Isomorphisms between pattern classes

Isomorphisms p between pattern classes A and B are considered. It is shown that, if p is not a symmetry of the entire set of permutations, then, to within symmetry, A is a subset of one a small set of pattern classes whose structure, including their enumeration, is determined.Comment: 11 page

Plastic response to pond drying in tadpoles Rana temporaria: tests of cost models

Tadpoles from two types of ponds, temporary and permanent, were raised in a common garden experiment. There was no clear effect of pond type on development rate (time for metamorphosis). From each sibship, one group was raised under a constant water regime (deep tanks) and one was subject to simulated pond drying (shallow tanks). The tadpoles exhibited a plastic response to pond drying: they metamorphosed earlier in the shallow than in the deep tanks. There was no interaction between pond type and tank type; that is, there was no indication of microevolution on plasticity per se. Sibships with a high degree of plasticity (much earlier metamorphosis in shallow than in deep tanks) had a larger size reduction from deep to shallow tanks, suggesting a trade-off between time and size. This may be considered an allocation cost sensu Tollrian and Harvell (1999). However, tadpoles from early sibships that were plastic were of a similar size to those from early sibships that were not plastic (those that were early in the deep tank as well). This suggests that there was no production cost sensu DeWitt et at (1998). Sibships with high plasticity had tadpoles that grew large in the deep tank and developed slowly (late metamorphosis) in this tank. This suggests that plastic tadpoles were those that, because of their size, most readily could afford any costs associated with plasticity and those that, because of slow development, most easily could increase development rate. The relation to size is the opposite to that predicted if the capacity for plasticity is associated with cost (plasticity cost sensu Tollrian and Harvell, 1999; maintenance cost sensu De Witt et al, 1998)

On the inverse image of pattern classes under bubble sort

Let B be the operation of re-ordering a sequence by one pass of bubble sort. We completely answer the question of when the inverse image of a principal pattern class under B is a pattern class.Comment: 11 page

16S rRNA gene sequencing of mock microbial populations- impact of DNA extraction method, primer choice and sequencing platform

peer-reviewedBackground Next-generation sequencing platforms have revolutionised our ability to investigate the microbiota composition of complex environments, frequently through 16S rRNA gene sequencing of the bacterial component of the community. Numerous factors, including DNA extraction method, primer sequences and sequencing platform employed, can affect the accuracy of the results achieved. The aim of this study was to determine the impact of these three factors on 16S rRNA gene sequencing results, using mock communities and mock community DNA. Results The use of different primer sequences (V4-V5, V1-V2 and V1-V2 degenerate primers) resulted in differences in the genera and species detected. The V4-V5 primers gave the most comparable results across platforms. The three Ion PGM primer sets detected more of the 20 mock community species than the equivalent MiSeq primer sets. Data generated from DNA extracted using the 2 extraction methods were very similar. Conclusions Microbiota compositional data differed depending on the primers and sequencing platform that were used. The results demonstrate the risks in comparing data generated using different sequencing approaches and highlight the merits of choosing a standardised approach for sequencing in situations where a comparison across multiple sequencing runs is required.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Numbers SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiome-determined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038)

Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

peer-reviewedRapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number ofmethodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance inmicrobiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced withMiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiome-determined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038)

Species classifier choice is a key consideration when analysing low-complexity food microbiome data

peer-reviewedBackground The use of shotgun metagenomics to analyse low-complexity microbial communities in foods has the potential to be of considerable fundamental and applied value. However, there is currently no consensus with respect to choice of species classification tool, platform, or sequencing depth. Here, we benchmarked the performances of three high-throughput short-read sequencing platforms, the Illumina MiSeq, NextSeq 500, and Ion Proton, for shotgun metagenomics of food microbiota. Briefly, we sequenced six kefir DNA samples and a mock community DNA sample, the latter constructed by evenly mixing genomic DNA from 13 food-related bacterial species. A variety of bioinformatic tools were used to analyse the data generated, and the effects of sequencing depth on these analyses were tested by randomly subsampling reads. Results Compositional analysis results were consistent between the platforms at divergent sequencing depths. However, we observed pronounced differences in the predictions from species classification tools. Indeed, PERMANOVA indicated that there was no significant differences between the compositional results generated by the different sequencers (p = 0.693, R2 = 0.011), but there was a significant difference between the results predicted by the species classifiers (p = 0.01, R2 = 0.127). The relative abundances predicted by the classifiers, apart from MetaPhlAn2, were apparently biased by reference genome sizes. Additionally, we observed varying false-positive rates among the classifiers. MetaPhlAn2 had the lowest false-positive rate, whereas SLIMM had the greatest false-positive rate. Strain-level analysis results were also similar across platforms. Each platform correctly identified the strains present in the mock community, but accuracy was improved slightly with greater sequencing depth. Notably, PanPhlAn detected the dominant strains in each kefir sample above 500,000 reads per sample. Again, the outputs from functional profiling analysis using SUPER-FOCUS were generally accordant between the platforms at different sequencing depths. Finally, and expectedly, metagenome assembly completeness was significantly lower on the MiSeq than either on the NextSeq (p = 0.03) or the Proton (p = 0.011), and it improved with increased sequencing depth. Conclusions Our results demonstrate a remarkable similarity in the results generated by the three sequencing platforms at different sequencing depths, and, in fact, the choice of bioinformatics methodology had a more evident impact on results than the choice of sequencer did.This research was funded by Science Foundation Ireland in the form of a centre grant (APC Microbiome Institute grant number SFI/12/RC/2273). Research in the Cotter laboratory is also funded by Science Foundation Ireland through the PI award “Obesibiotics” (11/PI/1137). Orla O’Sullivan is funded by Science Foundation Ireland through a Starting Investigator Research Grant award (13/SIRG/2160)

Microbial Succession and Flavor Production in the Fermented Dairy Beverage Kefir

peer-reviewedKefir is a putatively health-promoting dairy beverage that is produced when a kefir grain, consisting of a consortium of microorganisms, is added to milk to initiate a natural fermentation. Here, a detailed analysis was carried out to determine how the microbial population, gene content, and flavor of three kefirs from distinct geographic locations change over the course of 24-h fermentations. Metagenomic sequencing revealed that Lactobacillus kefiranofaciens was the dominant bacterial species in kefir during early stages of fermentations but that Leuconostoc mesenteroides became more prevalent in later stages. This pattern is consistent with an observation that genes involved in aromatic amino acid biosynthesis were absent from L. kefiranofaciens but were present in L. mesenteroides. Additionally, these shifts in the microbial community structure, and associated pathways, corresponded to changes in the levels of volatile compounds. Specifically, Acetobacter spp. correlated with acetic acid; Lactobacillus spp. correlated with carboxylic acids, esters and ketones; Leuconostoc spp. correlated with acetic acid and 2,3-butanedione; and Saccharomyces spp. correlated with esters. The correlation data suggest a causal relationship between microbial taxa and flavor that is supported by observations that addition of L. kefiranofaciens NCFB 2797 increased the levels of esters and ketones whereas addition of L. mesenteroides 213M0 increased the levels of acetic acid and 2,3-butanedione. Finally, we detected genes associated with probiotic functionalities in the kefir microbiome. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein and can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods. IMPORTANCE Traditional fermented foods represent relatively low-complexity microbial environments that can be used as model microbial communities to understand how microbes interact in natural environments. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein. In the process, the link between individual species, and associated pathways, with flavor compounds is revealed and several genes that could be responsible for the purported gut health-associated benefits of consuming kefir are identified. Ultimately, in addition to providing an important fundamental insight into microbial interactions, this information can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods

Thermoresponsive Pentablock Copolymer on Silica : Temperature Effects on Adsorption, Surface Forces, and Friction

The adsorption of hydrophilic or amphiphilic multiblock copolymers provides a powerful means to produce well-defined "smart" surfaces, especially if one or several blocks are sensitive to external stimuli. We focus here on an A-B-A-B-A copolymer, where A is a cationic poly((3acrylamido-propyl)-trimethylammonium chloride) (PAMPTMA) block containing 15 (end blocks) or 30 (middle block) repeat units and B is a neutral thermosensitive water-soluble poly(2-isopropyl-2-oxazoline) (PIPOZ) block with 50 repeat units. X-ray reflectivity and quartz crystal microbalance with dissipation monitoring were employed to study the adsorption of PAMPTMA(15)-PAMPTMA(30)-PIPOZ(50)-PAMPTMA(15) on silica surfaces. The latter technique was employed at different temperatures up to 50 degrees C. Surface forces and friction between the two silica surfaces across aqueous pentablock copolymer solutions at different temperatures were determined with the atomic force microscopy colloidal probe force and friction measurements. The cationic pentablock copolymer was found to have a high affinity to the negatively charged silica surface, leading to a thin (2 nm) and rigid adsorbed layer. A steric force was encountered at a separation of around 3 nm from hard wall contact. A capillary condensation of a polymer-rich phase was observed at the cloud point of the solution. The friction forces were evaluated using Amontons' rule modified with an adhesion term.Peer reviewe

Mechanical Properties of Organic Electronic Polymers on the Nanoscale

Funder: Belgian National Fund for Scientific Research; Id: http://dx.doi.org/10.13039/501100002661Abstract: Organic semiconducting polymers have attractive electronic, optical, and mechanical properties that make them materials of choice for large area flexible electronic devices. In these devices, the electronically active polymer components are micrometers in size, and sport negligible performance degradation upon bending the centimeter‐scale flexible substrate onto which they are integrated. A closer look at the mechanical properties of the polymers, on the grain‐scale and smaller, is not necessary in large area electronic applications. In emerging micromechanical and electromechanical applications where the organic polymer elements are flexed on length scales spanning their own micron‐sized active areas, it becomes important to characterize the uniformity of their mechanical properties on the nanoscale. In this work, the authors use two precision nanomechanical characterization techniques, namely, atomic force microscope based PeakForce quantitative nanomechanical mapping (PF‐QNM) and nanoindentation‐based dynamical mechanical analysis (nano‐DMA), to compare the modulus and the viscoelastic properties of organic polymers used routinely in organic electronics. They quantitatively demonstrate that the semiconducting near‐amorphous organic polymer indacenodithiophene‐co‐benzothiadiazole (C16‐IDTBT) has a higher carrier mobility, lower modulus, and greater nanoscale modulus areal uniformity compared to the semiconducting semicrystalline organic polymer poly[2,5‐bis(3‐tetradecylthiophen‐2‐yl)thieno[3,2‐b]thiophene] (C14‐PBTTT). Modulus homogeneity appears intrinsic to C16‐IDTBT but can be improved in C14‐PBTTT upon chemical doping

Ligand-Receptor Interactions

The formation and dissociation of specific noncovalent interactions between a variety of macromolecules play a crucial role in the function of biological systems. During the last few years, three main lines of research led to a dramatic improvement of our understanding of these important phenomena. First, combination of genetic engineering and X ray cristallography made available a simultaneous knowledg of the precise structure and affinity of series or related ligand-receptor systems differing by a few well-defined atoms. Second, improvement of computer power and simulation techniques allowed extended exploration of the interaction of realistic macromolecules. Third, simultaneous development of a variety of techniques based on atomic force microscopy, hydrodynamic flow, biomembrane probes, optical tweezers, magnetic fields or flexible transducers yielded direct experimental information of the behavior of single ligand receptor bonds. At the same time, investigation of well defined cellular models raised the interest of biologists to the kinetic and mechanical properties of cell membrane receptors. The aim of this review is to give a description of these advances that benefitted from a largely multidisciplinar approach