scholarly journals Beginner’s guide to comparative bacterial genome analysis using next-generation sequence data

Author(s):  
David J Edwards ◽  
Kathryn E Holt
2015 ◽  
Vol 31 (17) ◽  
pp. 2870-2873 ◽  
Author(s):  
Adrian Baez-Ortega ◽  
Fabian Lorenzo-Diaz ◽  
Mariano Hernandez ◽  
Carlos Ignacio Gonzalez-Vila ◽  
Jose Luis Roda-Garcia ◽  
...  

2010 ◽  
pp. 193-206 ◽  
Author(s):  
D.E. Soltis ◽  
G. Burleigh ◽  
W.B. Barbazuk ◽  
M.J. Moore ◽  
P.S. Soltis

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0002
Author(s):  
Yoonjung Choi ◽  
Irvin Oh

Category: Other Introduction/Purpose: Foot infections are often polymicrobial with diverse microbiomes. Accurate identification of the main pathogen in diabetic foot ulcer (DFU) remain challenging due to contamination or negative cultures often leading to ineffective post-surgical antibiotic treatment. Application of molecular diagnostics, such as next generation sequencing (NGS) has been explored as an alternative to standard culture in orthopaedic infections. NGS is highly sensitive and detects an entire bacterial genome along with pharmacologic resistant genes in a given sample. We sought to investigate the potential use of NGS for accurate diagnosis and quantification of various species in infected DFU. We hypothesize that NGS will provide a more accurate means of diagnosing and profiling microorganisms in infected DFU compared to the standard culture method. Methods: We investigated 30 infected DFU patients who underwent surgical treatment by a single academic orthopaedic surgeon from October 2018 to September 2019. The average age of the patient was 60.4 (range 33-82) years-old. Surgical procedures performed were irrigation and debridement (12), toe or ray amputation (13), calcanectomies (4), and below-knee amputation (1). Infected bone specimens were obtained intraoperatively and processed for standard culture and NGS. Quantitative PCR was performed to determine the bacterial burden present in the sample. DNA was amplified by PCR from a highly conserved region of the rRNA gene in the bacteria (16S rRNA). Once a high level of DNA was generated and determined, it was compared against NIH GenBank database. Concordance between the standard culture and NGS was assessed. Results: In 28 of 29 patients, pathogens were identified by both NGS and culture, with complete consistency of organisms in 13 cases (concordance rate: 43.3%). NGS provided relative quantitative measures and the presence of antibiotic resistant genes for each pathogen. In NGS, Anaerococcus species (79.3%) was the most common organism, followed by Streptococcus species (44.8%), Prevotella species (44.8%), Finegoldia magna (44.8%). In culture, S. aureus (58.6%) was the most common, followed by Streptococcus species (34.5%), coagulase-negative Staphylococci (24.1%), Corynebacterium species (20.7%). On average, NGS revealed 5.1 (1-11) number of pathogens, whereas standard culture revealed 2.6 (1-6) pathogens in a given sample. NGS identified 2 cases with false positive standard culture and detected antibiotic resistant organisms in 15 specimens. Conclusion: NGS is an emerging method of microbial identification in orthopedic infection. It is particularly helpful in profiling diverse microbes in polymicrobial infected DFU. It can identify major pathogens and may correct false positive or false negative culture. NGS may allow a faster invitation of postoperative targeted antibiotic therapy. [Table: see text]


2018 ◽  
Vol 8 (9) ◽  
pp. 1471 ◽  
Author(s):  
Seo-Joon Lee ◽  
Gyoun-Yon Cho ◽  
Fumiaki Ikeno ◽  
Tae-Ro Lee

Due to the development of high-throughput DNA sequencing technology, genome-sequencing costs have been significantly reduced, which has led to a number of revolutionary advances in the genetics industry. However, the problem is that compared to the decrease in time and cost needed for DNA sequencing, the management of such large volumes of data is still an issue. Therefore, this research proposes Blockchain Applied FASTQ and FASTA Lossless Compression (BAQALC), a lossless compression algorithm that allows for the efficient transmission and storage of the immense amounts of DNA sequence data that are being generated by Next Generation Sequencing (NGS). Also, security and reliability issues exist in public sequence databases. For methods, compression ratio comparisons were determined for genetic biomarkers corresponding to the five diseases with the highest mortality rates according to the World Health Organization. The results showed an average compression ratio of approximately 12 for all the genetic datasets used. BAQALC performed especially well for lung cancer genetic markers, with a compression ratio of 17.02. BAQALC performed not only comparatively higher than widely used compression algorithms, but also higher than algorithms described in previously published research. The proposed solution is envisioned to contribute to providing an efficient and secure transmission and storage platform for next-generation medical informatics based on smart devices for both researchers and healthcare users.


2020 ◽  
Vol 21 (9) ◽  
pp. 2763-2769
Author(s):  
Digdo Sudigyo ◽  
Gisti Rahmawati ◽  
Dicka Setiasari ◽  
Risky Poluan ◽  
Salsabila Sesotyosari ◽  
...  

2016 ◽  
Vol 36 (8) ◽  
Author(s):  
Livia Moura de Souza ◽  
Guilherme Toledo-Silva ◽  
Claudio Benicio Cardoso-Silva ◽  
Carla Cristina da Silva ◽  
Isabela Aparecida de Araujo Andreotti ◽  
...  

2013 ◽  
Vol 51 (9) ◽  
pp. 3163-3163
Author(s):  
N. L. Sherry ◽  
T. P. Stinear ◽  
B. P. Howden

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