Microarray long oligo probe designing for Bacteria: An in silico pan-genomic research

Home / Microarray long oligo probe designing for Bacteria: An in silico pan-genomic research

Suggested citation: Behzadi P, Ranjbar R. Microarray long oligo probe designing for Bacteria: An in silico pan-genomic research. Alban Med J 2016;2:5-11.

Microarray long oligo probe designing for Bacteria: An in silico pan-genomic research

Payam Behzadi1, Reza Ranjbar1

1 Molecular Biology Research Center, Baqiyatallah University of Medical Sciences,
Tehran, Iran.

Corresponding author: Dr. Reza Ranjbar
Address: Shahid Nosrati alley, Sheikh Bahaee Avenue, Molla Sadra Street, Vanak Square, Tehran, Iran;
Telephone: +982188039883; E-mail: ranjbarre@gmail.com

Abstract
Aim: Increasing the accuracy, reproducibility and flexibility of the output is the main goal for clinical and microbiological diagnostic techniques to control the progression of infection outbreaks and epidemiology. DNA microarray technology provides these goals via professional probe designing. In this research article we have shown the basis of microarray long oligo probe designing for detection and identification of different types of bacteria.
Methods: In this in silico investigation, a diversity of free online and offline softwares, databases, and tools were applied. Among a huge number of bioinformatics facilities, the authors have used AlleleID 7.7, BLAST/NCBI, GView Server, OligoAnalyzer 3.1, PanSeq Server.
Results: In this research project, the comparative pan-genomic methodology visualized an obvious and clear illustration regarding to the quality of microarray probes. By the help of
in silico methodology, we were able to predict the quality of the designed probes. Two types of microarray long oligo probes with ‘Good/Best’ quality were designed and produced.
Conclusion: The use of effective bioinformatics facilities directly affects on the accuracy, flexibility, reliability, rapidity and reproducibility of microarray diagnosis. Best probes guarantee the unbiased and high quality outcomes.

Keywords: bacteria, bioinformatics, in silico, long oligo probe, microarray.

Introduction
There are several molecular biology tools and techniques like Polymerase Chain Reaction (PCR) which are used as a proper and routine clinical and microbiological diagnostic tool. In parallel with PCR application, the advanced, rapid and accurate tool of microarray technology is applied for 2 decades. However, microarray technology has been performed in research centers rather than clinical centers. Among different types of microarray technologies, the DNA microarray technology is a whole genomic analytical method which is able to detect, identify and quantify 1 ng of DNA molecules. Interestingly, the DNA microarray technology has the capability of detection and identification of several thousands of microbial genera, species and strains at once (1-7).
In parallel with progression of next generation sequencing (NGS) methods like DNA microarray technologies in recent decade, the cost of advanced NGS techniques and diagnostics has significantly decreased. These types of diagnostic methods involve comparative genomic and pan-genomic characteristics of microorganisms like bacteria. The accuracy of whole genomic methodologies is guaranteed; because there are some specific genomic sequences (up to 40%) which are completely different to a specific bacterial species/strain (6,8,9).
As the bacterial pathogens may cause deathful and dangerous diseases and infections in contaminated people, an accurate, rapid and cost-effective diagnostic tool is needed. DNA microarray technology is an appropriate candidate for detection and identification of bacterial pathogens. DNA microarray technique is consisted of several different steps comprising microarray chip spotting, microarray probe designing, bacterial DNA labelling, hybridization, and microarray scanning. However, the last step may be replaced by fluorescence microscope, when the only goal is to detect and identify a particular bacterial agent (2,5,10-14).
According to previous studies, the type of platform and the kind of probe set used in microarray technologies determine the level of probable biases in final outcomes (2,4,15).
For this reason the aim of this in silico research article is to show how a microarray long oligo probe can be designed for detection and identification of pathogenic bacteria.

Methods
To design one or more microarray long oligo probes there is a vital need for pan-genomic similarities among the main bacterial strain and its close related bacteria. For example, among Enterobacteriaceae members there is a close relationship between Escherichia coli and Salmonella enterica/Shigella spp.. So, these bacteria must be checked by comparative genomic methodology (16-19).
There are some processes which must be performed one by one to produce the best outcome in association with microarray long oligo probes. By the help of National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/), the genomic information relating to the bacterial strains were extracted. This database encompasses a wide range of choices (1,2,10). The computational method for probe designing was achieved through the following steps:

Genomic data collection
The NCBI FTP Site was selected (ftp://ftp.ncbi.nlm.nih.gov/). This site offers several services. The Genomes folder involves a huge mass of data (ftp://ftp.ncbi.nlm.nih.gov/genomes/Bacteria/). This service has been modified (12/21/15, 5:16:00 PM) and some links and addresses have been changed (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/bacteria/). Prior to the latest modification in NCBI, the main bacterial strain .gbk file (the main bacterial strain is the strain that from its genome sequence the microarray long oligo probes were designed and produced) and for close related bacterial strains, the .fna files were downloaded. All these files were zipped and used for the next step. The whole genome sequences are available throughout other websites including Sanger Institute (http://www.sanger.ac.uk/resources/downloads/bacteria/), National Institute of Allergy and Infectious Diseases (NAID) Genomic Centers for Infectious Diseases (GCID) (http://www.niaid.nih.gov/labsandresources/resources/dmid/gsc/Pages/default.aspx) and the Ilumina (http://www.illumina.com/) (4,10,20,21).

Pan-genomic comparative analysis
Pan-genomics shows a 95% nucleotide sequence similarity between close strains pertaining to the same bacterial species. Despite this close similarity, there is a huge variability within genomic pools of close bacterial strains (22-25).
Because of the vast genomic diversity, there is an appropriate methodology to illustrate and visualize the similarities and dissimilarities within the gene content of several close bacterial strains. This online tool is available via GView Server (https://server.gview.ca/). GView is a free Java application which visualize the prokaryotic (Archaeal and Bacterial) genome maps in both forms of circular and linear. This bioinformatics application provides a complete, accurate and clear image to show the genome map, gene content, similarities and dissimilarities found between compared bacterial genomes (21,26-28).
For applying GView Server services, the user has to register for this free tool. After the registration is completed, the user can use GView Server.
To compare several genomes by GView Server, the unique genome option was selected as the analysis type. The main bacterial strain sequence data file (.gbk file) as the reference genome was uploaded. The GenBank ans EMBL file formats are permitted to upload for the main bacterial sequence (21,27).
At the end, the email address is needed to push the continue button and upload the .gbk file. In the next page the .fna files (more than 1 with FASTA format) belonging to close related bacterial strains were uploaded. There are some default parameters comprising value cutoff, genetic code, alignment length cutoff and percentage identity cutoff which must be regulated in accordance with the related aim (21,27).
In addition to GReview Server as a powerful pan-genome visualizer tool which is used for different purposes such as comparative pan-genomic analysis, there is the online tool of PanSeq Server which is a free access and rapid pan-genome sequence analysis program (https://lfz.corefacility.ca/panseq/) (29). However, there are other pan-genome sequence analyzer including mGenomeSubtractor (http://202.120.12.134/mGS2/) (30) and nWayComp (31). The PanSeq is capable to extract the unique regions in a genome or compared genomes. The outcomes resulted from PanSeq are easy to use. The Novel Region Finder (NRF) modulates the input sequences. The main bacterial strain (main pan-genome sequences) must be selected from Query Strain and added to selected Query. The other bacterial pan-genome sequences were selected from Reference Strains and added to Selected Reference. All the input sequences were chosen from complete genome choices. There are various default parameters which can be modulated in accordance with the final purpose. In the process of multiple sequence comparison by NRF module, the output of sequence analysis is provided as a file in FASTA format (21,29).

Pan-genomic alignment algorithm
The unique sequences resulted from PanSeq analysis were downloaded into FASTA format and blasted by BLAST search service/NCBI (http://blast.ncbi.nlm.nih.gov/Blast.cgi). The more repetitive sequences within the output unique sequences, the longer takes time to compute the matched sequences (21,29,32-34).

Probe designing software
The conserved sequences in a bacterial genome are proper genomic regions for designing microarray probes. Furthermore, an ideal conserved sequence using for microarray probe lacks mutation, and possesses a suitable biological melting temperature. These strain/species specific conserved sequences were detected precisely. Thus, an appropriate software like AlleleID is needed for designing and producing effective and flexible microarray long oligo probes. The selected conserved and unique sequences was added into Microarray tab/New sequence page in ALLELEID software. Then the sequence was analyzed by analyze/Probe Search options. The probe search page includes several default options such as design probes of length (in bp). For designing a long oligo probe, the 55-64 bp was selected. other defaults were selected relating to the research goal. The search button on probe search page produces and designs microarray long oligo probes (2,32,35,36).

Probe alignment algorithm
The designed and produced probes were tested again. This process was done by BLAST/NCBI. The BLAST aligns the sequence of designed probes (2,34,35).

Probe physico-chemical characteristics
The rechecked designed microarray probes were studied by the important online tool of OligoAnalyzer (https://eu.idtdna.com/calc/analyzer). OligoAnalizer is a proper physico-chemical calculator which predicts a wide range of probe characteristics such as target type (DNA/RNA), concentrations (oligonucleotide, dNTPs, and ions of Na, K, and Mg). Other options including Analyze, Hairpin, Self-Dimer, Hetero-Dimer, NCBI BLAST, and Tm mismatch determine the biophysical properties regarding to designed probes (2,37).

Results
The output of Greview Server was an illustration which showed the relationship of the main bacterial strain with other compared strains. In Figure 1 the central circle belongs to the main bacterial strain and the outer circles pertain to other compared strains. The colored outer circles show the unique sequences within the main bacterial strain. This figure is related to Brucella melitensis (the main bacterial strain) and other Brucella spp. including B.ovis, B.canis, B.suis, B.abortus, B.ceti.

Figure 1. A pan-genomic comparison between six bacterial strains of Brucella*

1

* The main bacterial strain is B.melitensis (central circle) which is compared with five other strains (outer circles).

The colored outer circles indicate the unique regions within B.melitensis pan-genome.

According to Figure 1, there is a very close relationship among aforementioned bacterial strains. In this case there will be a big problem for designing microarray probes; because the unique regions are limited for producing and designing best probes.
The output of PanSeq Server which shown the pan-genomic unique regions regarding to the main bacterial strain was confirmed by BLAST tool of NCBI. Then, the unique sequence is processed by AlleleID 7.7 which resulted in microarray long oligo probes. The produced probes were checked again by BLAST and OligoAnalyzer 3.1. Table 1 shows the designed long oligo probes in Salmonella enterica Typhi (Table 1). There is a close relationship between Slamonella spp, Shigella and E.coli strains. Thus, a comparative
pan-genomic operation was done among S.enterica Typhi, other strains of S.enterica,
Shigella spp. and E.coli bacteria (17).

tab 1

Discussion
The presence of a wide range of deathful and pathogenic bacterial agents provokes microbiologists to find out accurate, reliable, reproducible, rapid and cost effective diagnostic methods. As the previous studies show, the bacterial infectious diseases and the related epidemiology and outbreaks are in association with inappropriate diagnosis and incorrect treatment. Among different microbial diagnostics, molecular biology techniques and NGS technologies are known as effective and accurate methods (8,38,39).
There are a wide range of advanced molecular biology techniques like PCR which are cost effective, rapid, accurate and reliable. But the disadvantage of PCR technique is its limitation for processing several samples at once. PCR is not suitable for a huge number of samples (11,40,41).
In contrast to PCR, DNA microarray is a proper tool for detecting and identifying tens of thousand genes at once. The principle of microarray technology is based on bioinformatics. So, the process of probe designing determines the level of accuracy and reliability of the results. Besides, suitable probe designing makes microarray flexible and comfortable (32,42,43).
For designing an effective, specific and reliable probe, there is a vital need for bioinformatics knowledge. A significant low content of G-C, low number and diversity of nucleotide sequences and abundance of repeated sequences decrease the accuracy, specificity and reliability of the probe. So, the use of powerful and easy to use tools, softwares, and databases guarantees the accuracy of the designed probe. Furthermore, the use of very close strains to the main bacterial strain declines the quality of designed probes. This makes probes incorrect, ineffective and inaccurate (2-4,16,21,44).
The products of AlleleID software are divided into Good probes and Best probes. As Lukajancenko and Ussery (16) have shown in their study, a high number of probes may be designed and produced for a specific bacterial strain. But the number of useful and effective probes is limited. The reason of this feature refers to the quality of the designed probes. To have an unbiased and accurate outcome, there is a must for choosing the best quality probes and avoiding Good ones.
In conclusion, DNA microarray technology is an accurate, reliable, rapid, cost effective and reproducible diagnostic technique. However, the level of biases in its outcomes is in association with probe quality and designing. The microarray technology has shortened the period of diagnosis time from two weeks into less than five days. Therefore, probe designing is an important process of microarray technique which guarantees the specificity, accuracy, reliability, flexibility and reproducibility of this rapid diagnostic tool.

Acknowledgement
This research was performed via grant facility offered by the Deputy of Research and Technology, Ministry of Health and Medical Education, Tehran, Iran.

Conflicts of interest: None declared.

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