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Cell-free (CF) synthesis with highly productive E. coli lysates is a convenient method to produce labeled proteins for NMR studies. Despite reduced metabolic activity in CF lysates, a certain scrambling of supplied isotope labels is still notable. Most problematic are conversions of 15N labels of the amino acids L-Asp, L-Asn, L-Gln, L-Glu and L-Ala, resulting in ambiguous NMR signals as well as in label dilution. Specific inhibitor cocktails suppress most undesired conversion reactions, while limited availability and potential side effects on CF system productivity need to be considered. As alternative route to address NMR label conversion in CF systems, we describe the generation of optimized E. coli lysates with reduced amino acid scrambling activity. Our strategy is based on the proteome blueprint of standardized CF S30 lysates of the E. coli strain A19. Identified lysate enzymes with suspected amino acid scrambling activity were eliminated by engineering corresponding single and cumulative chromosomal mutations in A19. CF lysates prepared from the mutants were analyzed for their CF protein synthesis efficiency and for residual scrambling activity. The A19 derivative “Stablelabel” containing the cumulative mutations asnA, ansA/B, glnA, aspC and ilvE yielded the most useful CF S30 lysates. We demonstrate the optimized NMR spectral complexity of selectively labeled proteins CF synthesized in “Stablelabel” lysates. By taking advantage of ilvE deletion in "Stablelabel", we further exemplify a new strategy for methyl group specific labeling of membrane proteins with the proton pump proteorhodopsin.
Is it true that speed bumps level the playing field, make financial markets more stable and reduce negative externalities of high-frequency trading (HFT) firms? We examine how the implementation of a particular speed bump – Midpoint Extended Life order (M-ELO) on Nasdaq impacted financial markets stability in terms of occurrences of mini-flash crashes in individual securities. We use high-frequency order book message data around the implementation date and apply difference-in-differences analysis to estimate the average treatment effect of the speed bump on market stability and liquidity provision. The results suggest that the introduction of the M-ELO decreases the average number of crashes on Nasdaq compared to other exchanges by 4.7%. Liquidity provision by HFT firms also improves. These findings imply that technology-based solutions by exchanges are feasible alternatives to regulatory intervention towards safer markets.
This paper examines how the implementation of a new dark order - Midpoint Extended Life Order on NASDAQ - impacts financial markets stability in terms of occurrences of mini-flash crashes in individual securities. We use high-frequency order book data and apply panel regression analysis to estimate the effect of M-ELO trading on market stability and liquidity provision. The results suggest a predominance of a speed bump effect of M-ELO rather than a darkness effect. We find that the introduction of M-ELO increases market stability by reducing the average number of mini-flash crashes, but its impact on market quality is mixed.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
The evolution of cell-free protein synthesis (CFPS) over recent decades has made it a widely used system for expressing membrane proteins (MPs). Unlike traditional methods, CFPS allows direct and translocon-independent expression of MPs within lipid membranes, such as liposomes or nanodiscs (NDs), without the need for detergent solubilization. This open nature of CF systems enables customization of the experimental environment, including expression conditions, choice of nanoparticles (NPs), lipid composition, and addition of stabilizing molecules.
Membrane scaffold protein (MSP)-based NDs emerged as a gold standard for cotranslational solubilization of MPs using the CF-system. This approach allowed not only biochemical characterization, but also structural studies of MPs and even GPCRs. However, to solubilize MPs inside nanoparticles via the traditional reconstitution route, apart from MSPs other scaffolds were successfully implemented, e.g. the saposin A (commercially known as Salipro) scaffold system or the synthetic styrene maleic acid lipid particles (SMALPs). In this study the potential of saposin A-based nanoparticles (SapNPs) was explored for cotranslational MP solubilization.
Three strategies for applying SapNPs in CF systems were investigated: preassembly, (i) coassembly (ii), and coexpression (iii). (i) Preassembly involved forming SapNPs before CF expression and adding them to the CF reaction. In coassembly mode SapA and lipids were mixed in the CF reaction for spontaneous assembly with the synthesized MP. In coexpression mode lipids were added to the CF reaction while coexpressing SapA with the MP target. Proteorhodopsin (PR) served as a model protein to evaluate these strategies due to its ability to oligomerize and straightforward quantification using the cofactor retinal. Preassembled SapNPs provided homogeneous, aggregate-free particles yielding up to 200 µM solubilized PR inside in the CF reaction. Coassembly was also successfully applied to produce PR/SapNP complexes at slightly lower yields, however the system was prone to produce soluble aggregates at too high PR template concentrations and overall needed more adjustments. Coexpression resulted in PR yields below 20 µM and was not considered viable for MP production. Finally, the preassembled SapNPs were used to produce functional G-protein coupled receptor probes. Despite lower overall performance compared to MSP-based systems, SapNPs showed potential as an alternative in CF systems for specific MPs.
The second optimization approach was directed at the CF lysate itself. CF synthesis for NMR analysis benefits from selective labeling schemes enabled by truncated amino acid (AA) metabolic pathways in lysates, reducing spectral ambiguity. However, residual enzymatic AA conversions persist, leading to label dilution and ambiguous NMR spectra. This study aimed to eliminate these residual activities in the E. coli A19 strain, generating optimized CF lysates for NMR applications.
The approach involved cumulative gene deletions of the most problematic scrambling enzymes. The new strain, “Stablelabel,” included deletions and modifications in genes asnA, ansA, ansB, glnA, aspC, and ilvE, effectively eliminating background activities of L-Asn, L-Asp, and conversions of L-Glu to L-Asp and L-Gln. However, residual conversion of L-Gln to L-Glu persisted due to glutaminase activity of several glutaminases using the inhibitor 6 diazo-5-oxo-L-norleucine (DON). Stablelabel showed a slightly slower growth than A19, and an overall good performance with 2.7 mg/mL GFP expressed in the reaction mixture (RM) compared to the parental A19 strain with 3.5 mg/mL. Furthermore, the strain was successfully applied to demonstrate methyl group labeling of MPs using preconverted L-val and L-leu from their respective precursors 2-ketoisovalerate and 4-methyl-2-oxovalerate.
In this study, lipid nanoparticle particle-and strain engineering vividly demonstrated the potential of CFPS systems and their versatility. While the SapNP system requires further engineering to potentially reach the efficiency of the well-studied MSP NDs, this study provides an example of nanoparticle characterization allowing new insights into NP behavior in CF systems. Furthermore, it was shown that strain engineering is a straightforward solution to tailor CF lysates to the individual requirements. After this thesis was submitted, Stablelabel in fact was successfully applied for backbone assignment of casein kinase 1, thereby demonstrating its suitability to express complex targets for NMR studies.