Subunit rotation in a single FoF1-ATP synthase in a living bacterium monitored by FRET

FoF1-ATP synthase is the ubiquitous membrane-bound enzyme in mitochondria, chloroplasts and bacteria which provides the 'chemical energy currency' adenosine triphosphate (ATP) for cellular processes. In Escherichia coli ATP synthesis is driven by a proton motive force (PMF) comprising a proton concentration difference {\Delta}pH plus an electric potential {\Delta}{\Psi} across the lipid membrane. Single-molecule in vitro experiments have confirmed that proton-driven subunit rotation within FoF1-ATP synthase is associated with ATP synthesis. Based on intramolecular distance measurements by single-molecule fluorescence resonance energy transfer (FRET) the kinetics of subunit rotation and the step sizes of the different rotor parts have been unraveled. However, these experiments were accomplished in the presence of a PMF consisting of a maximum {\Delta}pH ~ 4 and an unknown {\Delta}{\Psi}. In contrast, in living bacteria the maximum {\Delta}pH across the plasma membrane is likely 0.75, and {\Delta}{\Psi} has been measured between -80 and -140 mV. Thus the problem of in vivo catalytic turnover rates, or the in vivo rotational speed in single FoF1-ATP synthases, respectively, has to be solved. In addition, the absolute number of functional enzymes in a single bacterium required to maintain the high ATP levels has to be determined. We report our progress of measuring subunit rotation in single FoF1-ATP synthases in vitro and in vivo, which was enabled by a new labeling approach for single-molecule FRET measurements.Comment: 9 pages, 6 figure

Simple sequence repeat variation in the Daphnia pulex genome

Background: Simple sequence repeats (SSRs) are highly variable features of all genomes. Their rapid evolution makes them useful for tracing the evolutionary history of populations and investigating patterns of selection and mutation across gnomes. The recently sequenced Daphnia pulex genome provides us with a valuable data set to study the mode and tempo of SSR evolution, without the inherent biases that accompany marker selection. Results: Here we catalogue SSR loci in the Daphnia pulex genome with repeated motif sizes of 1-100 nucleotides with a minimum of 3 perfect repeats. We then used whole genome shotgun reads to determine the average heterozygosity of each SSR type and the relationship that it has to repeat number, motif size, motif sequence, and distribution of SSR loci. We find that SSR heterozygosity is motif specific, and positively correlated with repeat number as well as motif size. For non-repeat unit polymorphisms, we identify a motif-dependent end-nucleotide polymorphism bias that may contribute to the patterns of abundance for specific homopolymers, dimers, and trimers. Our observations confirm the high frequency of multiple unit variation (multistep) at large microsatellite loci, and further show that the occurrence of multiple unit variation is dependent on both repeat number and motif size. Using the Daphnia pulex genetic map, we show a positive correlation between dimer and trimer frequency and recombination. Conclusions: This genome-wide analysis of SSR variation in Daphnia pulex indicates that several aspects of SSR variation are motif dependent and suggests that a combination of unit length variation and end repeat biased base substitution contribute to the unique spectrum of SSR repeat loci

The EADGENE Microarray Data Analysis Workshop (Open Access publication)

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies

Identification of G1-Regulated Genes in Normally Cycling Human Cells

BACKGROUND: Obtaining synchronous cell populations is essential for cell-cycle studies. Methods such as serum withdrawal or use of drugs which block cells at specific points in the cell cycle alter cellular events upon re-entry into the cell cycle. Regulatory events occurring in early G1 phase of a new cell cycle could have been overlooked. METHODOLOGY AND FINDINGS: We used a robotic mitotic shake-off apparatus to select cells in late mitosis for genome-wide gene expression studies. Two separate microarray experiments were conducted, one which involved isolation of RNA hourly for several hours from synchronous cell populations, and one experiment which examined gene activity every 15 minutes from late telophase of mitosis into G1 phase. To verify synchrony of the cell populations under study, we utilized methods including BrdU uptake, FACS, and microarray analyses of histone gene activity. We also examined stress response gene activity. Our analysis enabled identification of 200 early G1-regulated genes, many of which currently have unknown functions. We also confirmed the expression of a set of genes candidates (fos, atf3 and tceb) by qPCR to further validate the newly identified genes. CONCLUSION AND SIGNIFICANCE: Genome-scale expression analyses of the first two hours of G1 in naturally cycling cells enabled the discovery of a unique set of G1-regulated genes, many of which currently have unknown functions, in cells progressing normally through the cell division cycle. This group of genes may contain future targets for drug development and treatment of human disease

Les droits disciplinaires des fonctions publiques : « unification », « harmonisation » ou « distanciation ». A propos de la loi du 26 avril 2016 relative à la déontologie et aux droits et obligations des fonctionnaires

The production of tt‾ , W+bb‾ and W+cc‾ is studied in the forward region of proton–proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98±0.02 fb−1 . The W bosons are reconstructed in the decays W→ℓν , where ℓ denotes muon or electron, while the b and c quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions.The production of $t\overline{t}$, $W+b\overline{b}$ and $W+c\overline{c}$ is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 $\pm$ 0.02 \mbox{fb}^{-1}. The $W$ bosons are reconstructed in the decays $W\rightarrow\ell\nu$, where $\ell$ denotes muon or electron, while the $b$ and $c$ quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions

Differential branching fraction and angular analysis of the decay B0s→ ϕμ+μ−

The determination of the differential branching fraction and the first angular analysis of the decay B[superscript 0][subscript 0] → ϕμ[superscript +]μ[subscript −] are presented using data, corresponding to an integrated luminosity of 1.0 fb[superscript −1], collected by the LHCb experiment at s√=7s=7 TeV. The differential branching fraction is determined in bins of q[superscript 2], the invariant dimuon mass squared. Integration over the full q[superscript 2] range yields a total branching fraction of B(B[superscript 0][subscript s]→ϕμ[superscript +]μ[subscript −])=(7.07[superscript +0.64][subscript −0.59]±0.71±0.71)) × 10[subscript −7], where the first uncertainty is statistical, the second systematic, and the third originates from the branching fraction of the normalisation channel. An angular analysis is performed to determine the angular observables F[subscript L], S[subscript 3], A[subscript 6], and A[subscript 9]. The observables are consistent with Standard Model expectations.National Science Foundation (U.S.