title: Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing.
abstract: BACKGROUND
  The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species.
  
  
  RESULTS
  We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples.
  
  
  CONCLUSIONS
  The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method.
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Chih-Min
authors.initials: CM
authors.lastname: Chiu
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Feng-Mao
authors.initials: FM
authors.lastname: Lin
authors.affiliation: Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan.
authors.forename: Tzu-Hao
authors.initials: TH
authors.lastname: Chang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Wei-Chih
authors.initials: WC
authors.lastname: Huang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Chao
authors.initials: C
authors.lastname: Liang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Ting
authors.initials: T
authors.lastname: Yang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Wei-Yun
authors.initials: WY
authors.lastname: Wu
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Tzu-Ling
authors.initials: TL
authors.lastname: Yang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Department of Obstetrics and Gynecology, Hsinchu Mackay Memorial Hospital, Hsinchu, Taiwan.|Mackay Medicine, Nursing and Management College, Taipei, Taiwan.|Department of Medicine, Mackay Medical College, New Taipei City, Taiwan.
authors.forename: Shun-Long
authors.initials: SL
authors.lastname: Weng
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Department of Biological Science and Technology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
authors.forename: Hsien-Da
authors.initials: HD
authors.lastname: Huang