High-Resolution Structural Analysis of a Novel Octaheme Cytochrome c Nitrite Reductase from the Haloalkaliphilic Bacterium Thioalkalivibrio nitratireducens

Bacterial pentaheme cytochrome c nitrite reductases (NrfAs) are key enzymes involved in the terminal step of dissimilatory nitrite reduction of the nitrogen cycle. Their structure and functions are well studied. Recently, a novel octaheme cytochrome c nitrite reductase (TvNiR) has been isolated from the haloalkaliphilic bacterium Thioalkalivibrio nitratireducens. Here we present high-resolution crystal structures of the apoenzyme and its complexes with the substrate (nitrite) and the inhibitor (azide). Both in the crystalline state and in solution, TvNiR exists as a stable hexamer containing 48 hemes—the largest number of hemes accommodated within one protein molecule known to date. The subunit of TvNiR consists of two domains. The N-terminal domain has a unique fold and contains three hemes. The catalytic C-terminal domain hosts the remaining five hemes, their arrangement, including the catalytic heme, being identical to that found in NrfAs. The complete set of eight hemes forms a spatial pattern characteristic of other multiheme proteins, including structurally characterized octaheme cytochromes. The catalytic machinery of TvNiR resembles that of NrfAs. It comprises the lysine residue at the proximal position of the catalytic heme, the catalytic triad of tyrosine, histidine, and arginine at the distal side, channels for the substrate and product transport with a characteristic gradient of electrostatic potential, and, finally, two conserved Ca²⁺-binding sites. However, TvNiR has a number of special structural features, including a covalent bond between the catalytic tyrosine and the adjacent cysteine and the unusual topography of the product channels that open into the void interior space of the protein hexamer. The role of these characteristic structural features in the catalysis by this enzyme is discussed.     

Contrasting population structure and demographic history of cereal aphids in different environmental and agricultural landscapes

Genetic diversity of populations has important ecological and evolutionary consequences, whose understanding is fundamental to improve the sustainability of agricultural production. Studies of how differences in agricultural management and environment influence the population structure of insect pests are central to predict outbreaks and optimize control programs. Here, we have studied the population genetic diversity and evolution of Sitobion avenae and Sitobion miscanthi, which are among the most relevant aphid pests of cereals across Europe and Asia, respectively. We have used genotyping by sequencing (GBS) to identify genome‐wide single nucleotide polymorphisms (SNPs) to infer the geographic structure and migration patterns. In the present study, we show that the population structure in present‐day populations is different from that described in previous studies, which suggest that they have evolved recently possibly as a response to human‐induced changes in agriculture. This study shows that S. avenae in England is predominantly parthenogenetic and there has been a demographic and spatial expansion of a single genetic cluster, which could correspond with the insecticide resistance superclone identified in previous studies. Conversely, in China, S. miscanthi populations are mostly cyclical parthenogenetic, with one sexual stage in autumn to produce overwintering eggs, and there are six genetically differentiated subpopulations and high genetic differentiation between geographic locations, which suggests that further taxonomical research is needed. Unlike S. avenae in England, there is no evidence for insecticide resistance and there is no predominance of a single lineage in S. miscanthi in China.     

Viability and recovery from degranulation of isolated rat peritoneal mast cells

Using a culture system that allows prolonged maintenance of purified populations of peritoneal mast cells, we have examined them following stimulation by non-immunologic or immunologic agents. Employing phase-contrast microscopy of living cells and various pharmacological manipulations, we have noted that the recovery process includes a reduction in cell size, the probable sealing of exocytotic cavities, a pronounced displacement of the cell nucleus and a resynthesis of histamine. During recovery, mast cells can entrap molecules from the extracellular fluid and later release these substances by a Ca-dependent mechanism. Our results suggest that microfilaments, calmodulin, Ca, and metabolic energy are necessary for recovery.     

Invited review: mechanisms of ventilator-induced lung injury: a perspective.

Despite advances in critical care, the mortality rate in patients with acute lung injury remains high. Furthermore, most patients who die do so from multisystem organ failure. It has been postulated that ventilator-induced lung injury plays a key role in determining the negative clinical outcome of patients exposed to mechanical ventilation. How mechanical ventilation exerts its detrimental effect is as of yet unknown, but it appears that overdistension of lung units or shear forces generated during repetitive opening and closing of atelectatic lung units exacerbates, or even initiates, significant lung injury and inflammation. The term "biotrauma" has recently been elaborated to describe the process by which stress produced by mechanical ventilation leads to the upregulation of an inflammatory response. For mechanical ventilation to exert its deleterious effect, cells are required to sense mechanical forces and activate intracellular signaling pathways able to communicate the information to its interior. This information must then be integrated in the nucleus, and an appropriate response must be generated to implement and/or modulate its response and that of neighboring cells. In this review, we present a perspective on ventilator-induced lung injury with a focus on mechanisms and clinical implications. We highlight some of the most recent findings, which we believe contribute to the generation and propagation of ventilator-induced lung injury, placing a special emphasis on their implication for future research and clinical therapies.     

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

Objectives

To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans.

Methods

We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients.

Results

Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis.

Conclusion

Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications.     

Differential signaling mechanisms of HNP-induced IL-8 production in human lung epithelial cells and monocytes

Human neutrophil peptides (HNP) kill microorganisms but also modulate immune responses through upregulation of the chemokine IL-8 by activation of the nucleotide P2Y(6) receptor. However, the intracellular signaling mechanisms remain yet to be determined. Human lung epithelial cells (A549) and monocytes (U937) were stimulated with HNP in the absence and presence of the specific kinase inhibitors for Src, extracellular signal-regulated kinase-1 and -2 (ERK1/2), p38 mitogen-activated protein kinase (MAPK), c-Jun-N-terminal kinases (JNK), and Akt. HNP induced a rapid phosphorylation of the kinases in both cell types associated with a dose-dependent, selective production of IL-8 among 10 cytokines assayed. The HNP-induced IL-8 production was blocked by the Src tyrosine kinase inhibitor PP2, MEK1/2 inhibitor U0126, and the phosphatidylinositol 3 kinase (PI3K) inhibitor LY294002, but not by the JNK inhibitor SP600125 in both cell types. Treatment with the p38 inhibitor SB203580 attenuated the HNP-induced IL-8 production only in monocytes. Blockade of Src kinase blunted HNP-induced phosphorylation of the ERK1/2 and Akt but not p38 in monocytes. In contrast, Src inhibition had no effect on phosphorylation of the other kinases in the lung epithelial cells. We conclude that the activation of ERK1/2 and PI3K/Akt pathways is required for HNP-induced IL-8 release which occurs in a Src-independent manner in lung epithelial cells, while is Src-dependent in monocytes.     

Cation-pi interactions studied in a model coiled-coil peptide

Cation-pi interactions between aromatic amino acids and the positively charged residues lysine and arginine have been proposed to play an important role in stabilizing protein structure. We have used a peptide that adopts a coiled coil structure as a model system to evaluate the energetic contribution of cation-pi interactions to protein folding. Peptides were designed in which phenylalanine, tyrosine, and tryptophan were placed at a solvent-exposed position of the helix, one turn removed from an arginine residue that could provide a favorable cation-pi interaction. Only the arginine-phenylalanine pairing provided significant stabilization of the peptide structure and it appears that hydrophobic packing, rather than the cation-pi effect, is more likely to be responsible for the stability of this peptide. We conclude that any stabilizing effect of cation-pi interactions in these peptides is much smaller than that predicted from computational studies.     

The plasma peptidome

Background

It may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma using LC–ESI–MS/MS to identify, with a linear quadrupole ion trap to identify, quantify and compare the statistical distributions of peptides cleaved ex vivo from plasma samples from different clinical populations.

Methods

A systematic method for the organic fractionation of plasma peptides was applied to identify and quantify the endogenous tryptic peptides from human plasma from multiple institutions by C18 HPLC followed nano electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) with a linear quadrupole ion trap. The endogenous tryptic peptides, or tryptic phospho peptides (i.e. without exogenous digestion), were extracted in a mixture of organic solvent and water, dried and collected by preparative C18. The tryptic peptides from 6 institutions with 12 different disease and normal EDTA plasma populations, alongside ice cold controls for pre-analytical variation, were characterized by mass spectrometry. Each patient plasma was precipitated in 90% acetonitrile and the endogenous tryptic peptides extracted by a stepwise gradient of increasing water and then formic acid resulting in 10 sub-fractions. The fractionated peptides were manually collected over preparative C18 and injected for 1508 LC–ESI–MS/MS experiments analyzed in SQL Server R.

Results

Peptides that were cleaved in human plasma by a tryptic activity ex vivo provided convenient and sensitive access to most human proteins in plasma that show differences in the frequency or intensity of proteins observed across populations that may have clinical significance. Combination of step wise organic extraction of 200 μL of plasma with nano electrospray resulted in the confident identification and quantification ~?14,000 gene symbols by X!TANDEM that is the largest number of blood proteins identified to date and shows that you can monitor the ex vivo proteolysis of most human proteins, including interleukins, from blood. A total of 15,968,550 MS/MS spectra ≥?E4 intensity counts were correlated by the SEQUEST and X!TANDEM algorithms to a federated library of 157,478 protein sequences that were filtered for best charge state (2+ or 3+) and peptide sequence in SQL Server resulting in 1,916,672 distinct best-fit peptide correlations for analysis with the R statistical system. SEQUEST identified some 140,054 protein accessions, or some ~?26,000 gene symbols, proteins or loci, with at least 5 independent correlations. The X!TANDEM algorithm made at least 5 best fit correlations to more than 14,000 protein gene symbols with p-values and FDR corrected q-values of ~?0.001 or less. Log₁₀ peptide intensity values showed a Gaussian distribution from E8 to E4 arbitrary counts by quantile plot, and significant variation in average precursor intensity across the disease and controls treatments by ANOVA with means compared by the Tukey–Kramer test. STRING analysis of the top 2000 gene symbols showed a tight association of cellular proteins that were apparently present in the plasma as protein complexes with related cellular components, molecular functions and biological processes.

Conclusions

The random and independent sampling of pre-fractionated blood peptides by LC-ESI-MS/MS with SQL Server-R analysis revealed the largest plasma proteome to date and was a practical method to quantify and compare the frequency or log₁₀ intensity of individual proteins cleaved ex vivo across populations of plasma samples from multiple clinical locations to discover treatment-specific variation using classical statistics suitable for clinical science. It was possible to identify and quantify nearly all human proteins from EDTA plasma and compare the results of thousands of LC–ESI–MS/MS experiments from multiple clinical populations using standard database methods in SQL Server and classical statistical strategies in the R data analysis system.