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Sobolevsky Y, Guimarães RC, Trifonov EN. Towards functional repertoire of the earliest proteins. J Biomol Struct Dyn 2012; 31:1293-300. [PMID: 23140233 DOI: 10.1080/07391102.2012.735623] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The conserved protein sequence motifs present in all prokaryotic proteomes, "omnipresent motifs," presumably, correspond to the earliest proteins of the Last Universal Cellular Ancestor, from which all the proteomes have descended. Fifteen proteomes, each representing one of the total 15 diverse phyla of 131 Eubacteria and Archea, from which the omnipresent elements have been originally derived, are exhaustively screened. All those proteins which harbor the omnipresent motifs are identified. Six "omnipresent" protein types are revealed which are located in all 15 proteomes: ABC cassettes, FtsH proteases, translation initiation factors, translation elongation factors, isoleucyl-tRNA synthases, and RNA polymerases β'. In addition to the omnipresent motifs, these proteins also contain other highly conserved motifs, standing for additional modules of the proteins. Remarkably, the identified tentative earliest proteins are responsible for only three basic functions: supply of monomers (ABC transporters and proteases), protein synthesis (initiation and elongation factors, aminoacyl-tRNA synthases), and RNA synthesis (polymerases). No enzymes involved in metabolic activities are present in the list of the earliest proteins derived by this approach. Some of the omnipresent sequence motifs are found, indeed, in the metabolic enzymes (e.g. NTP binding motifs), but these enzymes do not make a sequence matching collection of 15 sequences, i.e. they are not omnipresent. Future analysis of less conserved sequence motifs may reveal at what degree of conservation (stage of evolution) the metabolic enzymes could have entered the scene.
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Affiliation(s)
- Y Sobolevsky
- a Faculdade de Gama , Universidade de Brasilia , Gama , 72405-610 , Brazil
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3
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Vashisht R, Mondal AK, Jain A, Shah A, Vishnoi P, Priyadarshini P, Bhattacharyya K, Rohira H, Bhat AG, Passi A, Mukherjee K, Choudhary KS, Kumar V, Arora A, Munusamy P, Subramanian A, Venkatachalam A, S G, Raj S, Chitra V, Verma K, Zaheer S, J B, Gurusamy M, Razeeth M, Raja I, Thandapani M, Mevada V, Soni R, Rana S, Ramanna GM, Raghavan S, Subramanya SN, Kholia T, Patel R, Bhavnani V, Chiranjeevi L, Sengupta S, Singh PK, Atray N, Gandhi S, Avasthi TS, Nisthar S, Anurag M, Sharma P, Hasija Y, Dash D, Sharma A, Scaria V, Thomas Z, Chandra N, Brahmachari SK, Bhardwaj A. Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis. PLoS One 2012; 7:e39808. [PMID: 22808064 PMCID: PMC3395720 DOI: 10.1371/journal.pone.0039808] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Accepted: 05/30/2012] [Indexed: 11/18/2022] Open
Abstract
A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.
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Affiliation(s)
- Rohit Vashisht
- Council of Scientific and Industrial Research (CSIR), Delhi, India
- Department of Biochemistry, Indian Institute of Science, Bangalore, Karnataka, India
| | | | - Akanksha Jain
- Council of Scientific and Industrial Research (CSIR), Delhi, India
| | - Anup Shah
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | - Priti Vishnoi
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | | | | | - Harsha Rohira
- Acharya Narendra Dev College, University of Delhi, India
| | - Ashwini G. Bhat
- Department of Biochemistry, Indian Institute of Science, Bangalore, Karnataka, India
| | - Anurag Passi
- Council of Scientific and Industrial Research (CSIR), Delhi, India
| | - Keya Mukherjee
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | | | | | - Anshula Arora
- Acharya Narendra Dev College, University of Delhi, India
| | | | | | | | | | - Sweety Raj
- Acharya Narendra Dev College, University of Delhi, India
| | - Vijaya Chitra
- Sree Narayan Guru College, Coimbatore, Tamil Nadu, India
| | - Kaveri Verma
- Maharshi Dayanand University, Rohtak, Haryana, India
| | - Salman Zaheer
- Amity Institute of Biotechnology, Amity University, Lucknow, Uttar Pradesh, India
| | - Balaganesh J
- Bharathiar University, Coimbatore, Tamil Nadu, India
| | | | - Mohammed Razeeth
- Bharathidasan University, Palkalaiperur, Tiruchirappall, Tamil Nadu, India
| | - Ilamathi Raja
- Bharathidasan University, Palkalaiperur, Tiruchirappall, Tamil Nadu, India
| | | | - Vishal Mevada
- Bitvirtual patan Node, Hem. North Gujarat University, Patan, Gujarat, India
| | - Raviraj Soni
- Bitvirtual patan Node, Hem. North Gujarat University, Patan, Gujarat, India
| | - Shruti Rana
- Bitvirtual patan Node, Hem. North Gujarat University, Patan, Gujarat, India
| | | | - Swetha Raghavan
- Business Intelligence Technologies India Pvt Ltd., Bangalore, Karnataka, India
| | - Sunil N. Subramanya
- Business Intelligence Technologies India Pvt Ltd., Bangalore, Karnataka, India
| | - Trupti Kholia
- Christ College, Vidya Niketan, Saurashtra University, Rajkot, Gujarat, India
| | - Rajesh Patel
- Department of Life Sciences, Hemchandracharya North Gujarat University, Patan, Gujarat, India
| | - Varsha Bhavnani
- Department of Biotechnology, University of Pune, Maharashtra State, India
| | | | - Soumi Sengupta
- Indian Statistical Institute, Kolkata, West Bengal, India
| | - Pankaj Kumar Singh
- Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India
| | - Naresh Atray
- Shri Ram College of Pharmacy, Karnal, Haryana, India
| | - Swati Gandhi
- The Maharaj Sayajirao University of Baroda, Gujarat, India
| | - Tiruvayipati Suma Avasthi
- Pathogen Biology Laboratory, Department of Biotechnology, School of Life Sciences, University of Hyderabad, Hyderabad, Andhra Pradesh, India
- Faculty of Science, Institute of Biological Sciences, University of Malaya, Kuala Lumpur, Malaysia
| | | | - Meenakshi Anurag
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | | | - Yasha Hasija
- Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Delhi, India
| | - Debasis Dash
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | - Arun Sharma
- Bioinformatics Centre, Institute of Microbial Technology, CSIR, Chandigarh, India
| | - Vinod Scaria
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
| | - Zakir Thomas
- Council of Scientific and Industrial Research (CSIR), Delhi, India
| | - OSDD Consortium
- Council of Scientific and Industrial Research (CSIR), Delhi, India
| | - Nagasuma Chandra
- Department of Biochemistry, Indian Institute of Science, Bangalore, Karnataka, India
- * E-mail: (SKB); (NC); (AB)
| | - Samir K. Brahmachari
- Council of Scientific and Industrial Research (CSIR), Delhi, India
- Institute of Genomics and Integrative Biology, CSIR, Delhi, India
- * E-mail: (SKB); (NC); (AB)
| | - Anshu Bhardwaj
- Council of Scientific and Industrial Research (CSIR), Delhi, India
- * E-mail: (SKB); (NC); (AB)
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Goto N, Kurokawa K, Yasunaga T. Analysis of invariant sequences in 266 complete genomes. Gene 2007; 401:172-80. [PMID: 17728079 DOI: 10.1016/j.gene.2007.07.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2006] [Revised: 07/13/2007] [Accepted: 07/16/2007] [Indexed: 11/29/2022]
Abstract
To date, the complete genome sequences of more than 250 organisms have been determined. This information can now be used to determine whether there exist any invariant sequences that are conserved among all organisms, from bacteria to plants, animals, and humans. The existence of invariant sequences would strongly suggest that these sequences have been inherited unchanged from the last common ancestor of all life, and that they have essential functions. We have developed a new software program to identify invariant sequences conserved among the currently sequenced genomes and applied this analysis to the complete genome sequences of 266 organisms. We have identified 3 invariant DNA sequences longer than or equal to 11 bp and 6 invariant amino acid sequences longer than or equal to 6 aa. The longest invariant DNA sequence, AAGTCGTACAAGGT (15 bp), was found in the 16S/18S rRNA gene. Two 8 aa sequences, GHVDHGKT in IF2 and EF-Tu and DTPGHVDF in EF-G, were the longest invariant amino acid sequences detected. These sequences could be essential elements from the genome of the last common ancestor and may have remained unchanged throughout evolution.
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MESH Headings
- Amino Acid Sequence/genetics
- Animals
- Archaeal Proteins/chemistry
- Archaeal Proteins/genetics
- Bacterial Proteins/chemistry
- Bacterial Proteins/genetics
- Base Sequence/genetics
- Conserved Sequence/genetics
- Fungal Proteins/chemistry
- Fungal Proteins/genetics
- Genome
- Genome, Archaeal
- Genome, Bacterial
- Genome, Fungal
- Genome, Human
- Genome, Plant
- Humans
- Protein Biosynthesis/genetics
- Protein Processing, Post-Translational/genetics
- RNA, Ribosomal, 16S/chemistry
- RNA, Ribosomal, 16S/genetics
- RNA, Ribosomal, 18S/chemistry
- RNA, Ribosomal, 18S/genetics
- RNA, Ribosomal, 23S/chemistry
- RNA, Ribosomal, 23S/genetics
- Sequence Analysis, DNA
- Sequence Analysis, Protein
- Software
- Transcription, Genetic
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Affiliation(s)
- Naohisa Goto
- Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
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Guerrero G, Peralta H, Aguilar A, Díaz R, Villalobos MA, Medrano-Soto A, Mora J. Evolutionary, structural and functional relationships revealed by comparative analysis of syntenic genes in Rhizobiales. BMC Evol Biol 2005; 5:55. [PMID: 16229745 PMCID: PMC1276791 DOI: 10.1186/1471-2148-5-55] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2005] [Accepted: 10/17/2005] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Comparative genomics has provided valuable insights into the nature of gene sequence variation and chromosomal organization of closely related bacterial species. However, questions about the biological significance of gene order conservation, or synteny, remain open. Moreover, few comprehensive studies have been reported for rhizobial genomes. RESULTS We analyzed the genomic sequences of four fast growing Rhizobiales (Sinorhizobium meliloti, Agrobacterium tumefaciens, Mesorhizobium loti and Brucella melitensis). We made a comprehensive gene classification to define chromosomal orthologs, genes with homologs in other replicons such as plasmids, and those which were species-specific. About two thousand genes were predicted to be orthologs in each chromosome and about 80% of these were syntenic. A striking gene colinearity was found in pairs of organisms and a large fraction of the microsyntenic regions and operons were similar. Syntenic products showed higher identity levels than non-syntenic ones, suggesting a resistance to sequence variation due to functional constraints; also, an unusually high fraction of syntenic products contained membranal segments. Syntenic genes encode a high proportion of essential cell functions, presented a high level of functional relationships and a very low horizontal gene transfer rate. The sequence variability of the proteins can be considered the species signature in response to specific niche adaptation. Comparatively, an analysis with genomes of Enterobacteriales showed a different gene organization but gave similar results in the synteny conservation, essential role of syntenic genes and higher functional linkage among the genes of the microsyntenic regions. CONCLUSION Syntenic bacterial genes represent a commonly evolved group. They not only reveal the core chromosomal segments present in the last common ancestor and determine the metabolic characteristics shared by these microorganisms, but also show resistance to sequence variation and rearrangement, possibly due to their essential character. In Rhizobiales and Enterobacteriales, syntenic genes encode a high proportion of essential cell functions and presented a high level of functional relationships.
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Affiliation(s)
- Gabriela Guerrero
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Humberto Peralta
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Alejandro Aguilar
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Rafael Díaz
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Miguel Angel Villalobos
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Arturo Medrano-Soto
- Program of Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
| | - Jaime Mora
- Program of Functional Genomics of Prokaryotes, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México. Ave. Universidad s/n (P.O. Box 565-A), Cuernavaca, Morelos, 62210, México
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