Looking inside the box: using Raman microspectroscopy to deconstruct microbial biomass stoichiometry one cell at a time

Stoichiometry of microbial biomass is a key determinant of nutrient recycling in a wide variety of ecosystems. However, little is known about the underlying causes of variance in microbial biomass stoichiometry. This is primarily because of technological constraints limiting the analysis of macromolecular composition to large quantities of microbial biomass. Here, we use Raman microspectroscopy (MS), to analyze the macromolecular composition of single cells of two species of bacteria grown on minimal media over a wide range of resource stoichiometry. We show that macromolecular composition, determined from a subset of identified peaks within the Raman spectra, was consistent with macromolecular composition determined using traditional analytical methods. In addition, macromolecular composition determined by Raman MS correlated with total biomass stoichiometry, indicating that analysis with Raman MS included a large proportion of a cell''s total macromolecular composition. Growth phase (logarithmic or stationary), resource stoichiometry and species identity each influenced each organism''s macromolecular composition and thus biomass stoichiometry. Interestingly, the least variable peaks in the Raman spectra were those responsible for differentiation between species, suggesting a phylogenetically specific cellular architecture. As Raman MS has been previously shown to be applicable to cells sampled directly from complex environments, our results suggest Raman MS is an extremely useful application for evaluating the biomass stoichiometry of environmental microorganisms. This includes the ability to partition microbial biomass into its constituent macromolecules and increase our understanding of how microorganisms in the environment respond to resource heterogeneity.     

Chemiosmotic energy conservation with Na(+) as the coupling ion during hydrogen-dependent caffeate reduction by Acetobacterium woodii

Cell suspensions of Acetobacterium woodii prepared from cultures grown on fructose plus caffeate catalyzed caffeate reduction with electrons derived from molecular hydrogen. Hydrogen-dependent caffeate reduction was strictly Na(+) dependent with a K(m) for Na(+) of 0.38 mM; Li(+) could substitute for Na(+). The sodium ionophore ETH2120, but not protonophores, stimulated hydrogen-dependent caffeate reduction by 280%, indicating that caffeate reduction is coupled to the buildup of a membrane potential generated by primary Na(+) extrusion. Caffeate reduction was coupled to the synthesis of ATP, and again, ATP synthesis coupled to hydrogen-dependent caffeate reduction was strictly Na(+) dependent and abolished by ETH2120, but not by protonophores, indicating the involvement of a transmembrane Na(+) gradient in ATP synthesis. The ATPase inhibitor N,N'-dicyclohexylcarbodiimide (DCCD) abolished ATP synthesis, and at the same time, hydrogen-dependent caffeate reduction was inhibited. This inhibition could be relieved by ETH2120. These experiments are fully compatible with a chemiosmotic mechanism of ATP synthesis with Na(+) as the coupling ion during hydrogen-dependent caffeate reduction by A. woodii.     

Computational approaches toward the design of pools for the in vitro selection of complex aptamers

It is well known that using random RNA/DNA sequences for SELEX experiments will generally yield low-complexity structures. Early experimental results suggest that having a structurally diverse library, which, for instance, includes high-order junctions, may prove useful in finding new functional motifs. Here, we develop two computational methods to generate sequences that exhibit higher structural complexity and can be used to increase the overall structural diversity of initial pools for in vitro selection experiments. Random Filtering selectively increases the number of five-way junctions in RNA/DNA pools, and Genetic Filtering designs RNA/DNA pools to a specified structure distribution, whether uniform or otherwise. We show that using our computationally designed DNA pool greatly improves access to highly complex sequence structures for SELEX experiments (without losing our ability to select for common one-way and two-way junction sequences).     

Three-dimensional structure of the large ribosomal subunit from Escherichia coli.

The three-dimensional structure of the large (50S) ribosomal subunit from Escherichia coli has been determined from electron micrographs of negatively stained specimens. A new method of three-dimensional reconstruction was used which combines many images of individual subunits recorded at a single high tilt angle. A prominent feature of the reconstruction is a large groove on the side of the subunit that interacts with the small ribosomal subunit. This feature is probably of functional significance as it includes the regions where the peptidyl transferase site and the binding locations of the elongation factors have been mapped previously by immunoelectron microscopy.     

Endothelial adhesion molecule ESAM binds directly to the multidomain adaptor MAGI-1 and recruits it to cell contacts

Endothelial cell-selective adhesion molecule (ESAM) is an immunoglobulin-like transmembrane protein associated with endothelial tight junctions (TJ). Based on a yeast two-hybrid screen, we have identified the membrane-associated guanylate kinase protein MAGI-1 as an intracellular binding partner of ESAM. MAGI-1 is a multidomain adaptor protein, which binds to transmembrane, cytoskeletal, and signaling molecules, and has been localized to tight junctions in epithelial cells. MAGI-1 associates with the very C-terminal sequence of ESAM most likely through a PDZ domain-mediated interaction. The direct interaction between ESAM and MAGI-1 was confirmed by pull-down experiments. The two proteins formed stable complexes in transfected Chinese hamster ovary (CHO) cells, which could be immunoisolated. We found MAGI-1 to be associated with cell-cell contacts in human umbilical vein endothelial cells (HUVECs) and in mouse endothelium, where it colocalizes with ESAM. In CHO cells, recruitment of MAGI-1 to cell contacts required the presence of ESAM. Hence, ESAM may be involved in anchoring MAGI-1 at endothelial tight junctions.     

Behavioral and Psychological Care in Weight Loss Surgery: Best Practice Update

The objective of this study is to update evidence‐based best practice guidelines for psychological evaluation and treatment of weight loss surgery (WLS) patients. We performed a systematic search of English‐language literature on WLS and mental health, quality of life, and behavior modification published between April 2004 and May 2007 in MEDLINE and the Cochrane Library. Key words were used to narrow the search for a selective review of abstracts, retrieval of full articles, and grading of evidence according to systems used in established evidence‐based models. Our literature search identified 17 articles of interest; 13 of the most relevant were reviewed in detail. From these, we developed evidence‐based best practice recommendations on the psychological assessment and treatment of WLS patients. Regular updates of evidence‐based recommendations for best practices in psychological care are required to address the impact of mental health on short‐ and long‐term outcomes after WLS. Key factors in patient safety include comprehensive preoperative evaluation, use of appropriate and reliable evaluation instruments, and the development of short‐ and long‐term treatment plans.     

Anterior segment mesenchymal dysgenesis: Probable linkage to the MNS blood group on chromosome 4

Thirty-seven blood samples were analyzed for linkage from members of a single family with an anterior segment mesenchymal dysgenesis (ASMD1) with variable expressivity affecting members of at least six generations. Maximum-likelihood analysis for linkage between ASMD1 and 14 biochemical and serological markers in the family showed a probable linkage between ASMD1 and the MNS blood group on the long arm of chromosome 4 (Z = 2.36 at a recombination fraction of .09).     

The multiple‐specificity landscape of modular peptide recognition domains

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.     

Single-molecule analysis of genome rearrangements in cancer

Rearrangements of the genome can be detected by microarray methods and massively parallel sequencing, which identify copy-number alterations and breakpoint junctions, but these techniques are poorly suited to reconstructing the long-range organization of rearranged chromosomes, for example, to distinguish between translocations and insertions. The single-DNA-molecule technique HAPPY mapping is a method for mapping normal genomes that should be able to analyse genome rearrangements, i.e. deviations from a known genome map, to assemble rearrangements into a long-range map. We applied HAPPY mapping to cancer cell lines to show that it could identify rearrangement of genomic segments, even in the presence of normal copies of the genome. We could distinguish a simple interstitial deletion from a copy-number loss at an inversion junction, and detect a known translocation. We could determine whether junctions detected by sequencing were on the same chromosome, by measuring their linkage to each other, and hence map the rearrangement. Finally, we mapped an uncharacterized reciprocal translocation in the T-47D breast cancer cell line to about 2 kb and hence cloned the translocation junctions. We conclude that HAPPY mapping is a versatile tool for determining the structure of rearrangements in the human genome.