Schematics of the general process of Raman data collection and analysis where a single spectrum is attained from a single cell and classified via deep learning.
A synergistic combination of surface-enhanced Raman spectroscopy and deep learning serves as an effective platform for separation-free detection of bacteria in arbitrary media
Bacterial identification can take hours and often longer, precious time when diagnosing infections and selecting appropriate treatments. There may be a quicker, more accurate process according to researchers at KAIST. By teaching a deep learning algorithm to identify the “fingerprint” spectra of the molecular components of various bacteria, the researchers could classify various bacteria in different media with accuracies of up to 98%.
Their results were made available online on Jan. 18 in Biosensors and Bioelectronics, ahead of publication in the journal’s April issue.
Bacteria-induced illnesses, those caused by direct bacterial infection or by exposure to bacterial toxins, can induce painful symptoms and even lead to death, so the rapid detection of bacteria is crucial to prevent the intake of contaminated foods and to diagnose infections from clinical samples, such as urine. “By using surface-enhanced Raman spectroscopy (SERS) analysis boosted with a newly proposed deep learning model, we demonstrated a markedly simple, fast, and effective route to classify the signals of two common bacteria and their resident media without any separation procedures,” said Professor Sungho Jo from the School of Computing.
Raman spectroscopy sends light through a sample to see how it scatters. The results reveal structural information about the sample — the spectral fingerprint — allowing researchers to identify its molecules. The surface-enhanced version places sample cells on noble metal nanostructures that help amplify the sample’s signals.
However, it is challenging to obtain consistent and clear spectra of bacteria due to numerous overlapping peak sources, such as proteins in cell walls. “Moreover, strong signals of surrounding media are also enhanced to overwhelm target signals, requiring time-consuming and tedious bacterial separation steps,” said Professor Yeon Sik Jung from the Department of Materials Science and Engineering.
To parse through the noisy signals, the researchers implemented an artificial intelligence method called deep learning that can hierarchically extract certain features of the spectral information to classify data. They specifically designed their model, named the dual-branch wide-kernel network (DualWKNet), to efficiently learn the correlation between spectral features. Such an ability is critical for analyzing one-dimensional spectral data, according to Professor Jo.
“Despite having interfering signals or noise from the media, which make the general shapes of different bacterial spectra and their residing media signals look similar, high classification accuracies of bacterial types and their media were achieved,” Professor Jo said, explaining that DualWKNet allowed the team to identify key peaks in each class that were almost indiscernible in individual spectra, enhancing the classification accuracies. “Ultimately, with the use of DualWKNet replacing the bacteria and media separation steps, our method dramatically reduces analysis time.”
The researchers plan to use their platform to study more bacteria and media types, using the information to build a training data library of various bacterial types in additional media to reduce the collection and detection times for new samples.
“We developed a meaningful universal platform for rapid bacterial detection with the collaboration between SERS and deep learning,” Professor Jo said. “We hope to extend the use of our deep learning-based SERS analysis platform to detect numerous types of bacteria in additional media that are important for food or clinical analysis, such as blood.”
The Latest on: Bacterial detection
- IPC releases revised draft general chapters on microbiology in IPon August 9, 2022 at 7:30 pm
IPC releases revised draft general chapters on microbiology in IP: Laxmi Yadav, Mumbai Wednesday, August 10, 2022, 08:00 Hrs [IST] In order to control the microbial quality of the ...
- Spatial patterns of benthic biofilm diversity among streams draining proglacial floodplainson August 7, 2022 at 10:47 pm
Glacier shrinkage opens new proglacial terrain with pronounced environmental gradients along longitudinal and lateral chronosequences. Despite the environmental harshness of the streams that drain ...
- New CDC study offers best look at how many people got sick at Kansas park last yearon August 6, 2022 at 1:05 pm
Families reported that their children got violently ill and even hospitalized after visiting the park last year.
- What Is Melioidosis, the Deadly Bacterial Infection the CDC Is Warning About?on July 28, 2022 at 11:06 am
The CDC is warning about the detection of bacteria that causes melioidosis, a rare and deadly disease that has never been spotted in the U.S.There have been four cases of the tropical illness in ...
- Bacteria that causes rare, serious illness melioidosis is endemic in parts of Mississippi Gulf Coast, CDC sayson July 27, 2022 at 8:14 pm
The bacteria that causes a rare, serious disease called melioidosis has been detected in water and soil samples in Mississippi, the US Centers for Disease Control and Prevention said Wednesday.
- First spotting of rare bacteria in U.S. found on Mississippi Gulf Coaston July 27, 2022 at 3:03 pm
An uncommon bacteria known to cause illness has been found on the Gulf Coast. This is the first time it's been found in the United States.
- Leaky gut and autoimmune disorders: Dormant 'bad' gut bacteria may be keyon July 19, 2022 at 5:00 pm
“We discovered that the evolution of individual bacterial species within our guts over time can lead to increases in the ability of that species to evade immune detection and clearance, cross ...
- In China's Wuhan, cholera-causing bacteria in turtles strikes nerveon July 14, 2022 at 9:04 pm
BEIJING (Reuters) -Detection in the Chinese city of Wuhan of a bacteria that caused cholera in a student and was separately found in samples from softshell turtles at a food market has struck a ...
- Adjuvant Immunotherapies as a Novel Approach to Bacterial Infectionson July 11, 2022 at 5:01 pm
The immune system discriminates between virulent and less virulent bacteria through the detection of virulence factors by, for example, inflammasomes. Viability–associated pathogen–associated ...
- How Nanoparticle Sensor is Changing Pneumonia Treatment Approach?on July 10, 2022 at 2:21 pm
which could help doctors choose the best antibiotic to combat that type of bacteria. The urine-based readout is also amenable to future detection with a paper strip, similar to a pregnancy test ...
via Bing News
The Latest on: Bacterial detection
via Google News