Molecular simulations unravel the molecular principles that mediate selective permeability of carboxysome shell protein

Bacterial microcompartments (BMCs) are nanoscale proteinaceous organelles that encapsulate enzymes from the cytoplasm using an icosahedral protein shell that resembles viral capsids. Of particular interest are the carboxysomes (CBs), which sequester the CO 2 -fixing enzymes ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) to enhance carbon assimilation. The carboxysome shell serves as a semi-permeable barrier for passage of metabolites in and out of the carboxysome to enhance CO 2 fixation. How the protein shell directs influx and efflux of molecules in an effective manner has remained elusive. Here we use molecular dynamics and umbrella sampling calculations to determine the free-energy profiles of the metabolic substrates, bicarbonate, CO 2 and ribulose bisphosphate and the product 3-phosphoglycerate associated with their transition through the major carboxysome shell protein CcmK2. We elucidate the electrostatic charge-based permeability and key amino acid residues of CcmK2 functioning in mediating molecular transit through the central pore. Conformational changes of the loops forming the central pore may also be required for transit of specific metabolites. The importance of these in-silico findings is validated experimentally by site-directed mutagenesis of the key CcmK2 residue Serine 39. This study provides insight into the mechanism that mediates molecular transport through the shells of carboxysomes, applicable to other BMCs. It also offers a predictive approach to investigate and manipulate the shell permeability, with the intend of engineering BMC-based metabolic modules for new functions in synthetic biology

Probing the Internal pH and Permeability of a Carboxysome Shell

The carboxysome is a protein-based nanoscale organelle in cyanobacteria and many proteobacteria, which encapsulates the key CO2-fixing enzymes ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) and carbonic anhydrase (CA) within a polyhedral protein shell. The intrinsic self-assembly and architectural features of carboxysomes and the semipermeability of the protein shell provide the foundation for the accumulation of CO2 within carboxysomes and enhanced carboxylation. Here, we develop an approach to determine the interior pH conditions and inorganic carbon accumulation within an α-carboxysome shell derived from a chemoautotrophic proteobacterium Halothiobacillus neapolitanus and evaluate the shell permeability. By incorporating a pH reporter, pHluorin2, within empty α-carboxysome shells produced in Escherichia coli, we probe the interior pH of the protein shells with and without CA. Our in vivo and in vitro results demonstrate a lower interior pH of α-carboxysome shells than the cytoplasmic pH and buffer pH, as well as the modulation of the interior pH in response to changes in external environments, indicating the shell permeability to bicarbonate ions and protons. We further determine the saturated HCO3- concentration of 15 mM within α-carboxysome shells and show the CA-mediated increase in the interior CO2 level. Uncovering the interior physiochemical microenvironment of carboxysomes is crucial for understanding the mechanisms underlying carboxysomal shell permeability and enhancement of Rubisco carboxylation within carboxysomes. Such fundamental knowledge may inform reprogramming carboxysomes to improve metabolism and recruit foreign enzymes for enhanced catalytical performance

Kidney Failure Prediction Models: A Comprehensive External Validation Study in Patients with Advanced CKD

Background: Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks.Methods: To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration.Results: The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%-18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.Conclusions: Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years)