Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors

Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data with the use of a mathematical model of the metabolic network. A critical step in MFA is model selection: choosing what compartments, metabolites, and reactions to include in the metabolic network model. Model selection is often done informally during the modelling process, based on the same data that is used for model fitting (estimation data). This can lead to either overly complex models (overfitting) or too simple ones (underfitting), in both cases resulting in poor flux estimates. Here, we propose a method for model selection based on independent validation data. We demonstrate in simulation studies that this method consistently chooses the correct model in a way that is independent on errors in measurement uncertainty. This independence is beneficial, since estimating the true magnitude of these errors can be difficult. In contrast, commonly used model selection methods based on the χ²-test choose different model structures depending on the believed measurement uncertainty; this can lead to errors in flux estimates, especially when the magnitude of the error is substantially off. We present a new approach for quantification of prediction uncertainty of mass isotopomer distributions in other labelling experiments, to check for problems with too much or too little novelty in the validation data. Finally, in an isotope tracing study on human mammary epithelial cells, the validation-based model selection method identified pyruvate carboxylase as a key model component. Our results argue that validation-based model selection should be an integral part of MFA model development.     

Epidemiological and evolutionary consequences of different types of CRISPR-Cas systems

Bacteria have adaptive immunity against viruses (phages) in the form of CRISPR-Cas immune systems. Currently, 6 types of CRISPR-Cas systems are known and the molecular study of three of these has revealed important molecular differences. It is unknown if and how these molecular differences change the outcome of phage infection and the evolutionary pressure the CRISPR-Cas systems faces. To determine the importance of these molecular differences, we model a phage outbreak entering a population defending exclusively with a type I/II or a type III CRISPR-Cas system. We show that for type III CRISPR-Cas systems, rapid phage extinction is driven by the probability to acquire at least one resistance spacer. However, for type I/II CRISPR-Cas systems, rapid phage extinction is characterized by an a threshold-like behaviour: any acquisition probability below this threshold leads to phage survival whereas any acquisition probability above it, results in phage extinction. We also show that in the absence of autoimmunity, high acquisition rates evolve. However, when CRISPR-Cas systems are prone to autoimmunity, intermediate levels of acquisition are optimal during a phage outbreak. As we predict an optimal probability of spacer acquisition 2 factors of magnitude above the one that has been measured, we discuss the origin of such a discrepancy. Finally, we show that in a biologically relevant parameter range, a type III CRISPR-Cas system can outcompete a type I/II CRISPR-Cas system with a slightly higher probability of acquisition.     

Statistical and conformational analysis of the electron density of protein side chains

Protein side chains make most of the specific contacts between proteins and other molecules, and their conformational properties have been studied for many years. These properties have been analyzed primarily in the form of rotamer libraries, which cluster the observed conformations into groups and provide frequencies and average dihedral angles for these groups. In recent years, these libraries have improved with higher resolution structures and using various criteria such as high thermal factors to eliminate side chains that may be misplaced within the crystallographic model coordinates. Many of these side chains have highly non-rotameric dihedral angles. The origin of side chains with high B-factors and/or with non-rotameric dihedral angles is of interest in the determination of protein structures and in assessing the prediction of side chain conformations. In this paper, using a statistical analysis of the electron density of a large set of proteins, it is shown that: (1) most non-rotameric side chains have low electron density compared to rotameric side chains; (2) up to 15% of chi1 non-rotameric side chains in PDB models can clearly be fit to density at a single rotameric conformation and in some cases multiple rotameric conformations; (3) a further 47% of non-rotameric side chains have highly dispersed electron density, indicating potentially interconverting rotameric conformations; (4) the entropy of these side chains is close to that of side chains annotated as having more than one chi(1) rotamer in the crystallographic model; (5) many rotameric side chains with high entropy clearly show multiple conformations that are not annotated in the crystallographic model. These results indicate that modeling of side chains alternating between rotamers in the electron density is important and needs further improvement, both in structure determination and in structure prediction.     

Domain movements of elongation factor eEF2 and the eukaryotic 80S ribosome facilitate tRNA translocation

An 11.7-A-resolution cryo-EM map of the yeast 80S.eEF2 complex in the presence of the antibiotic sordarin was interpreted in molecular terms, revealing large conformational changes within eEF2 and the 80S ribosome, including a rearrangement of the functionally important ribosomal intersubunit bridges. Sordarin positions domain III of eEF2 so that it can interact with the sarcin-ricin loop of 25S rRNA and protein rpS23 (S12p). This particular conformation explains the inhibitory action of sordarin and suggests that eEF2 is stalled on the 80S ribosome in a conformation that has similarities with the GTPase activation state. A ratchet-like subunit rearrangement (RSR) occurs in the 80S.eEF2.sordarin complex that, in contrast to Escherichia coli 70S ribosomes, is also present in vacant 80S ribosomes. A model is suggested, according to which the RSR is part of a mechanism for moving the tRNAs during the translocation reaction.     

Introduction and clearance of beta-glucan in the downstream processing of monoclonal antibodies

β-Glucan process-related impurities can be introduced into biopharmaceutical products via upstream or downstream processing or via excipients. This study obtained a comprehensive process-mapping dataset for five monoclonal antibodies to assess β-glucan introduction and clearance during development and production runs at various scales. Overall, 198 data points were available for analysis. The greatest β-glucan concentrations were found in the depth-filtration filtrate (37–2,745 pg/ml). Load volume correlated with β-glucan concentration in the filtrate, whereas flush volume was of secondary importance. Cation-exchange chromatography significantly cleared β-glucans. Furthermore, β-glucan leaching from the Planova 20N virus removal filter was reduced by increasing the flush volume (1 vs. 10 L/m²). β-glucan concentrations after filter flush with 10 L/m² were consistently <10 pg/ml. No or only limited β-glucan clearance was attained via ultrafiltration/diafiltration (UF/DF). However, during the first run with monoclonal antibody (mAb) 4, β-glucan concentration in the UF/DF retentate was 10.8 pg/mg, potentially due to β-glucan leaching from the first run with a regenerated cellulose membrane. Overall, β-glucan levels in the final mAb drug substance were 1–12 pg/mg. Assuming high doses of 1,000–5,000 mg, a β-glucan contamination at 20 pg/mg would translate to 20–100 ng/dose, which is below the previously suggested threshold for product safety (≤500 ng/dose).     

PavB is a surface‐exposed adhesin of Streptococcus pneumoniae contributing to nasopharyngeal colonization and airways infections

The genomic analysis of Streptococcus pneumoniae strains identified the Pneumococcal adherence and virulence factor B (PavB), whose repetitive sequences, designated Streptococcal Surface REpeats (SSURE), interact with human fibronectin. Here, we showed the gene in all tested pneumococci and identified that the observed differences in the molecular mass of PavB rely on the number of repeats, ranging from five to nine SSURE. PavB interacted with fibronectin and plasminogen in a dose‐dependent manner as shown by using various SSURE peptides. In addition, we identified PavB as colonization factor. Mice infected intranasally with ΔpavB pneumococci showed significantly increased survival times compared with wild‐type bacteria. Importantly, the pavB‐mutant showed a delay in transmigration to the lungs as observed in real‐time using bioluminescent pneumococci and decreased colonization rates in a nasopharyngeal carriage model. In co‐infection experiments the wild‐type out‐competed the pavB‐mutant and infections of epithelial cells demonstrated that PavB contributes to adherence to host cell. Blocking experiments suggested a function of PavB as adhesin, which was confirmed by direct binding of SSURE peptides to host cells. Finally, PavB may represent a new vaccine candidate as SSURE peptides reacted with human sera. Taken together, PavB is a surface‐exposed adhesin, which contributes to pneumococcal colonization and infections of the respiratory airways.