Comparison of K-Means Clustering and Otsu Thresholding Methods in the Detection of Tuberculosis Extra Pulmonary Bacilli in the HSV Color Space

Tuberculosis Extra Pulmonary (TBEP) is an infectious disease caused by the bacterium Mycobacterium tuberculosis and can cause death. Patients suffering from this disease must be treated quickly without waiting long. Currently, anyone who will be detected caused by this bacterium takes a long time and costs a lot. The biopsy is one of the techniques used to take the patient's lung fluid and give Ziehl Neelsen chemical dye and then observe using a microscope to determine this TBEP disease. This research aims to help detect bacteria quickly and precisely by performing computer-aided image processing by creating an application system. The technique used is to develop the segmentation method. The segmentation process is to develop a Hue Saturation Value (HSV) color space transformation technique with the K-Means and Otsu Thresholding techniques. From the results of the two methods used, it turns out that the Otsu Thresholding method can detect TBEP results with more accuracy than the K-Means method. So the method developed is beneficial in accelerating and minimizing costs for detecting TBEP

Gold nanoparticles-based sensors for detection of mycobacterium tuberculosis genomic DNA

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB), is an airborne disease that strikes one third of the globe’s population. In addition to infection of 9.6 million patients, TB claimed the lives of 1.5 million people in 2014 only. The majority of TB patients are present in the third world where the balance between cost-effective diagnostic method and prevalence of TB is difficult to achieve. Accurate diagnosis of TB is necessary to timely initiation of treatment. The available diagnostic tools are slow, while the rapid methods are either inaccurate or relatively unaffordable. So, sometimes the diagnosis is presumptive based on the clinical findings and the treatment is empiric. The treatment is lengthy and demands the administration of multiple antibiotics. However, the emergence of drug resistance threatened the global control programs of TB. The objective of this work is to develop cheap, fast and accurate detection methods. Two gold nanoparticles (AuNPs) based sensors were developed for colorimetric and fluorometric detection of MTB. Seventy two anonymous sputum samples were cultured then DNA was extracted. MTB H37Ra was the positive control while M. smegmatis and 8 non-MTB and negative controls. Characterization of the samples was achieved by multiplex PCR using MTB and NTM specific primers. Random samples were amplified by 16S-23S ITS primers and sequenced. Drug resistance associated mutations of MDR-TB were identified by MAS-PCR. The colorimetric assay aim was the detection of amplified MTB DNA by cationic AuNPs. The samples were amplified by IS6110 and rpoB primers. Only MTB samples yielded amplicons. So the negatively charged dsDNA attracted the positively charged AuNPs inducing their aggregation and the color turned blue. While the negative samples did not yield any amplicons and the AuNPs remained dispersed so the color was red. The sensitivity and specificity was 100% and the detection limit was 5.4 ng/μl of MTB DNA. The fluorometric assay exploited the quenching property of 40 nm AuNPs. The unamplified DNA was fragmented in the presence of 16s rDNA specific probe tagged with the fluorophore CY-3 by sonication and denatured for 3 min at 95 ºC followed by annealing at 52ºC for 45 sec. Then AuNPs were added and the fluorescence was measured. By FRET, the relative fluorescence was calculated revealing a cut-off value of 3. In MTB samples, the CY3-16s rDNA specific probe hybridized with its target and became spaced from the AuNPs allowing high fluorescence to be detected. Due to the lack of target-probe hybridization in the negative samples, the AuNPs were adsorbed on the probe and thus the fluorescence is quenched. Thirteen samples were chosen randomly, amplified and sequenced. Sequencing confirmed that 12/13 samples were MTB with 100% concordance with the multiplex PCR and FRET. The assay had sensitivity and specificity of 98.6% and 90% respectively and concordance of 98% with multiplex PCR. The detection limited was calculated to be 10 ng/ul. In conclusion, two AuNPs based sensors were developed to allow low cost and rapid detection of MTB on low source settings. The assays are rapid, sensitive and can have great potential in clinical practice for TB diagnosis

Direct detection of mycobacterium tuberculosis complex using gold nanoparticles

Tuberculosis (TB) is still one of the most significant causes of morbidity and mortality worldwide. According to WHO, TB causes 2 million deaths and more than 9 million new cases annually; the overwhelming majority of TB cases occur in developing countries where accurate diagnosis of TB remains a challenge. This work aims to develop a rapid nano-gold assay for specific detection of mycobacterium tuberculosis complex (MTBC). In the first version of the assay, DNA was extracted from clinical isolates grown on LJ media. 16s rDNA regions were amplified by PCR then the genus and species of MTB were confirmed by semi-nested PCR. Spherical gold nanoparticles (AuNPs; 13 nm) were synthesized by citrate reduction method of HAuCl4 and characterized by spectrophotometry and SEM. In the first assay, the 16srDNA amplicons were denatured (95 oC, 30 s) then allowed to anneal (48 oC, 30 s) with genus- and species-specific oligotargeters in a hybridization buffer contaning NaCl (40 nM). This was followed by the addition of unmodified AuNPs (14 nM). In case of a positive specimen, the AuNPs aggregated and the solution color changed from red to blue. The solution retained red color in case of negative specimen. This assay was further optimized to specificially differentiate MTBC from other mycobacterial strains. In the second version of the assay, MTBC was directly detected in the extracted genomic DNA. Species-specific oligotargeter was added to genomic DNA and denatured for 3 min at 95 oC followed by annealing at 48 oC for 1 min. AuNPs were added and solution color changed from red to blue in case of MTBC-positive specimens. The assay detection limit was 1 ng for PCR product and 40 ng for genomic DNA. The assay showed 100% sensitivity and specificity (n = 27) as compared with automated liquid culture system (MGIT) and semi-nested PCR. Following DNA extraction according to standard procedures, the assay turnaround time is about 1 hour. In conclusion, we have developed a nano-gold assay prototype for direct detection of MTBC as a low cost alternative to current amplification-based detection platforms. The developed assay is simple, sensitive, rapid, and shows a great potential in the clinical diagnosis of TB especially in developing countries with low resource settings

A report on Tuberculosis in Monkeys (Macaca mulatta): A case study at Chittagong Zoo

Simian tuberculosis is one of the most important bacterial diseases of captive monkey in Bangladesh. A prevalence study to characterize Mycobacterium infecting tuberculous monkeys in captive managemental systems in Chittagong Zoo was carried out. In the present study, 14 rhesus monkeys which were newly arrived in the zoo and kept in the quarantine were used for the tuberculin skin testing (TST) to determine the prevalence of tuberculosis. An overall of 28.57% (4/14) was recorded by the TST. There were also marked differences in the prevalence of the disease within different age groups. In the tested positive animals, one was died within two days and showed tubercle in the lung and other organs in the post-mortem examination. The lung sample was collected for Zeihl-Neelsen revealed red colored tubercule bacilli.The above examination confirmed that, the macaques were suffering from tuberculosis

A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis

Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far

Secondary Metabolites Production of Bacillus spp. Isolated from Sea Cucumbers (Holothuria scabra) and their Activity against Mycobacterium smegmatis

New anti-tuberculosis agents are very important due to Multidrug-Resistant and Extensively Drug-Resistant Tuberculosis problems. Mycobacterium smegmatis can be used to replace Mycobacterium tuberculosis as bacteria test to increase the velocity of anti-tuberculosis screening. To answer the need for new drugs, exploration of secondary metabolites from Bacillus spp. can be conducted. Bacillus spp. are known to produce antimicrobials, including discovery of iturins, fengycins, and pumilacidins. This study explored the Bacillus spp. isolated from fermented intestines of Holothuria scabra. The production of Bacillus sp. Holothuria scabra Fermented Intestine (HSFI) secondary metabolites was done using culture media containing starch as a carbon source, as well as yeast and peptone as a nitrogen source. Production capacity of secondary metabolites of Bacillus sp. HSFI was calculated, to determine its potential as an antibacterial producer. Inhibition testing of secondary metabolites of Bacillus sp. HSFI against M. smegmatis was performed using the Kirby-Bauer disk diffusion method. Based on the results of the inhibition test, it was concluded that Bacillus sp. HSFI-9 has the greatest potential to inhibit the growth of M. smegmatis, with a moderate inhibition (7.67 mm). Production of secondary metabolites from Bacillus sp. HSFI-9 is exceptionally good with an extract production capacity of 24.6 mg/L

Automated methods for tuberculosis detection/diagnosis : a literature review

Funding: Welcome Trust Institutional Strategic Support fund of the University of St Andrews, grant code 204821/Z/16/Z.Tuberculosis (TB) is one of the leading infectious causes of death worldwide. The effective management and public health control of this disease depends on early detection and careful treatment monitoring. For many years, the microscopy-based analysis of sputum smears has been the most common method to detect and quantify Mycobacterium tuberculosis (Mtb) bacteria. Nonetheless, this form of analysis is a challenging procedure since sputum examination can only be reliably performed by trained personnel with rigorous quality control systems in place. Additionally, it is affected by subjective judgement. Furthermore, although fluorescence-based sample staining methods have made the procedure easier in recent years, the microscopic examination of sputum is a time-consuming operation. Over the past two decades, attempts have been made to automate this practice. Most approaches have focused on establishing an automated method of diagnosis, while others have centred on measuring the bacterial load or detecting and localising Mtb cells for further research on the phenotypic characteristics of their morphology. The literature has incorporated machine learning (ML) and computer vision approaches as part of the methodology to achieve these goals. In this review, we first gathered publicly available TB sputum smear microscopy image sets and analysed the disparities in these datasets. Thereafter, we analysed the most common evaluation metrics used to assess the efficacy of each method in its particular field. Finally, we generated comprehensive summaries of prior work on ML and deep learning (DL) methods for automated TB detection, including a review of their limitations.Publisher PDFPeer reviewe