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Can a bacterial cell model vet large datasets from disparate sources? Macklin et al. explored whether a comprehensive mathematical model can be used to verify or find conflicts in massive amounts of data that have been reported for the bacterium Escherichia coli , produced in thousands of papers from hundreds of labs. Although most data were consistent, there were data that could not accommodate known biological results, such as insufficient output of RNA polymerases and ribosomes to produce measured cell-doubling times. Other analyses showed that for some essential proteins, no RNA may be transcribed or translated in a cell's lifetime, but viability can be maintained without certain enzymes through a pool of stable metabolites produced earlier. Science , this issue p. eaav3751 Construction of a large-scale mechanistic model of Escherichia coli brings models and large datasets together to enhance knowledge in biology. The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle—and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

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. Complex networks are relevant to wide range of areas, from biology to social sciences and economics, however the aspect that networks can move through space has not been elaborated. The authors propose a concept of traveling networks that can dynamically restructure themselves in space and perform search tasks.

An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mrnA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ~93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales. One main goal of synthetic biology is to make the engineering of biology easier 1,2. DNA synthesis and assembly has progressed to the point where entire metabolic pathways, chromosomes and genomes can now be synthesized and transplanted 3-5. However, our capacity to rationally design increasingly complicated genetic systems as enabled by improvements in DNA construction methods has not kept pace 2,6. One of the greatest claimed barriers to efficient and scalable genetic design is the lack of standard parts that can be reused reliably in novel combinations 6,7. Many examples instead highlight, even within well-studied organisms such as E. coli, how seemingly simple genetic functions behave differently in different settings 8,9. For example, a prokaryotic ribosome-binding site (RBS) element that initiates translation for one coding sequence might not function at all with another coding sequence 10. If the genetic elements that encode control of central cellular processes such as transcription and translation cannot be reliably reused, then there is little chance that higher-order objects encoded from such basic elements will be reliable in larger-scale systems 6,11. Standard biological parts could, in theory, enable hierarchical abstraction of biological functions 1,2,12,13. The behavior of integrated genetic systems could then be represented via simpler models of individual elements and ultimately mapped to underlying genetic sequences whose encoded functions are dependent on a limited number of measurable or calculable intrinsic variables. Such abstraction of function seems necessary to manage biological complexity and to allow the engineering of increasingly sophisticated genetic systems 6,12,14. We engineered ~500 transcription and translation initiation elements that are compatible within a standardized genetic context, or expression operating unit (EOU), that enables predictable forward engineering of gene expression over a wide dynamic range. We characterized representative parts for each type by testing more than 1,200 part-part combinations to establish and validate functional composition rules while quantifying scores for part activity. From this data we also estimated the 'quality' of each part, a second-order statistic that represents the extent to which the activity of a part varies across changes in context 15. Our results demonstrate how, when combined with standardized transcription control elements, a more physically complex design for the control of translation initiation creates simply modeled parts enabling reliable forward engineering of gene expression. results Prioritizing part composition puzzles In related work, we systematically assembled and tested all combinations of frequently used prokaryotic transcription and translation control elements to quantify average part activities and also variation in activities as parts are reused in novel combinations 15. Here we focus on developing rules for a genetic layout architecture underlying gene expression cassettes that eliminate

Transthyretin amyloid cardiomyopathy (ATTR‐CM) is a progressive, often fatal disease arising from the dissociation of circulating transthyretin (TTR) tetramers into monomers that misfold and form amyloid fibrils that deposit in the myocardium and other tissues. Approved treatment paradigms involve tetramer stabilization with small molecules or TTR knockdown via RNA interference. Despite the clinical success of these drugs across several metrics (including all‐cause mortality and cardiovascular hospitalization), gaps remain in understanding how measurable biological changes, such as differences in serum TTR concentration, translate into reductions in amyloid deposition. To address this, we built a mechanistic mathematical model of the TTR system that integrates heterogeneous data sources, including in vitro assays and clinical data, and recapitulates key features of ATTR‐CM disease biology. The model predicts “monomer efflux,” the rate at which unfolded monomers could potentially form amyloid, as a proxy for the pathogenic mechanism, which is difficult to measure. Model‐predicted monomer efflux linearly correlated with reported rates of change in clinical measures, supporting its validity as a comparative metric. The model showed that monomer efflux is nearly twice as high in hereditary ATTR‐CM (ATTRv) as in wild‐type ATTR‐CM (ATTRwt). Comparison of treatment modalities showed that acoramidis yields the greatest reduction in monomer efflux (96% in ATTRwt, 95% in ATTRv) due to rapid, near‐complete stabilization of TTR. This framework enables quantitative interrogation of the disease system and principled comparisons across modalities that may help inform treatment selection. Study Highlights What is the current knowledge on the topic? ○Transthyretin amyloid cardiomyopathy (ATTR‐CM) is a progressive cardiomyopathy driven by dissociation of circulating transthyretin tetramers into monomers that can misfold and form amyloid fibrils. Approved therapies improve outcomes via two paradigms: small molecule tetramer stabilization and hepatic transthyretin knockdown. What question did this study address? ○We built a quantitative model that can assess how different therapeutic approaches translate to reductions in amyloid formation and explain how physiological factors can play a role in disease state and biomarkers such as circulating transthyretin. What does this study add to our knowledge? ○We utilized a quantitative systems pharmacology approach, integrating in vitro, ex vivo, and clinical data across multiple genotypes and pharmaceutical interventions to develop a unified mathematical model. The model quantifies “monomer efflux” as a proxy for amyloidogenic potential. We showed that monomer efflux predictions are correlated with rates of change in clinical outcomes such as 6‐minute walk distance, Kansas City Cardiomyopathy Questionnaire Overall Summary score, and N‐terminal pro‐B‐type natriuretic peptide levels. We utilized the model and monomer efflux predictions to quantify the effect of renal monomer loss rate in modulating disease severity and treatment responses. Additionally, the model provides a comparison of treatment modalities under a common mechanistic framework. How might this change drug discovery, development, and/or therapeutics? ○The framework offers a mechanistic basis for evaluating therapeutic strategies in ATTR‐CM by quantifying the effect of distinct interventions on model‐predicted monomer efflux and serum transthyretin. This can support candidate evaluation and therapeutic choice, for example, by contextualizing changes in serum transthyretin concentration with changes in potential disease severity.

Background Plant biotechnology can be leveraged to produce food, fuel, medicine, and materials. Standardized methods advocated by the synthetic biology community can accelerate the plant design cycle, ultimately making plant engineering more widely accessible to bioengineers who can contribute diverse creative input to the design process. Results This paper presents work done largely by undergraduate students participating in the 2010 International Genetically Engineered Machines (iGEM) competition. Described here is a framework for engineering the model plant Arabidopsis thaliana with standardized, BioBrick compatible vectors and parts available through the Registry of Standard Biological Parts ( http://www.partsregistry.org ). This system was used to engineer a proof-of-concept plant that exogenously expresses the taste-inverting protein miraculin. Conclusions Our work is intended to encourage future iGEM teams and other synthetic biologists to use plants as a genetic chassis. Our workflow simplifies the use of standardized parts in plant systems, allowing the construction and expression of heterologous genes in plants within the timeframe allotted for typical iGEM projects.

Disclosure: E. Muslimova: Employee; Self; QED Therapeutics. Stock Owner; Self; QED Therapeutics. B. Demuynck: None. L. Loisay: None. M. Paull: Employee; Self; QED Therapeutics. Stock Owner; Self; QED Therapeutics. L. Legeai-Mallet: None. Background: FGFR3 is a negative regulator of bone growth and gain-of-function mutations in the FGFR3 gene result in different skeletal osteochondrodysplasias, including achondroplasia (ACH) and hypochondroplasia (HCH). ACH is the most common form of rhizomelic short stature, affecting between 1 in 15,000 and 1 in 30,000 live births worldwide. The incidence of HCH is thought to be approximately the same as ACH. Currently, there is only one approved therapy for ACH and no approved therapies for HCH. Previously we demonstrated that the oral, selective FGFR 1-3 tyrosine kinase inhibitor (TKI) infigratinib has preclinical activity in a mouse model mimicking ACH (Fgfr3Y367C/+). We hypothesized that infigratinib could improve defective endochondral ossification and ameliorate the phenotype in a mouse model of HCH (Fgfr3N534K/+), which is the first and only HCH mouse model that expresses the most frequent human heterozygous mutation p.Asn540Lys.Methods:Fgfr3N534K/+ mice were given subcutaneous injections of infigratinib or vehicle control every 3 days (1 mg/kg) or daily (1 mg/kg) for 15 days (post-natal day [PND] 4-19) or 21 days (PND 3-24), respectively. Results:Fgfr3N534K/+ mice treated with 1 mg/kg infigratinib daily for a total of 21 days showed a statistically significant increase in appendicular and axial skeleton (tibia +3.18%, femur +3.16%, humerus +3.04%, ulna +2.94%, radius +3.01%). Treatment with infigratinib modified skull shape, length of the mandible, and foramen magnum length (+3.72%). Cartilage growth plate organization, in particular the hypertrophic chondrocyte area, was modified, indicating that chondrocyte differentiation is improved. These results, although of a lower magnitude, are in line with those previously reported from the Fgfr3Y367C/+ mouse model of ACH, which showed a statistically significant improvement in upper limbs (humerus +7.3%, ulna +11.1%, radius +14.2 %), lower limbs (femur +10.4%, tibia +16.8%), and foramen magnum length (+3.76%), when infigratinib was administered at a dose of 0.5 mg/kg. Conclusions: Low-dose treatment with infigratinib in the Fgfr3N534K/+ HCH mouse model ameliorated the clinical hallmarks of human pathology and significantly lengthened the axial skeleton, the appendicular skeleton and improved foramen magnum length. Development of infigratinib in ACH is currently ongoing. These latest findings with infigratinib in this mouse model of HCH support the rationale for targeting FGFR3 with a specific TKI such as infigratinib for the treatment of children with HCH. Presentation: Saturday, June 17, 2023

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model ofEscherichia colienabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle—and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

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.Competing Interest StatementThe authors have declared no competing interest.

An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mrnA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with 93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales. One main goal of synthetic biology is to make the engineering of biology easier 1,2. DNA synthesis and assembly has progressed to the point where entire metabolic pathways, chromosomes and genomes can now be synthesized and transplanted 3-5. However, our capacity to rationally design increasingly complicated genetic systems as enabled by improvements in DNA construction methods has not kept pace 2,6. One of the greatest claimed barriers to efficient and scalable genetic design is the lack of standard parts that can be reused reliably in novel combinations 6,7. Many examples instead highlight, even within well-studied organisms such as E. coli, how seemingly simple genetic functions behave differently in different settings 8,9. For example, a prokaryotic ribosome-binding site (RBS) element that initiates translation for one coding sequence might not function at all with another coding sequence 10. If the genetic elements that encode control of central cellular processes such as transcription and translation cannot be reliably reused, then there is little chance that higher-order objects encoded from such basic elements will be reliable in larger-scale systems 6,11. Standard biological parts could, in theory, enable hierarchical abstraction of biological functions 1,2,12,13. The behavior of integrated genetic systems could then be represented via simpler models of individual elements and ultimately mapped to underlying genetic sequences whose encoded functions are dependent on a limited number of measurable or calculable intrinsic variables. Such abstraction of function seems necessary to manage biological complexity and to allow the engineering of increasingly sophisticated genetic systems 6,12,14. We engineered 500 transcription and translation initiation elements that are compatible within a standardized genetic context, or expression operating unit (EOU), that enables predictable forward engineering of gene expression over a wide dynamic range. We characterized representative parts for each type by testing more than 1,200 part-part combinations to establish and validate functional composition rules while quantifying scores for part activity. From this data we also estimated the 'quality' of each part, a second-order statistic that represents the extent to which the activity of a part varies across changes in context 15. Our results demonstrate how, when combined with standardized transcription control elements, a more physically complex design for the control of translation initiation creates simply modeled parts enabling reliable forward engineering of gene expression. results Prioritizing part composition puzzles In related work, we systematically assembled and tested all combinations of frequently used prokaryotic transcription and translation control elements to quantify average part activities and also variation in activities as parts are reused in novel combinations 15. Here we focus on developing rules for a genetic layout architecture underlying gene expression cassettes that eliminate

A continuing challenge in material science is how to create active materials in which shape changes or displacements can be generated electrically or thermally. Here we borrow principles from hydraulics, in particular that confined geometries can be used to focus expansion into large displacements, to create solid materials with amplified shape changes. Specifically, we confined an elastomeric poly(dimethylsiloxane) sheet between two more rigid layers and caused focused expansion into embossed channels by local resistive heating, resulting in a 10x greater relative displacement than the unconfined geometry. We used this effect to create electrically controlled microfluidic valves that open and close in less than 100 ms, can cycle >10,000 times, and operate with as little as 20 mW of power. We investigate this mechanism and establish design rules by varying dimensions, configurations, and materials. We show the generality of elastomeric focusing by creating additional devices where local heating and expansion are generated either wirelessly through inductive coupling or optically with a laser, allowing arbitrary and dynamic positioning of a microfluidic valve along the channels.