Amino acid sequence repertoire of the bacterial proteome and the occurrence of untranslatable sequences.
Ontology highlight
ABSTRACT:
SUBMITTER: Navon SP
PROVIDER: S-EPMC4932979 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDue to the ever-expanding gap between the number of proteins being discovered and their functional characterization, protein function inference remains a fundamental challenge in computational biology. Currently, known protein annotations are organized in human-curated ontologies, however, all possible protein functions may not be organized accurately. Meanwhile, recent advancements in natural language processing and machine learning have developed models which embed amino acid sequences as vectors in n-dimensional space. So far, these embeddings have primarily been used to classify protein sequences using manually constructed protein classification schemes.ResultsIn this work, we describe the use of amino acid sequence embeddings as a systematic framework for studying protein ontologies. Using a sequence embedding, we show that the bacterial carbohydrate metabolism class within the SEED annotation system contains 48 clusters of embedded sequences despite this class containing 29 functional labels. Furthermore, by embedding Bacillus amino acid sequences with unknown functions, we show that these unknown sequences form clusters that are likely to have similar biological roles.ConclusionsThis study demonstrates that amino acid sequence embeddings may be a powerful tool for developing more robust ontologies for annotating protein sequence data. In addition, embeddings may be beneficial for clustering protein sequences with unknown functions and selecting optimal candidate proteins to characterize experimentally.
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Project description:We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate--slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory.
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Project description:BackgroundThe evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins.ResultsWe introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form approximately p-gamma with the value of the exponent gamma around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent alpha approximately 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate.ConclusionWe separately measure the short-term ("raw") duplication and deletion rates , which include gene copies that will be removed soon after the duplication event and their dramatically reduced long-term counterparts r(*)dup, r(*)del. High deletion rate among recently duplicated proteins is consistent with a scenario in which they didn't have enough time to significantly change their functional roles and thus are to a large degree disposable. Systematic trends of each of the four duplication/deletion rates with the total number of genes in the genome were analyzed. All but the deletion rate of recent duplicates r(*)del were shown to systematically increase with Ngenes. Abnormally flat shapes of sequence identity histograms observed for yeast and human are consistent with lineages leading to these organisms undergoing one or more whole-genome duplications. This interpretation is corroborated by our analysis of the genome of Paramecium tetraurelia where the p-4 profile of the histogram is gradually restored by the successive removal of paralogs generated in its four known whole-genome duplication events.
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Project description:What kinds of amino acid sequences could possibly be protein sequences? From all existing databases that we can find, known proteins are only a small fraction of all possible combinations of amino acids. Beginning with Sanger's first detailed determination of a protein sequence in 1952, previous studies have focused on describing the structure of existing protein sequences in order to construct the protein universe. No one, however, has developed a criteria for determining whether an arbitrary amino acid sequence can be a protein. Here we show that when the collection of arbitrary amino acid sequences is viewed in an appropriate geometric context, the protein sequences cluster together. This leads to a new computational test, described here, that has proved to be remarkably accurate at determining whether an arbitrary amino acid sequence can be a protein. Even more, if the results of this test indicate that the sequence can be a protein, and it is indeed a protein sequence, then its identity as a protein sequence is uniquely defined. We anticipate our computational test will be useful for those who are attempting to complete the job of discovering all proteins, or constructing the protein universe.
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Project description:We have identified four repeats and ten domains that are novel in proteins encoded by the Bacillus anthracis str. Ames proteome using automated in silico methods. A "repeat" corresponds to a region comprising less than 55-amino-acid residues that occur more than once in the protein sequence and sometimes present in tandem. A "domain" corresponds to a conserved region with greater than 55-amino-acid residues and may be present as single or multiple copies in the protein sequence. These correspond to (1) 57-amino-acid-residue PxV domain, (2) 122-amino-acid-residue FxF domain, (3) 111-amino-acid-residue YEFF domain, (4) 109-amino-acid-residue IMxxH domain, (5) 103-amino-acid-residue VxxT domain, (6) 84-amino-acid-residue ExW domain, (7) 104-amino-acid-residue NTGFIG domain, (8) 36-amino-acid-residue NxGK repeat, (9) 95-amino-acid-residue VYV domain, (10) 75-amino-acid-residue KEWE domain, (11) 59-amino-acid-residue AFL domain, (12) 53-amino-acid-residue RIDVK repeat, (13) (a) 41-amino-acid-residue AGQF repeat and (b) 42-amino-acid-residue GSAL repeat. A repeat or domain type is characterized by specific conserved sequence motifs. We discuss the presence of these repeats and domains in proteins from other genomes and their probable secondary structure.
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