Computational redesign of the Escherichia coli ribose-binding protein ligand binding pocket for 1,3-cyclohexanediol and cyclohexanol.

Bacterial periplasmic-binding proteins have been acclaimed as general biosensing platform, but their range of natural ligands is too limited for optimal development of chemical compound detection. Computational redesign of the ligand-binding pocket of periplasmic-binding proteins may yield variants with new properties, but, despite earlier claims, genuine changes of specificity to non-natural ligands have so far not been achieved. In order to better understand the reasons of such limited success, we revisited here the Escherichia coli RbsB ribose-binding protein, aiming to achieve perceptible transition from ribose to structurally related chemical ligands 1,3-cyclohexanediol and cyclohexanol. Combinations of mutations were computationally predicted for nine residues in the RbsB binding pocket, then synthesized and tested in an E. coli reporter chassis. Two million variants were screened in a microcolony-in-bead fluorescence-assisted sorting procedure, which yielded six mutants no longer responsive to ribose but with 1.2-1.5 times induction in presence of 1 mM 1,3-cyclohexanediol, one of which responded to cyclohexanol as well. Isothermal microcalorimetry confirmed 1,3-cyclohexanediol binding, although only two mutant proteins were sufficiently stable upon purification. Circular dichroism spectroscopy indicated discernable structural differences between these two mutant proteins and wild-type RbsB. This and further quantification of periplasmic-space abundance suggested most mutants to be prone to misfolding and/or with defects in translocation compared to wild-type. Our results thus affirm that computational design and library screening can yield RbsB mutants with recognition of non-natural but structurally similar ligands. The inherent arisal of protein instability or misfolding concomitant with designed altered ligand-binding pockets should be overcome by new experimental strategies or by improved future protein design algorithms.

Impaired TLR9 responses in B cells from patients with systemic lupus erythematosus.

B cells play a central role in systemic lupus erythematosus (SLE) pathophysiology but dysregulated pathways leading to a break in B cell tolerance remain unclear. Since Toll-like receptor 9 (TLR9) favors the elimination of autoreactive B cells in the periphery, we assessed TLR9 function in SLE by analyzing the responses of B cells and plasmacytoid dendritic cells (pDCs) isolated from healthy donors and patients after stimulation with CpG, a TLR9 agonist. We found that SLE B cells from patients without hydroxychloroquine treatment displayed defective in vitro TLR9 responses, as illustrated by the impaired upregulation of B cell activation molecules and the diminished production of various cytokines including antiinflammatory IL-10. In agreement with CD19 controlling TLR9 responses in B cells, decreased expression of the CD19/CD21 complex on SLE B cells was detected as early as the transitional B cell stage. In contrast, TLR7 function was preserved in SLE B cells, whereas pDCs from SLE patients properly responded to TLR9 stimulation, thereby revealing that impaired TLR9 function in SLE was restricted to B cells. We conclude that abnormal CD19 expression and TLR9 tolerogenic function in SLE B cells may contribute to the break of B cell tolerance in these patients.

Mechanistic Modeling of Genetic Circuits for ArsR Arsenic Regulation.

Bioreporters are living cells that generate an easily measurable signal in the presence of a chemical compound. They acquire their functionality from synthetic gene circuits, the configuration of which defines the response signal and signal-to-noise ratio. Bioreporters based on the Escherichia coli ArsR system have raised significant interest for quantifying arsenic pollution, but they need to be carefully optimized to accurately work in the required low concentration range (1-10 µg arsenite L-1). To better understand the general functioning of ArsR-based genetic circuits, we developed a comprehensive mechanistic model that was empirically tested and validated in E. coli carrying different circuit configurations. The model accounts for the different elements in the circuits (proteins, DNA, chemical species), and their detailed affinities and interactions, and predicts the (fluorescent) output from the bioreporter cell as a function of arsenite concentration. The model was parametrized using existing ArsR biochemical data, and then complemented by parameter estimations from the accompanying experimental data using a scatter search algorithm. Model predictions and experimental data were largely coherent for feedback and uncoupled circuit configurations, different ArsR alleles, promoter strengths, and presence or absence of arsenic efflux in the bioreporters. Interestingly, the model predicted a particular useful circuit variant having steeper response at low arsenite concentrations, which was experimentally confirmed and may be useful as arsenic bioreporter in the field. From the extensive validation we expect the mechanistic model to further be a useful framework for detailed modeling of other synthetic circuits.

Circulating TFH subset distribution is strongly affected in lupus patients with an active disease.

Follicular helper T cells (TFH) represent a distinct subset of CD4(+) T cells specialized in providing help to B lymphocytes, which may play a central role in autoimmune diseases having a major B cell component such as systemic lupus erythematosus. Recently, TFH subsets that share common phenotypic and functional characteristics with TFH cells from germinal centers, have been described in the peripheral blood from healthy individuals. The aim of this study was to analyze the distribution of such populations in lupus patients. Circulating TFH cell subsets were defined by multicolor flow cytometry as TFH17 (CXCR3(-)CCR6(+)), TFH1 (CXCR3 (+) CCR6(-)) or TFH2 (CXCR3(-)CCR6(-)) cells among CXCR5 (+) CD45RA(-)CD4(+) T cells in the peripheral blood of 23 SLE patients and 23 sex and age-matched healthy controls. IL-21 receptor expression by B cells was analyzed by flow cytometry and the serum levels of IL-21 and Igs were determined by ELISA tests. We found that the TFH2 cell subset frequency is strongly and significantly increased in lupus patients with an active disease (SLEDAI score>8), while the TFH1 cell subset percentage is greatly decreased. The TFH2 and TFH1 cell subset frequency alteration is associated with the presence of high Ig levels and autoantibodies in patient's sera. Moreover, the TFH2 cell subset enhancement correlates with an increased frequency of double negative memory B cells (CD27(-)IgD(-)CD19(+) cells) expressing the IL-21R. Finally, we found that IgE levels in lupus patients' sera correlate with disease activity and seem to be associated with high TFH2 cell subset frequency. In conclusion, our study describes for the first time the distribution of circulating TFH cell subsets in lupus patients. Interestingly, we found an increased frequency of TFH2 cells, which correlates with disease activity. Our results suggest that this subset might play a key role in lupus pathogenesis.

Life in an arsenic-containing gold mine: genome and physiology of the autotrophic arsenite-oxidizing bacterium rhizobium sp. NT-26.

Arsenic is widespread in the environment and its presence is a result of natural or anthropogenic activities. Microbes have developed different mechanisms to deal with toxic compounds such as arsenic and this is to resist or metabolize the compound. Here, we present the first reference set of genomic, transcriptomic and proteomic data of an Alphaproteobacterium isolated from an arsenic-containing goldmine: Rhizobium sp. NT-26. Although phylogenetically related to the plant-associated bacteria, this organism has lost the major colonizing capabilities needed for symbiosis with legumes. In contrast, the genome of Rhizobium sp. NT-26 comprises a megaplasmid containing the various genes, which enable it to metabolize arsenite. Remarkably, although the genes required for arsenite oxidation and flagellar motility/biofilm formation are carried by the megaplasmid and the chromosome, respectively, a coordinate regulation of these two mechanisms was observed. Taken together, these processes illustrate the impact environmental pressure can have on the evolution of bacterial genomes, improving the fitness of bacterial strains by the acquisition of novel functions.