Biology subjects

Riedel-Kruse, I. H.

Publications and source records attributed to Riedel-Kruse, I. H..

9 recordsLinked to original sources

bioRxiv2026

A traveling network model predicts emergent dynamics and search behavior from local remodeling in Physarum polycephalum

A variety of connected systems, ranging from the cytoskeleton to human organizations, dynamically rearrange themselves in order to move through physical or abstract space. However, our understanding of how systems-level behaviors arise from local restructuring actions remains limited, necessitating comparison of real-world data to models that predict network structure and dynamics. To understand these systems, we study an accessible example, the branching slime mold Physarum polycephalum, by imaging the organism as it travels and extracting key fundamental quantities from its continuously remodeling tubular network. By using these quantities as input parameters to a traveling network model, we find that with no further fitting, the model quantitatively matches key emergent properties from P. polycephalum dynamics including path length, relocation time, and search efficiency at different spatial resolutions. These findings demonstrate how a traveling network model can capture P. polycephalum behaviors, highlighting the potential to use traveling networks more broadly for understanding and predicting connected dynamic systems by linking local measurements to emergent, system-wide behaviors.

biophysics↗

bioRxiv2026

Enhancing Reverse Methanogenesis Using RNA-Guided Silencing

Utilizing methane and carbon dioxide before it can enter the upper atmosphere is beneficial for mitigating climate change as well as for producing valuable chemicals. Because anaerobic methanotrophic archaea (ANME) have not yet been cultured in isolation, we previously reversed methanogenesis by cloning the genes encoding methyl-coenzyme M reductase (Mcr) derived from Black Sea ANME-1 into the methanogen Methanosarcina acetivorans. The resulting engineered archaeal strain captures, rather than produces, methane and may be used to convert methane and carbon dioxide into electricity, acetate, L-lactate, and ethanol. However, the engineered M. acetivorans strain also contains a chromosomal locus encoding its native Mcr (McrM.a.), which produces methane from substrates such as methanol, whereas the heterologously expressed ANME-1 Mcr (McrANME-1) promotes methane oxidation. Therefore, we reasoned that McrM.a. may compete with McrANME-1-mediated reversal of methanogenesis. To enhance the reversal of methanogenesis, here we implemented an antisense RNA (asRNA) silencing approach to suppress McrM.a. during growth on methane while still allowing its expression during routine growth on methanol. We found that silencing McrM.a. during McrANME-1-mediated growth on methane increased ethanol and acetate production by more than an order of magnitude. These results were corroborated by both a more than 10-fold increase in methane utilization by McrANME-1 and a greater than 1,000-fold reduction in the McrM.a. mcrBGA transcript levels under methane-grown conditions. Therefore, asRNA-mediated silencing may be used to enhance methane capture by suppressing production of the host McrM.a. for biotechnological applications.

synthetic biology↗

bioRxiv2025

Tuning viscoelasticity and fine structure of living materials via synthetic adhesion logic and rheological perturbations

Engineered living materials (ELMs) at the multicelluar level represent an innovation that promises programmable properties for biomedical, environmental, and consumer applications. However, the rational tuning of the mechanical properties of such ELMs from first principles remains a challenge. Here we use synthetic cell-cell adhesins to systematically characterize how rheological and viscoelastic properties of multicellular materials made from living bacteria can be tuned via adhesin strength, cell size and shape, and adhesion logic. We confirmed that the previous results obtained for non-living materials also apply to bacterial ELMs. Additionally, the incorporation of synthetic adhesins, combined with the adaptability of bacterial cells in modifying various cellular parameters, now enables novel and precise control over material properties. Furthermore, we demonstrate that rheology is a powerful tool for actively shaping the microscopic structure of ELMs, enabling control over cell aggregation and particle rearrangement, a key feature for complex material design. These results deepen our understanding of tuning the viscoelastic properties and fine structure of ELMs for applications like bioprinting and microbial consortia design including natural systems.

synthetic biology↗

bioRxiv2024

Structure, motion, and multiscale search of traveling networks

Network models are widely applied to describe connectivity and flow in diverse systems. In contrast, the fact that many connected systems move through space as the result of dynamic restructuring has received little attention. Therefore, we introduce the concept of traveling networks, and we analyze a tree-based model where the leaves are stochastically manipulated to grow, branch, and retract. We derive how these restructuring rates determine key attributes of network structure and motion, enabling a compact understanding of higher-level network behaviors such as multiscale search. These networks self-organize to the critical point between exponential growth and decay, allowing them to detect and respond to environmental signals with high sensitivity. Finally, we demonstrate how the traveling network concept applies to real-world systems, such as slime molds, the actin cytoskeleton, and human organizations, exemplifying how restructuring rules and rates in general can select for versatile search strategies in real or abstract spaces.

biophysics↗

bioRxiv2020

Nonlinear delay differential equations and their application to modeling biological network motifs

Biological regulatory systems, such as transcription factor or kinase networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. "Network motif" models focus on small sub-networks to provide quantitative insight into overall behavior. However, conventional network motif models often ignore time delays either inherent to biological processes or associated with multi-step interactions. Here we systematically examine explicit-delay versions of the most common network motifs via delay differential equations (DDEs), both analytically and numerically. We find many broadly applicable results, such as the reduction in number of parameters compared to canonical descriptions via ordinary differential equations (ODE), criteria for when delays may be ignored, a complete phase space for autoregulation, explicit dependence of feedforward loops on a difference of delays, a unified framework for Hill-function logic, and conditions for oscillations and chaos. We emphasize relevance to biological function throughout our analysis, summarize key points in non-mathematical form, and conclude that explicit-delay modeling simplifies the phenomenological understanding of many biological networks and may aid in discovering new functional motifs.

systems biology↗

bioRxiv2018

Polygonal motion and adaptable phototaxis via flagellar beat switching in Euglena gracilis

Biological microswimmers exhibit versatile strategies for sensing and navigating their environment 1-7, e.g., run-and-tumble 2 and curvature modulation 3. Here we report a striking behavior of Euglena gracilis, where Euglena cells swim in polygonal trajectories due to exposure to increasing light intensities. While smoothly curved trajectories are common for microswimmers 3, 8, such quantized ones have not been reported previously. This polygonal behavior emerges from periodic switching between the flagellar beating patterns of helical swimming 6, 9 and spinning 10 behaviors. We develop and experimentally validate a biophysical model that describes the phase relationship between the eyespot, cell orientation, light detection, and cellular reorientation, that accounts for all three behavioral states. Coordinated switching between these behaviors allows ballistic, superdiffusive, diffusive, or subdiffusive motion 11,12 (i.e., the tuning of the diffusion constant over 3 orders of magnitude) and enables navigation in structured light fields, e.g., edge avoidance and gradient descent. This feedback-control links multiple system scales (flagellar beats, cellular behaviors, phototaxis strategies) with implications for other natural and synthetic microswimmers 13.

biophysics↗

bioRxiv2017

A genetically encoded adhesin toolbox for programming multicellular morphologies and patterns

Synthetic multicellular systems hold promise for understanding natural development of biofilms and higher organisms1,2, as well as for engineering complex multi-component metabolic pathways2,3 and materials4. However, such efforts will require tools to adhere cells into defined morphologies and patterns, and these tools are currently lacking1,5,6. Here we report the first 100% genetically encoded synthetic platform for modular cell-cell adhesion in Escherichia coli, which provides control over multicellular self-assembly. Adhesive selectivity is provided by a library of outer membrane-displayed nanobody7,8 and antigen peptides with orthogonal intra-library specificities, while affinity is controlled by intrinsic adhesin affinity, competitive inhibition, and inducible expression. We demonstrate the resulting capabilities for rational design of well-defined morphologies and patterns through homophilic and heterophilic interactions, lattice-like self-assembly, phase separation, differential adhesion, and sequential layering. This adhesion toolbox, compatible with synthetic biology standards9, will enable construction of high-level multicellular designs and shed light on the evolutionary transition to multicellularity6,10.

synthetic biology↗

bioRxiv2017

Bioty: A cloud-based development toolkit for programming experiments and interactive applications with living cells

Recent advancements in life-science instrumentation and automation enable entirely new modes of human interaction with microbiological processes and corresponding applications for science and education through biology cloud labs. A critical barrier for remote life-science experimentation is the absence of suitable abstractions and interfaces for programming living matter. To this end we conceptualize a programming paradigm that provides stimulus control functions and sensor control functions for realtime manipulation of biological (physical) matter. Additionally, a simulation mode facilitates higher user throughput, program debugging, and biophysical modeling. To evaluate this paradigm, we implemented a JavaScript-based web toolkit, Bioty, that supports realtime interaction with swarms of phototactic Euglena cells hosted on a cloud lab. Studies with remote users demonstrate that individuals with little to no biology knowledge and intermediate programming knowledge were able to successfully create and use scientific applications and games. This work informs the design of programming environments for controlling living matter in general and lowers the access barriers to biology experimentation for professional and citizen scientists, learners, and the lay public.\n\nSignificance StatementBiology cloud labs are an emerging approach to lower access barriers to life-science experimentation. However, suitable programming approaches and user interfaces are lacking, especially ones that enable the interaction with the living matter itself - not just the control of equipment. Here we present and implement a corresponding programming paradigm for realtime interactive applications with remotely housed biological systems, and which is accessible and useful for scientists, programmers and lay people alike. Our user studies show that scientists and non-scientists are able to rapidly develop a variety of applications, such as interactive biophysics experiments and games. This paradigm has the potential to make first-hand experiences with biology accessible to all of society and to accelerate the rate of scientific discovery.

bioengineering↗

bioRxiv2017

Biofilm Lithography: High-resolution cell patterning via optogenetic adhesin expression

Bacterial biofilms represent a promising opportunity for engineering of microbial communities. However our ability to control spatial structure in biofilms remains limited. Here we engineer Escherichia coli with a light-activated transcriptional promoter to optically regulate adhesin gene expression. When illuminated with patterned blue light, long-term viable biofilms with spatial resolution down to 25m can be formed on a variety of substrates and inside enclosed culture chambers without the need for surface pretreatment. A biophysical model suggests the patterning mechanism involves stimulation of transiently surface-adsorbed cells, lending new evidence to a previously proposed role of adhesin expression during natural biofilm maturation. Overall, this tool - termed Biofilm Lithography - has distinct advantages over existing cell-depositing and patterning methods and provides the ability to grow structured biofilms, with applications towards an improved understanding natural biofilm communities, as well as the engineering of living biomaterials and bottom-up approaches to microbial consortia design.

synthetic biology↗