2 ms·
Checking out the actual article (https://www.nature.com/articles/s41467-024-55457-7 https://www.nature.com/articles/s41467-024-55457-7) the authors write that:
by WJW 1y ago
Checking out the actual article (https://www.nature.com/articles/s41467-024-55457-7 https://www.nature.com/articles/s41467-024-55457-7) the authors write that:
"In recent years, matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) has been rapidly adopted in clinical practice to identify bacteria based on unique protein profiles6,7. However, while the identification process itself is faster, MALDI-MS-based analysis suffers from the same time-consuming isolation step as traditional approaches. Time, however, is a decisive factor in the successful treatment of several infection scenarios such as sepsis4,8. Consequently, the ideal scenario of microbial diagnosis is to identify bacteria directly from the clinical sample. Using MALDI, so far only a small number of applications could be implemented due to the high protein background in most clinical samples9."
While mass spectrometry is an old(-ish) method, only recently has it become good and fast enough for clinical use. They also needed to make their own database of bacterial byproduct signatures to look for, as that did not exist yet.
As to "why just now": not everything has been invented yet, even things that might seem relatively straightforward.
- w10-1 1y agoglossing... Article mentions existing tools e.g., MasSpec Pen, which detect signals of interest in samples with minimal processing (i.e., avoiding the hard part of processing/cleaning bio samples). But those were specific cancer signals that stood out from the general protein noise. (See also the cancer knife, that burns to cut and analyzes the smoke to see if you have enough margin). Problem with bacteria is (a) wide diversity and (b) previous work was mostly on lipids, not small molecules. For small molecule metabolites of bacteria, previous article reported a medium-size proof of concept (hundreds of target), and this is doing more (thousands), where they identify a few hundred unique patterns and then demonstrate their detection. At 90%, it's likely this would be used for pre-screening to identify possible candidates, though it might reinforce initial clinical suspicion and preliminary antibiotics.