollution to marine ecosystems and coastal economies has led to the development of biodegradable plastics; however, their limited decomposition in cold, dark marine environments remains a challenge. Here, we present our newly developed technologies for creating 3D-bioprinted living materials for bioplastic degradation with specific use in marine environments. Our approach integrates halotolerant bioplastic-degrading bacterium Bacillus sp. NRRL B-14911 into alginate-based bio-ink to print an engineered living material (ELM) termed a "bio-sticker." Quantification of bacteria viability reveals that bioprinted marine bacteria survive within bio-stickers for more than three weeks. The rate at which the bio-stickers degrade the bioplastic polyhydroxybutyrate (PHB) can be tuned by altering bio-sticker biomass concentration, bioplastic concentration, or incubation temperature. Bio-stickers that are transferred to a new PHB sample still retain high biodegradation activity, demonstrating their durability. Strain sweep oscillatory tests demonstrate viscoelastic behavior of the bio-stickers. Monotonic tensile tests indicate that the elastic modulus and the adhesion of the bio-stickers are not negatively impacted by bacteria growth or incubation temperature. Our work paves the way for development of ELMs to facilitate the inclusion of bioplastics within the blue economy, promoting the emergence of more sustainable and eco-friendly materials.

synthetic biology↗

bioRxiv2024

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

Shewanella oneidensis (S. oneidensis) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labour-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its utilization of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCEShewanella oneidensis (S. oneidensis) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor intensive to operate and require days to produce results, so use of a model assay would reduce the time and expense needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

bioengineering↗

bioRxiv2024

Integrative, high-resolution analysis of single cells across experimental conditions with PARAFAC2

Effective and scalable exploration and analysis tools are vital for the extraction of insights from large-scale single-cell data. However, current techniques for modeling single-cell studies performed across experimental conditions (e.g., samples, perturbations, or patients) require restrictive assumptions, lack flexibility, or do not adequately deconvolute condition-to-condition variation from cell-to-cell variation. Here, we report that Reduction and Insight in Single-cell Exploration (RISE), an adaptation of the tensor decomposition method PARAFAC2, enables the dimensionality reduction and analysis of single-cell data across conditions. We demonstrate the benefits of RISE across two distinct examples of single-cell RNA-sequencing experiments of peripheral immune cells: pharmacologic drug perturbations and systemic lupus erythematosus (SLE) patient samples. RISE enables straightforward associations of gene variation patterns with specific patients or perturbations, while connecting each coordinated change to single cells without requiring cell type annotations. The theoretical grounding of RISE suggests a unified framework for many single-cell data modeling tasks. Thus, RISE provides an intuitive universal dimensionality reduction approach for multi-sample single-cell studies across diverse biological contexts. HighlightsO_LIRISE enables tensor-based analysis of single-cell experiments across conditions. C_LIO_LIRISE separates condition-specific effects from cell-to-cell variation. C_LIO_LIRISE provides intuitive isolation of patterns into condition-, cell-, and gene-specific patterns. C_LI

systems biology↗

bioRxiv2024

Censored Least Squares for Imputing Missing Values in PARAFAC Tensor Factorization

Tensor factorization is a dimensionality reduction method applied to multidimensional arrays. These methods are useful for identifying patterns within a variety of biomedical datasets due to their ability to preserve the organizational structure of experiments and therefore aid in generating meaningful insights. However, missing data in the datasets being analyzed can impose challenges. Tensor factorization can be performed with some level of missing data and reconstruct a complete tensor. However, while tensor methods may impute these missing values, the choice of fitting algorithm may influence the fidelity of these imputations. Previous approaches, based on alternating least squares with prefilled values or direct optimization, suffer from introduced bias or slow computational performance. In this study, we propose that censored least squares can better handle missing values with data structured in tensor form. We ran censored least squares on four different biological datasets and compared its performance against alternating least squares with prefilled values and direct optimization. We used the error of imputation and the ability to infer masked values to benchmark their missing data performance. Censored least squares appeared best suited for the analysis of high-dimensional biological data by accuracy and convergence metrics across several studies.

systems biology↗

bioRxiv2024

Multivalent binding model quantifies antibody species from systems serology

Systems serology aims to broadly profile the antigen binding, Fc biophysical features, immune receptor engagement, and effector functions of antibodies. This experimental approach excels at identifying antibody functional features that are relevant to a particular disease. However, a crucial limitation of this approach is its incomplete description of what structural features of the antibodies are responsible for the observed immune receptor engagement and effector functions. Knowing these antibody features is important for both understanding how effector responses are naturally controlled through antibody Fc structure and designing antibody therapies with specific effector profiles. Here, we address this limitation by modeling the molecular interactions occurring in these assays and using this model to infer quantities of specific antibody species among the antibodies being profiled. We used several validation strategies to show that the model accurately infers antibody properties. We then applied the model to infer previously unavailable antibody fucosylation information from existing systems serology data. Using this capability, we find that COVID-19 vaccine efficacy is associated with the induction of afucosylated spike protein-targeting IgG. Our results also question an existing assumption that controllers of HIV exhibit gp120-targeting IgG that are less fucosylated than those of progressors. Additionally, we confirm that afucosylated IgG is associated with membrane-associated antigens for COVID-19 and HIV, and present new evidence indicating that this relationship is specific to the host cell membrane. Finally, we use the model to identify redundant assay measurements and subsets of information-rich measurements from which they can be inferred. In total, our modeling approach provides a quantitative framework for the reasoning typically applied in these studies, improving the ability to draw mechanistic conclusions from these data. Author summaryAntibodies play an important role in our immune response by binding to pathogens and engaging other immune cells to eliminate threats. Mounting evidence points toward the importance of which immune cells are being engaged by antibodies in determining the effectiveness of an immune response. While sophisticated experimental methods such as systems serology have been developed to broadly profile the engagement activities of antibodies, determining the presence of antibody structural features relevant to immune engagement remains challenging. Our study addresses this gap by developing a computational model that interprets data from systems serology, allowing us to infer detailed, engagement-relevant structural information about antibodies that are difficult to measure directly. We applied our approach to existing data from COVID-19 and HIV studies, revealing new insights into how antibody structure relates to vaccine efficacy and disease progression. For instance, we found that COVID-19 vaccine effectiveness is linked to the production of certain antibodies lacking a sugar residue called fucose. Our model also helps identify which measurements in systems serology are most informative, potentially streamlining future studies. This work enhances our ability to understand antibody function in disease and may guide the development of more effective antibody-based therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/602296v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@16e8b3forg.highwire.dtl.DTLVardef@77ffe3org.highwire.dtl.DTLVardef@40d0f2org.highwire.dtl.DTLVardef@155fd8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2024

Engineered bacteria that self-assemble ''bioglass'' polysilicate coatings display enhanced light focusing

Photonic devices are cutting-edge optical materials that produce narrow, intense beams of light, but their synthesis typically requires toxic, complex methodology. Here we employ a synthetic biology approach to produce environmentally-friendly, living microlenses with tunable structural properties. We engineered Escherichia coli bacteria to display the silica biomineralization enzyme silicatein from aquatic sea sponges. Our silicatein-expressing bacteria can self-assemble a shell of polysilicate "bioglass" around themselves. Remarkably, the polysilicate-encapsulated bacteria can focus light into intense nanojets that are nearly an order of magnitude brighter than unmodified bacteria. Polysilicate-encapsulated bacteria are metabolically active for up to four months, potentially allowing them to sense and respond to stimuli over time. Our data demonstrate that engineered bacterial particles have the potential to revolutionize the development of multiple optical and photonic technologies. Significance StatementIn this work, we apply the principles of synthetic biology to create living optical devices. Utilizing the ability of sea sponges to polymerize bioglass from silica precursors in the ocean water using only a single enzyme, silicatein, we have fused this same enzyme to the surface of Escherichia coli bacterial cells. The modified bacteria can polymerize a layer of bioglass at their surface. This bioglass shell allows the bacteria to act as engineered optical devices that are able to scatter high intensity, focused light while also surviving for several months, opening the door to a wide range of sense-and-respond applications. ClassificationBiological Sciences, Applied Biological Sciences

synthetic biology↗

bioRxiv2024

Using rapid invisible frequency tagging (RIFT) to probe the attentional distribution between speech planning and comprehension

Interlocutors often use the semantics of comprehended speech to inform the semantics of planned speech. Do representations of the comprehension and planning stimuli interact on a neural level? We used rapid invisible frequency tagging (RIFT) and EEG to probe the attentional distribution between spoken distractor words and target pictures in the picture-word interference (PWI) paradigm. We presented participants with auditory distractor nouns (auditory (f1); tagged at 54Hz) together with categorically related or unrelated pictures (visual (f2); tagged at 68Hz), which had to be named after a delay. RIFT elicits steady-state evoked potentials, which reflect attentional allocation to the tagged stimuli. When representations of the tagged stimuli interact, integrative effects have been observed at the intermodulation frequency resulting from an interaction of the base frequencies (f2{+/-}f1; Drijvers et al., 2021). Our results showed clear power increases at 54Hz and 68Hz during the tagging window, but no differences between related or unrelated conditions. More interestingly, we observed a larger power difference in the unrelated compared to the related condition at the intermodulation frequency (68Hz - 54Hz: 14Hz), indicating stronger interaction between the auditory and visual representations when they were unrelated. Our results go beyond standard PWI results (e.g., Burki et al., 2020) by showing that participants do not have more difficulty visually attending to the related pictures or inhibiting the related auditory distractors. Instead, processing difficulties arise when the representations of the stimuli interact, meaning that participants might be trying to prevent integration between the auditory and visual representations in the related condition. Significance statementStudying speech planning during comprehension with EEG has been difficult due to a lack of appropriate methodology. This study demonstrates that rapid invisible frequency tagging (RIFT) can explore attentional allocation to speech planning and comprehension stimuli, as well as their interaction. Our results show that the content of the speech planning and comprehension representations affects their interaction in the neural signal, which should always be considered when these processes are studied jointly. In future work, RIFT could be used to investigate speech planning and comprehension in more conversational settings, as tagging can be added to videos or speech segments. This is the first study that demonstrates that RIFT can be used together with EEG to study cognitive phenomena.

neuroscience↗

bioRxiv2024

Bridging DNA contacts allow Dps from E. coli to condense DNA

The DNA-binding protein from starved cells (Dps) plays a crucial role in maintaining bacterial cell viability during periods of stress. Dps is a nucleoid-associated protein that interacts with DNA to create biomolecular condensates in live bacteria. Purified Dps protein can also rapidly form large complexes when combined with DNA in vitro. However, the mechanism that allows these complexes to nucleate on DNA remains unclear. Here, we examine how DNA topology influences the formation of Dps-DNA complexes. We find that DNA supercoils offer the most preferred template for the nucleation of condensed Dps structures. More generally, bridging contacts between different regions of DNA can facilitate the nucleation of condensed Dps structures. In contrast, Dps shows little affinity for stretched linear DNA before it is relaxed. Once DNA is condensed, Dps forms a stable complex that can form inter-strand contacts with nearby DNA, even without free Dps present in solution. Taken together, our results establish the important role played by bridging contacts between DNA strands in nucleating and stabilizing Dps complexes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/576774v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1e4d842org.highwire.dtl.DTLVardef@131f3c6org.highwire.dtl.DTLVardef@7b6358org.highwire.dtl.DTLVardef@b73c32_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract.C_FLOATNO Working model of nucleation and formation of Dps-DNA complex. Regions of supercoiled or stochastically bent DNA act as nucleation points for the formation of Dps-DNA complexes by allowing Dps to form bridging contacts. Dps does not readily bind to straight stretches of DNA in isolation. Once Dps-DNA complexes are formed they can form bridging contacts to bind additional DNA. C_FIG

biophysics↗

bioRxiv2023

Relationships of crystallinity and reaction rates for enzymatic degradation of poly (ethylene terephthalate), PET

Biocatalytic degradation of plastic waste is anticipated to play an important role in future recycling systems. However, enzymatic degradation of crystalline poly (ethylene terephthalate) (PET) remains consistently poor. Herein, we employed functional assays to elucidate the molecular underpinnings of this limitation. This included utilizing complementary activity assays to monitor the degradation of PET disks with varying crystallinity (XC), as well as kinetic parameters for soluble PET fragments. The results indicate that a proficient PET-hydrolase, LCCICCG, operates through an endolytic mode of action, and that its activity is limited by conformational constraints in the PET polymer. Such constraints become more pronounced at high XC values, and this limits the density of productive sites on the PET surface. Endolytic chain-scissions are the dominant reaction type in the initial stage, and this means that little or no soluble organic product occurs here. However, endolytic cuts gradually and locally promote chain mobility and hence the density of attack sites on the surface. This leads to an upward concave progress curve; a behavior sometimes termed lag-phase kinetics.

biochemistry↗