Rapidly analyzing samples for the presence of bacteria and similar organic structures is generally quite a time-intensive process, with often the requirement of a cell culture being developed. Proposed by Fareeha Safir and colleagues in Nano Letters is a method to use an acoustic droplet printer combined with Raman spectroscopy. Advantages of this method are a high throughput, which could make analysis of samples at sewage installations, hospitals and laboratories significantly faster.

Raman spectroscopy works on the principle of Raman scattering, which is the inelastic scattering of photons by matter, causing a distinct pattern in the thus scattered light. By starting with a pure light source (that is, a laser), the relatively weak Raman scattering can be captured and the laser light filtered out. The thus captured signal can be analyzed and matched with known pathogens.

In the experiment, the researchers were able to distinguish between red blood cells (RBCs) and a host of distinct bacterial pathogens, both Gram-negative and Gram-positive. In addition, samples were printed onto a cell culture growth medium and incubated to demonstrate that the thus printed samples were still viable, even after the pass through the printing head.

To enable easy classification, a machine-learning algorithm was used, which was able to accurately identify the cells present in a given sample. This research may enable rapid and affordable diagnostics, without the need for sending samples to a central laboratory, instead offering stand-alone diagnostics units that could be used even by untrained personnel.