Indirect minor histocompatibility antigen presentation by allograft recipient cells in the draining lymph node leads to the activation and clonal expansion of CD4+ T cells that cause obliterative airways disease

Ag recognition by OVA-reactive OT-II (I-Ab restricted) and DO11.10 (I-Ad restricted) TCR-Tg CD4+ T cells after heterotopic transplantation of OVA transgene-expressing tracheal grafts was examined as a model of minor histocompatibility Ag (mHAg)-induced chronic allograft rejection. In response to airway allotransplantation with grafts expressing the OVA transgene, these TCR-Tg CD4+ T cells expressed the activation markers CD69 and CD44, demonstrated evidence of blastogenesis, underwent multiple rounds of cell division leading to their clonal expansion in the draining lymph node, and proceeded to differentiate to a effector/memory T cell phenotype based on a reduction in the expression of CD45RB. These mHAg-specific TCR-Tg CD4+ T cells responded equally well to fully MHC-mismatched tracheas and to class II-deficient allografts, demonstrating that donor mHAg recognition by recipient CD4+ T cells does not rely on Ag presentation by donor-derived APC. The activation of mHAg-specific TCR-Tg CD4+ T cells after their adoptive transfer into recipient mice given MHC-matched, but mHAg-disparate, airway allografts was associated with their movement into the allograft and the near uniform destruction of the transplanted airway tissue secondary to the development of obliterative airways disease. These results demonstrate that an activation of mHAg-reactive CD4+ T cells in the draining lymph node by recipient APC that indirectly express graft mHAg-derived peptide/class II MHC complexes precedes responder T cell proliferation and differentiation, and leads to the eventual migration of these alloreactive T cells to the transplanted airway tissue and the promotion of chronic graft rejection.     

A synergistic approach to protein crystallization: Combination of a fixed‐arm carrier with surface entropy reduction

Protein crystallographers are often confronted with recalcitrant proteins not readily crystallizable, or which crystallize in problematic forms. A variety of techniques have been used to surmount such obstacles: crystallization using carrier proteins or antibody complexes, chemical modification, surface entropy reduction, proteolytic digestion, and additive screening. Here we present a synergistic approach for successful crystallization of proteins that do not form diffraction quality crystals using conventional methods. This approach combines favorable aspects of carrier‐driven crystallization with surface entropy reduction. We have generated a series of maltose binding protein (MBP) fusion constructs containing different surface mutations designed to reduce surface entropy and encourage crystal lattice formation. The MBP advantageously increases protein expression and solubility, and provides a streamlined purification protocol. Using this technique, we have successfully solved the structures of three unrelated proteins that were previously unattainable. This crystallization technique represents a valuable rescue strategy for protein structure solution when conventional methods fail.     

Deducing Underlying Mechanisms from Protein Recruitment Data

By using fluorescent labelling techniques, the distribution and dynamics of proteins can be measured within living cells, allowing to study in vivo the response of cells to a triggering event, such as DNA damage. In order to evaluate the reaction rate constants and to identify the proteins and reactions that are essential for the investigated process, mechanistic models are used, which often contain many proteins and associated parameters and are therefore underdetermined by the data. In order to establish criteria for assessing the significance of a model, we present here a systematic investigation of the information that can be reliably deduced from protein recruitment data, assuming that the complete set of reactions that affect the data of the considered protein species is not known. To this purpose, we study in detail models where one or two proteins that influence each other are recruited to a substrate. We show that in many cases the kind of interaction between the proteins can be deduced by analyzing the shape of the recruitment curves of one protein. Furthermore, we discuss in general in which cases it is possible to discriminate between different models and in which cases it is impossible based on the data. Finally, we argue that if different models fit experimental data equally well, conducting experiments with different protein concentrations would allow discrimination between the alternative models in many cases.     

Autotaxin and its product lysophosphatidic acid suppress brown adipose differentiation and promote diet-induced obesity in mice

Brown adipose tissue is a thermogenic organ that dissipates stored energy as heat to maintain body temperature. This process may also provide protection from development of diet-induced obesity. We report that the bioactive lipid mediator lysophosphatidic acid (LPA) markedly decreases differentiation of cultured primary brown adipocyte precursors, whereas potent selective inhibitors of the LPA-generating enzyme autotaxin (ATX) promote differentiation. Transgenic mice overexpressing ATX exhibit reduced expression of brown adipose tissue-related genes in peripheral white adipose tissue and accumulate significantly more fat than wild-type controls when fed a high-fat diet. Our results indicate that ATX and its product LPA are physiologically relevant negative regulators of brown fat adipogenesis and are consistent with a model in which a decrease in mature peripheral brown adipose tissue results in increased susceptibility to diet-induced obesity in mice.     

Cross-scale quality assessment of a mechanistic cation exchange chromatography model

Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing-scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing-scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass-action (SMA) adsorption model was applied to the scale-up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory- to manufacturing-scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large-scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.     

The structure of F1-ATPase from Saccharomyces cerevisiae inhibited by its regulatory protein IF1

The structure of F₁-ATPase from Saccharomyces cerevisiae inhibited by the yeast IF₁ has been determined at 2.5 Å resolution. The inhibitory region of IF₁ from residues 1 to 36 is entrapped between the C-terminal domains of the α_DP- and β_DP-subunits in one of the three catalytic interfaces of the enzyme. Although the structure of the inhibited complex is similar to that of the bovine-inhibited complex, there are significant differences between the structures of the inhibitors and their detailed interactions with F₁-ATPase. However, the most significant difference is in the nucleotide occupancy of the catalytic β_E-subunits. The nucleotide binding site in β_E-subunit in the yeast complex contains an ADP molecule without an accompanying magnesium ion, whereas it is unoccupied in the bovine complex. Thus, the structure provides further evidence of sequential product release, with the phosphate and the magnesium ion released before the ADP molecule.     

Mannose receptor ligand-positive cells express the metalloprotease decysin in the B cell follicle.

Decysin, a gene encoding a disintegrin metalloprotease, is transcribed in human dendritic cells (DC) and germinal centers (GC). We have cloned its murine homologue and show that it is processed by the endoprotease furin before secretion of the catalytic domain. We have defined the cell types that express decysin in mouse spleen in the course of an immune response to T cell-dependent Ags. Like in humans, decysin is transcribed by activated CD11c(+) DC that enter the T cell zone from the marginal zone (MZ). In the GC, decysin is expressed by follicular DC and tingible body macrophages. In addition, a MZ cell population expresses decysin and appears to migrate into the B cell follicle. The majority of these follicle-homing cells express the mannose receptor ligand, a marker for the macrophage-like MZ metallophils. The follicle-homing cells are M-CSF dependent, as they are absent in op/op mice that lack functional M-CSF. This suggests that mannose receptor ligand(+) MZ metallophils differentiate into cells that migrate from the MZ into the B cell follicle. Decysin represents the first marker for this previously unrecognized cell population of the mouse spleen, which may represent a precursor for GCDC and may be specialized in the transport of unprocessed Ag from the MZ into developing GC.     

Soil carbon sequestration and land use change associated with biofuel production: empirical evidence

Soil organic carbon (SOC) change can be a major impact of land use change (LUC) associated with biofuel feedstock production. By collecting and analyzing data from worldwide field observations of major LUCs from cropland, grassland, and forest to lands producing biofuel crops (i.e. corn, switchgrass, Miscanthus, poplar, and willow), we were able to estimate SOC response ratios and sequestration rates and evaluate the effects of soil depth and time scale on SOC change. Both the amount and rate of SOC change were highly dependent on the specific land transition. Irrespective of soil depth or time horizon, cropland conversions resulted in an overall SOC gain of 6–14% relative to initial SOC level, while conversion from grassland or forest to corn (without residue removal) or poplar caused significant carbon loss (9–35%). No significant SOC changes were observed in land converted from grasslands or forests to switchgrass, Miscanthus, or willow. The SOC response ratios were similar in both 0–30 and 0–100 cm soil depths in most cases, suggesting SOC changes in deep soil and that use of top soil only for SOC accounting in biofuel life cycle analysis (LCA) might underestimate total SOC changes. Soil carbon sequestration rates varied greatly among studies and land transition types. Generally, the rates of SOC change tended to be the greatest during the 10 years following land conversion and had declined to approach 0 within about 20 years for most LUCs. Observed trends in SOC change were generally consistent with previous reports. Soil depth and duration of study significantly influence SOC change rates and so should be considered in carbon emission accounting in biofuel LCA. High uncertainty remains for many perennial systems and forest transitions, additional field trials, and modeling efforts are needed to draw conclusions about the site‐ and system‐specific rates and direction of change.     

Characterization of initial events in bacterial surface colonization by two Pseudomonas species using image analysis

The processes leading to bacterial colonization on solidwater interfaces are adsorption, desorption, growth, and erosion. These processes have been measured individually in situ in a flowing system in real time using image analysis. Four different substrata (copper, silicon, 316 stainless-steel and glass) and 2 different bacterial species (Pseudomonas aeruginosa and Pseudomonas fluorescens) were used in the experiments. The flow was laminar (Re = 1.4) and the shear stress was kept constant during all experiments at 0.75 N m(-2). The surface roughness varied among the substrata from 0.002 mum (for silicon) to 0.015 mum (for copper). Surface free energies varied from 25.1 dynes cm(-1) for silicon to 31.2 dynes cm(-1) for copper. Cell curface hydrophobicity, reported as hydrocarbon partitioning values, ranged from 0.67 for Ps. fluorescens to 0.97 for Ps. aeruginosa.The adsorption rate coefficient varried by as much as a factor of 10 among the combinations of bacterial strain and substratum material, and was positively correlated with surface free energy, the surface roughness of the substratum, and the hydrophobicity of the cells. The probability of desorption decreased with increasing surface free energy and surface roughness of the substratum. Cell growth was inhibited on copper, but replication of cells overlying an initial cell layer was observed with increased exposure time to the cell-containing bulk water. A mathematical model describing cell accumulation on a substratum is presented.