Bioinformatics comparison of sulfate-reducing metabolism nucleotide sequences

The sulfate-reducing bacteria can be traced back to 3.5 billion years ago. The thermodynamics details of the sulfur cycle have been well documented. A recent sulfate-reducing bacteria report (Robator, Jungbluth, et al , 2015 Jan, Front. Microbiol) with Genbank nucleotide data has been analyzed in terms of the sulfite reductase (dsrAB) via fractal dimension and entropy values. Comparison to oil field sulfate-reducing sequences was included. The AUCG translational mass fractal dimension versus ATCG transcriptional mass fractal dimension for the low temperature dsrB and dsrA sequences reported in Reference Thirteen shows correlation R-sq ~ 0.79 , with a probably of about 3% in simulation. A recent report of using Cystathionine gamma-lyase sequence to produce CdS quantum dot in a biological method, where the sulfur is reduced just like in the H2S production process, was included for comparison. The AUCG mass fractal dimension versus ATCG mass fractal dimension for the Cystathionine gamma-lyase sequences was found to have R-sq of 0.72, similar to the low temperature dissimilatory sulfite reductase dsr group with 3% probability, in contrary to the oil field group having R-sq ~ 0.94, a high probable outcome in the simulation. The other two simulation histograms, namely, fractal dimension versus entropy R-sq outcome values, and di-nucleotide entropy versus mono-nucleotide entropy R-sq outcome values are also discussed in the data analysis focusing on low probability outcomes.

[1]  Michael Wagner,et al.  Phylogeny of Dissimilatory Sulfite Reductases Supports an Early Origin of Sulfate Respiration , 1998, Journal of bacteriology.

[2]  Anagha Joshi,et al.  Post‐transcriptional regulatory networks play a key role in noise reduction that is conserved from micro‐organisms to mammals , 2012, The FEBS journal.

[3]  Chang-Yong Lee.  Mass fractal dimension of the ribosome and implication of its dynamic characteristics. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Peter H von Hippel.  Increased subtlety of transcription factor binding increases complexity of genome regulation , 2014, Proceedings of the National Academy of Sciences.

[5]  Eugene I Shakhnovich,et al.  Multi-scale sequence correlations increase proteome structural disorder and promiscuity. , 2010, Journal of molecular biology.

[6]  Muhammad Nawaz Tahir,et al.  Molybdenum trioxide nanoparticles with intrinsic sulfite oxidase activity. , 2014, ACS nano.

[7]  L. Barton,et al.  Suitability of fluorescence measurements to quantify sulfate-reducing bacteria. , 2013, Journal of microbiological methods.

[8]  Charles S. Cockell,et al.  An Estimate of the Total DNA in the Biosphere , 2015, PLoS biology.

[9]  Pau Carrió,et al.  Fractal dimension as a measure of surface roughness of G protein-coupled receptors: implications for structure and function , 2012, Journal of Molecular Modeling.

[10]  Linda L. Blackall,et al.  Multiple Lateral Transfers of Dissimilatory Sulfite Reductase Genes between Major Lineages of Sulfate-Reducing Prokaryotes , 2001, Journal of bacteriology.

[11]  Leen Bastiaens,et al.  Synergistic effects of sulfate reducing bacteria and zero valent iron on zinc removal and stability in aquifer sediment , 2015 .

[12]  Sean P. Jungbluth,et al.  Activity and phylogenetic diversity of sulfate-reducing microorganisms in low-temperature subsurface fluids within the upper oceanic crust , 2015, Front. Microbiol..

[13]  Joshua Krissansen-Totton,et al.  Transient Sulfate Aerosols as a Signature of Exoplanet Volcanism. , 2015, Astrobiology.

[14]  Christopher J. Kiely,et al.  Biomanufacturing of CdS quantum dots , 2015 .

[15]  M Michael Gromiha,et al.  Hydrophobic environment is a key factor for the stability of thermophilic proteins , 2013, Proteins.

[16]  M. Schatz,et al.  Big Data: Astronomical or Genomical? , 2015, PLoS biology.

[17]  Leen Bastiaens,et al.  Inhibition of sulfate reducing bacteria in aquifer sediment by iron nanoparticles. , 2014, Water research.

[18]  Ji-Dong Gu,et al.  Diversity and distribution of sulfate-reducing bacteria in four petroleum reservoirs detected by using 16S rRNA and dsrAB genes , 2013 .

[19]  T. Higuchi.  Approach to an irregular time series on the basis of the fractal theory , 1988 .

[20]  D. Haussler,et al.  An RNA gene expressed during cortical development evolved rapidly in humans , 2006, Nature.

[21]  J. Kuever,et al.  Phylogeny of the alpha and beta subunits of the dissimilatory adenosine-5'-phosphosulfate (APS) reductase from sulfate-reducing prokaryotes--origin and evolution of the dissimilatory sulfate-reduction pathway. , 2007, Microbiology.

[22]  Anirban Banerji,et al.  Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding , 2013, Journal of molecular recognition : JMR.

[23]  M. Martins,et al.  Sulfate-reducing bacteria as new microorganisms for biological hydrogen production , 2013 .

[24]  Michael Wagner,et al.  Diversity of Sulfate-Reducing Bacteria in Oxic and Anoxic Regions of a Microbial Mat Characterized by Comparative Analysis of Dissimilatory Sulfite Reductase Genes , 1999, Applied and Environmental Microbiology.

[25]  Sarath Chandra Janga,et al.  Interplay between posttranscriptional and posttranslational interactions of RNA-binding proteins. , 2011, Journal of molecular biology.

[26]  Brian C. Thomas,et al.  Unusual biology across a group comprising more than 15% of domain Bacteria , 2015, Nature.

[27]  Raluca Gordân,et al.  Protein−DNA binding in the absence of specific base-pair recognition , 2014, Proceedings of the National Academy of Sciences.

[28]  Eugene I Shakhnovich,et al.  Sequence correlations shape protein promiscuity. , 2011, The Journal of chemical physics.

[29]  M. Friedrich.  Phylogenetic Analysis Reveals Multiple Lateral Transfers of Adenosine-5′-Phosphosulfate Reductase Genes among Sulfate-Reducing Microorganisms , 2002, Journal of bacteriology.

[30]  H. Eugene Stanley,et al.  Application of fractal concepts to polymer statistics and to anomalous transport in randomly porous media , 1984 .

[31]  D. B. Lukatsky,et al.  DNA sequence correlations shape nonspecific transcription factor-DNA binding affinity. , 2011, Biophysical journal.