417 research outputs found

    Xanthusbase: adapting wikipedia principles to a model organism database

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    xanthusBase () is the official model organism database (MOD) for the social bacterium Myxococcus xanthus. In many respects, M.xanthus represents the pioneer model organism (MO) for studying the genetic, biochemical, and mechanistic basis of prokaryotic multicellularity, a topic that has garnered considerable attention due to the significance of biofilms in both basic and applied microbiology research. To facilitate its utility, the design of xanthusBase incorporates open-source software, leveraging the cumulative experience made available through the Generic Model Organism Database (GMOD) project, MediaWiki (), and dictyBase (), to create a MOD that is both highly useful and easily navigable. In addition, we have incorporated a unique Wikipedia-style curation model which exploits the internet's inherent interactivity, thus enabling M.xanthus and other myxobacterial researchers to contribute directly toward the ongoing genome annotation

    Unitary designs and codes

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    A unitary design is a collection of unitary matrices that approximate the entire unitary group, much like a spherical design approximates the entire unit sphere. In this paper, we use irreducible representations of the unitary group to find a general lower bound on the size of a unitary t-design in U(d), for any d and t. We also introduce the notion of a unitary code - a subset of U(d) in which the trace inner product of any pair of matrices is restricted to only a small number of distinct values - and give an upper bound for the size of a code of degree s in U(d) for any d and s. These bounds can be strengthened when the particular inner product values that occur in the code or design are known. Finally, we describe some constructions of designs: we give an upper bound on the size of the smallest weighted unitary t-design in U(d), and we catalogue some t-designs that arise from finite groups.Comment: 25 pages, no figure

    Mechanobiology as a tool for addressing the genotype-to- phenotype problem in microbiology

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    The central hypothesis of the genotype–phenotype relationship is that the phenotype of a developing organism (i.e., its set of observable attributes) depends on its genome and the environment. However, as we learn more about the genetics and biochemistry of living systems, our understanding does not fully extend to the complex multiscale nature of how cells move, interact, and organize; this gap in understanding is referred to as the genotype-to-phenotype problem. The physics of soft matter sets the background on which living organisms evolved, and the cell environment is a strong determinant of cell phenotype. This inevitably leads to challenges as the full function of many genes, and the diversity of cellular behaviors cannot be assessed without wide screens of environmental conditions. Cellular mechanobiology is an emerging field that provides methodologies to understand how cells integrate chemical and physical environmental stress and signals, and how they are transduced to control cell function. Biofilm forming bacteria represent an attractive model because they are fast growing, genetically malleable and can display sophisticated self-organizing developmental behaviors similar to those found in higher organisms. Here, we propose mechanobiology as a new area of study in prokaryotic systems and describe its potential for unveiling new links between an organism\u27s genome and phenome

    Spreading rates of bacterial colonies depend on substrate stiffness and permeability

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    The ability of bacteria to colonize and grow on different surfaces is an essential process for biofilm development. Here, we report the use of synthetic hydrogels with tunable stiffness and porosity to assess physical effects of the substrate on biofilm development. Using time-lapse microscopy to track the growth of expanding Serratia marcescens colonies, we find that biofilm colony growth can increase with increasing substrate stiffness, unlike what is found on traditional agar substrates. Using traction force microscopy-based techniques, we find that biofilms exert transient stresses correlated over length scales much larger than a single bacterium, and that the magnitude of these forces also increases with increasing substrate stiffness. Our results are consistent with a model of biofilm development in which the interplay between osmotic pressure arising from the biofilm and the poroelastic response of the underlying substrate controls biofilm growth and morphology

    Ataluren stimulates ribosomal selection of near-cognate tRNAs to promote nonsense suppression

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    A premature termination codon (PTC) in the ORF of an mRNA generally leads to production of a truncated polypeptide, accelerated degradation of the mRNA, and depression of overall mRNA expression. Accordingly, nonsense mutations cause some of the most severe forms of inherited disorders. The small-molecule drug ataluren promotes therapeutic nonsense suppression and has been thought to mediate the insertion of near-cognate tRNAs at PTCs. However, direct evidence for this activity has been lacking. Here, we expressed multiple nonsense mutation reporters in human cells and yeast and identified the amino acids inserted when a PTC occupies the ribosomal A site in control, ataluren-treated, and aminoglycoside-treated cells. We find that ataluren\u27s likely target is the ribosome and that it produces full-length protein by promoting insertion of near-cognate tRNAs at the site of the nonsense codon without apparent effects on transcription, mRNA processing, mRNA stability, or protein stability. The resulting readthrough proteins retain function and contain amino acid replacements similar to those derived from endogenous readthrough, namely Gln, Lys, or Tyr at UAA or UAG PTCs and Trp, Arg, or Cys at UGA PTCs. These insertion biases arise primarily from mRNA:tRNA mispairing at codon positions 1 and 3 and reflect, in part, the preferred use of certain nonstandard base pairs, e.g., U-G. Ataluren\u27s retention of similar specificity of near-cognate tRNA insertion as occurs endogenously has important implications for its general use in therapeutic nonsense suppression

    Spatially Resolved Stellar Populations of 0.3<z<6.00.3<z<6.0 Galaxies in WHL0137-08 and MACS0647+70 Clusters as Revealed by JWST: How do Galaxies Grow and Quench Over Cosmic Time?

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    We study the spatially resolved stellar populations of 444 galaxies at 0.3<z<6.00.3<z<6.0 in two clusters (WHL0137-08 and MACS0647+70) and a blank field, combining imaging data from HST and JWST to perform spatially resolved spectral energy distribution (SED) modeling using pixedfit. The high spatial resolution of the imaging data combined with magnification from gravitational lensing in the cluster fields allows us to resolve some galaxies to sub-kpc scales (for 109 of our galaxies). At redshifts around cosmic noon and higher (2.5≲z≲6.02.5\lesssim z\lesssim 6.0), we find mass doubling times to be independent of radius, inferred from flat specific star formation rate (sSFR) radial profiles and similarities between the half-mass and half-SFR radii. At lower redshifts (1.5≲z≲2.51.5\lesssim z\lesssim 2.5), a significant fraction of our star-forming galaxies show evidence for nuclear starbursts, inferred from centrally elevated sSFR, and a much smaller half-SFR radius compared to the half-mass radius. At later epochs, we find more galaxies suppress star formation in their center but are still actively forming stars in the disk. Overall, these trends point toward a picture of inside-out galaxy growth consistent with theoretical models and simulations. We also observe a tight relationship between the central mass surface density and global stellar mass with ∼0.38\sim 0.38 dex scatter. Our analysis demonstrates the potential of spatially resolved SED analysis with JWST data. Future analysis with larger samples will be able to further explore the assembly of galaxy mass and the growth of their structuresComment: 31 pages, 18 figures, accepted for publication in ApJ. Some examples and tutorials of spatially resolved SED analysis will be available at https://github.com/aabdurrouf/JWST-HST_resolvedSEDfit
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