Mycobacterium tuberculosis LAM (lipoarabinomannan) detection kit, preparation and use method thereof

Abstract

The present invention relates to a nano immunomagnetic bead-near infrared fluorescence notation labeling method-based mycobacterium tuberculosis lipoarabinomannan (LMA) detection kit, a near-infrared fluorescence dye is used for labeling of a monoclonal antibody targeted to LAM, and nano magnetic bead surface is coated with a polyclonal antibody targeted to LAM, by use of the principle of double antibody sandwich method, a conjugate and free substances are magnetically separated, a a portable high sensitivity and low noise excitation fluorescence detector is used to detect the fluorescence intensity of the magnetic conjugate so as to detect the LAM content of a sample to be tested. The detection kit is applicable to the LAM detection in clinical and pathological specimens, and has the characteristics of being rapid, sensitive, anti-stray fluorescence interference, and long in emission fluorescence save time.

Description

technical field [0001] The invention belongs to the field of biology, and in particular relates to a detection kit for mycobacterium tuberculosis lipoarabinomannan (LMA), a preparation method and a use method. technical background [0002] The invention establishes a nano-magnetic bead-near-infrared fluorescent label-detection kit for detecting LAM, a component related to mycobacterium tuberculosis. Including the near-infrared fluorescent dye labeling method of monoclonal antibodies, the polyclonal antibody coating method of nano magnetic beads and a series of related reagents. The invention uses a near-infrared fluorescent dye as a mark and adopts the principle of immunoassay to prepare a near-infrared fluorescent kit for detecting LAM double-antibody sandwich method. The fluorescence intensity of the magnetic bead-conjugate was measured using a portable flow injection fluorescence detector. In quantitative detection, the concentration of the target protein in the test sa...

AI Technical Summary

Problems solved by technology

[0004] At present, the detection methods for Mycobacterium tuberculosis mainly include smear microscopy. This method requires the detection personnel to have skilled detection skills, and the detection sensitivity of the method is low. Generally, the presence of 10 3 CFU / ml bacteria have a positive rate of 10-15%, and the bacteria cannot be accurately identified; the culture method is mainly carried out in infectious disease hospitals, and the detection cycle is long, and it generally takes 6 weeks to issue a report Although the automatic microbial identification instrument that appeared recently has greatly shortened the inspection cycle, it usually takes about 2 weeks, this still does not fundamentally solve the problem of efficiency, and there is a defect of high cost. The simple reagent cost is 120 yuan / test, And it requires large-scale equipment; serological testing methods mainly focus on the detection of Mycobacterium tuberculosis-related antibodies, because patients with tuberculosis infection have low immunity, often do not express relevant antibodies, or because adults have a high chance of being infected with Mycobacterium tuberculosis, due to Immunological memory, many people who have been infected can also detect related antibodies, which makes it difficult to judge; molecular biology methods have been widely used in clinical detection recently, such as PCR method, probe detection method, etc. These methods have good specificity, However, special detection instruments are required, and there are problems in popularization and application. The ultra-high sensitivity also brings insurmountable problems-false positives; tuberculosis infection T cell spot test is used to detect gamma-interferon secreted by specific T cells after tuberculosis infection , and based on the results to determine whether you are infected with tuberculosis, this method is characterized by cumbersome, high cost, and is not suitable for promotion. However, it also has the disadvantages of cumbersomeness, high cost, and the need for sufficient experience in judging the results.

Images