Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Despite the fast progress in our understanding of the complex functions of gut microbiota, it is still challenging to directly investigate the in vivo microbial activities and processes on an individual cell basis. To gain knowledge of the indigenous growth/division patterns of the diverse mouse gut bacteria with a relatively high throughput, here, we propose an integrative strategy, which combines the use of fluorescent probe labeling, confocal imaging with single-cell sorting, and sequencing. Mouse gut bacteria sequentially labeled by two fluorescent d-amino acid probes in vivo were first imaged by confocal microscopy to visualize their growth patterns, which can be unveiled by the distribution of the two fluorescence signals on each bacterium. Bacterial cells of interest on the imaging slide were then sorted using a laser ejection equipment, and the collected cells were then sequenced individually to identify their taxa. Our strategy allows integrated acquirement of the growth pattern knowledge of a variety of gut bacteria and their genomic information on a single-cell basis, which should also have great potential in studying many other complex bacterial systems.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10989894 | PMC |
http://dx.doi.org/10.1002/mlf2.12041 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!