Scientists Develop Optical Microring Resonator for the Rapid Detection of Ebola

A new tool can rapidly and reliably detect the presence of Ebola virus in blood samples at lower concentrations than existing tests, researchers from the US report. The device has the potential to help control future outbreaks of the deadly infection.

Ebola virus disease is a viral haemorrhagic fever that is estimated to kill up to 89% of those who contract it. It is spread through contact with the blood, bodily fluids or organs of an infected person or animal. First discovered following two simultaneous outbreaks in Nzara, in South Sudan, and Yambuku, in the Democratic Republic of the Congo, it has since led to dozens of outbreaks in the tropical regions of sub-Saharan Africa. The worst outbreak to date occurred in West Africa between late 2013 and early 2016, and is estimated to have caused 11,323 deaths.

In recent years, a selection of vaccines and effective therapies for Ebola have been developed. Unfortunately, however, they are not widely available. Accordingly, health officials typically combat the disease by attempting to contain outbreaks, an approach that relies on being able to quickly identify infections and inhibit further transmission. This is a challenge though, as Ebola symptoms – body aches, bleeding, diarrhoea and fever – are highly nonspecific, meaning that it can be easily mistaken for other viral infections or malaria.

Existing tests for the disease, meanwhile – which include PCR-based techniques, lateral flow assays and enzyme-linked immunosorbent assays (ELISAs) – are limited by lengthy assay times, and the need for additional electronics for sample processing, trained technicians and even cold chain custody. In addition, they tend not to be very sensitive until the virus has had days to multiply to high levels in the body.

In this latest study, clinical pathologist Abraham Qavi of Washington University in St Louis and his colleagues propose an alternative based on optical microring resonators, a type of whispering gallery mode device that can be used for highly sensitive molecular detection.

Such tools take their name from the effect originally discovered for sound waves in the Whispering Gallery in London’s St Paul’s Cathedral. Words whispered against the wall of the dome can be heard clearly more than 30 m away, thanks to the way in which sound waves travel around the concave surface. This is an example of the principle of acoustic resonance – a phenomenon that can also be seen with light waves at a much smaller scale.

Explaining how their whispering gallery mode device can detect the presence of tiny amounts of Ebola-related molecules in blood samples, Qavi says: “We trap light in the resonators and use resonance to enhance and boost our signal. By monitoring where this resonance wavelength occurs, we can tell how much of the molecule we have.”

The molecule in question is a sensitive antibody developed to react to a soluble glycoprotein released by the Ebola virus. This protein is also key to current diagnostic tests for Ebola — but the new antibody is capable of detecting it at lower levels. In tests on blood from infected animals, the microring resonator devices could detect the diagnostic glycoprotein as early as, or earlier than, the current leading tests. The test, which only took 40 min, also provided information on the viral glycoprotein concentration. This information could potentially be used to tailor treatment plans for individual patients.

“Any time you can diagnose an infection earlier, you can allocate healthcare resources more efficiently and promote better outcomes for the individual and the community,” Qavi says. “Using a biomarker of Ebola infection, we’ve shown that we can detect Ebola in the crucial early days after infection. A few days makes a big difference in terms of getting people the medical care they need and breaking the cycle of transmission.”

“Rapid, biosensor-based assays are needed to deal with a myriad of global health concerns, among them the detection of virus infections with the potential to spread across the globe,” says Frank Vollmer, a physicist from the University of Exeter, UK, who was not involved in the new study. Whispering gallery mode sensors, he explained, have emerged as one of the most sensitive and multiplexed biosensor technologies that can address this need.

He added: “[The researchers] impressively combine the high sensitivity and multiplexed readout of the whispering gallery mode sensor with the specific detection of the Ebola virus glycoprotein in patient samples – providing the real-world whispering gallery mode biosensor application that can save lives.”

With their initial study complete, the researchers are now looking to miniaturize the device and test their diagnostic approach on infected individuals.

The study is described in Cell Reports Methods.

Source: Physics World 

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Researchers Pioneer A New Way To Detect Microbial Contamination In Cell Cultures

Researchers from the Critical Analytics For Manufacturing Personalized-Medicine (CAMP) interdisciplinary research group at the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, have developed a new method of detecting adventitious microbial contamination in mesenchymal stromal cell (MSC) cultures, ensuring the rapid and accurate testing of cell therapy products intended for use in patients. Utilizing machine learning to predict if a culture is clean or contaminated in near-real time, this breakthrough method can be used during the cell manufacturing process, compared to less efficient end-point testing.

Cell therapy has, in recent years, become a vital treatment option for a variety of diseases, injuries, and illnesses. By transferring healthy human cells into a patient’s body to heal or replace damaged cells, cell therapy has shown increasing promise in effectively treating cancers, autoimmune diseases, spinal cord injuries, and neurological conditions, among others. As cell therapies advance and hold the potential to save more lives, researchers continue to refine cell culture manufacturing methods and processes to ensure the safety, efficiency, and sterility of these products for patient use.

The anomaly-detection model developed by CAMP is a rapid, label-free process analytical technology for detecting microbial contamination in cell cultures. The team’s research is explained in an oral abstract “Process Development and Manufacturing: Anomaly Detection for Microbial Contamination In Mesenchymal Stromal Cell Culture,” published recently in the journal Cytotherapy.

The machine learning model was developed by first collecting sterile cell culture media samples from a range of MSC cultures of different culture conditions. Some of the collected samples were spiked with different bacteria strains at different colony-forming units, a measurement of the estimated concentration of microorganisms in a test sample. The absorbance spectra of the sterile, unspiked and bacteria-spiked samples were obtained with ultraviolet-visible spectrometry, and the spectra of the sterile samples were used to train the machine learning model. Testing the model with a mixture of sterile and bacteria-spiked samples demonstrated the model’s performance in accurately predicting sterility.

“The practical application of this discovery is vast. When combined with at-line technologies, the model can be used to continuously monitor cultures grown in bioreactors at Good Manufacturing Practice (GMP) facilities in-process,” says Shruthi Pandi Chelvam, lead author and research engineer at SMART CAMP who worked with Derrick Yong and Stacy Springs, SMART CAMP principal investigators, on the development of this method. “Consequently, GMP facilities can conduct sterility tests for bacteria in spent culture media more quickly with less manpower under closed-loop operations. Lastly, patients receiving cell therapy as part of their treatment can be assured that products have been thoroughly evaluated for safety and sterility.”

During the process of cell therapy manufacturing, this anomaly-detection model can be used to detect the presence of adventitious microbial contamination in cell cultures within a few minutes. This in-process method can help to save time and resources, as contaminated cultures can immediately be discarded and reconstructed. This method provides a rapid alternative to conventional sterility tests and other microbiological bacteria detection methods, often taking a few days and almost always performed on finished products.

“Our increased adoption of machine learning in microbial anomaly detection has enabled us to develop a unique test which quickly performs in-process contamination monitoring, marking a huge step forward in further streamlining the cell therapy manufacturing process. Besides ensuring the safety and sterility of cell products prior to infusion in patients, this method also offers cost and resource effectiveness for manufacturers, as it allows for decisive batch restarting and stoppage should the culture be contaminated,” adds Yie Hou Lee, scientific director of SMART CAMP.

Moving forward, CAMP aims to develop an in-process monitoring pipeline in which this anomaly detection model can be integrated with some of the in-house at-line technologies that are being developed, which would allow for periodic culture analysis using a bioreactor. This would open the possibilities for further, long-term experimental studies in continuous culture monitoring.

Lead author Shruthi Pandi Chelvam also won the Early Stage Professionals Abstract Award, which is presented to three outstanding scholars, and abstracts are scored through a blinded peer-review process. The research was also accepted for the oral presentation at the 2022 International Society for Cell and Gene Therapy (ISCT) conference, a prestigious event in cell and gene therapies.

“This team-based, interdisciplinary approach to technology development that addresses critical bottlenecks in cell therapy manufacturing — including rapid safety assessment that allows on intermittent or at-line monitoring of plausible adventitious agent contamination — is a hallmark of SMART CAMP’s research goals,” adds MIT’s Krystyn Van Vliet, who is associate vice president for research, associate provost, a professor of materials science and engineering, and co-lead of SMART CAMP with Hanry Yu, professor at the National University of Singapore.

The research is carried out by SMART and supported by the National Research Foundation (NRF) Singapore under its Campus for Research Excellence And Technological Enterprise (CREATE) program. The study collaborated with a team from the Integrated Manufacturing Program for Autologous Cell Therapy, one of the sister programs in the Singapore Cell Therapy Advanced Manufacturing Program, of which CAMP is a part, to help develop an automated sampling system. This technology would integrate into the anomaly detection model.

CAMP is a SMART interdisciplinary research group launched in June 2019. It focuses on better ways to produce living cells as medicine, or cellular therapies, to provide more patients access to promising and approved therapies. The investigators at CAMP address two key bottlenecks facing the production of a range of potential cell therapies: critical quality attributes (CQA) and process analytic technologies (PAT). Leveraging deep collaborations within Singapore and MIT in the United States, CAMP invents and demonstrates CQA/PAT capabilities from stem to immune cells. Its work addresses ailments ranging from cancer to tissue degeneration, targeting adherent and suspended cells, with and without genetic engineering.

CAMP is the R&D core of a comprehensive national effort on cell therapy manufacturing in Singapore.

SMART was established by MIT in partnership with the NRF in 2007. SMART is the first entity in CREATE developed by NRF. SMART serves as an intellectual and innovation hub for cutting-edge research interactions of interest to both MIT and Singapore. SMART currently comprises an Innovation Center and five IRGs: Antimicrobial Resistance (AMR), CAMP, Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP), Future Urban Mobility (FM), and Low Energy Electronic Systems (LEES).

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UTSW Researchers Develop Rapid COVID-19 Test to Identify Variants in Hours

In just a few hours, UT Southwestern scientists can tell which variant has infected a COVID-19 patient – a critical task that can potentially influence treatment decisions but takes days or weeks at most medical centers.

Last year, pathologist Jeffrey SoRelle, M.D., and colleagues developed CoVarScan, a rapid COVID-19 test that detects the signatures of eight hotspots on the SARS-CoV-2 virus. Now, after testing CoVarScan on more than 4,000 patient samples collected at UT Southwestern, the team reports in Clinical Chemistry that their test is as accurate as other methods used to diagnose COVID-19 and can successfully differentiate between all current variants of SARS-CoV-2. 

“Using this test, we can determine very quickly what variants are in the community and if a new variant is emerging,” said Dr. SoRelle, Assistant Professor of Pathology and senior author of the study. “It also has implications for individual patients when we’re dealing with variants that respond differently to treatments.”

The testing results at UT Southwestern’s Once Upon a Time Human Genomics Center have helped public health leaders track the spread of COVID-19 in North Texas and make policy decisions based on the prevalence of variants.  Doctors have also used the results to choose monoclonal antibodies that are more effective against certain strains infecting critically ill COVID-19 patients.

While a number of other tests for COVID-19 exist, they generally detect either a fragment of SARS-CoV-2 genetic material or small molecules found on the surface of the virus, and don’t provide information to identify the variant. In addition, many researchers worry that these tests aren’t accurate in detecting some variants – or may miss future strains. To determine which variant of COVID-19 a patient has, scientists typically must use whole genome sequencing, which is time-consuming and expensive, relying on sophisticated equipment and analysis to spell out the entire RNA sequence contained in the viruses.

In early 2021, Dr. SoRelle and his colleagues at UT Southwestern wanted to track how well current tests were detecting emerging variants of SARS-CoV-2. But they realized that sequencing a lot of specimens would not be timely or cost-effective, so they designed their own test, working in the McDermott Center Next Generation Sequencing Core, part of the Eugene McDermott Center for Human Growth and Development directed by Helen Hobbs, M.D., Professor of Internal Medicine and Molecular Genetics.

CoVarScan hones in on eight regions of SARS-CoV-2 that commonly differ between viral variants. It detects small mutations – where the sequence of RNA building blocks varies – and measures the length of repetitive genetic regions that tend to grow and shrink as the virus evolves. The method relies on polymerase chain reaction (PCR) – a technique common in most pathology labs – to copy and measure the RNA at these eight sites of interest. 

To test how well CoVarScan works, Dr. SoRelle’s team ran the test on more than 4,000 COVID-19-positive nasal swab samples collected at UT Southwestern from April 2021 to February 2022 – from patients both with and without symptoms. The tests were validated with the gold-standard whole genome sequencing, and the results were used by doctors to choose treatments in some critically ill COVID-19 patients.  

Compared to whole genome sequencing, CoVarScan had 96% sensitivity and 99% specificity. It identified and differentiated Delta, Mu, Lambda, and Omicron variants of COVID-19, including the BA.2 version of Omicron, once known as “stealth Omicron” because it did not show up on some tests designed to detect only the Omicron strain.

“A common critique of this kind of test is that it requires constant adjustment for new variants, but CoVarScan has not needed any adjustment in more than a year; it is still performing very well,” said Dr. SoRelle. “In the future, if we did need to adjust it, we could easily add as many as 20 or 30 additional hotspots to the test.”

Dr. SoRelle plans to continue developing CoVarScan as a commercial test and has a pending patent application based on this work. As the inventor of the genotyping PCR test for variants, Dr. SoRelle is entitled to income from its use.

Other UTSW researchers who contributed to this study include Andrew Clark, Zhaohui Wang, Emily Ostman, Hui Zheng, Huiyu Yao, Brandi Cantarel, Mohammed Kanchwala, Chao Xing, Li Chen, Pei Irwin, Yan Xu, Dwight Oliver, Francesca Lee, Jeffrey Gagan, Laura Filkins, Alagarraju Muthukumar, Jason Park, and Ravi Sarode.

Dr. Hobbs holds the 1995 Dallas Heart Ball Chair in Cardiology Research, the Philip O’Bryan Montgomery, Jr., M.D. Distinguished Chair in Developmental Biology, and the Eugene McDermott Distinguished Chair for the Study of Human Growth and Development. Dr. Sarode holds the John H. Childers, M.D. Professorship in Pathology.

About UT Southwestern Medical Center

UT Southwestern, one of the nation’s premier academic medical centers, integrates pioneering biomedical research with exceptional clinical care and education. The institution’s faculty has received six Nobel Prizes, and includes 26 members of the National Academy of Sciences, 17 members of the National Academy of Medicine, and 14 Howard Hughes Medical Institute Investigators. The full-time faculty of more than 2,900 is responsible for groundbreaking medical advances and is committed to translating science-driven research quickly to new clinical treatments. UT Southwestern physicians provide care in more than 80 specialties to more than 100,000 hospitalized patients, more than 360,000 emergency room cases, and oversee nearly 4 million outpatient visits a year.

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