Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method of diagnosing dysbiosis

A technology of flora imbalance and bacteria, applied in disease diagnosis, biochemical equipment and methods, pharmaceutical formulations, etc., can solve problems that are difficult to determine or predict the exact relationship between microbiota

Pending Publication Date: 2020-03-17
SMARTDNA PTY LTD
View PDF9 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the highly complex interactions between bacterial species in the microbiota, it is difficult to determine or predict the exact impact of the microbiota on human health and its relationship to human diseases

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method of diagnosing dysbiosis
  • Method of diagnosing dysbiosis
  • Method of diagnosing dysbiosis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0126] Example 1: Bioinformatics process

[0127] A "bioinformatics pipeline" is a set of computational tasks applied sequentially to raw nucleic acid sequencing data in the form of FASTQ files (produced by a MiSeq (Illumina) high-throughput sequencing instrument). To ensure consistency, a set of informatics procedures were implemented in the process, which increased the reproducibility and validity of the results. Open source programs and databases are used in the process. figure 1 An overview of the bioinformatics pipeline is given.

[0128] Primary quality control analysis of raw FASTQ files

[0129] Raw sequences of individual samples analyzed in the MiSeq instrument are in FASTQ format (fastq.gz). Sequences for each sample are provided as two compressed FASTQ files; one for forward strand reads and one for reverse strand reads.

[0130] The integrity of the downloaded FASTQ file is checked using the ExactFile program based on the MD5 sums algorithm ( figure 1 , Box A...

Embodiment 2

[0170] Embodiment 2 Relative to healthy individual, to the diagnosis of subject's flora imbalance

[0171] sample

[0172] Fecal samples were collected using a DNA genotek OMNIgene GUT (OMR-200) collection device, which is used to stabilize DNA for quantitative gut microbiome profiling. After each stool sample was received by the laboratory, it was frozen at -20°C for no longer than 3 months. Prepare each sample for the extraction process by taking a pea-sized sample and aliquoting the fecal material into Pathogen Lysis Tubes (Catalog #: 19091 Qiagen). Each sample was centrifuged at 13000 rpm for 5 minutes and the supernatant was discarded. For consistency, more solid feces can be used to fill approximately half the volume of the pathogen lysis tube if desired. Pathogen lysis tubes containing fecal samples were then stored in a -20 °C freezer until further processing. The samples were processed in batches for a total of 48 samples. DNA was extracted from fecal samples usi...

Embodiment 3IB

[0191] Example 3 IBS subtype prediction

[0192] Predictive models using machine learning algorithms and supervised classification (such as random forest and naive Bayesian algorithms) to predict IBS subtypes: IBS-D (diarrhea), IBS-C (constipation), and IBS-M (mixed) . A training dataset was generated using microbiome profiles from individuals, classified by clinicians into three subtypes using Rome IV criteria:

[0193] · IBS-D (diarrhea type), n=78

[0194] · IBS-M (mixed type), n=22

[0195] · IBS-C (constipation type), n=78

[0196]The purpose of the prediction algorithm is to detect reproducible differences in microbiome profiles between groups of individuals with known IBS subtypes, which can be used to predict subtypes in individuals with unknown IBS subtypes. In this case, the Naive Bayes classifier was used as it showed improved performance compared to other algorithms. Bayesian classifiers are known to be used in a variety of domains, such as spam filtering prog...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present disclosure relates to methods of diagnosing a dysbiosis in a subject, methods of determining a suitable treatment, and methods of treating a dysbiosis. In some aspects, the present disclosure relates to diagnosing or determining a subtype of irritable bowel syndrome (IBS).

Description

technical field [0001] The present disclosure relates to methods of diagnosing dysbiosis in a subject, methods of determining appropriate treatment, and methods of treating dysbiosis. Background technique [0002] The human microbiota consists of trillions of microorganisms, most of which are of bacterial origin and are nonpathogenic. The microbiota plays a vital role in human health and works with the host's immune system to prevent the invasion and colonization of pathogens. It also has essential metabolic functions by providing a source of essential vitamins and nutrients and assisting in the extraction of energy and nutrients, such as amino acids and short-chain fatty acids, from food. In this regard, the host is highly dependent on its microbiota for many important biological functions that contribute significantly to health. [0003] Accumulating evidence indicates that dysbiosis of the human microbiota is associated with various diseases. However, due to the highly...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): C12Q1/689C12Q1/06G01N33/50G01N33/569
CPCA61K35/741C12Q1/06G01N2800/065G01N2800/28G01N2800/52C12Q1/689A23L33/135
Inventor M·史密斯
Owner SMARTDNA PTY LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com