Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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One of the most widely used techniques in microbiota research is 16S-rRNA-sequencing. Several laboratory processes have been shown to impact sequencing results, especially in low biomass samples. Low biomass samples are prone to off-target amplification, where instead of bacterial DNA, host DNA is erroneously amplified. Knowledge on the laboratory processes influencing off-target amplification and detection is however scarce. We here expand on previous findings by demonstrating that off-target amplification is not limited to invasive biopsy samples, but is also an issue in low bacterial biomass respiratory (mucosal) samples, especially when below 0.3 pg/μL. We show that off-target amplification can partly be mitigated by using gel-based library purification methods. Importantly, we report a higher off-target amplicon detection rate when using MiSeq reagent kit v3 compared to v2 (mean 13.3% vs 0.1% off-target reads/sample, respectively), possibly as a result of differences in reagents or sequencing recipes. However, since after bioinformatic removal of off-target reads, MiSeq reagent kit v3 still results in a twofold higher number of reads when compared to v2, v3 is still preferred over v2. Together, these results add to the growing knowledge base on off-target amplification and detection, allowing researchers to anticipate this problem in 16S-rRNA-based microbiome studies involving low biomass samples.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526709 | PMC |
http://dx.doi.org/10.1038/s41598-022-20573-1 | DOI Listing |