Supplementary material to "Uncovering chemical signatures of salinity gradients through compositional analysis of protein sequences"

2020 ◽  
Author(s):  
Jeffrey M. Dick ◽  
Miao Yu ◽  
Jingqiang Tan
Keyword(s):  
Compositional Analysis ◽  
Protein Sequences ◽  
Salinity Gradients ◽  
Chemical Signatures ◽  
Supplementary Material

scholarly journals Uncovering chemical signatures of salinity gradients through compositional analysis of protein sequences

2020 ◽  
Vol 17 (23) ◽  
pp. 6145-6162
Author(s):  
Jeffrey M. Dick ◽  
Miao Yu ◽  
Jingqiang Tan
Keyword(s):  
Environmental Conditions ◽  
Microbial Mats ◽  
Compositional Analysis ◽  
Protein Sequences ◽  
Hyperosmotic Stress ◽  
Chemical Compositions ◽  
Salinity Gradients ◽  
Gene And Protein Expression ◽  
The Baltic ◽  
The Impact

Abstract. Prediction of the direction of change of a system under specified environmental conditions is one reason for the widespread utility of thermodynamic models in geochemistry. However, thermodynamic influences on the chemical compositions of proteins in nature have remained enigmatic despite much work that demonstrates the impact of environmental conditions on amino acid frequencies. Here, we present evidence that the dehydrating effect of salinity is detectable as chemical differences in protein sequences inferred from (1) metagenomes and metatranscriptomes in regional salinity gradients and (2) differential gene and protein expression in microbial cells under hyperosmotic stress. The stoichiometric hydration state (nH2O), derived from the number of water molecules in theoretical reactions to form proteins from a particular set of basis species (glutamine, glutamic acid, cysteine, O2, H2O), decreases along salinity gradients, including the Baltic Sea and Amazon River and ocean plume, and decreases in particle-associated compared to free-living fractions. However, the proposed metric does not respond as expected for hypersaline environments. Analysis of data compiled for hyperosmotic stress experiments under controlled laboratory conditions shows that differentially expressed proteins are on average shifted toward lower nH2O. Notably, the dehydration effect is stronger for most organic solutes compared to NaCl. This new method of compositional analysis can be used to identify possible thermodynamic effects in the distribution of proteins along chemical gradients at a range of scales from microbial mats to oceans.

scholarly journals Uncovering chemical signatures of salinity gradients through compositional analysis of protein sequences

2020 ◽  
Author(s):  
Jeffrey M. Dick ◽  
Miao Yu ◽  
Jingqiang Tan
Keyword(s):  
Compositional Analysis ◽  
Protein Sequences ◽  
Hyperosmotic Stress ◽  
Differentially Expressed ◽  
Chemical Compositions ◽  
Chemical Gradients ◽  
Salinity Gradients ◽  
Gene And Protein Expression ◽  
The Baltic ◽  
The Impact

Abstract. Thermodynamic influences on the chemical compositions of proteins in nature have remained enigmatic despite much work that demonstrates the impact of environmental conditions on amino acid frequencies. Here, we present evidence that the dehydrating effect of salinity is detectable as chemical differences in protein sequences inferred from (1) metagenomes and metatranscriptomes in regional salinity gradients and (2) differential gene and protein expression in microbial cells under hyperosmotic stress. The stoichiometric hydration state (nH2O), derived from the number of water molecules in theoretical reactions to form proteins from a particular set of basis species (glutamine, glutamic acid, cysteine, O2, H2O), decreases along salinity gradients including the Baltic Sea and Amazon River and ocean plume and in particle-associated compared to free-living fractions. However, the proposed metric does not behave as expected for hypersaline environments. Analysis of data compiled for hyperosmotic stress experiments under controlled laboratory conditions shows that differentially expressed proteins, as well as proteins coded by differentially expressed transcripts, are on average shifted toward lower nH2O. Notably, the dehydration effect is stronger for most organic solutes compared to NaCl. This new method of compositional analysis can be used to identify possible thermodynamic effects in the distribution of proteins along chemical gradients at a range of scales from biofilms to oceans.

scholarly journals Glaciomarine sequence stratigraphy in the Mississippian Río Blanco Basin, Argentina, southwestern Gondwana. Basin analysis and palaeoclimatic implications for the Late Paleozoic Ice Age during the Tournaisian.

2020 ◽  
Vol 177 (6) ◽  
pp. 1107-1128 ◽  
Author(s):  
Miguel Ezpeleta ◽  
Juan José Rustán ◽  
Diego Balseiro ◽  
Federico Miguel Dávila ◽  
Juan Andrés Dahlquist ◽  
...  
Keyword(s):  
Compositional Analysis ◽  
Ice Age ◽  
Late Paleozoic ◽  
Provenance Analysis ◽  
Glacial Ice ◽  
Content Type ◽  
Late Paleozoic Ice Age ◽  
Glacial Stage ◽  
Supplementary Material ◽  
Age Constraints

The Late Paleozoic Ice Age (LPIA) has been well recorded in the uppermost Mississippian–Pennsylvanian of Gondwana. Nevertheless, little is known about the temporal and geographic dynamics, particularly during the early Mississippian. We report on exceptional Tournaisian glaciomarine stratigraphic sections from central Argentina (Río Blanco Basin). Encompassing c. 1400 m, these successions contain conspicuous glacigenic strata with age constraints provided by palaeontological data and U/Pb detrital zircon age spectra. A variety of marine, glaciomarine and fan-deltaic environments indicate relative sea-level variations mainly associated with tectonism and repetitive cycles of glacial activity. Provenance analysis indicates a source from the Sierras Pampeanas basement located to the east. Fifteen sequences were grouped into three depositional models: (1) Transgressive Systems Tracts (TST) to Highstand Systems Tracts (HST) sequences unaffected by glacial ice; (2) Lowstand Systems Tracts (LST) to TST and then to HST with glacial influence; and (3) non-glacial Falling-Stage Systems Tracts (FSST) to TST and HST. The glacial evidence indicates that the oldest Mississippian glacial stage of the LPIA in southwestern Gondwana is constrained to the middle Tournaisian. In contrast with previous descriptions of Gondwanan coeval glacial records, our sequence analysis confirms complex hierarchical climate variability, rather than a single episode of ice advance and retreat.Supplementary material: Detailed stratigraphic sections, palaeocurrents and compositional analysis and U/Pb detrital Zr methodology and data are available at: https://doi.org/10.6084/m9.figshare.c.5011424

scholarly journals COMPOSITIONAL ANALYSIS OF PROTEIN SEQUENCES OF DIFFERENT SPECIES

2010 ◽  
Vol 2 (2) ◽  
pp. 7-11
Author(s):  
Vinobha CS ◽  
◽  
Rajasekaran E ◽  
Rajadurai M
Keyword(s):  
Compositional Analysis ◽  
Protein Sequences

scholarly journals Supplementary material to "Organic Iron Complexes Enhance Iron Transport Capacity along Estuarine Salinity Gradients"

2019 ◽  
Author(s):  
Simon David Herzog ◽  
Kristina Kvashnina ◽  
Per Persson ◽  
Emma Kritzberg
Keyword(s):  
Iron Transport ◽  
Iron Complexes ◽  
Transport Capacity ◽  
Salinity Gradients ◽  
Supplementary Material ◽  
Estuarine Salinity

scholarly journals Supplementary material to "Ozonolysis of α-phellandrene – Part 2: Compositional analysis of secondary organic aerosol highlights the role of stabilised Criegee intermediates"

2017 ◽  
Author(s):  
Felix A. Mackenzie-Rae ◽  
Helen J. Wallis ◽  
Andrew R. Rickard ◽  
Kelly Pereira ◽  
Sandra M. Saunders ◽  
...  
Keyword(s):  
Secondary Organic Aerosol ◽  
Compositional Analysis ◽  
Organic Aerosol ◽  
Criegee Intermediates ◽  
Supplementary Material

scholarly journals Supplementary material to "Alternation of heterotrophic bacterial and archaeal production along nitrogen and salinity gradients in coastal wetlands"

2020 ◽  
Author(s):  
Gema L. Batanero ◽  
Andy J. Green ◽  
Juan A. Amat ◽  
Marion Vittecoq ◽  
Curtis A. Suttle ◽  
...  
Keyword(s):  
Coastal Wetlands ◽  
Salinity Gradients ◽  
Supplementary Material

scholarly journals HAMAP rules as SPARQL A portable annotation pipeline for genomes and proteomes

2019 ◽  
Author(s):  
Jerven Bolleman ◽  
Eduoard de Castro ◽  
Delphine Baratin ◽  
Sebastien Gehant ◽  
Beatrice A. Cuche ◽  
...  
Keyword(s):  
Data Quality ◽  
Protein Sequences ◽  
Cost Effective ◽  
Supplementary Information ◽  
Biological Knowledge ◽  
Supplementary Data ◽  
Annotation Pipeline ◽  
Link Type ◽  
Supplementary Material

AbstractMotivationGenome and proteome annotation pipelines are generally custom built and therefore not easily reusable by other groups, which leads to duplication of effort, increased costs, and suboptimal results. One cost-effective way to increase the data quality in public databases is to encourage the adoption of annotation standards and technological solutions that enable the sharing of biological knowledge and tools for genome and proteome annotation.ResultsWe have translated the rules of our HAMAP proteome annotation pipeline to queries in the W3C standard SPARQL 1.1 syntax and applied them with two off-the-shelf SPARQL engines to UniProtKB/Swiss-Prot protein sequences described in RDF format. This approach is applicable to any genome or proteome annotation pipeline and greatly simplifies their reuse.AvailabilityHAMAP SPARQL rules and documentation are freely available for download from the HAMAP FTP site ftp://ftp.expasy.org/databases/hamap/hamapsparql.tar.gz under a CC-BY-ND 4.0 license. The annotations generated by the rules are under the CC-BY 4.0 [email protected] informationSupplementary data are included at the end of this document.

Compositional Analysis of III-V Interface Lattice Images

1980 ◽  
Vol 38 ◽  
pp. 318-319
Author(s):  
A. Olsen ◽  
J.C.H. Spence ◽  
P. Petroff
Keyword(s):  
Crystal Structure ◽  
Image Matching ◽  
Compositional Analysis ◽  
Depth Of Field ◽  
Limit Set ◽  
High Contrast ◽  
Resolution Limit ◽  
Fourier Image ◽  
Lattice Images ◽  
True Structure

Since the point resolution of the JEOL 200CX electron microscope is up = 2.6Å it is not possible to obtain a true structure image of any of the III-V or elemental semiconductors with this machine. Since the information resolution limit set by electronic instability (1) u0 = (2/πλΔ)½ = 1.4Å for Δ = 50Å, it is however possible to obtain, by choice of focus and thickness, clear lattice images both resembling (see figure 2(b)), and not resembling, the true crystal structure (see (2) for an example of a Fourier image which is structurally incorrect). The crucial difficulty in using the information between Up and u0 is the fractional accuracy with which Af and Cs must be determined, and these accuracies Δff/4Δf = (2λu2Δf)-1 and ΔCS/CS = (λ3u4Cs)-1 (for a π/4 phase change, Δff the Fourier image period) are strongly dependent on spatial frequency u. Note that ΔCs(up)/Cs ≈ 10%, independent of CS and λ. Note also that the number n of identical high contrast spurious Fourier images within the depth of field Δz = (αu)-1 (α beam divergence) decreases with increasing high voltage, since n = 2Δz/Δff = θ/α = λu/α (θ the scattering angle). Thus image matching becomes easier in semiconductors at higher voltage because there are fewer high contrast identical images in any focal series.

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