Method for judging background introduced microorganism sequence and application thereof
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A technology of microorganisms and pathogenic microorganisms, applied in the field of biological information analysis, can solve the problems of batch false positives, false negatives, internal parameters, etc., and achieve the effect of correcting quantitative errors in comparison and easy operation.
Active Publication Date: 2021-08-17
GZ VISION GENE TECH CO LTD +3
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This type of method can only obtain a list of potential background contamination, and use a one-size-fits-all approach to directly remove these microorganisms
However, common clinical pathogens, such as Acinetobacter baumannii, Pseudomonas aeruginosa, Klebsiella pneumoniae, Stenotrophomonas maltophilia, Escherichia coli, Enterococcus faecalis, Serratia marcescens, etc., all exist at the same time Microorganisms in the background of nucleic acid extraction or reagents cannot determine whether the microorganisms in the sample are background contamination or originate from the sample itself.
[0007] The other method is to quantify by adding internal references to remove microorganisms whose relative abundance is below the threshold. This method has higher requirements for internal references and requires an internal reference set with accurate quantification and high complexity, and the operation is more complicated.
However, in actual operation, we found that different sample types require different pre-processing steps. When adding internal references will have different effects on the final quantitative results. Different sample types need to calculate the corresponding thresholds separately. In addition, this method is based on strict Assuming that the nucleic acid of background microorganisms is a stable constant, it is often found that the background contamination of different batches of experimental consumables will still fluctuate in practical operations, so it is easy to have batches of false positives or false negatives
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Embodiment 1
[0057] A method for judging background microbial sequences, comprising the following steps:
[0058] 1. Determine the list of background microorganisms.
[0059] 1. Sequencing.
[0060] Obtain 1000 negative control plasma samples, extract nucleic acid and quantify the total amount of nucleic acid D, and then perform library sequencing.
[0061] mNGS off-machine data for microbial quantification: first use fastp software to remove adapters, low-quality sequences or sequences with a length less than 35bp; then use bwa software to compare to the human reference genome, and remove the sequences compared to the human reference gene; after that, The obtained non-human genome sequence (unHost Reads) was compared to the microbial database (including reference sequences of 18562 microorganisms) with bwa; finally, the quantitative value A of microbial abundance was obtained according to the number of aligned sequences.
[0062] 2. Determine the background microorganisms.
[0063] Acc...
Embodiment 2
[0092] 1464 clinical samples were collected as a verification set, among which 275 samples were detected with E. coli sequences (22 cases were clinically judged as E. coli positive samples), and the method of Example 1 was used to analyze and judge the background introduced microbial sequences.
[0093] Sequence according to the method of Example 1, obtain the Escherichia coli gene sequence data, substitute it into the above judgment model, and judge with the log-likelihood ratio LLR statistic in Example 1, the threshold is 40.684, and evaluate the classification effect of the model.
[0094] ROC curve such as image 3 As shown, the AUC value is 0.996, the specificity is 0.956, and the sensitivity is 1.000.
[0095] The above results show that the method of introducing microbial sequences into the judgment background of the present invention can achieve a better discrimination effect on samples from different source batches, and has the advantages of high judgment stability an...
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Abstract
The invention relates to a method for judging a background introduced microorganism sequence and application thereof, and belongs to the technical field of biological information analysis. The method comprises the following steps: determining a background microorganism list: taking a plurality of pathogenic microorganism negative samples, performing correlation test on a quantitative value A of abundance of each microorganism and a total nucleic acid amount D, and judging that the sample is a background pathogenic microorganism if the sample is in negative correlation; establishing a judgment model: respectively taking a negative control sample set and a positive sample set of background pathogenic microorganisms, comparing gene sequence data of the background pathogenic microorganisms to a feature sequence region of the microorganisms, calculating abundance, and establishing a judgment model; and quantitatively analyzing the specific region of the microorganisms, namely obtaining the gene sequence data of the background pathogenic microorganisms in a sample to be detected, and judging by adopting the judgment model. The method can accurately judge whether the microorganism sequence obtained by sequencing is background introduction or not, can reduce the batch false positive or false negative problem, and can be widely applied to data analysis of pathogenic microorganism detection.
Description
technical field [0001] The invention relates to the technical field of biological information analysis, in particular to a method for judging background-introduced microbial sequences and its application. Background technique [0002] Pathogenic metagenomics (mNGS) is a high-throughput sequencing technology that does not depend on culture, directly extracts nucleic acids from clinical specimens and detects pathogens. Compared with traditional clinical laboratory detection methods, pathogenic mNGS is based on the detection of sequences at the nucleic acid level, which can break through the limitations of different pathogen types, comprehensively cover thousands of pathogens without bias, and simultaneously identify bacteria, fungi, viruses and Various types of pathogenic microorganisms such as parasites, pathogenic mNGS has gradually become an important tool in the field of clinical microbial identification. [0003] However, the accuracy of mNGS can be affected by contamina...
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