Genome-based phylogenetic analysis of Streptomyces and its relatives

MotivationStreptomyces is one of the best-studied genera of the order Actinomycetales due to its great importance in medical science, ecology and the biotechnology industry. A comprehensive, detailed and robust phylogeny of Streptomyces and its relatives is needed for understanding how this group emerged and maintained such a vast diversity throughout evolution and how soil-living mycelial forms (e.g., Streptomyces s. str.) are related to parasitic, unicellular pathogens (e.g., Mycobacterium tuberculosis) or marine species (e.g., Salinispora tropica). The most important application area of such a phylogenetic analysis will be in the comparative re-annotation of genome sequences and the reconstruction of Streptomyces metabolic networks for biotechnology.MethodsClassical 16S-rRNA-based phylogenetic reconstruction does not guarantee to produce well-resolved robust trees that reflect the overall relationship between bacterial species with widespread horizontal gene transfer. In our study we therefore combine three whole genome-based phylogenies with eight different, highly informative single-gene phylogenies to determine a new robust consensus tree of 45 Actinomycetales species with completely sequenced genomes.ResultsNone of the individual methods achieved a resolved phylogeny of Streptomyces and its relatives. Single-gene approaches failed to yield a detailed phylogeny; even though the single trees are in good agreement among each other, they show very low resolution of inner branches. The three whole genome-based methods improve resolution considerably. Only by combining the phylogenies from single gene-based and genome-based approaches we finally obtained a consensus tree with well-resolved branches for the entire set of Actinomycetales species. This phylogenetic information is stable and informative enough for application to the system-wide comparative modeling of bacterial physiology.     

Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits

Impaired glucose tolerance (IGT) which precedes overt type 2 diabetes (T2DM) for decades is associated with multiple metabolic alterations in insulin sensitive tissues. In an UPLC-qTOF-mass spectrometry-driven non-targeted metabonomics approach we investigated plasma as well as spot urine of 51 non-diabetic, overnight fasted individuals aiming to separate subjects with IGT from controls thereby identify pathways affected by the pre-diabetic metabolic state. We could clearly demonstrate that normal glucose tolerant (NGT) and IGT subjects clustered in two distinct groups independent of the investigated metabonome. These findings reflect considerable differences in individual metabolite fingerprints, both in plasma and urine. Pre-diabetes associated alterations in fatty acid-, tryptophan-, uric acid-, bile acid-, and lysophosphatidylcholine-metabolism, as well as the TCA cycle were identified. Of note, individuals with IGT also showed decreased levels of gut flora-associated metabolites namely hippuric acid, methylxanthine, methyluric acid, and 3-hydroxyhippuric acid. The findings of our non-targeted UPLC-qTOF-MS metabonomics analysis in plasma and spot urine of individuals with IGT vs NGT offers novel insights into the metabolic alterations occurring in the long, asymptomatic period preceding the manifestation of T2DM thereby giving prospects for new intervention targets.     

Contribution of charged and polar residues for the formation of the E1–E2 heterodimer from Hepatitis C Virus

The transmembrane domains of the envelope glycoprotein E1 and E2 have crucial multifunctional roles in the biogenesis of hepatitis C virus. We have performed molecular dynamics simulations to investigate a structural model of the transmembrane segments of the E1–E2 heterodimer. The simulations support the key role of the Lys370–Asp728 ion pair for mediating the E1–E2 heterodimerization. In comparison to these two residues, the simulation results also reveal the differential effect of the conserved Arg730 residue that has been observed in experimental studies. Furthermore, we discovered the formation of inter-helical hydrogen bonds via Asn367 that stabilize dimer formation. Simulations of single and double mutants further demonstrate the importance of the ion-pair and polar interactions between the interacting helix monomers. The conformation of the E1 fragment in the simulation of the E1–E2 heterodimer is in close agreement with an NMR structure of the E1 transmembrane segment. The proposed model of the E1–E2 heterodimer supports the postulated cooperative insertion of both helices by the translocon complex into the bilayer.     

Differential expression of protease activity in serum samples of prostate carcinoma patients with metastases

We present here the results from MS peptide profiling experiments of prostate carcinoma patients and controls with a specific focus on protease activity‐related protein fragments. After purification with surface‐active magnetic beads, MALDI‐TOF profiling experiments were performed on tryptic digests of serum samples of prostate cancer patients with metastases (n=27) and controls (n=30). This resulted in the reproducible detection of eight differentially expressed peptides, which were then identified by nanoLC‐MALDI‐TOF/TOF and confirmed by MALDI‐FTMS exact mass measurements. All differentially expressed peptides are derived from two homologous parts of human serum albumin; two of the eight peptides were tryptic and six were nontryptic. The presence of the nontryptic fragments indicates that a proteolysis process occurs which is not mediated by trypsin. Since the nontryptic fragments were found at significantly higher levels in control samples compared with metastases samples, it is proposed that a specific proteolytic inhibition process is in effect in the serum of prostate cancer patients. Experiments using synthetic peptides showed that this proteolytic activity occurs ex vivo and is sequence specific. Importantly, the observed prostate carcinoma‐related inhibition of the proteolysis was reproduced ex vivo using synthetic peptides.     

Evidence of neurotoxicity of ecstasy: sustained effects on electroencephalographic activity in polydrug users

Objective

According to previous EEG reports of indicative disturbances in Alpha and Beta activities, a systematic search for distinct EEG abnormalities in a broader population of Ecstasy users may especially corroborate the presumed specific neurotoxicity of Ecstasy in humans.

Methods

105 poly-drug consumers with former Ecstasy use and 41 persons with comparable drug history without Ecstasy use, and 11 drug naives were investigated for EEG features. Conventional EEG derivations of 19 electrodes according to the 10-20-system were conducted. Besides standard EEG bands, quantitative EEG analyses of 1-Hz-subdivided power ranges of Alpha, Theta and Beta bands have been considered.

Results

Ecstasy users with medium and high cumulative Ecstasy doses revealed an increase in Theta and lower Alpha activities, significant increases in Beta activities, and a reduction of background activity. Ecstasy users with low cumulative Ecstasy doses showed a significant Alpha activity at 11 Hz. Interestingly, the spectral power of low frequencies in medium and high Ecstasy users was already significantly increased in the early phase of EEG recording. Statistical analyses suggested the main effect of Ecstasy to EEG results.

Conclusions

Our data from a major sample of Ecstasy users support previous data revealing alterations of EEG frequency spectrum due rather to neurotoxic effects of Ecstasy on serotonergic systems in more detail. Accordingly, our data may be in line with the observation of attentional and memory impairments in Ecstasy users with moderate to high misuse. Despite the methodological problem of polydrug use also in our approach, our EEG results may be indicative of the neuropathophysiological background of the reported memory and attentional deficits in Ecstasy abusers. Overall, our findings may suggest the usefulness of EEG in diagnostic approaches in assessing neurotoxic sequela of this common drug abuse.     

Differential effects of painful and non-painful stimulation on tactile processing in fibromyalgia syndrome and subjects with masochistic behaviour

Background

In healthy subjects repeated tactile stimulation in a conditioning test stimulation paradigm yields attenuation of primary (S1) and secondary (S2) somatosensory cortical activation, whereas a preceding painful stimulus results in facilitation.

Methodology/Principal Findings

Since previous data suggest that cognitive processes might affect somatosensory processing in S1, the present study aims at investigating to what extent cortical reactivity is altered by the subjective estimation of pain. To this end, the effect of painful and tactile stimulation on processing of subsequently applied tactile stimuli was investigated in patients with fibromyalgia syndrome (FMS) and in subjects with masochistic behaviour (MB) by means of a 122-channel whole-head magnetoencephalography (MEG) system. Ten patients fulfilling the criteria for the diagnosis of FMS, 10 subjects with MB and 20 control subjects matched with respect to age, gender and handedness participated in the present study. Tactile or brief painful cutaneous laser stimuli were applied as conditioning stimulus (CS) followed by a tactile test stimulus (TS) 500 ms later. While in FMS patients significant attenuation following conditioning tactile stimulation was evident, no facilitation following painful stimulation was found. By contrast, in subjects with MB no attenuation but significant facilitation occurred. Attenuation as well as facilitation applied to cortical responses occurring at about 70 ms but not to early S1 or S2 responses. Additionally, in FMS patients the amount of attenuation was inversely correlated with catastrophizing tendency.

Conclusion

The present results imply altered cortical reactivity of the primary somatosensory cortex in FMS patients and MB possibly reflecting differences of individual pain experience.     

Mapping determinants of gene expression plasticity by genetical genomics in C. elegans

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 °C and 24 °C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 °C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.     

Ab initio prediction of metabolic networks using Fourier transform mass spectrometry data

Fourier transform mass spectrometry has recently been introduced into the field of metabolomics as a technique that enables the mass separation of complex mixtures at very high resolution and with ultra high mass accuracy. Here we show that this enhanced mass accuracy can be exploited to predict large metabolic networks ab initio, based only on the observed metabolites without recourse to predictions based on the literature. The resulting networks are highly information-rich and clearly non-random. They can be used to infer the chemical identity of metabolites and to obtain a global picture of the structure of cellular metabolic networks. This represents the first reconstruction of metabolic networks based on unbiased metabolomic data and offers a breakthrough in the systems-wide analysis of cellular metabolism.