Using First Passage Statistics to Extract Environmentally Dependent Amino Acid Correlations

In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background di...

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Vydáno v:	PloS one Ročník 9; číslo 7; s. e101665
Hlavní autoři:	Greenbaum, Benjamin D., Kumar, Pradeep, Libchaber, Albert
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 07.07.2014 Public Library of Science (PLoS)
Témata:	Amino Acids Arginine Biology Biology and Life Sciences Chemical bonds Computational Biology - methods Correlation Correlation analysis Cysteine Ecosystem Environment Environmental statistics Genomes Genomics Glutamic acid High temperature High temperature environments Markov analysis Natural selection Organisms Phylogeny Physical Sciences Physics Physiochemistry Probability Proteins Residues Sequences Statistics Studies Temperature Temperature dependence Thermal stability New York United States > US New Jersey
ISSN:	1932-6203, 1932-6203
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Abstract	In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background distribution for an organism, and infer lengths at which the first passage has a probability that differs from what is expected. While many features of an organism's genome are due to natural selection, others are related to amino acid chemistry and the environment in which an organism lives, constraining the randomness of genomes upon which selection can further act. We therefore use this approach to infer amino acid correlations, and then study how these correlations vary across a wide range of organisms under a wide range of optimal growth temperatures. We find a nearly universal exponential background distribution, consistent with the idea that most amino acids are globally uncorrelated from other amino acids in genomes. When we are able to extract significant correlations, these correlations are reliably dependent on optimal growth temperature, across phylogenetic boundaries. Some of the correlations we extract, such as the enhanced probability of finding, for the first time, a cysteine three residues away from a cysteine or glutamic acid two residues away from an arginine, likely relate to thermal stability. However, other correlations, likely appearing on alpha helical surfaces, have a less clear physiochemical interpretation and may relate to thermal stability or unusual metabolic properties of organisms that live in a high temperature environment.
AbstractList	In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background distribution for an organism, and infer lengths at which the first passage has a probability that differs from what is expected. While many features of an organism's genome are due to natural selection, others are related to amino acid chemistry and the environment in which an organism lives, constraining the randomness of genomes upon which selection can further act. We therefore use this approach to infer amino acid correlations, and then study how these correlations vary across a wide range of organisms under a wide range of optimal growth temperatures. We find a nearly universal exponential background distribution, consistent with the idea that most amino acids are globally uncorrelated from other amino acids in genomes. When we are able to extract significant correlations, these correlations are reliably dependent on optimal growth temperature, across phylogenetic boundaries. Some of the correlations we extract, such as the enhanced probability of finding, for the first time, a cysteine three residues away from a cysteine or glutamic acid two residues away from an arginine, likely relate to thermal stability. However, other correlations, likely appearing on alpha helical surfaces, have a less clear physiochemical interpretation and may relate to thermal stability or unusual metabolic properties of organisms that live in a high temperature environment. In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background distribution for an organism, and infer lengths at which the first passage has a probability that differs from what is expected. While many features of an organism's genome are due to natural selection, others are related to amino acid chemistry and the environment in which an organism lives, constraining the randomness of genomes upon which selection can further act. We therefore use this approach to infer amino acid correlations, and then study how these correlations vary across a wide range of organisms under a wide range of optimal growth temperatures. We find a nearly universal exponential background distribution, consistent with the idea that most amino acids are globally uncorrelated from other amino acids in genomes. When we are able to extract significant correlations, these correlations are reliably dependent on optimal growth temperature, across phylogenetic boundaries. Some of the correlations we extract, such as the enhanced probability of finding, for the first time, a cysteine three residues away from a cysteine or glutamic acid two residues away from an arginine, likely relate to thermal stability. However, other correlations, likely appearing on alpha helical surfaces, have a less clear physiochemical interpretation and may relate to thermal stability or unusual metabolic properties of organisms that live in a high temperature environment.In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background distribution for an organism, and infer lengths at which the first passage has a probability that differs from what is expected. While many features of an organism's genome are due to natural selection, others are related to amino acid chemistry and the environment in which an organism lives, constraining the randomness of genomes upon which selection can further act. We therefore use this approach to infer amino acid correlations, and then study how these correlations vary across a wide range of organisms under a wide range of optimal growth temperatures. We find a nearly universal exponential background distribution, consistent with the idea that most amino acids are globally uncorrelated from other amino acids in genomes. When we are able to extract significant correlations, these correlations are reliably dependent on optimal growth temperature, across phylogenetic boundaries. Some of the correlations we extract, such as the enhanced probability of finding, for the first time, a cysteine three residues away from a cysteine or glutamic acid two residues away from an arginine, likely relate to thermal stability. However, other correlations, likely appearing on alpha helical surfaces, have a less clear physiochemical interpretation and may relate to thermal stability or unusual metabolic properties of organisms that live in a high temperature environment.
Audience	Academic
Author	Greenbaum, Benjamin D. Libchaber, Albert Kumar, Pradeep
AuthorAffiliation	4 Department of Physics, University of Arkansas at Little Rock, Little Rock, Arkansas, United States of America 3 Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, United States of America Rosalind Franklin University, United States of America 2 The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America 1 Departments of Medicine, Division of Hematology and Medical Oncology, and Pathology, and the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
AuthorAffiliation_xml	– name: 1 Departments of Medicine, Division of Hematology and Medical Oncology, and Pathology, and the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America – name: 2 The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America – name: 4 Department of Physics, University of Arkansas at Little Rock, Little Rock, Arkansas, United States of America – name: 3 Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, United States of America – name: Rosalind Franklin University, United States of America
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CitedBy_id	crossref_primary_10_3390_microorganisms10020274 crossref_primary_10_1016_j_jtbi_2016_08_011
Cites_doi	10.1016/j.bpj.2013.06.029 10.1016/S0378-1119(03)00660-7 10.1007/s00792-007-0076-z 10.1098/rspb.2005.3441 10.1016/S1074-5521(02)00156-4 10.1111/j.1742-4658.2006.05421.x 10.1186/gb-2002-3-8-preprint0006 10.1146/annurev.biophys.37.032807.125811 10.1007/978-1-4612-6200-8 10.1002/prot.20386 10.1016/S0168-9525(02)02691-4 10.1007/978-4-431-53898-1 10.1093/nar/gks1048 10.1007/s00726-007-0589-x 10.1016/S0065-2164(09)01202-7 10.1371/journal.pone.0028766 10.1016/0304-4149(82)90016-3 10.1371/journal.pone.0021624 10.1007/BFb0068322 10.1016/j.febslet.2006.02.013 10.1002/jmr.657 10.1371/journal.pcbi.0030005 10.1021/bi025523t 10.1093/protein/13.3.179 10.1089/ars.2009.2510 10.1146/annurev.genet.32.1.163 10.1016/j.cell.2009.07.038 10.1073/pnas.89.4.1358 10.1074/jbc.R111.275578 10.1093/nar/gkj134 10.1038/nrmicro1892
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DocumentTitleAlternate	Using First Passage Statistics to Extract Amino Acid Correlations
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: BG AL. Performed the experiments: BG. Analyzed the data: BG AL PK. Wrote the paper: BG PK AL.
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SubjectTerms	Amino Acids Arginine Biology Biology and Life Sciences Chemical bonds Computational Biology - methods Correlation Correlation analysis Cysteine Ecosystem Environment Environmental statistics Genomes Genomics Glutamic acid High temperature High temperature environments Markov analysis Natural selection Organisms Phylogeny Physical Sciences Physics Physiochemistry Probability Proteins Residues Sequences Statistics Studies Temperature Temperature dependence Thermal stability
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Title	Using First Passage Statistics to Extract Environmentally Dependent Amino Acid Correlations
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