scholarly journals Resource conservation manifests in the genetic code

2019 ◽  
Author(s):  
Liat Shenhav ◽  
David Zeevi
Keyword(s):  
Genetic Code ◽  
Nutrient Limitation ◽  
Nitrogen Availability ◽  
Resource Conservation ◽  
Marine Microbes ◽  
Coding Sequences ◽  
Carbon And Nitrogen ◽  
Nutrient Conservation ◽  
Cell Data ◽  
Competition For Resources

AbstractNutrient limitation is a strong selective force, driving competition for resources. However, much is unknown about how selective pressures resulting from nutrient limitation shape microbial coding sequences. Here, we study this ‘resource-driven’ selection using metagenomic and single-cell data of marine microbes, alongside environmental measurements. We show that a significant portion of the selection exerted on microbes is explained by the environment and is strongly associated with nitrogen availability. We further demonstrate that this resource conservation optimization is encoded in the structure of the standard genetic code, providing robustness against mutations that increase carbon and nitrogen incorporation into protein sequences. Overall, we demonstrate that nutrient conservation exerts a significant selective pressure on coding sequences and may have even contributed to the evolution of the genetic code.

scholarly journals Resource conservation manifests in the genetic code

Science ◽  
2020 ◽  
Vol 370 (6517) ◽  
pp. 683-687
Author(s):  
Liat Shenhav ◽  
David Zeevi
Keyword(s):  
Genetic Code ◽  
Nutrient Limitation ◽  
Nitrogen Availability ◽  
Resource Conservation ◽  
Marine Microbes ◽  
Carbon And Nitrogen ◽  
Selective Pressures ◽  
Domains Of Life ◽  
Cell Data ◽  
Competition For Resources

Nutrient limitation drives competition for resources across organisms. However, much is unknown about how selective pressures resulting from nutrient limitation shape microbial coding sequences. Here, we study this “resource-driven selection” by using metagenomic and single-cell data of marine microbes, alongside environmental measurements. We show that a significant portion of the selection exerted on microbes is explained by the environment and is associated with nitrogen availability. Notably, this resource conservation optimization is encoded in the structure of the standard genetic code, providing robustness against mutations that increase carbon and nitrogen incorporation into protein sequences. This robustness generalizes to codon choices from multiple taxa across all domains of life, including the human genome.

RUNS OF AMINO ACIDS ARE LONGER THAN EXPECTED IN PROTEINS BASED ON A GRAPH THEORY REPRESENTATION OF THE GENETIC CODE

2002 ◽  
Vol 10 (04) ◽  
pp. 319-335
Author(s):  
DAVID DIGBY ◽  
WILLIAM SEFFENS ◽  
FISSEHA ABEBE
Keyword(s):  
Amino Acids ◽  
Graph Theory ◽  
Genetic Code ◽  
Protein Sequences ◽  
Test Statistic ◽  
Coding Sequences ◽  
Reverse Complement ◽  
In Silico Study ◽  
Z Scores ◽  
The Difference

An in silico study of mRNA secondary structure has found a bias within the coding sequences of genes that favors "in-frame" pairing of nucleotides. This pairing of codons, each with its reverse-complement, partitions the 20 amino acids into three subsets. The genetic code can therefore be represented by a three-component graph. The composition of proteins in terms of amino acid membership in the three subgroups has been measured, and sequence runs of members within the same subgroup have been analyzed using a runs statistic based on Z-scores. In a GENBANK database of over 416,000 protein sequences, the distribution of this runs-test statistic is negatively skewed. To assess whether this statistical bias was due to a chance grouping of the amino acids in the real genetic code, several alternate partitions of the genetic code were examined by permuting the assignment of amino acids to groups. A metric was constructed to define the difference, or "distance", between any two such partitions, and an exhaustive search was conducted among alternate partitions maximally distant from the natural partition of the genetic code, to select sets of partitions that were also maximally distant from one another. The statistical skewness of the runs statistic distribution for native protein sequences were significantly more negative under the natural partition than they were under all of the maximally different partition of codons, although for all partitions, including the natural one, the randomized sequences had quite similar skewness. Hence under the natural graph theory partition of the genetic code there is a preference for more protein sequences to contain fewer runs of amino acids, than they do under the other partitions, meaning that the average run must be longer under the natural partition. This suggests that a corresponding bias may exist in the coding sequences of the actual genes that code for these proteins.

SOME HINTS ON OPEN READING FRAME STATISTICS — HOW ORF LENGTH DEPENDS ON SELECTION

1999 ◽  
Vol 10 (04) ◽  
pp. 635-643 ◽  
Author(s):  
AGNIESZKA GIERLIK ◽  
PAWEŁ MACKIEWICZ ◽  
MARIA KOWALCZUK ◽  
STANISŁAW CEBRAT ◽  
MIROSŁAW R. DUDEK
Keyword(s):  
Genetic Code ◽  
Dna Sequences ◽  
Nucleotide Composition ◽  
Open Reading Frames ◽  
Open Reading Frame ◽  
Antisense Strand ◽  
Coding Sequences ◽  
Reading Frame ◽  
Intergenic Sequences ◽  
Reading Frames

Coding sequences of DNA generate Open Reading Frames (ORFs) inside them with much higher frequency than random DNA sequences do, especially in the antisense strand. This is a specific feature of the genetic code. Since coding sequences are selected for their length, the generated ORFs are indirect results of this selection and their length is also influenced by selection. That is why ORFs found in any genome, even much longer ones than those spontaneously generated in random DNA sequences, should be considered as two different sets of ORFs: The first one coding for proteins, the second one generated by the coding ORFs. Even intergenic sequences possess greater capacity for generating ORFs than random DNA sequences of the same nucleotide composition, which seems to be a premise that intergenic sequences were generated from coding sequences by recombinational mechanisms.

scholarly journals Improved Eco-Friendly RecombinantAnabaenasp. Strain PCC7120 with Enhanced Nitrogen Biofertilizer Potential

2010 ◽  
Vol 77 (2) ◽  
pp. 395-399 ◽  
Author(s):  
Akhilesh Kumar Chaurasia ◽  
Shree Kumar Apte
Keyword(s):  
Recombinant Strain ◽  
Nitrogen Availability ◽  
Nitrogenase Activity ◽  
Inducible Promoter ◽  
Paddy Fields ◽  
Environmental Application ◽  
Carbon And Nitrogen ◽  
Enhanced Expression ◽  
Photosynthesis And Respiration ◽  
Nitrogen Demand

ABSTRACTPhotosynthetic, nitrogen-fixingAnabaenastrains are native to tropical paddy fields and contribute to the carbon and nitrogen economy of such soils. Genetic engineering was employed to improve the nitrogen biofertilizer potential ofAnabaenasp. strain PCC7120. Constitutive enhanced expression of an additional integrated copy of thehetRgene from a light-inducible promoter elevated HetR protein expression and enhanced functional heterocyst frequency in the recombinant strain. The recombinant strain displayed consistently higher nitrogenase activity than the wild-type strain and appeared to be in homeostasis with compatible modulation of photosynthesis and respiration. The enhanced combined nitrogen availability from the recombinant strain positively catered to the nitrogen demand of rice seedlings in short-term hydroponic experiments and supported better growth. The engineered strain is stable, eco-friendly, and useful for environmental application as nitrogen biofertilizer in paddy fields.

Water table and species identity outweigh carbon and nitrogen availability in a softwater plant community

2013 ◽  
Vol 47 ◽  
pp. 57-67 ◽  
Author(s):  
Floris Vanderhaeghe ◽  
Alfons J.P. Smolders ◽  
Jan G.M. Roelofs ◽  
Maurice Hoffmann
Keyword(s):  
Plant Community ◽  
Water Table ◽  
Nitrogen Availability ◽  
Species Identity ◽  
Carbon And Nitrogen ◽  
Carbon And Nitrogen Availability

scholarly journals The genetic code is not optimized for resource conservation

2021 ◽  
Author(s):  
Haiqing Xu ◽  
Jianzhi Zhang
Keyword(s):  
Genetic Code ◽  
Recent Article ◽  
Resource Conservation ◽  
Universal Genetic Code ◽  
Genetic Codes

AbstractShenhav and Zeevi conclude in a recent article (Science 370:683-687) that the universal genetic code (UGC) is optimized for resource conservation because mutations are less likely to increase proteomic nitrogen and carbon uses under the UGC than under random genetic codes (RGCs). Their finding results from miscalculating mutational effects and benchmarking against biased RGCs. Our reanalysis refutes their conclusion.

Disentangling the long-term foliar 15N signal using a land surface model

2020 ◽  
Author(s):  
Silvia Caldararu ◽  
Tea Thum ◽  
Richard Nair ◽  
Sönke Zaehle
Keyword(s):  
Nutrient Limitation ◽  
Land Surface ◽  
Nitrogen Availability ◽  
Land Surface Model ◽  
Ecosystem Dynamics ◽  
Surface Model ◽  
Terrestrial Vegetation ◽  
Climate System Model ◽  
Foliar N

<p>Terrestrial vegetation growth is hypothesised to increase under elevated atmospheric CO<sub>2</sub>, a process known as the CO<sub>2</sub> fertilisation effect. However, the magnitude of this effect and its long-term sustainability remains uncertain. One of the main limitations to the CO2  fertilisation effect is nutrient limitation to plant growth, in particular nitrogen (N) in temperate and boreal ecosystems. Recent studies have suggested that decreases in observed foliar N content (N%) and δ<sup>15</sup>N indicate widespread nitrogen limitation with increasing CO<sub>2</sub>  concentrations. However, the factors driving these two variables, and especially the foliar δ<sup>15</sup>N values, are complex and can be caused by a number of processes. On one hand, if the observed trends reflect nutrient limitation, this limitation can be caused by either CO<sub>2</sub> or warming driven growth. On the other hand, it is possible that nutrient limitation does not occur to its full extent due to plant plastic responses to alleviate nutrient limitation, causing a decrease in N%, but changes in the anthropogenic N deposition 15N signal cause the observed δ<sup>15</sup>N trend. In reality, it is likely that all these factors contribute to the observed trends. To understand ecosystem dynamics it is important to disentangle the processes behind these signals which is very difficult based on observational datasets only.</p><p>We use a novel land surface model to explore the causes behind the observed trends in foliar N% and δ<sup>15</sup>N. The QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) model  has the unique capacity to track ecologically relevant isotopic composition, including <sup>15</sup>N in plant and soil pools. The model also includes a realistic representation of plant plastic acclimation processes, specifically a representation of nitrogen allocation to and inside the canopy in response to nitrogen availability, so implicitly to changes in CO<sub>2 </sub> concentrations. We test the different hypotheses above behind the observed changes in N% and δ<sup>15</sup>N separately and quantify the contribution of each of the factors towards the observed trend. We then test the different hypotheses against existing observations of N% and δ<sup>15</sup>N from the ICP Forests database and other published datasets such as the global dataset of Craine et al. 2018.</p><p>Our study showcases the use of an isotope-enabled land surface model in conjunction with long-term observations to strengthen our understanding of the ecosystem processes behind the observed trends.</p>

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