FUNCTIONAL GENOMICS OF MYCOBACTERIUM TUBERCULOSIS

FUNCTIONAL GENOMICS OF MYCOBACTERIUM TUBERCULOSIS

Anitha Jabamalai Raj ¹, Sangilimuthu Algar Yadav ², Velliyur Kanniappan Gopalakrishnan ³, Akila Selvaraj ⁴ and Sudarsanam Dorairaj*⁵

Research and Development Centre, Bharathiar University ¹, Coimbatore- 641 046, Tamilnadu, India

Department of Biotechnology, Karpagam University ², Coimbatore- 641021, Tamilnadu, India

Department of Bioinformatics, Karpagam University ^{1, 3, 4}, Coimbatore- 641021, Tamilnadu, India

Department of Advanced Zoology, Biotechnology and Bioinformatics Unit, Loyola College ⁵, Chennai- 600034, Tamil Nadu, India

ABSTRACT

Mycobacterium tuberculosis is a deadly infectious disease, there is rising death of humans every year because of this disease, availability of genome sequences of Mycobacterium tuberculosis has provided tremendous amount of  information that can be useful in drug target and new vaccine development. Sequence similarity provides accurate annotation for genes in newly sequenced genomes. In this present work about 107 hypothetical proteins of Mycobacetrium tuberculosis were taken and its functions were predicted using bioinformatics tools BLAST, BLOCKS, COGs, InterProScan and PFP. From our analysis of 107 hypothetical proteins only two shows 100% functions these proteins may serve as target for few antibiotics

Drug target

INTRODUCTION: The proteomics of Mycobacterium tuberculosis was intensively studied to expand our knowledge base and identify proteins or enzymes that would serve as targets for few antibiotics, many number of proteins present without any function. Tuberculosis is a common and often deadly infectious disease caused by mycobacteria, mainly Mycobacterium tuberculosis ¹.

Mycobacterium tuberculosis is reputed to have the highest annual global mortality among all of the pathogens. The rise in tuberculosis incidence over the last two decades is partly due to tuberculosis deaths in HIV-infected patients and partly due to the emergence of multidrug resistant strains of the bacteria ². This rapid increase in the disease has led to potential finding arrangements aimed at a large effort towards stopping this disease before it becomes a global epidemic. Due to its slow growth and high virulence it is extremely difficult to work with the tuberculosis bacterium. However, rapidly evolving Mycobacterium genomics with complete genome sequences known along with powerful bioinformatics approaches. The proteomics of Mycobacterium tuberculosis will be intensively studied to expand our knowledge base and identify proteins or enzymes that would serve as targets for few antibiotics ³; Mycobacterium tuberculosis has totally 4189 number of proteins.

In these proteins 2038 hypothetical proteins were present out of the 107 hypothetical proteins were taken for this work and its functions was predicted using bioinformatics tools such as BLAST, BLOCKS, COGs ⁴, InterProScan ⁵ and PROTEIN FUNCTION PREDICTION (PFP) ⁶.

The main aim of this present work was to predict the function of selected hypothetical proteins.

MATERIALS AND METHODS: The complete genome for Mycobacterium tuberculosis was sequenced at the Institute of Genome Research (TIGR) and complete genome sequence of Mycobacterium tuberculosis was downloaded from ExPASY ⁷ databases and NCBI database ⁸. In the genome sequence of Mycobacterium tuberculosis 2038 hypothetical proteins were present. Out of that only 107 hypothetical proteins of genome sequence was downloaded from the site ⁹ the function for these hypothetical proteins were predicted using bioinformatics tools such as BLAST ¹⁰ (11), BLOCKS ¹¹, COGs ¹², InterProScan ¹³ and PROTEIN FUNCTION PREDICTION (PFP) ¹⁴ . The confidence level can be measured on the basis of above tools.

1. 100% confidence level was given to those proteins that indicate same functions in all the given five tools.
2. 80% confidence level was given to those proteins that indicate same functions in any of the given four tools other are different.
3. 60% confidence level was given to those proteins that indicate same functions in any of the given three tools other two given different functions.
4. 40% confidence level was given to those proteins that indicate same functions in any of the give two tools other three given different functions.
5. 20% confidence level was given to those proteins that indicates some function in any of the given tools
6. Moreover 0% confidence level was given to those proteins that indicate unknown functions in all the given tools.

RESULTS AND DISCUSSION: Mycobacterium tuberculosis has totally 4189 proteins. In this 2038 proteins are hypothetical proteins from which 107 hypothetical proteins of Mycobacterium tuberculosis were retrieved for this work from NCBI Database hypothetical proteins were submitted to bioinformatics tools BLAST, InterProScan, BLOCKS, PFP and COGs. The results of different tools were analyzed and the functions observed in each output were noted down and tabulated against the sequence ID.

Table 1 (Functions of Hypothetical Protein) shows functional genomics of Mycobacterium tuberculosis using Bioinformatics tools. Protein function can be predicted from sequence, including posttranslational modifications, subcellular localization, and physical/chemical properties ¹⁵. Function prediction of genomic sequences for hypothetical proteins of Mycobacterium tuberculosis will help in the identification of new drug targets.

TABLE 1: FUNCTIONAL GENOMICS OF MYCOBACTERIUM TUBERCULOSIS  

The results obtained was 100% confidence level for 2 proteins, with 80% confidence level for 4 proteins and some hypothetical proteins has not been predicted with much confidence level (i.e., Confidence level 60.0%; 40.0%; 20.0% and unknown function).  All 107 hypothetical proteins were tabulated against their functions; only two proteins [GENE ID: 15839950 & 15839958] shows 100% results in future these two proteins are taken for modeling which may servers as target for drug designing.

Thus, by this functional genomics approach, the functions of hypothetical proteins of Mycobacterium tuberculosis were delineated and their target is identified which paved a way for curing this dreadful disease through docking approach.

CONCLUSION: The function of hypothetical proteins of Mycobacterium tuberculosis is predicted using Bioinformatics tools BLAST, BLOCKS, COGs, InterProScan, PROTFUN and PFP (Table 2).

TABLE 2: PERCENTAGE OF SIMILARITY

Among 107 hypothetical proteins, only two proteins show 100% confidence level in all the mentioned tools. Three proteins were found to have the same function in any of the four tools. Seven Proteins were found to have the same function in any of the three tools. Thirteen Proteins were found to have the same function in any of the two tools. Seventy eight Proteins were found to have the some function in any of the tools. Three Proteins were found to have no functions. Two proteins those obtained same function such as METHYL TRANSFERASE and HYDROLASE’S. Further these two proteins may serves as target for few antibiotics, which helps in curing this dreadful disease.

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