Crystal Structure of BamB Bound to a Periplasmic Domain Fragment of BamA,the Central Component of the β-Barrel Assembly Machine

The β-barrel assembly machinery (BAM) mediates folding and insertion of β-barrel outer membrane proteins (OMPs) into the outer membrane of Gram-negative bacteria. BAM is a five-protein complex consisting of the β-barrel OMP BamA and lipoproteins BamB, -C, -D, and -E. High resolution structures of all the individual BAM subunits and a BamD-BamC complex have been determined. However, the overall complex architecture remains elusive. BamA is the central component of BAM and consists of a membrane-embedded β-barrel and a periplasmic domain with five polypeptide translocation-associated (POTRA) motifs thought to interact with the accessory lipoproteins. Here we report the crystal structure of a fusion between BamB and a POTRA3–5 fragment of BamA. Extended loops 13 and 17 protruding from one end of the BamB β-propeller contact the face of the POTRA3 β-sheet in BamA. The interface is stabilized by several hydrophobic contacts, a network of hydrogen bonds, and a cation-π interaction between BamA Tyr-255 and BamB Arg-195. Disruption of BamA-BamB binding by BamA Y255A and probing of the interface by disulfide bond cross-linking validate the physiological relevance of the observed interface. Furthermore, the structure is consistent with previously published mutagenesis studies. The periplasmic five-POTRA domain of BamA is flexible in solution due to hinge motions in the POTRA2–3 linker. Modeling BamB in complex with full-length BamA shows BamB binding at the POTRA2–3 hinge, suggesting a role in modulation of BamA flexibility and the conformational changes associated with OMP folding and insertion.     

Metabolic profiling and enhanced production of phytosterols by elicitation with methyl jasmonate and silver nitrate in whole plant cultures of Lemna paucicostata

In this study, the effects of methyl jasmonate (MJ) and silver nitrate (SN) treatment on metabolic profiles and yields of phytosterols such as campesterol, stigmasterol, and β-sitosterol in whole plant cultures of Lemna paucicostata were investigated using gas chromatography–mass spectrometry coupled with multivariate statistical analysis. The MJ and SN treatments retarded the growth of L. paucicostata plants, while they enhanced the yields of three phytosterols, compared to control. Higher yields of phytosterols were attained at day 28 compared to day 42. Moreover, stigmasterol yield was the highest at 0.85 mg/g from day 28 plants grown under MJ + SN co-treated culture. Among the various metabolites, the levels of palmitic and stearic acids, which might participate in a defense mechanism, were higher in the MJ + SN condition than in control. To determine the optimal timing of MJ + SN addition, MJ + SN was added on days 21, 28, and 35 after inoculation. The total yield and productivity of phytosterol reached maximum levels when the MJ + SN was added at day 35. The highest productivity of stigmasterol (6.08 mg/L) was also achieved when MJ + SN was added on day 35.     

Molecular dynamics simulation of fluorination effect for solvation of trifluoromethylbenzoic acid isomers in supercritical carbon dioxide

A molecular dynamics (MD) simulation was applied to carbon dioxide+trifluoromethylbenzoic acid isomer and carbon dioxide+methylbenzoic acid isomer systems to investigate the interactions between carbon dioxide and the solutes. The pair correlation functions between the carbon dioxide and trifluoromethyl group or methyl group in the solutes were calculated to study the fluorination effect of solvation. As a result, it was found that the interactions between carbon dioxide and trifluoromethyl group in trifluoromethylbenzoic acid isomers were stronger than those between carbon dioxide and the methyl group in methylbenzoic acid isomers. The simulation results had the same tendency as the experimental solubility enhancements and coincided with the trend of the interaction parameters of the Peng-Robinson equation of state that were determined from the solubility data.     

An “elite hacker”

The year 2011 marked the 40 year anniversary of Richard Nixon signing the National Cancer Act, thus declaring the beginning of the “War on Cancer” in the United States. Whereas we have made tremendous progress toward understanding the genetics of tumors in the past four decades, and in developing enabling technology to dissect the molecular underpinnings of cancer at unprecedented resolution, it is only recently that the important role of the stromal microenvironment has been studied in detail. Cancer is a tissue-specific disease, and it is becoming clear that much of what we know about breast cancer progression parallels the biology of the normal breast differentiation, of which there is still much to learn. In particular, the normal breast and breast tumors share molecular, cellular, systemic and microenvironmental influences necessary for their progression. It is therefore enticing to consider a tumor to be a “rogue hacker”—one who exploits the weaknesses of a normal program for personal benefit. Understanding normal mammary gland biology and its “security vulnerabilities” may thus leave us better equipped to target breast cancer. In this review, we will provide a brief overview of the heterotypic cellular and molecular interactions within the microenvironment of the developing mammary gland that are necessary for functional differentiation, provide evidence suggesting that similar biology—albeit imbalanced and exaggerated—is observed in breast cancer progression particularly during the transition from carcinoma in situ to invasive disease. Lastly we will present evidence suggesting that the multigene signatures currently used to model cancer heterogeneity and clinical outcome largely reflect signaling from a heterogeneous microenvironment—a recurring theme that could potentially be exploited therapeutically.     

Plant secretome — From cellular process to biological activity

Recent studies suggest that plants secrete a large number of proteins and peptides into the extracellular space. Secreted proteins play a crucial role in stress response, communication and development of organisms. Here we review the current knowledge of the secretome of more than ten plant species, studied in natural conditions or during (a)biotic stress. This review not only deals with the classical secretory route via endoplasmic reticulum and Golgi followed by proteins containing a known N-terminal signal peptide, but also covers new findings about unconventional secretion of leaderless proteins. We describe alternative secretion pathways and the involved compartments like the recently discovered EXPO. The well characterized secreted peptides that function as ligands of receptor proteins exemplify the biological significance and activity of the secretome. This article is part of a Special Issue entitled: An Updated Secretome.     

metaBIT,an integrative and automated metagenomic pipeline for analysing microbial profiles from high‐throughput sequencing shotgun data

Micro‐organisms account for most of the Earth's biodiversity and yet remain largely unknown. The complexity and diversity of microbial communities present in clinical and environmental samples can now be robustly investigated in record times and prices thanks to recent advances in high‐throughput DNA sequencing (HTS). Here, we develop metaBIT, an open‐source computational pipeline automatizing routine microbial profiling of shotgun HTS data. Customizable by the user at different stringency levels, it performs robust taxonomy‐based assignment and relative abundance calculation of microbial taxa, as well as cross‐sample statistical analyses of microbial diversity distributions. We demonstrate the versatility of metaBIT within a range of published HTS data sets sampled from the environment (soil and seawater) and the human body (skin and gut), but also from archaeological specimens. We present the diversity of outputs provided by the pipeline for the visualization of microbial profiles (barplots, heatmaps) and for their characterization and comparison (diversity indices, hierarchical clustering and principal coordinates analyses). We show that metaBIT allows an automatic, fast and user‐friendly profiling of the microbial DNA present in HTS shotgun data sets. The applications of metaBIT are vast, from monitoring of laboratory errors and contaminations, to the reconstruction of past and present microbiota, and the detection of candidate species, including pathogens.     

Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, demyelinating disease that affects the central nervous system and is characterized by a complex pathogenesis and difficult management. The identification of new biomarkers would be clinically useful for more accurate diagnoses and disease monitoring. Metabolomics, the identification of small endogenous molecules, offers an instantaneous molecular snapshot of the MS phenotype. Here the metabolomic profiles (utilizing plasma from patients with MS) were characterized with a Gas cromatography-mass spectrometry-based platform followed by a multivariate statistical analysis and comparison with a healthy control (HC) population. The obtained partial least square discriminant analysis (PLS-DA) model identified and validated significant metabolic differences between individuals with MS and HC (R2X = 0.223, R2Y = 0.82, Q2 = 0.562; p < 0.001). Among discriminant metabolites phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate were correctly identified, and some resulted as unknown. A receiver operating characteristic (ROC) curve with AUC 0.84 (p = 0.01; CI: 0.75–1) generated with the concentrations of the discriminant metabolites, supported the strength of the model. Pathway analysis indicated asparagine and citrulline biosynthesis as the main canonical pathways involved in MS. Changes in the citrulline biosynthesis pathway suggests the involvement of oxidative stress during neuronal damage. The results confirmed metabolomics as a useful approach to better understand the pathogenesis of MS and to provide new biomarkers for the disease to be used together with clinical data.