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
Fed-batch culture of Chinese hamster ovary (CHO) cells remains the most commonly used method for producing biopharmaceuticals. Static CHO cell-line engineering approaches have incrementally improved productivity, growth and product quality through permanent knockout of genes with a negative impact on production, or constitutive overexpression of genes with a positive impact. However, during fed-batch culture, conditions (such as nutrient availability) are continually changing. Therefore, traits that are most beneficial during early-phase culture (such as high growth rate) may be less desirable in late phase. Unlike with static approaches, dynamic cell line engineering strategies can optimise such traits by implementing synthetic sense-and-respond programmes. Here, we review emerging synthetic biology tools that can be used to build dynamic, self-regulating CHO cells, capable of detecting intra-/extracellular cues and generating user-defined responses tailored to the stage-specific needs of the production process.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.copbio.2022.102806 | DOI Listing |
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