Mega-scale experimental analysis of protein folding stability in biology and design.

Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain largely unknown2. The hidden thermodynamics of folding can drive disease3,4, shape protein evolution5-7 and guide protein engineering8-10, and new approaches are needed to reveal these thermodynamics for every sequence and structure. Here we present cDNA display proteolysis, a method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. From 1.8 million measurements in total, we curated a set of around 776,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40-72 amino acids in length. Using this extensive dataset, we quantified (1) environmental factors influencing amino acid fitness, (2) thermodynamic couplings (including unexpected interactions) between protein sites, and (3) the global divergence between evolutionary amino acid usage and protein folding stability. We also examined how our approach could identify stability determinants in designed proteins and evaluate design methods. The cDNA display proteolysis method is fast, accurate and uniquely scalable, and promises to reveal the quantitative rules for how amino acid sequences encode folding stability.

Linking the Salmonella enterica 1,2-Propanediol Utilization Bacterial Microcompartment Shell to the Enzymatic Core via the Shell Protein PduB.

Bacterial microcompartments (MCPs) are protein-based organelles that house the enzymatic machinery for metabolism of niche carbon sources, allowing enteric pathogens to outcompete native microbiota during host colonization. While much progress has been made toward understanding MCP biogenesis, questions still remain regarding the mechanism by which core MCP enzymes are enveloped within the MCP protein shell. Here, we explore the hypothesis that the shell protein PduB is responsible for linking the shell of the 1,2-propanediol utilization (Pdu) MCP from Salmonella enterica serovar Typhimurium LT2 to its enzymatic core. Using fluorescent reporters, we demonstrate that all members of the Pdu enzymatic core are encapsulated in Pdu MCPs. We also demonstrate that PduB is critical for linking the entire Pdu enzyme core to the MCP shell. Using MCP purifications, transmission electron microscopy, and fluorescence microscopy, we find that shell assembly can be decoupled from the enzymatic core, as apparently empty MCPs are formed in Salmonella strains lacking PduB. Mutagenesis studies reveal that PduB is incorporated into the Pdu MCP shell via a conserved, lysine-mediated hydrogen bonding mechanism. Finally, growth assays and system-level pathway modeling reveal that unencapsulated pathway performance is strongly impacted by enzyme concentration, highlighting the importance of minimizing polar effects when conducting these functional assays. Together, these results provide insight into the mechanism of enzyme encapsulation within Pdu MCPs and demonstrate that the process of enzyme encapsulation and shell assembly are separate processes in this system, a finding that will aid future efforts to understand MCP biogenesis. IMPORTANCE MCPs are unique, genetically encoded organelles used by many bacteria to survive in resource-limited environments. There is significant interest in understanding the biogenesis and function of these organelles, both as potential antibiotic targets in enteric pathogens and also as useful tools for overcoming metabolic engineering bottlenecks. However, the mechanism by which these organelles are formed natively is still not completely understood. Here, we provide evidence of a potential mechanism in S. enterica by which a single protein, PduB, links the MCP shell and metabolic core. This finding is critical for those seeking to disrupt MCPs during pathogenic infections or for those seeking to harness MCPs as nanobioreactors in industrial settings.

pH determines the energetic efficiency of the cyanobacterial CO2 concentrating mechanism.

Many carbon-fixing bacteria rely on a CO2 concentrating mechanism (CCM) to elevate the CO2 concentration around the carboxylating enzyme ribulose bisphosphate carboxylase/oxygenase (RuBisCO). The CCM is postulated to simultaneously enhance the rate of carboxylation and minimize oxygenation, a competitive reaction with O2 also catalyzed by RuBisCO. To achieve this effect, the CCM combines two features: active transport of inorganic carbon into the cell and colocalization of carbonic anhydrase and RuBisCO inside proteinaceous microcompartments called carboxysomes. Understanding the significance of the various CCM components requires reconciling biochemical intuition with a quantitative description of the system. To this end, we have developed a mathematical model of the CCM to analyze its energetic costs and the inherent intertwining of physiology and pH. We find that intracellular pH greatly affects the cost of inorganic carbon accumulation. At low pH the inorganic carbon pool contains more of the highly cell-permeable H2CO3, necessitating a substantial expenditure of energy on transport to maintain internal inorganic carbon levels. An intracellular pH ≈8 reduces leakage, making the CCM significantly more energetically efficient. This pH prediction coincides well with our measurement of intracellular pH in a model cyanobacterium. We also demonstrate that CO2 retention in the carboxysome is necessary, whereas selective uptake of HCO3 (-) into the carboxysome would not appreciably enhance energetic efficiency. Altogether, integration of pH produces a model that is quantitatively consistent with cyanobacterial physiology, emphasizing that pH cannot be neglected when describing biological systems interacting with inorganic carbon pools.

Inorganic carbon and pH dependency of photosynthetic rates in Trichodesmium.

Increasing atmospheric CO2 concentrations are leading to increases in dissolved CO2 and HCO3- concentrations and decreases in pH and CO32- in the world's oceans. There remain many uncertainties as to the magnitude of biological responses of key organisms to these chemical changes. In this study, we established the relationship between photosynthetic carbon fixation rates and pH, CO2, and HCO3- concentrations in the diazotroph, Trichodesmium erythraeum IMS101. Inorganic 14C-assimilation was measured in TRIS-buffered artificial seawater medium where the absolute and relative concentrations of CO2, pH, and HCO3- were manipulated. First, we varied the total dissolved inorganic carbon concentration (TIC) (<0 to ~5 mM) at constant pH, so that ratios of CO2 and HCO3- remained relatively constant. Second, we varied pH (~8.54 to 7.52) at constant TIC, so that CO2 increased whilst HCO3- declined. We found that 14C-assimilation could be described by the same function of CO2 for both approaches, but it showed different dependencies on HCO3- when pH was varied at constant TIC than when TIC was varied at constant pH. A numerical model of the carbon-concentrating mechanism (CCM) of Trichodesmium showed that carboxylation rates are modulated by HCO3- and pH. The decrease in assimilation of inorganic carbon (Ci) at low CO2, when TIC was varied, was due to HCO3- uptake limitation of the carboxylation rate. Conversely, when pH was varied, Ci assimilation declined due to a high-pH mediated increase in HCO3- and CO2 leakage rates, potentially coupled to other processes (uncharacterised within the CCM model) that restrict Ci assimilation rates under high-pH conditions.

A systems-level model reveals that 1,2-Propanediol utilization microcompartments enhance pathway flux through intermediate sequestration.

The spatial organization of metabolism is common to all domains of life. Enteric and other bacteria use subcellular organelles known as bacterial microcompartments to spatially organize the metabolism of pathogenicity-relevant carbon sources, such as 1,2-propanediol. The organelles are thought to sequester a private cofactor pool, minimize the effects of toxic intermediates, and enhance flux through the encapsulated metabolic pathways. We develop a mathematical model of the function of the 1,2-propanediol utilization microcompartment of Salmonella enterica and use it to analyze the function of the microcompartment organelles in detail. Our model makes accurate estimates of doubling times based on an optimized compartment shell permeability determined by maximizing metabolic flux in the model. The compartments function primarily to decouple cytosolic intermediate concentrations from the concentrations in the microcompartment, allowing significant enhancement in pathway flux by the generation of large concentration gradients across the microcompartment shell. We find that selective permeability of the microcompartment shell is not absolutely necessary, but is often beneficial in establishing this intermediate-trapping function. Our findings also implicate active transport of the 1,2-propanediol substrate under conditions of low external substrate concentration, and we present a mathematical bound, in terms of external 1,2-propanediol substrate concentration and diffusive rates, on when active transport of the substrate is advantageous. By allowing us to predict experimentally inaccessible aspects of microcompartment function, such as intra-microcompartment metabolite concentrations, our model presents avenues for future research and underscores the importance of carefully considering changes in external metabolite concentrations and other conditions during batch cultures. Our results also suggest that the encapsulation of heterologous pathways in bacterial microcompartments might yield significant benefits for pathway flux, as well as for toxicity mitigation.

A modeling pipeline to relate municipal wastewater surveillance and regional public health data.

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Deconstructing synthetic biology across scales: a conceptual approach for training synthetic biologists.

Synthetic biology allows us to reuse, repurpose, and reconfigure biological systems to address society's most pressing challenges. Developing biotechnologies in this way requires integrating concepts across disciplines, posing challenges to educating students with diverse expertise. We created a framework for synthetic biology training that deconstructs biotechnologies across scales-molecular, circuit/network, cell/cell-free systems, biological communities, and societal-giving students a holistic toolkit to integrate cross-disciplinary concepts towards responsible innovation of successful biotechnologies. We present this framework, lessons learned, and inclusive teaching materials to allow its adaption to train the next generation of synthetic biologists.

Developing, characterizing and modeling CRISPR-based point-of-use pathogen diagnostics.

Recent years have seen intense interest in the development of point-of-care nucleic acid diagnostic technologies to address the scaling limitations of laboratory-based approaches. Chief among these are combinations of isothermal amplification approaches with CRISPR-based detection and readouts of target products. Here, we contribute to the growing body of rapid, programmable point-of-care pathogen tests by developing and optimizing a one-pot NASBA-Cas13a nucleic acid detection assay. This test uses the isothermal amplification technique NASBA to amplify target viral nucleic acids, followed by Cas13a-based detection of amplified sequences. We first demonstrate an in-house formulation of NASBA that enables optimization of individual NASBA components. We then present design rules for NASBA primer sets and LbuCas13a guide RNAs for fast and sensitive detection of SARS-CoV-2 viral RNA fragments, resulting in 20 - 200 aM sensitivity without any specialized equipment. Finally, we explore the combination of high-throughput assay condition screening with mechanistic ordinary differential equation modeling of the reaction scheme to gain a deeper understanding of the NASBA-Cas13a system. This work presents a framework for developing a mechanistic understanding of reaction performance and optimization that uses both experiments and modeling, which we anticipate will be useful in developing future nucleic acid detection technologies.

Characterization of larval growth in C. elegans cuticle mutants.

In Caenorhabditis elegans, many genes involved in the formation of the cuticle are also known to influence body size and shape. We assessed post-embryonic growth of both long and short C. elegans body size mutants from the L1 to L4 stage. We found similar developmental trajectories of N2 and lon-3 animals. By contrast, we observed overall decreases in body length and increases in body width of tested dpy mutants compared to N2, consistent with the Dpy phenotype. We further show that the dynamics of animal shape in the mutant strains are consistent with a previously proposed "Stretcher" growth model.

GAMES: A Dynamic Model Development Workflow for Rigorous Characterization of Synthetic Genetic Systems.

Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier to reproduction and critical analysis of the development process itself, reducing the potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce the Generation and Analysis of Models for Exploring Synthetic Systems (GAMES) workflow, which includes both automated and human-in-the-loop processes. We systematically consider the process of developing dynamic models, including model formulation, parameter estimation, parameter identifiability, experimental design, model reduction, model refinement, and model selection. We demonstrate the workflow with a case study on a chemically responsive transcription factor. The generalizable workflow presented in this tutorial can enable biologists to more readily build and analyze models for various applications.

Modelling the pyrenoid-based CO2-concentrating mechanism provides insights into its operating principles and a roadmap for its engineering into crops.

Many eukaryotic photosynthetic organisms enhance their carbon uptake by supplying concentrated CO2 to the CO2-fixing enzyme Rubisco in an organelle called the pyrenoid. Ongoing efforts seek to engineer this pyrenoid-based CO2-concentrating mechanism (PCCM) into crops to increase yields. Here we develop a computational model for a PCCM on the basis of the postulated mechanism in the green alga Chlamydomonas reinhardtii. Our model recapitulates all Chlamydomonas PCCM-deficient mutant phenotypes and yields general biophysical principles underlying the PCCM. We show that an effective and energetically efficient PCCM requires a physical barrier to reduce pyrenoid CO2 leakage, as well as proper enzyme localization to reduce futile cycling between CO2 and HCO3-. Importantly, our model demonstrates the feasibility of a purely passive CO2 uptake strategy at air-level CO2, while active HCO3- uptake proves advantageous at lower CO2 levels. We propose a four-step engineering path to increase the rate of CO2 fixation in the plant chloroplast up to threefold at a theoretical cost of only 1.3 ATP per CO2 fixed, thereby offering a framework to guide the engineering of a PCCM into land plants.

Vertex protein PduN tunes encapsulated pathway performance by dictating bacterial metabolosome morphology.

Engineering subcellular organization in microbes shows great promise in addressing bottlenecks in metabolic engineering efforts; however, rules guiding selection of an organization strategy or platform are lacking. Here, we study compartment morphology as a factor in mediating encapsulated pathway performance. Using the 1,2-propanediol utilization microcompartment (Pdu MCP) system from Salmonella enterica serovar Typhimurium LT2, we find that we can shift the morphology of this protein nanoreactor from polyhedral to tubular by removing vertex protein PduN. Analysis of the metabolic function between these Pdu microtubes (MTs) shows that they provide a diffusional barrier capable of shielding the cytosol from a toxic pathway intermediate, similar to native MCPs. However, kinetic modeling suggests that the different surface area to volume ratios of MCP and MT structures alters encapsulated pathway performance. Finally, we report a microscopy-based assay that permits rapid assessment of Pdu MT formation to enable future engineering efforts on these structures.

Changes in body shape implicate cuticle stretch in C. elegans growth control.

Growth control establishes organism size, requiring mechanisms to sense and adjust growth during development. Studies of single cells revealed that size homeostasis uses distinct control methods. In multicellular organisms, mechanisms that regulate single cell growth must integrate control across organs and tissues during development to generate adult size and shape. We leveraged the roundworm Caenorhabditis elegans as a scalable and tractable model to collect precise growth measurements of thousands of individuals, measure feeding behavior, and quantify changes in animal size and shape during a densely sampled developmental time course. As animals transitioned from one developmental stage to the next, we observed changes in body aspect ratio while body volume remained constant. Then, we modeled a physical mechanism by which constraints on cuticle stretch could cause changes in C. elegans body shape. The model-predicted shape changes are consistent with those observed in the data. Theoretically, cuticle stretch could be sensed by the animal to initiate larval-stage transitions, providing a means for physical constraints to influence developmental timing and growth rate in C. elegans.

Spatially organizing biochemistry: choosing a strategy to translate synthetic biology to the factory.

Natural biochemical systems are ubiquitously organized both in space and time. Engineering the spatial organization of biochemistry has emerged as a key theme of synthetic biology, with numerous technologies promising improved biosynthetic pathway performance. One strategy, however, may produce disparate results for different biosynthetic pathways. We use a spatially resolved kinetic model to explore this fundamental design choice in systems and synthetic biology. We predict that two example biosynthetic pathways have distinct optimal organization strategies that vary based on pathway-dependent and cell-extrinsic factors. Moreover, we demonstrate that the optimal design varies as a function of kinetic and biophysical properties, as well as culture conditions. Our results suggest that organizing biosynthesis has the potential to substantially improve performance, but that choosing the appropriate strategy is key. The flexible design-space analysis we propose can be adapted to diverse biosynthetic pathways, and lays a foundation to rationally choose organization strategies for biosynthesis.

Improving the Carrier Lifetime of Tin Sulfide via Prediction and Mitigation of Harmful Point Defects.

Tin monosulfide (SnS) is an emerging thin-film absorber material for photovoltaics. An outstanding challenge is to improve carrier lifetimes to >1 ns, which should enable >10% device efficiencies. However, reported results to date have only demonstrated lifetimes at or below 100 ps. In this study, we employ defect modeling to identify the sulfur vacancy and defects from Fe, Co, and Mo as most recombination-active. We attempt to minimize these defects in crystalline samples through high-purity, sulfur-rich growth and experimentally improve lifetimes to >3 ns, thus achieving our 1 ns goal. This framework may prove effective for unlocking the lifetime potential in other emerging thin-film materials by rapidly identifying and mitigating lifetime-limiting point defects.