The humble lateral flow assay grew in prominence during the COVID-19 pandemic as a quick at-home method to check your COVID status, but this technology was already a staple of such applications as pregnancy testing. Now, researchers are increasingly aware of its utility as a rapid point-of-care diagnostic technology and are beginning to apply it to the detection of other diseases. In this instance, these researchers at the University of Cincinnati have developed a lateral flow assay to detect the bacteria responsible for gingivitis.

Gingivitis is caused by P. gingivalis, which typically starts as mild gum inflammation. However, this can spread to other parts of the periodontal tissue, causing damage to soft tissue and bone that stabilize our teeth. This damage can eventually lead to tooth loss. Moreover, researchers have also linked P. gingivalis to other conditions, including cardiovascular diseases, rheumatoid arthritis, and even neurodegenerative diseases such as Alzheimer’s disease.  

There are lab-based tests available to detect P. gingivalis, but compared with a lateral flow test, they are complex, slow, expensive, and lack portability. If a diagnostic technique is too expensive, time consuming and inconvenient, then patients or clinicians will only tend to seek it out or recommend it if symptoms have already developed. However, for routine testing and health screening, a convenient, rapid, and point-of-care test is much preferred. A lateral flow test for gingivitis, for example, could be administered by a dentist every time someone undergoes a routine dental checkup.   

The assay detects a bacterial endotoxin released into the saliva by P. gingivalis through a simple immunoassay, whereby antibodies capture and identify the toxin. An enzyme present in saliva called amylase can interfere with this, so the assay requires the saliva to be pretreated with potato starch to deactivate this enzyme. In the future, you may be able to use such lateral flow assays to conveniently detect a wide variety of pathogens and biomarkers, and you can thank SARS-CoV-2 for the privilege. 

Reference: Salivary endotoxin detection using combined mono/polyclonal antibody-based sandwich-type lateral flow immunoassay device. Sens. Diagn., 2023, Advance Article. 

Wastewater surveillance involves monitoring wastewater and sewage water in an area for pathogens to ascertain the health of a community. Studies have shown that the concentration of pathogens in wastewater can be used as an accurate measure for the population-level spread of a disease. “The origin of monitoring wastewater and sewage for pathogen detection and outbreak of epidemics goes all the way back to 1939 when the initial application of wastewater surveillance for detecting poliovirus on a community level was demonstrated,” says Prof. Siddharth Tallur, from the Department of Electrical Engineering, IIT Bombay and a part of the team that developed the new portable sensor.

In recent times, the COVID-19 pandemic has once again brought out the importance of wastewater surveillance. Some of those infected with the SARS-CoV-2 were asymptomatic, showing no external signs of infection, and hence posing challenges to track them with clinical surveillance alone. Data from wastewater surveillance complemented clinical surveillance data by providing valuable estimates as to how many individuals were infected and which SARS-CoV-2 variants were circulating in a community. “Wastewater-based epidemiology serves as a tool for data collection from populations which lack adequate access to healthcare and large-scale individual- level diagnostic testing,” adds Prof. Tallur.

Currently, the most commonly used method for detecting disease-causing agents is the real-time quantitative polymerase chain reaction (RT-qPCR), a technique known for its high specificity and sensitivity. However, the qPCR method requires expensive probes and trained personnel to administer, thereby limiting its application to well-equipped laboratories.

The COVID-19 pandemic saw the invention of several new biosensors and detectors that could pick out the SARS-CoV-2 virus from wastewater samples. There have also been smartphone-based sensors that detect changes in colour in a sample denoting the presence of pathogen DNA. These, however, either sacrifice sensitivity or require expensive reagents and equipment, sterile lab conditions and experts to operate. The new portable sensor developed at IIT Bombay significantly reduces these limitations. It is highly sensitive to any DNA present in a sample, yet keeps the costs low.

The IIT Bombay device functions by detecting colour changes in samples created by the interaction of DNA with methylene blue (MB) dye. Intercalation is the process by which molecules, such as methylene blue, insert themselves in between bases of DNA. This causes a change in the property of the material to absorb light of different wavelengths, thereby causing a change in its colour. In a sample prepared for testing, this leads to a change in the colour of the sample. The colourimetric sensor system is designed around an indigenously built circuit, called a phase-sensitive detection circuit, which detects this change in colour. The sensor consists of a sample holder connected to the colourimetric sensor. Once a sample is placed in the sample holder, the sensor picks up any colour change in the sample due to DNA, which is then converted to a voltage signal for measurement and recording. The IIT Bombay team has also developed a mobile application that can read this voltage signal via Bluetooth and display the information on a smartphone.

PCR is a process used to multiply a specific DNA segment. Unpurified PCR products, along with the DNA, contain other organic materials like enzymes and nucleotides along with chemical contaminants, like primers and buffers used for the process. The sensor proved to be capable of detecting DNA in unpurified PCR products and distinguishing these from control samples, containing purified DNA.

The phase-sensitive detection circuit, which was completely designed and built at IIT Bombay, is constructed from low-cost semiconductor integrated circuit components and a low-power LED light source. Methylene blue is a widely used dye – easy to obtain and inexpensive. These factors have allowed the researchers to keep the cost of manufacturing and operating the sensor low. “The technology developed in our work holds promise for the realisation of a truly cost-effective solution for wastewater-based epidemiology,” opines Prof. Tallur.

The sensor is, however, not without its limitations. The use of methylene blue dye means reduced specificity of the device. According to Prof. Tallur “It (methylene blue) will bind with any DNA present in the sample to which it is added, and therefore the overall specificity of the sensor is determined by purity and choice of the primers used for target amplification in PCR (chemicals added to target DNA of a specific pathogen).” The research team envisions that with advancements like other dyes with higher specificity, target-specific probes and robust microfluidic chips, the system can be enhanced for improved sensitivity, specificity, and robustness.

The development of the device is in its nascent stages and with time more improvements are expected. “We are working on developing more time-efficient and low-cost methods for sample pre-processing, and robust and highly specific assays that can be used for optical and electrochemical DNA sensors. We have filed some patent applications based on these ideas and work, and more will be filed in future as we continue to make progress in this direction,” remarks Prof. Tallur about the future of the new device.

The successful application of this sensor could prove crucial for regular surveillance and early warning systems for potential epidemic outbreaks. It has the potential to revolutionise environmental screening methods for viral and bacterial infections, enabling early detection and prevention strategies to be initiated at the outset. The most important aspect is that it is possible to achieve all of this without a significant dent in the finances of institutions and nations.

Reference: Portable absorbance platform for sensing of viral and bacterial nucleic acid leveraging intercalation with methylene blue: Application for wastewater-based epidemiology. Biosensors and Bioelectronics: X Volume 14, September 2023. 

http://rapidmicromethods.com/files/regulatory.php. 

The study is available online in the journal ACS Sensors. The same group of researchers recently published a paper in the journal Nature Communications about an air monitor they had built to detect airborne SARS-CoV-2 — the virus that causes COVID-19 — within about five minutes in hospitals, schools and other public places.

The new study is about a breath test that could become a tool for use in doctors’ offices to quickly diagnose people infected with the virus. If and when new strains of COVID-19 or other airborne pathogenic diseases arise, such devices also could be used to screen people at public events. The researchers said the breath test also has the potential to help prevent outbreaks in situations where many people live or interact in close quarters — for example aboard ships, in nursing homes, in residence halls at colleges and universities, or on military bases.

“With this test, there are no nasal swabs and no waiting 15 minutes for results, as with home tests,” said co-corresponding author Rajan K. Chakrabarty, PhD, the Harold D. Jolley Career Development Associate Professor of Energy, Environment & Chemical Engineering at the McKelvey School of Engineering. “A person simply blows into a tube in the device, and an electrochemical biosensor detects whether the virus is there. Results are available in about a minute.”

Technology Behind the Test

The biosensor used in the device was adapted from an Alzheimer’s disease-related technology developed by scientists at Washington University School of Medicine in St. Louis to detect amyloid beta and other Alzheimer’s disease-related proteins in the brains of mice. The School of Medicine’s John R. Cirrito, PhD, a professor of neurology, and Carla M. Yuede, PhD, an associate professor of psychiatry — both also co-corresponding authors on the study — used a nanobody, an antibody from llamas, to detect the virus that causes COVID-19.

Chakrabarty and Cirrito said the breath test could be modified to simultaneously detect other viruses, including influenza and respiratory syncytial virus (RSV). They also believe they can develop a biodetector for any newly emerging pathogen within two weeks of receiving samples of it.

“It’s a bit like a breathalyzer test that an impaired driver might be given,” Cirrito said. “And, for example, if people are in line to enter a hospital, a sports arena or the White House Situation Room, 15-minute nasal swab tests aren’t practical, and PCR tests take even longer. Plus, home tests are about 60% to 70% accurate, and they produce a lot of false negatives. This device will have diagnostic accuracy.”

Development Journey

The researchers began working on the breath test device — made with 3D printers — after receiving a grant from the National Institutes of Health (NIH) in August 2020, during the first year of the pandemic. Since receiving the grant, they’ve tested prototypes in the laboratory and in the Washington University Infectious Diseases Clinical Research Unit. The team continues to test the device, to further improve its efficacy at detecting the virus in people.

For the study, the research team tested COVID-positive individuals, each of whom exhaled into the device two, four, or eight times. The breath test produced no false negatives and gave accurate reads after two breaths from each person tested. The clinical study is ongoing to test COVID-positive and -negative individuals to further test and optimize the device.

Strain Detection and Operation

The researchers also found that the breath test successfully detected several different strains of SARS-CoV-2, including the original strain and the omicron variant, and their clinical studies are measuring active strains in the St. Louis area.

To conduct the breath test, the researchers insert a straw into the device. A patient blows into the straw, and then aerosols from the person’s breath collect on a biosensor inside the device. The device then is plugged into a small machine that reads signals from the biosensor, and in less than a minute, the machine reveals a positive or negative finding of COVID-19.

Future Prospects

Clinical studies are continuing, and the researchers soon plan to employ the device in clinics beyond Washington University’s Infectious Diseases Clinical Research Unit. In addition, Y2X Life Sciences, a New York-based company, has an exclusive option to license the technology. That company has consulted with the research team from the beginning of the project and during the device’s design stages to facilitate possible commercialization of the test in the future.

Reference

“Rapid Direct Detection of SARS-CoV-2 Aerosols in Exhaled Breath at the Point of Care” by Dishit P. Ghumra, Nishit Shetty, Kevin R. McBrearty, Joseph V. Puthussery, Benjamin J. Sumlin, Woodrow D. Gardiner, Brookelyn M. Doherty, Jordan P. Magrecki, David L. Brody, Thomas J. Esparza, Jane A. O’Halloran, Rachel M. Presti, Traci L. Bricker, Adrianus C. M. Boon, Carla M. Yuede, John R. Cirrito and Rajan K. Chakrabarty, 27 July 2023, ACS Sensors. DOI: 10.1021/acssensors.3c00512

The study was funded by the National Institutes of Health (NIH) RADx-Rad program. Grant numbers U01 AA029331 and U01 AA029331-S1. Additional funding from the National Institute of Neurological Disorders and Stroke Intramural Research Program, the Uniformed Services University of Health Sciences, and the NIH SARS-CoV-2 Assessment of Viral Evolution (SAVE) Program.

The results were published in the Annals of Clinical Microbiology and Antimicrobials on Oct. 30.

Widespread in the environment, RGM pose challenges due to their high level of antibiotic resistance, mostly notably Mycobacterium abscessus. A rapid, accurate AST for RGM is urgently needed to improve clinical management, given the limitations of traditional culture methods and emerging molecular diagnostics.

Using the self-developed Clinical Antimicrobial Susceptibility Test Ramanometry (CAST-R) instrument, the team focused on Mycobacterium abscessus, the predominant pathogenic type among RGM, as a model to establish the heavy water–labeled rapid AST workflow for RGM (CAST-R-RGM). They obtained AST results based on "metabolic inhibition levels" calculated from Raman spectra data.

Compared to the traditional gold standard for AST (3–5 days), CAST-R-RGM shortens the test cycle to just 24 hours. Mao Yuli, co-first author of the study from QIBEBT, highlighted an accuracy rate of 90% for detecting clarithromycin susceptibility and 83% for detecting linezolid susceptibility in clinical isolates of Mycobacterium abscessus. This represents a significant improvement in both the speed and accuracy of detection.

Through a comprehensive analysis of Raman spectroscopy, the researchers further identified distinctive Raman spectra features of Mycobacterium abscessus standard strains under different concentrations and durations of exposure to two drugs. These features, termed the Raman barcode of cellular stress-response (RBCS), outline the dynamic cellular metabolic profile under drug exposure.

Prof. Sun Luyang, co-corresponding author of the study, said that the RBCS not only characterizes the metabolic heterogeneity of drug-exposed Mycobacterium abscessus cell populations at the level of the metabolic phenome, but also reveals the mechanism of bacterial metabolic transformation after drug exposure.

"Effective evaluation of drug sensitivity in RGM is essential to improve patient prognosis. The CAST-R-RGM technology represents a significant advance in achieving rapid and accurate drug susceptibility testing," said Prof. Pang Yu, co-corresponding author of the study from the Beijing Chest Hospital.

"CAST-R-RGM demonstrates the capabilities of our innovative CAST-R instrument in addressing urgent clinical needs for rapid pathogenic microorganism AST. We are committed to expanding the application of CAST-R to various types of pathogens," said by Prof. Xu Jian, co-corresponding author of the study from QIBEBT.

More information: Weicong Ren et al, Rapid Mycobacterium abscessus antimicrobial susceptibility testing based on antibiotic treatment response mapping via Raman Microspectroscopy, Annals of Clinical Microbiology and Antimicrobials (2023). DOI: 10.1186/s12941-023-00644-5

A revision to chapter <1071>, Rapid Microbial Tests for Release of Sterile Short-Life Products: A Risk-Based Approach, has also been published for public comment. Additionally, chapter <86>, Bacterial Endotoxins Test Using Recombinant Reagents, can also be reviewed and commented on.

All chapters are currently open for public comment through March 31, 2024.

A summary of each chapter is provided below.

<72> Respiration-Based Microbiological Methods for the Detection of Contamination in Short-Life Products. 

This new chapter proposal is based on the version published in PF 46(6) as "Respiration-Based Rapid Microbial Methods for the Release of Short Shelf Life Products". The previous proposal has been canceled and is being replaced by this updated version, which includes the following revisions by the Microbiology Expert Committee:

• Change the title to "Respiration-Based Microbiological Methods for the Detection of Contamination in Short-Life Products."
• Change the requirements of the selection of culture media and incubation temperature to align with existing USP chapters.
• Add more requirements in the Method Suitability Test to include the following:
• Inoculation of test microorganisms at not more than 10 CFU.
• Specification that the list of microorganisms in Table 1 is the minimal requirement. Inclusion of product- and processing-relevant strains and local isolates should be considered with appropriate risk-based justification.
• Specification that positive control and negative controls should be included in the suitability test.
• Introduction of a safety margin concept to determine the longest time to detection.

<73> ATP Bioluminescence-Based Microbiological Methods for the Detection of Contamination in Short-Life Products. 

This new chapter proposal is based on the version published in PF 46(6) as "ATP Bioluminescence-Based Rapid Microbial Methods for the Release of Short Shelf Life Products". The previous proposal has been canceled and is being replaced by this updated version, which includes the following revisions by the Microbiology Expert Committee:

• Change the title to "ATP Bioluminescence-Based Microbiological Methods for the Detection of Contamination in Short-Life Products".
• Change the requirements of the selection of culture media and incubation temperature to align with existing USP chapters.
• Add more requirements in the Method Suitability Test to include the following:
• Inoculation of test microorganisms at not more than 10 CFU.
• Specification that the list of microorganisms in Table 1 is the minimal requirement. Inclusion of product- and processing-relevant strains and local isolates should be considered with appropriate risk-based justification.
• Specification that positive control and negative controls should be included in the suitability test.
• Guidance for the direct inoculation of the culture medium and membrane filtration when testing for the microbial detection in the product to be examined.
• Introduction of a safety margin concept to determine the longest time to detection.

<1071> Rapid Microbial Tests for Release of Sterile Short-Life Products: A Risk-Based Approach. 

This proposal is based on the version of the chapter official as of December 1, 2019. The Microbiology Expert Committee proposes the following revisions:

• Change the title to “Rapid Microbiological Methods for the Detection of Contamination in Short-Life Products—A Risk-Based Approach”.
• Redefine the application of rapid microbiological methods to short-life products.
• Introduce a calculation to evaluate the probability of contamination and define an adequate sample volume.
• Remove the limit of detection as the critical operation parameter to be used in determining a risk-based microbiological method.
• Provide more guidance on the validation and suitability testing of the rapid microbiological method.
• Update the example technologies to align with the USP Microbiology Expert Committee evaluation: ATP bioluminescence, nucleic acid amplification, respiration, and solid phase cytometry.

<86> Bacterial Endotoxins Test Using Recombinant Reagents. 

This proposed new test chapter provides additional techniques using non-animal derived reagents to the Bacterial Endotoxins Test <85>.

This general chapter is not currently being introduced into a specific monograph or listed in General Notices. It is the responsibility of the user to review the supplier's primary validation package and to verify product suitability for use in testing specific products or materials. This verification must include specific experiments to confirm that the method is suitable for its intended purpose under the conditions of use for the material, drug substance, and/or drug product. The selected verification experiments should be based on an assessment of the complexity of the material to which the method is being applied. The user should refer to Verification of Compendial Procedures <1226>. Regulatory authorities may require supplemental data prior to acceptance. An example of supplemental data may include a comparative study of the material tested by techniques described in this chapter and those in <85>.

Remember: the USP must receive comments no later than March 31, 2024 to be considered. You may submit comments by clicking on the "Submit Comment" button found in each proposed chapter. 

Sepsis, also known as ‘blood poisoning’, is hard to identify and there is currently no test to diagnose it. Without prompt treatment, it can lead to multiple organ failure and death. Every year in the UK there are 48,000 sepsis-related deaths, according to the UK Sepsis Trust. 

The non-invasive and low-cost test being trialled for the first time in the UK uses patient blood samples to identify high levels of DNA fragments associated with sepsis within just 45 minutes. It could be used to screen patients for sepsis when they present with symptoms in the emergency department (A&E), or if their condition deteriorates on a hospital ward.

Early results suggest the test is able to identify patients who may be at higher risk of developing sepsis and progressing to organ failure. If the trial is successful, the test will help clinicians to identify the sickest patients more quickly and respond faster to prevent a patient getting sicker.

Sepsis occurs when the immune system, the body’s defense mechanism to infection, goes into overdrive. Immune cells, known as neutrophils, release an excessive number of spider-like-webs of DNA in an attempt to trap infections and prevent them spreading further – potentially leading to organ damage. These webs are called neutrophil extracellular traps (NETs).

The test being trialled at Guy’s and St Thomas’ NHS Foundation Trust identifies a protein found in NETs. Quantifying the levels of these in the blood will indicate if someone has too many NETs, and therefore is more likely to have, or develop, sepsis. This is the first time a test to detect NETs directly has been brought to the bedside. 

The year long study, launched on 27 November with funding from Volition Diagnostics UK Limited, will test the protein levels of 450 patients with sepsis or septic shock in the intensive care unit at St Thomas’ hospital. No additional blood samples are required from participants in the study. The success of the new test will be compared with the current standard blood tests used by clinicians to evaluate sepsis. These cannot diagnose sepsis in isolation.

If successful, the new test could also help in triaging patients, making it easier to plan admissions and discharge from critical care. Additionally, there is ongoing research into the role of NETs as a potential new treatment for sepsis.

Dr Andrew Retter, critical care consultant at Guy’s and St Thomas’ who is leading the study, said:

Detecting sepsis early is critical to saving lives. Sepsis is the number one cause of death in hospitals and mortality increases as much as 8% for every hour that treatment is delayed.

Being able to spot those patients most at risk of sepsis using a simple blood test would be a paradigm shift in the field and could save thousands of lives every year.

Dr Ron Daniels BEM, Founder and Joint CEO of the UK Sepsis Trust said: "Sepsis is one of the biggest causes of avoidable harm and death within our NHS. Delays in diagnosis results not only in lives lost, and not only in increased cost of care, but also in poor outcomes for survivors, including disability.

"Any test which can help us to identify which patients are at increased risk of sepsis can ensure that we identify and treat patients with the most urgent need first: if this research demonstrates that NET proteins fulfil their promise as a risk stratification tool then lives will undoubtedly be saved."

The identification of microorganisms involved in infection is a major challenge in ensuring that patients receive optimal treatment. Recent epidemics have shown the importance of a tool capable of detecting new or unexpected pathogens and those with rapidly evolving genomes. Currently, the search for infectious agents is mostly 'targeted' and requires prior knowledge of the possible causes of infection. In many cases however, no microorganism is identified by first-line testing and the cause of the infection remains unknown, leading to suboptimal treatment.

Metagenomics(1) using next-generation sequencing (mNGS) can identify a wide range of pathogens, including rare or novel microorganisms. This study aims to improve use of this innovative microbial identification technique, which remains complex and costly for hospital laboratories as it requires cross-disciplinary skills ranging from specific sample preparation to bioinformatics analysis of a large number of sequences. The hospital team drew on the technical and IT skills of the Institut Pasteur's Pathogen Discovery Laboratory(2) and worked to make mNGS available within the AP-HP and to practitioners in healthcare centers in mainland France and overseas.

In this study, 742 samples were collected for mNGS analysis from 523 patients between October 29, 2019 and November 7, 2022. Samples were accompanied by a mandatory prescription form completed by the physician, indicating the level of clinical suspicion of infection.

The results relate to a panel whose initial suspicion of infection was either high (63%) or low (37%). In 117 patient samples where infection was strongly suspected – i.e. 25% of samples where infection was strongly suspected according to the practitioners' preliminary assessment – causative or potentially causative pathogens were detected.

The diagnostic yield of mNGS was particularly high in immunocompromised patients and in patients with neurological disorders where brain biopsies were available. In fact, mNGS more easily detects a causative or potentially causative pathogenic virus in brain biopsies than in cerebrospinal fluid, which is traditionally used because it is easier to obtain. Furthermore, the study showed that stool analyses could be used to investigate not only digestive disorders, but also hepatitis and various neurological symptoms.

In addition, the clinical performance of mNGS compares favorably to conventional microbiology. Together with future studies, the results of this prospective observational study will help to define the role of mNGS in decision making relating to diagnosis and treatment.

"The Microbiology Laboratory (Prof. Leruez-Ville), in conjunction with the Department of Infectious and Tropical Diseases (Prof. Lortholary and Prof. Lecuit) and the Pediatric Immunohematology and Rheumatology Department (Prof. Quartier dit Maire and Prof. Neven) at Necker-Enfants Malades Hospital (AP-HP), has developed extensive expertise in the management of immunocompromised patients prone to infections caused by unusual microorganisms. The Institut Pasteur's Pathogen Discovery Laboratory2, which was led by Prof. Marc Eloit at the time of the study, had already optimized the use of high-throughput sequencing for pathogen discovery by developing the technique for both sample preparation methods and bioinformatics analysis tools. This collaboration between Necker-Enfants Malades (AP-HP) and the Institut Pasteur was therefore well placed to identify novel causes of infection in cases where conventional techniques were missing diagnoses," explains Dr. Anne Jamet, the study's final author, who is head of mNGS at Necker-Enfants Malades Hospital (AP-HP) and a researcher at the Institut Necker-Enfants Malades (AP-HP).

"Our instincts have translated into reliable diagnoses in everyday practice as well as several noteworthy discoveries, including the identification of a new virus responsible for hepatitis," adds Dr. Jacques Fourgeaud, first author of the study and lead virologist for mNGS at Necker-Enfants Malades Hospital (AP-HP).

"This sequencing-based tool is now indispensable for diagnosing patients with a suspected infection. We are now using it earlier and earlier in severe cases, particularly those involving the brain, and in immunocompromised adults and children," says Prof. Olivier Lortholary, an infectious diseases specialist who is head of the Department of Infectious and Tropical Diseases at Necker-Enfants Malades Hospital (AP-HP) and co-author of the study.

"We're delighted to be able to contribute to better medical care, while at the same time increasing our knowledge of infectious diseases," adds Prof. Marc Eloit, co-last author of the study, who led the Pathogen Discovery Laboratory2 until September 2023 and is now a visiting researcher at the Institut Pasteur. The study also provides an insight into the future of infection diagnostics. "The microorganisms we identify with the Necker microbiology laboratory will enable us to develop new tools to make sequencing technology faster and more accessible for front-line microbiological analysis while enhancing its potential for the discovery of new human pathogens," says co-author Philippe Pérot, a research engineer in the Institut Pasteur's Pathogen Discovery Laboratory2 and lead for mNGS at the Institut Pasteur.

The study was funded by Necker-Enfants Malades Hospital (AP-HP) and the Institut Pasteur.

1. Study of all genomes from a single environment and interactions between them
2. The Institut Pasteur's Pathogen Discovery Laboratory was led by Prof. Marc Eloit until August 31, 2023. Dr. Nolwenn Dheilly took over as head of the laboratory on September 1, 2023.

Source

Performance of clinical metagenomics in France: a prospective observational study, The Lancet Microbe, 1er décembre 2023

The environments in which these bacteria are most frequently found include soil, plants, and water. They can even be found on human and animal skin, without causing illness, in a process known as bacterial colonization. Microbiological research can help establish the cause of certain infectious diseases, making it easier to choose the best treatment. This is why it is important to find a quick and easy way to identify these bacteria.

A new study, published in BioRisk, has explored this by applying spectroscopic techniques for quick analysis directly from an object, which in this case was turtle skin.

"Microbial organisms play key roles in animal health and ecology. The European pond turtle often lives in city zoo gardens and private houses. Often, the most commonly found bacteria from turtle skin surfaces was Pseudomonas species," says Aleksandrs Petjukevics of Daugavpils University, whose team conducted the study.

What is Raman spectroscopy?

"Classical microbiological research techniques have several disadvantages: first of all, it is a rather lengthy process. The minimum period is 3-4 days, but many days and even weeks may pass before the isolated pathogen is accurately identified, and it uses expensive chemicals and resources," says Petjukevics.

As an alternative, spectrometry makes it possible to identify a prepared sample of a microorganism while reducing the identification time to 5-30 minutes. Raman spectra represent an ensemble of signals that arise from the molecular vibrations of individual cell components of gram-negative bacteria, integrating over proteins, lipids, and carbohydrates.

"This non-destructive chemical analysis technique provides detailed information about chemical structure, phase and polymorphy, crystallinity, and molecular interactions. It is based on the interaction of light with the chemical bonds within a material," Petjukevics says.

Research results and implications

The study's findings showed that Pseudomonas bacteria can be quickly identified using this detection technology, with excellent analytical and diagnostic sensitivity, making it a dependable technique. Unlike other methods, this technique does not require long-term bacterial sample preparation and expensive reagents, which makes it promising for studying other strains of bacteria.

"This study demonstrated the ability to obtain fast and high-quality Raman spectra of bacterial cells using vibrational spectroscopy," concludes Petjukevics. "Raman spectroscopy can be considered an express method for identifying microorganisms. It holds great potential for future research involving different microorganisms."

Source: Aleksandrs Petjukevičs et al, Prospects and possibilities of using Raman spectroscopy for the identification of Pseudomonas aeruginosa from turtle Emys orbicularis (Linnaeus, 1758) skin, BioRisk (2023). DOI: 10.3897/biorisk.21.111983

Far too many antibiotics are used around the world. As a result, bacteria are becoming resistant.

Curing bacterial diseases is becoming more difficult than before, because antibiotics are perhaps our foremost weapons in the fight against them.

An important step towards using fewer antibiotics is to find better methods for identifying pathogens, and here is the good news.

We have developed a simple tool that can identify all of the genetic material in bacteria. This allows us to find out more quickly what kind of bacteria a sick person or animal is affected by, or what kind of bacteria are found in food or the environment. We can then also decide whether it is necessary to use antibiotics against the bacterium, and if so what kind, so we don't have to use as much medication. (Professor Erika Eiser at Norwegian University of Science and Technology's (NTNU)Department of Physics)

No need to copy genetic material

An international research group is behind the latest findings. The results have been presented in the prestigious Proceedings of the National Academy of Sciences (PNAS) journal. Playing a key role in the work was Dr Peicheng Xu from the Institute of Physics Chinese Academy of Sciences in Beijing, for whom Eiser was previously an academic supervisor.

One reason why the new method is faster is that users do not have to go through a step called 'gene amplification'. This involves making several copies of the genetic material so it is easier to analyse, but this step can now be skipped.

"We can analyse all of the bacterium's DNA without gene amplification by using a method previously used in simulations," says Professor Eiser.

Eiser was part of a research group led by Tine Curk from Johns Hopkins University that developed the theory behind the method, which also works in reality.

"We get excellent results when we apply the theoretical method to real samples," says Professor Eiser.

The method creates clumps

This paragraph might be a bit difficult to understand, but basically, DNA is made up of rows of so-called nucleotides. The new method enables researchers to find short sequences of the bacteria's DNA. They do this by seeing how these sequences bind to different variants of DNA that are grafted onto colloids, which are particles dissolved in a liquid.

If you are interested in finding out more, you can read about the process in more detail here. What it means, however, is that researchers can quickly identify the bacteria, because they bind themselves to these colloids in various ways and cause them to clump together.

The bottom line is: you don't have to analyse so much material. You can skip the step of having to copy them, and this saves time and money.

"Using this method, we saw how as few as five E. coli bacteria caused the colloids to create clusters," says Professor Eiser.

Still a way to go

All of this is currently in its early stages. Eiser has published a proof-of-principle experiment. This means that there is still a lot of work to be done before it becomes a widely used method.

"The findings can provide us with a reliable method for identifying pathogens in disciplines such as food safety, disease control and environmental monitoring," says Professor Eiser.

In a world where more and more bacteria are becoming resistant to antibiotics, this is particularly good news.

Journal Reference: Xu, P., et al. (2023). Whole-genome detection using multivalent DNA-coated colloids. Proceedings of the National Academy of Sciences. doi.org/10.1073/pnas.2305995120.

In their study published in Communications Biology, the team used a combination of fluorescence microscopy and artificial intelligence (AI) to detect antimicrobial resistance (AMR). This method relies on training deep-learning models to analyse bacterial cell images and detect structural changes that may occur in cells when they are treated with antibiotics. The method was shown to be effective across multiple antibiotics, achieving at least 80% accuracy on a per-cell basis.

The researchers say their model could be used to identify whether cells in clinical samples are resistant to a range of a wide variety of antibiotics in the future.

Co-author of the paper Achillefs Kapanidis, Professor of Biological Physics and Director of the Oxford Martin Programme on Antimicrobial Resistance Testing, said:

‘Antibiotics that stop the growth of bacterial cells also change how cells look under a microscope, and affect cellular structures such as the bacterial chromosome.’

‘Our AI-based approach detects such changes reliably and rapidly. Equally, if a cell is resistant, the changes we selected are absent, and this forms the basis for detecting antibiotic resistance.’

The researchers tested their method on a range of clinical isolates of E. coli, each with varying levels of resistance to the antibiotic ciprofloxacin. The deep-learning models were able to detect antibiotic resistance reliably and at least 10 times faster than established state-of-the art clinical methods considered to be gold standard.

The team hopes to continue developing their method so that it becomes faster and more scalable for clinical use, as well as adapting its usage for different types of bacteria and antibiotics.

According to the Global Research on Antimicrobial Resistance (GRAM) Project – a partnership involving the University – almost 1.3 million people died in 2019 due to AMR.

Current testing methods rely on growing bacterial colonies in the presence of antibiotics. However, such tests are slow, often requiring several days to understand how resistant bacteria are to a range of antibiotics.

This can be problematic when patients have potentially life-threatening infections, such as sepsis, requiring urgent treatment. This usually forces doctors to either prescribe specific antibiotics based on their clinical experience or a cocktail of antibiotics known to be effective across multiple bacterial infections. However, if ineffective antibiotics are prescribed the patients’ infections may get worse and they will need to be treated with more antibiotics. One potential outcome of this is increased antimicrobial resistance to antibiotics in the community.

The researchers say that if developed further, the rapid nature of their method may facilitate targeted antibiotic treatments – helping to decrease treatment times, minimise side effects, and ultimately slow down the rise of AMR.

Co-author of the paper Dr Piers Turner, Postdoctoral Researcher with the Oxford Martin Programme on Antimicrobial Resistance Testing and the University’s Department of Physics, said:

‘In an era where antimicrobial resistance poses a critical public health threat, our team has made a ground-breaking advancement toward rapid detection of antimicrobial resistance. This innovation may hold the potential to revolutionise the way we respond to infectious diseases, allowing for more precise and timely treatment decisions, ultimately saving lives.’

Co-author of the paper Aleksander Zagajewski, doctoral student with the University’s Department of Physics, said:

‘Time is beginning to run out for our antibiotic arsenal; we are hoping our novel diagnostics will pave the way for a new generation of precision treatments for the most sick patients.’

Researchers from across the University contributed to the study, including from the Department of Physics, Nuffield Department of Medicine, Sir William Dunn School of Pathology and Nuffield Department of Women’s Reproductive Health. Researchers from the Oxford University Hospitals NHS Foundation Trust’s Department of Microbiology and Infectious Diseases were also involved.

Reference: Deep learning and single-cell phenotyping for rapid antimicrobial susceptibility detection in Escherichia coli. Communications Biology volume 6, Article number: 1164 (2023). 

The new strategy sets out a programme to improve UKHSA's ability to detect and understand the pathogens that pose the greatest risks to the UK population, which will help to ensure that policy and public health decision making is underpinned by the best possible scientific evidence.

Sequencing pathogen genomes to examine their genetic code can reveal vital information about their identity and ancestry. When combined with other health data and research, it becomes a powerful tool for understanding how a pathogen is behaving in a human population and why.

We can use genomics to detect new threats, to:

• identify outbreaks and find their source
• track transmission of disease between people
• understand whether human immune responses will be protective
• choose the most effective vaccines for the population
• detect antimicrobial resistance and determine the optimal treatments for individuals 

The COVID-19 pandemic response showed us that genomics can be fully integrated into public health systems and can inform decision-making locally, nationally and globally. The UK submitted over 3 million SARS-CoV-2 sequences to the international GISAID database over the course of the pandemic, a quarter of the global total and more than any other nation except the USA.

Since then, genomics has continued to show its value - identifying foodborne outbreaks, helping us to assess the risk from emerging pathogens like mpox and influenza and helping to inform the choice of treatment for diseases like tuberculosis.

The UKHSA Pathogen Genomics Strategy recognises that pathogen genomics is a crucial element of modern infectious disease control, and it will ensure that the UK remains at the forefront of genomic research, developing and implementing genomics to benefit public health, protect lives and livelihoods.

By leveraging existing infrastructure, capacity, and scientific capabilities, the strategy outlines UKHSA's vision for pathogen genomics over the next five years through seven strategic aims. These are:

• using pathogen genomic data to optimise clinical/public health decision-making, from local to global settings;
• using pathogen genomic data to drive improvements in diagnostics, vaccines and therapeutics;
• providing a nationally coordinated, scaled-up pathogen genomics service;
• supporting a pathogen genomics workforce transformation within and beyond UKHSA;
• committing to pathogen genomic data sharing and global collaboration;
• driving innovation in pathogen genomics;
• building high-impact pathogen genomic services that are good value for money

Each of these strategic aims will support and boost UK capability in 3 priority public health areas, directly aligned with UKHSA's priorities:

• antimicrobial resistance;
• emerging infections and biosecurity;
• vaccine preventable diseases and elimination programmes.

Dr Meera Chand, Deputy Director for Emerging Infections and Clinical Lead for the Genomics Programme at UKHSA said:

Pathogen genomics is an essential component of the world's ability to respond quickly to infectious disease threats, whether by increasing the speed at which we can identify emerging pathogens or control outbreaks, or by improving our understanding of what treatments or vaccines might be effective.

The new UKHSA Pathogen Genomics Strategy will provide a framework for us to build on our already substantial capacity in this area, and to implement genomics across all our work to keep the public safe from threats to their health.

Professor Dame Jenny Harries, UKHSA Chief Executive said:

UK experts in the field of pathogen genomics made a vital contribution to the COVID-19 pandemic response and pathogen genomics remains central to the national and international effort to keep the public safe from many other types of infectious disease threats, from tuberculosis to mpox and avian influenza.

We know it will become even more important in the years to come, and our new strategy will ensure that UKHSA continues to be at the forefront of implementing this technology to keep our communities safe, save lives and protect livelihoods."

Minister for Women's Health Strategy, Maria Caulfield said:

Detecting new infectious disease threats, identifying outbreaks and finding their source, and tracking transmission of disease through the community are of critical importance in keeping the country safe from threats to public health.

This new strategy published by UKHSA will help us to identify and analyse the pathogens which pose the greatest threat to the UK population, and to respond to them quickly and effectively.

Case studies of the recent impact of UKHSA Genomics 

Salmonella

In April 2022, UKHSA used Whole Genome Sequencing (WGS) to identify and inform the response to contaminated chocolate products. The chocolate was contaminated with a very distinct type of salmonella, from a genetic cluster not seen previously in the UK.

Before the advent of genotyping, we could not always confirm with certainty what organisms were present in contaminated products, hindering decision-making around food recalls. Now, genome sequencing provides the evidence base needed to inform these decisions with a much greater level of confidence.

Early notification of the detection of the outbreak, along with epidemiological investigations and rapid sharing of microbiological sequence information, provided confirmation of the link between the company's products and the outbreak. Routine surveillance using WGS was crucial in detecting the unique genetic cluster.

Following the alert, comparisons of the UK data with national sequences in other countries revealed more cases linked to the outbreak across Europe. A larger multi-country investigation was launched and resulted in the identification of chocolate products from the same business as the source of the outbreak.

SARS-CoV2 variant: Alpha

In March 2020, while investigating an unexplained spike in COVID-19 cases in Kent, scientists from UKHSA's predecessor organisation, Public Health England, sequenced the genomes of samples taken from people with COVID-19.

Their analysis showed that a large number of these sequences were very similar and genomically distinct from other SARS-CoV-2 samples sequenced in the UK up to that point. This was the first identification of the Alpha variant of SARS-CoV-2, a variant with much higher levels of transmissibility than the dominant variants of the time.

Without the use of genomic sequencing, it would have taken far longer for public health officials to understand the significance of the rising cases in Kent, and interventions to slow its spread would have been significantly delayed. In fact, the use of genomic sequencing prevented the hospitalisation, and even deaths, of many more people.

SARS-CoV2 variant: Omicron

In November 2021, the UKHSA's genomic sequencing programme identified the first cases of the Omicron variant of SARS-CoV-2 in the UK, having previously been identified in South Africa, Botswana and Hong Kong.

The speed of this detection - which would not have been possible without Whole Genome Sequencing (WGS) - meant that UK health protection teams were able to take rapid action to slow its onward spread.

Omicron went on to become the dominant SARS-CoV-2 variant around the world, but the delay that the use of WGS bought the UK once again meant that interventions could be put in place before it took over, lessening its potential impact and reducing the number of people in danger of hospitalisation and death.

SARS-CoV2 variant: BA.2.86

Last year scientists used global sequence data to identify a SARS-CoV2 lineage with an unusual mutation. Once recognised as a new variant, we were able to track its appearance in the UK and to quickly identify and control local outbreaks.

Our knowledge of mutations quickly allowed us to establish vaccine and diagnostic test efficacy via a programme of laboratory work to determine that current vaccines and Lateral Flow Devices (LFDs) were effective against BA.2.86.

Tuberculosis (TB) and Antimicrobial resistance (AMR)

In 2017, Public Health England (PHE), one of UKHSA's predecessor organisations, announced its pioneering use of Whole Genome Sequencing (WGS) in diagnosing and managing TB. The UK now uses WGS as a routine tool in TB surveillance - setting it apart from most European neighbours.

Prior to the adoption of WGS in laboratories, our ability to trace the spread of TB between people was far more limited and less precise.

To build up a picture of how the virus could be spreading across populations, scientists first determine whether different cases of TB are related.

Previous methods relied on identifying repeating segments found in the bacteria's genetic code, and then comparing these to those found in bacteria from other samples. By contrast, Whole Genome Sequencing takes the entire genetic code of TB bacteria from different samples, allowing them to be compared at a very detailed level.

Since 2015 there have been a number of improvements in TB diagnostics due to the introduction of Whole Genome Sequencing, including the ability to determine and monitor TB transmission, reduce the diagnosis time of new cases from over a month to just over a week, and make treatment choices which are best suited to each individual - slowing the march of antimicrobial resistance in multidrug-resistant TB.

Where previously it could take up to a month to confirm a diagnosis of TB, confirm the treatment choices and to detect spread between cases, this can now be done in just over a week. This slows the spread of the disease, informs appropriate medication choice and aids in the fight against anti-microbial resistance.

Rajan Chakrabarty, the Harold D. Jolley Career Development Associate Professor of Energy, Environmental & Chemical Engineering at the McKelvey School of Engineering, and John Cirrito, professor of neurology at the School of Medicine, will adapt their COVID-19-detecting breathalyzer to one that can also screen for influenza A and RSV with a two-year $3.6 million grant from Flu Lab, an organization that funds efforts to defeat influenza. With the funding, they plan to take the technology from bench into clinical trials at Washington University’s Infectious Disease Clinical Research Unit with the goals of design and specifications for commercial application and preparing the breath test for FDA registration.

COVID-19, RSV and influenza A are the most predominant of seasonal viruses, each transmitted through aerosols and droplets that are easily spread indoors. Influenza A infects up to 40 million people in the U.S. annually, and RSV can hospitalize 240,000 children and older adults. While preferable to diagnose viruses early, the viral load is often low in the early stages of the disease, requiring a rapid and sensitive test. An accurate diagnostic device that provides fast sampling and test results and could identify multiple viruses even at early stages would reduce time to treatment and lead to earlier decisions by individuals to isolate, more efficiently protecting households, communities and businesses.

“The testing options available now are not the aerosol itself, but biomarker tests, which is an indirect detection,” said Chakrabarty, an aerosol scientist. “The second disadvantage is that the commercially available devices are bulky, and a patient tires out blowing into it, so it’s not user-friendly. We really focused on the design of our exhaled breath collection unit to include the best of both worlds.”

The work stems from a breathalyzer the team developed for COVID-19 that was detailed in ACS Sensors in July 2023. To conduct the breath test, the researchers insert a straw into the device. A person blows into the straw, and aerosols from the person’s warm breath collect on a cold surface inside the device, which are then read by the biosensor. The device then is plugged into a small machine that reads signals from the biosensor. In less than a minute, the machine reveals a positive or negative finding of COVID-19, and potentially, RSV and influenza A.

The device uses a biosensor adapted from an Alzheimer’s disease-related technology developed a decade ago by Cirrito and Carla M. Yuede, an associate professor of psychiatry at the School of Medicine. Cirrito and Yuede used a nanobody — an antibody from llamas — to detect the virus that causes COVID-19. The researchers began working on the breath test device — made with 3D printers — after receiving a grant from the National Institutes of Health (NIH) in November 2020.

“For COVID, we got a nanobody from David Brody, who used to be at Washington University and is now at the National Institutes of Health,” Cirrito said. “We will make new nanobodies to detect influenza A and RSV. But ultimately the biosensors can be adapted for all kinds of airborne pathogens, including other viruses or even bacteria and fungi.”

Each COVID-19-specific test should cost less than $20, leading Chakrabarty to estimate an even lower cost for a combined test when produced in larger quantities.

The team will work with design firm TE Connectivity to adapt the current research prototype that detects COVID-19 into the multi-pathogen device that can be tested for an FDA clinical trial and eventually commercialized.

While the initial device will be built to detect the three most common seasonal viruses, the team plans to include other pathogens, emerging pathogens or bioterror threats in future designs, which could be useful for the military or the federal government.

“The team is very excited to take something we developed in the lab and finally have an avenue to make it a real product so people around the world can use it,” Chakrabarty said. “A rapid breath diagnostic that would screen a large group of people for viruses could seriously reduce disease spread in crowds. Or rapidly diagnosing which respiratory virus someone has in a clinic means they could get the right medicine immediately instead of waiting hours or even days before they could get treated and start feeling better.”

The team is working with the university’s Office of Technology Management to license the technology for potential commercialization and has continued development support from the NIH. In addition, Y2X Life Sciences, a New York-based company, has an exclusive option to license the technology. That company has consulted with the research team from the beginning of the project and during the device’s design stages to facilitate commercialization of the test in the future.

From fireflies to lantern fish, many animals possess the chemical tools to produce light. Typically, this reaction requires the substrate luciferin and the enzyme luciferase. However, a class of less discriminating luciferins, known as imidazopyrazinone-type (IPT) compounds, can glow when encountering other proteins, including ones that aren't considered enzymes. Previous research suggests that IPT luciferins could serve as the basis for a new type of medical test that uses luminescence to announce the presence of a target protein in a specimen. Ryo Nishihara, Ryoji Kurita and colleagues suspected that an IPT luciferin could react with the SARS-CoV-2 spike protein, which allows the virus particles to invade cells and cause COVID-19 - and open the door to develop a glowing test.

The team first investigated 36 different IPT luciferins' abilities to react with a single unit of spike protein. Only one molecule, which came from tiny crustaceans from the genus Cypridina, emitted light. The researchers then tested the luciferin's activity with the spike protein in its natural state, as three units folded together. They found that, over the course of 10 minutes, an adequate amount of light could be detected. A commercially available luminescence reading device was required; the light could not be seen by the naked eye. Additional experiments indicated that the IPT luciferin was selective because it did not glow when exposed to six proteins that occur in saliva. They define this specific luminescence reaction by non-luciferase biomolecules as "biomolecule-catalyzing chemiluminescence (BCL)".

Finally, they found that the luciferin could detect the amount of the spike protein in saliva with the same accuracy as a technique currently used in vaccine development. However, the luciferin system delivered results in one minute -; significantly faster than the current rapid point-of-care tests.

This BCL-based approach could serve as the basis for a simple "mix and read" test in which the IPT luciferin is added to untreated saliva from someone suspected of having COVID-19, according to the researchers. They note that a similar approach could be adapted to detect other viruses that possess spike-like proteins, such as influenza, MERS-CoV and other coronaviruses.

Malaria is the leading cause of illness and death in many low-income countries, with young children and pregnant women most affected.

In 2022, there were 608,000 malaria deaths worldwide, with 95 per cent of them occurring in the African region, according to the World Health Organization.

Detecting malaria in people who do not show symptoms is vital in order to better control the tropical disease in endemic areas, the researchers said in a study published this month (4 January) in the journal The Lancet Microbe.

“Our current findings provide critical information on the burden of asymptomatic malaria that we hope one day will be useful to the national malaria control program in Uganda and other malaria-endemic African countries.”

Tonny Owalla, researcher at Medical Biotech Laboratory, Kampala

The scientists from the University of Washington and Med Biotech Laboratories in Kampala said that due to the changing nature of malaria pathogens, parasite densities in the blood can suddenly drop below the level of detection. This is especially the case when older, less sensitive tests are used and when testing is done only at a single point in time.

Sean Murphy, professor of laboratory medicine and pathology at the University of Washington and lead author of the study, said: “To make anti-infection vaccines, drugs and therapeutics and test them in endemic areas means that you need diagnostic tools that can detect even the lowest density infections.”

He noted that the ultrasensitive molecular diagnostic tools are more analytically sensitive than other tests like blood smear, malaria rapid diagnostics tests, and even other types of molecular tests.

“This means we can ‘see deeper into the water’ and identify true, albeit low density infections that would have been missed by other tests,” Murphy said.

Murphy explains that having all this information can help researchers better assess candidate vaccines and drugs to decide which products provide the most effective outcomes.

Ultrasensitive tests

The researchers used ultrasensitive molecular diagnostic tools to test adults aged 18 to 59 and children aged eight to 17 who were not pregnant and were not under malaria medication in the Katawki district in eastern Uganda, which has a high incidence of malaria.

They tested dried blood spots for the presence of Plasmodium ribosomal RNA, which helps produce the parasite proteins, to determine and classify the type and densities of the parasites over a period of one month.

By analysing the resulting data, the researchers hoped to discern a sampling schedule -comparable to testing every day but less burdensome – to reliably identify asymptomatic cases.

About 60 per cent of participants had a Plasmodium infection at some point during the study. Fewer than half had an infection detected at the start of the study. The average infection rate was 30 per cent.

“We know that Plasmodium falciparum is common in Africa and is the most likely species to make people sick with malaria,” Murphy told SciDev.Net.

“I was surprised by the high number of P falciparum in our study,” he added.

“In some cases, these were present on their own in participants, but in other cases participants had mixed species infections.”

In a few cases, a species present at the start of the month tapered off and a new later emerged, he added.

“To capture these transitions with our approach was very enlightening,” he said.

‘Emerging trend’

Tonny Owalla, a researcher at Medical Biotech Laboratory in Kampala and co-author, told SciDev.Net that there is an emerging trend of parasite prevalence in children over five years old in Uganda with no symptoms.

He says more research is needed into the dynamics of asymptomatic malaria.

“We still need to build the body of evidence about asymptomatic infections before health ministries and other agencies can act on the information,” Owalla told SciDev.Net.

“Our current findings provide critical information on the burden of asymptomatic malaria that we hope one day will be useful to the national malaria control program in Uganda and other malaria-endemic African countries.”

Peter Ofware, Kenya’s country director for the global health and human rights organisation, HealthRight International, says multiple approaches are needed to fight malaria.

“It is encouraging that more vaccine candidates are being introduced, but none so far has achieved the desired efficacy rate,” he told SciDev.Net.

“Any innovations that can lead to better vaccines and treatments are most welcome.”

In a four-year project funded by CEPI and led by FIND, the team will examine and evaluate all available point-of-care testing options for the two diseases. They will work to advance the best performing ones for further testing, approval and widespread use down the line.

“High quality and rapid diagnostic tests for Nipah and Lassa are badly needed to be able to help patients as soon as they seek healthcare in the community, and to help public health workers respond to outbreaks. Fast disease detection means health workers can begin targeted treatment quickly and make referral to the next level of health care for better investigation and management if needed,” said In-Kyu Yoon,

CEPI’s Executive Director for Research and Development. “The rapid tests can also be used for public health interventions such as patient isolation and contact tracing, and to help develop tools such as vaccines to counter these deadly diseases. 

CEPI has agreed to grant up to $14.9 million to the project, which will run from February 2024 through January 2028. FIND researchers will identify the criteria for an optimum rapid diagnostic test and select rapid tests for Lassa and Nipah to test against those criteria. Successful diagnostics will be progressed to licensure for widespread use.

“Access to quality, rapid diagnostic testing is the cornerstone of global health security. This initiative is the first of its kind under the 100 Days Mission framework, of integrated development of a portfolio of tools spanning diagnostics and vaccines,” said Cassandra Kelly-Cirino Vice-President of FIND’s Health Programmes.

“Lack of testing to identify frequent outbreaks of both Nipah and Lassa puts individuals at risk of these deadly diseases as well as posing a threat to whole populations. Having the tools to spot these outbreaks early is critical so that outbreaks can be contained.

This FIND–CEPI collaboration will accelerate development of urgently needed, high-quality tests that can be used within communities and primary health centres so that people can quickly get the care they need and transmission can be stopped in its tracks. We are also concerned about making sure these tests are available, accessible and affordable to the countries that need them.

”Nipah is a zoonotic disease first identified in 1999 in Malaysia. Its natural hosts are fruit bats, also known as “flying foxes”, and it can spread to people from infected animals or, in rarer cases, from person-to-person. Nipah outbreaks have until now been confined to South and Southeast Asia, but fruit bats are found in a large geographical area covering a population of more than 2 billion people, making this virus a potential pandemic threat. Nipah can cause severe, rapidly progressive illness, including inflammation of the brain, and up to 70 percent of those infected with Nipah die.

Lassa Fever is a rat-borne viral disease which causes acute haemorrhagic disease in many countries across West Africa. As many as 80 percent of people infected with Lassa virus may be asymptomatic, and initial signs and symptoms are non-specific, making accurate early diagnosis difficult. Among Lassa patients hospitalized with severe disease, the death rate is around 15 percent.

There are currently no available vaccines against Nipah and Lassa, but several are in development. CEPI is funding four vaccine candidates against Lassa and three against Nipah. As part of the vaccine development process, high quality diagnostic tests are essential, particularly for the optimal design and conduct of clinical trials. With the vaccine pipelines for both Nipah and Lassa progressing towards late-phase clinical trials, robust, on-the-spot tests will be vital to rapidly identify cases. Along with the critical need for tests to ensure early detection for rapid patient management and outbreak detection, they are also key to aiding the identification of high-risk areas to better design efficacy trials, and to providing proper case management for infected patients enrolled in studies.

Early pathogen detection is critical to the 100 Days Mission – a goal, embraced by the G7 and G20, to develop vaccines, diagnostics and therapeutics against novel pathogens within 100 days of virus identification and give the world a chance of preventing the next pandemic.

The potential pandemic pathogen must first be correctly identified to start the vaccine development process, and pathogen spread must be well characterized to support ongoing vaccine development. Rapid and accurate testing empowers patients and healthcare workers to make informed decisions about protecting health and to prevent the infection of others, as well as providing robust data to support evidence-based public health decision-making.

This project is part of the framework agreement between CEPI and FIND. CEPI and FIND are committed to enabling equitable access to the outputs of their partnership, in line with CEPI’s Equitable Access Policy and FIND’s Global Access Policy, ensuring that any new tests or vaccines developed are made accessible to those who need them. Relevant project results, including data generated as part of this project, will be published open access for the benefit of the global scientific community.

One of greatest challenges facing the world is the rise of disease-causing bacteria that are resistant to antibiotics. Their emergence has been fuelled by the misuse and overuse of antibiotics, the researchers said.

According to the World Health Organisation (WHO), a handful of such bacteria -- including E. coli and Staphylococcus aureus -- have caused over a million deaths, and these numbers are projected to rise in the coming years.

Timely diagnosis can improve the efficiency of treatment, the researchers said.

"Generally, the doctor diagnoses the patient and gives them medicines. The patient then takes it for 2-3 days before realising that the medicine is not working and goes back to the doctor," said Uday Maitra, a professor at the Indian Institute of Science (IISc) Bangalore.

"Even diagnosing that the bacteria is antibiotic-resistant from blood or urine tests takes time. We wanted to reduce that time-to-diagnosis," Maitra said in a statement.

The latest research, published in the journal ACS Sensors, addressed this challenge by developing a rapid diagnosis protocol that uses a luminescent paper-based platform to detect the presence of antibiotic-resistant bacteria.

There are different ways by which a bacterium becomes resistant to antibiotics. In one, the bacterium evolves, and can recognise and eject the medicine out of its cell.

In another, the bacterium produces an enzyme called beta-lactamase, which hydrolyses or breaks down the beta-lactam ring -- a key structural component of common antibiotics like penicillin and carbapenem -- rendering the medication ineffective.

The approach developed by researchers at the IISc and Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) in Karnataka involves incorporating biphenyl-4-carboxylic acid (BCA) within a supramolecular hydrogel matrix containing terbium cholate (TbCh).

This hydrogel normally emits green fluorescence when ultraviolet (UV) light is shined on it.

"In the lab, we synthesised an enzyme-substrate by tethering BCA to the cyclic (beta-lactam) ring that is a part of the antibiotic. When you mix this with TbCh hydrogel, there is no green emission as the sensitiser is ‘masked,’" said Arnab Dutta, a PhD student at IISc, and lead author of the research paper.

“In the presence of beta-lactamase enzyme, the gel will produce green emission. Beta-lactamase enzyme in the bacteria is the one that cuts open the drug, destroys, and unmasks the sensitiser BCA. So, the presence of beta-lactamase is signalled by green emission," Dutta said.

The luminescence signals the presence of antibiotic-resistant bacteria, and the intensity of the luminescence indicates the bacterial load, the researchers said.

For non-resistant bacteria, the green intensity was found to be extremely low, making it easier to distinguish them from resistant bacteria, they said.

The next step was to find a way to make the technology inexpensive. Currently used diagnostics instruments are costly, which drives up the price for testing.

The team collaborated with a Tamil Nadu-based company called Adiuvo Diagnostics to design a customised, portable and miniature imaging device, named Illuminate Fluorescence Reader.

Infusing the hydrogel in a sheet of paper as the medium reduced the cost significantly. The instrument is fitted with different LEDs that shine UV radiation as required, the researchers said.

Green fluorescence from the enzyme is captured by a built-in camera, and a dedicated software app measures the intensity, which can help quantify the bacterial load, they said.

The team then analysed their approach on urine samples.

“We used samples from healthy volunteers and added pathogenic bacteria to mimic urinary tract infections. It successfully produced the outcome within two hours," Maitra added.

The researchers now plan to tie up with hospitals to test this technology with samples from patients. 

Md. Ahasan Ahamed, a graduate student mentored by Weihua Guan at Pennsylvania State University will present this research at the 68th Biophysical Society Annual Meeting, to be held February 10 - 14, 2024 in Philadelphia, Pennsylvania.

Though mpox symptoms are generally mild with fever, rash, and swollen lymph nodes, severe cases can occur and require medical attention. Because the disease is contagious, testing is important so that people with the disease can isolate until symptoms resolve or get appropriate medical care.

To develop a faster test, the researchers used CRISPR, the Nobel-prize winning gene editing technology. Since 2017, scientists have expanded the application of CRISPR technology from gene editing to molecular diagnostic techniques.

For this study, Ahamed created a genetic sequence combined with a reporter to specifically target the mpox virus. Then a programmable CRISPR RNA binds to both the target and a protein called Cas12a and together, the CRISPR/Cas12a cleaves the reporter to create various sizes of fragments. The researchers can then use nanopore sensing technology to analyze those reporters’ fragments, providing a rapid and accurate test that detects whether or not mpox is present in the sample.

The team confirmed that the test they created is specific to mpox—when they tested samples of cowpox virus, a close relative of mpox, the test did not show a positive result.

The whole process is quick, “in total it takes 32 to 55 minutes to detect the target, depending on viral load,” Ahamed said, which is much faster than it currently takes to test for mpox in a lab using PCR method.

The researchers plan to apply this nanopore technology to create tests for other pathogens, allowing one sample to be tested for multiple targets using portable device. And while the technology is not currently commercially available, Ahamed is hopeful that they will soon create a device that could make this kind of pathogen testing widely available.

Group B Streptococcus (GBS) bacteria is carried by 1 in 5 pregnant women, and GBS infection can cause serious complications, leading to preterm births, stillbirths and neonatal deaths.

The good news is the infection, once detected, is easily treatable with standard antibiotics.

RMIT University is part of a consortium that has just won $3 million in funding in the latest Cooperative Research Centres Projects (CRC-P) round for StrepSure®, a sensor technology that’s anticipated to be able to identify GBS bacteria within minutes.

RMIT has already filed a provisional patent application to protect the key intellectual property underpinning the GBS sensor technology.

Within the next 3 years, the RAT-like technology will undergo large-scale clinical trials and be taken to regulators in Australia, the United States and the United Kingdom.

RMIT is partnering with innovation company NEXSEN Biotech, clinicians at Northern Health and Atomo Diagnostics.

Lead researcher Professor Vipul Bansal from RMIT said testing for GBS during weeks 36 to 37 of a pregnancy took 5 to 7 days in a pathology lab.

“This new sensor technology would cut the testing time down to 15 minutes. That won’t just save babies’ lives, it will also save millions in medical costs,” said Bansal from the School of Science.

GBS pathology testing cost the Australian healthcare system about $94 million last financial year.

This new sensor technology would cut the testing time down to 15 minutes.  NEXSEN Managing Director Thomas Hanly said many developing and developed countries did not screen for GBS, leading to preventable pre-term births, stillborn births and disabilities creating emotional and financial pressure for families and disability support agencies.

“A rapid accessible test can bring hope and we are excited to work with Vipul and his team at RMIT to bring this solution to the world,” he said.

Bansal said the RMIT team had very strong capabilities both in biosensor development and biomarker discovery, and had developed a range of nano-sensor technologies to detect very small amounts of bacteria, pathogens and viruses.

“We have developed biomarkers that can detect GBS bacteria with accuracy and high sensitivity,” said Bansal, Director of the Sir Ian Potter NanoBioSensing Facility at RMIT.

“Now we are in the process of making a prototype test, to detect the presence of GBS in vaginal swabs. The test will show a colour change when GBS is present in the samples.”

Total funding for the GBS sensor project is $7.6 million, with a $3 million grant from the Federal Government for field trials of new low-cost sensor technology in the Northern Health system.

“We will optimise the sensor through pre-clinical trials in the second year, before NEXSEN will conduct clinical trials and then take the final product with the results to regulators in Australia, the US and the UK,” Bansal said.

Associate Professor Prahlad Ho, Chair of Northern Health Research Executive Committee and Divisional Director of Diagnostic Services, said Northern Health was proud and excited to be the clinical partner in the project, which will help improve clinical outcomes for babies.

“As one of the busiest healthcare providers in the region, Northern Health is committed to providing the best care for its large volume of clinically and ethnically diverse populations through its research collaborations and partnerships,” he said.

“Northern Health’s clinical partnership, led by Professor Lisa Hui and the Northern Pathology team, will enable the clinical testing of the diagnostic sensor being developed, thereby making it available for wider and equitable use in the community.”

The Hon. Ed Husic, Minister for Industry and Science, said the development of this “Aussie know-how” would give doctors a fighting chance against one of the leading causes of death and disability for newborn babies.

“The fact this technology also offers the potential to free up tens of millions of dollars within our healthcare system to help other Australians in need is just cherry on the cake,” he said.

“Just more proof that Australian science and our know-how matters and can make a difference.”

Details of the method and results from a clinical pilot using blood samples from pediatric patients are provided in the Journal of Molecular Diagnostics in a paper titled, “Universal digital high resolution melt analysis for the diagnosis of bacteremia.” Results from the pilot study showed that their DNA melting approach matched results of blood cultures collected for sepsis testing. They were also able to quantify how much of the pathogen was present in the samples using DNA melting. 

The approach to testing relies on universal digital high-resolution DNA melting (U-dHRM), where DNA is heated until it splits—at about 120 to 190 degrees—and then analyzed. Each sequence has a specific signature during melting, which can be detected with a special dye. The dye causes the unwinding process to give off fluorescent light, creating a melting curve—the unique signature for each type of pathogen.

Those signatures are analyzed by a machine learning algorithm which determines the type of DNA present and identifies the pathogens present. Specifically, the algorithm can reliably detect the difference between melt curves from the pathogens and background noise by matching the curves to a database of known DNA melt curves. It’s also able to detect curves created by organisms that are not in this database, which could show up in a sample if it contains rare or emerging pathogens.   

The current study marks “the first time this method has been tested on whole blood from patients suspected of having sepsis. So this study is a more realistic preview of how the technology could perform in real clinical scenarios,” said Stephanie Fraley, PhD, the paper’s senior author and a professor in UCSD’s department of bioengineering. 

Sepsis-related complications account for one out of every five deaths worldwide. About 41% of these deaths occur in children. Early detection is critical for sepsis survival as mortality risk rises rapidly as the infection goes undiagnosed or improperly treated. Physicians typically treat sepsis cases with antibiotics while waiting for results from blood cultures. 

“The bottom line is, we’re not treating based on evidence,” Fraley said. “And the more we treat without evidence, the more we can cause unintended problems. Sometimes, we’re treating patients who have fungal or viral infections with antibacterials. This can cause antibiotic resistance and alter the patient’s microbiome in a significant way.” 

For the pilot, the researchers collected a milliliter of blood from 17 infants and toddlers along with samples for blood cultures for comparison. The results from DNA melting not only matched the results from blood cultures; the method is also much less likely to generate false positives compared to other types of tests that rely on nucleic acid amplification and next-generation sequencing.

“Our test has incorporated sample preparation processes, assay design techniques, and algorithms that ensure we only detect DNA from intact organisms, which is clinically relevant,” Mridu Sinha, a former PhD student in Fraley’s lab and one of the authors on the paper, noted. 

For their next steps, the researchers plan to conduct a broader clinical study, as well as expand the method to adult patients. Fraley and Sinha have since licensed the U-dHRM technology from UCSD and co-founded the startup Melio to commercialize it. They plan to work first on testing for newborns.

Reference Abstract

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. Here, the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood is assessed. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

The team has shared that the rapid detection of pathogens including E. coli and Salmonella is “crucial in preventing outbreaks of foodborne illness”.

Typically, practices to detect bacterial contamination involves testing food samples in a laboratory to asses the type and quantity of bacteria that forms in a petri dish over a span of days. However the Osaka Metropolitan University research team have claimed their novel handheld device allows for “quick on-site detection”.

The study was led by Professor Hiroshi Shiigi of the Graduate School of Engineering and was published in the journal Analytical Chemistry. The research group experimented with a biosensor that can “simultaneously detect multiple disease-causing bacterial species within an hour”.

“The palm-sized device for detection can be linked to a smartphone app to easily check bacterial contamination levels,” commented Professor Shiigi.

To carry out the study, the team synthesised organic metallic nanohybrids of gold and copper that do not interfere with each other, so that electrochemical signals can be distinguished on the same screen-printed electrode chip of the biosensor. These organic−inorganic hybrids are made up of conductive polymers and metal nanoparticles. Following this, the antibody for the specific target bacteria was introduced into these nanohybrids to serve as electrochemical labels.

Results of the study confirmed that the synthesised nanohybrids functioned as efficient electrochemical labels, enabling the simultaneous detection and quantification of multiple bacteria in “less than an hour”.

“This technique enables rapid determination of the presence or absence of harmful bacteria prior to shipment of food and pharmaceutical products, thereby helping to quickly ensure safety at the manufacturing site,” continued Professor Shiigi.

Looking to the future, the research team has said that it is looking to develop new organic metallic nanohybrids to simultaneously detect additional bacterial species.

Abstract

Simultaneous Electrochemical Detection of Multiple Bacterial Species Using Metal–Organic Nanohybrids

Organic metallic nanohybrids (NHs), in which many small metal nanoparticles are encapsulated within a conductive polymer matrix, are useful as sensitive electrochemical labels because the constituents produce characteristic oxidation current responses. Gold NHs, consisting of gold nanoparticles and poly(m-toluidine), and copper NHs, consisting of copper nanoparticles and polyaniline, did not interfere with each other in terms of the electrochemical signals obtained on the same electrode. Antibodies were introduced into these NHs to function as electrochemical labels for targeting specific bacteria. Electrochemical measurements using screen-printed electrodes dry-fixed with NH-labeled bacterial cells enabled the estimation of bacterial species and number within minutes, based on the distinct current response of the labels. Our proposed method achieved simultaneous detection of enterohemorrhagic Escherichia coli and Staphylococcus aureus in a real sample. These NHs will be powerful tools as electrochemical labels and are expected to be useful for rapid testing in food and drug-related manufacturing sites.

Bacterial viability detection is a critical necessity for the pharmaceutical, medical, and food industries. Yet, a rapid and non-destructive approach for distinguishing between intact live and dead bacteria remains elusive.

Prof. Guo's team has introduced a robust and accessible methodology that integrates atomic force microscopy (AFM) imaging, quantitative nanomechanics, and machine learning algorithms to assess the viability of Gram-negative and Gram-positive bacteria.

The team employed liquid AFM to acquire the morphology and force spectroscopy data of both live and dead bacteria. Subsequent processing of the force spectroscopy data enabled the extraction of essential data points, encompassing deformation, bacterial spring constant, and Young's modulus values.

These extracted parameters served as inputs in the computational framework, constructing a stacking classifier. This classifier operated swiftly and autonomously, effectively identifying bacterial viability in a rapid and automated manner.

"Looking ahead, we envision extending the application of this method to detect viability in other bacterial species and explore its potential in various environmental and biological contexts," said Prof. Guo.

This work exemplifies the power of interdisciplinary collaboration in driving scientific breakthroughs, and provides a valuable framework for future research in the fields of microbiology, nanotechnology, and machine learning.

Reference

Xiaoyan Xu et al, AFM-based nanomechanics and machine learning for rapid and non-destructive detection of bacterial viability, Cell Reports Physical Science (2024). 

Abstract

Detecting bacterial viability remains a critical necessity across the pharmaceutical, medical, and food sectors. Yet, a rapid, non-destructive approach for distinguishing between intact live and dead bacteria remains elusive. Here, this work introduces a robust and accessible methodology that integrates atomic force microscopy (AFM) imaging, quantitative nano-mechanics, and machine learning algorithms to assess the survival of gram-negative (Escherichia coli [E. coli]) and gram-positive (Staphylococcus aureus [S. aureus]) bacteria. The results reveal distinctive changes in ultraviolet-killed E. coli and S. aureus manifesting intact morphological structures but increased stiffness. Three specific features—bacterial deformation, spring constant, and Young’s modulus—extracted from AFM force spectroscopy are established as pivotal inputs for a machine-learning-based stacking classifier. Trained on extensive AFM datasets encompassing known bacterial viability, this methodology demonstrates exceptional predictive accuracy exceeding 95% for both E. coli and S. aureus. These results underscore its universal applicability, rapidity, and non-destructive nature, positioning it as a definitive method for universally detecting bacterial viability.

Each year, bacterial infections claim several million lives worldwide. That is why detecting harmful microorganisms is crucial – not only in the diagnosis of diseases but also, for example, in food production. However, the methods available so far are often time-consuming, require expensive equipment or can only be used by specialists. Moreover, they are often unable to distinguish between active bacteria and their decay products.

By contrast, the newly developed method detects only intact bacteria. It makes use of the fact that microorganisms only ever attack certain body cells, which they recognize from the latter’s specific sugar molecule structure. This matrix, known as the glycocalyx, differs depending on the type of cell. It serves, so to speak, as an identifier for the body cells. This means that to capture a specific bacterium, we need only to know the recognizable structure in the glycocalyx of its preferred host cell and then use this as “bait”.

This is precisely what the researchers have done. “In our study, we wanted to detect a specific strain of the gut bacterium Escherichia coli – or E. coli for short,” explains Professor Andreas Terfort from the Institute of Inorganic and Analytical Chemistry at Goethe University Frankfurt. “We knew which cells the pathogen usually infects. We used this to coat our chip with an artificial glycocalyx that mimics the surface of these host cells. In this way, only bacteria from the targeted E. coli strain adhere to the sensor.”

E. coli has many short arms, known as pili, which the bacterium uses to recognize its host’s glycocalyx and cling onto it. “The bacteria use their pili to bind to the sensor in several places, which allows them to hang on particularly well,” says Terfort. In addition, the chemical structure of the artificial glycocalyx is such that microbes without the right arms slide off it – like an egg off a well-greased frying pan. This ensures that indeed only the pathogenic E. coli bacteria are retained.

But how were the scientists able to corroborate that bacteria really were attached to the artificial glycocalyx? “We bonded the sugar molecules to a conductive polymer,” explains Sebastian Balser, a doctoral researcher under Professor Terfort and the first author of the paper. “By applying an electrical voltage via these ‘wires’, we are able to read how many bacteria had bonded to the sensor.”

The study documents how effective this is: The researchers mixed pathogens from the targeted E. coli strain among harmless E. coli bacteria in various concentrations. “Our sensor was able to detect the harmful microorganisms even in very small quantities,” explains Terfort. “What’s more, the higher the concentration of the targeted bacteria, the stronger the emitted signals.”

The paper is initial proof that the method works. In the next step, the involved working groups want to investigate whether it also stands the test in practice. Using it in regions where there are no hospitals with sophisticated lab diagnostics is conceivable, for example.

Publication

Sebastian Balser, Michael Röhrl, Carina Spormann, Thisbe K. Lindhorst, Andreas Terfort: Selective Quantification of Bacteria in Mixtures by Using Glycosylated Polypyrrole/Hydrogel Nanolayers. ACS Applied Materials & Interfaces Article ASAP.

Abstract

Here, we present a covalent nanolayer system that consists of a conductive and biorepulsive base layer topped by a layer carrying biorecognition sites. The layers are built up by electropolymerization of pyrrole derivatives that either carry polyglycerol brushes (for biorepulsivity) or glycoside moieties (as biorecognition sites). The polypyrrole backbone makes the resulting nanolayer systems conductive, opening the opportunity for constructing an electrochemistry-based sensor system. The basic concept of the sensor exploits the highly selective binding of carbohydrates by certain harmful bacteria, as bacterial adhesion and infection are a major threat to human health, and thus, a sensitive and selective detection of the respective bacteria by portable devices is highly desirable. To demonstrate the selectivity, two strains of Escherichia coli were selected. The first strain carries type 1 fimbriae, terminated by a lectin called FimH, which recognizes α-d-mannopyranosides, which is a carbohydrate that is commonly found on endothelial cells. The otherE. coli strain was of a strain that lacked this particular lectin. It could be demonstrated that hybrid nanolayer systems containing a very thin carbohydrate top layer (2 nm) show the highest discrimination (factor 80) between the different strains. Using electrochemical impedance spectroscopy, it was possible to quantify in vivo the type 1-fimbriated E. coli down to an optical density of OD600 = 0.0004 with a theoretical limit of 0.00005. Surprisingly, the selectivity and sensitivity of the sensing remained the same even in the presence of a large excess of nonbinding bacteria, making the system useful for the rapid and selective detection of pathogens in complex matrices. As the presented covalent nanolayer system is modularly built, it opens the opportunity to develop a broad band of mobile sensing devices suitable for various field applications such as bedside diagnostics or monitoring for bacterial contamination, e.g., in bioreactors.

The work appears in Lancet Microbe, and the lead author is Sukripong Pakdeerat of the University of Bangkok. The test was developed by researchers in Thailand and the Wellcome Sanger Institute in the U.K.

Professor Nick Day, senior author and Director of the Mahidol-Oxford Tropical Medicine Research Unit (MORU), Thailand, and the Wellcome Trust Thailand Asia and Africa Programme, said, “Melioidosis has been neglected despite its high mortality rate and high incidence in many parts of Asia. Early diagnosis is essential so that the specific treatment required can be started as soon as possible. The new rapid diagnostic tool developed through this collaboration has the potential to be a game-changer.”

The team identified a genetic target specific to B. pseudomallei by analyzing over 3,000 B. pseudomallei genomes, most of which were sequenced at the Sanger Institute. They searched for conserved regions of the genome and screened the targets against other pathogens and human host genomes, to ensure their chosen target was specific to B. pseudomallei.

Their test, called CRISPR-BP34, ruptures bacterial cells and uses a recombinase polymerase reaction to amplify the bacterial target DNA. A CRISPR reaction is then used and a simple lateral flow ‘dipstick’ read-out is employed to confirm cases of melioidosis.

There is no vaccine for melioidosis. Intravenous antibiotics—ceftazidime or carbapenem— are effective during the first intensive phase of treatment. However, with current bacterial culture-based diagnostics, many patients receive a range of ineffective antibiotics first. It’s estimated that about 40 percent die, many before it’s known which antibiotic they actually need.

To assess the efficacy of CRISPR-BP34, the team collected clinical samples from 114 patients with melioidosis and 216 patients without the disease at Sunpasitthiprasong Hospital in northeast Thailand, where melioidosis is endemic. The CRISPR-BP34 test was then applied to these samples.

The team will next study how the test works in clinical settings. They will also begin investigating the role of human genetics in susceptibility and immune response to melioidosis infection.

Professor Nick Thomson, senior author and head of parasites and microbes at the Wellcome Sanger Institute, said, “This research is a testament to international collaboration and how the application of genomics at scale leads to clinical intervention. Using a genetic target mined from a bank of thousands of bacterial genomes, the team was able to produce an incredibly sensitive test that is specific to the bacterium behind melioidosis. I look forward to seeing the clinical impacts of this research.”

Reference

Benchmarking CRISPR-BP34 for point-of-care melioidosis detection in low-income and middle-income countries: a molecular diagnostics study. Lancet Microbe 2024; 5: e379–89. Published Online March 13, 2024 https://doi.org/10.1016/ S2666-5247(23)00378-6.

Background

Melioidosis is a neglected but often fatal tropical disease. The disease has broad clinical manifestations, which makes diagnosis challenging and time consuming. To improve diagnosis, we aimed to evaluate the performance of the CRISPR-Cas12a system (CRISPR-BP34) to detect Burkholderia pseudomallei DNA across clinical specimens from patients suspected to have melioidosis.

Methods

We conducted a prospective, observational cohort study of adult patients (aged ≥18 years) with melioidosis at Sunpasitthiprasong Hospital, a tertiary care hospital in Thailand. Participants were eligible for inclusion if they had culture-confirmed B pseudomallei infection from any clinical samples. Data were collected from patient clinical records and follow-up telephone calls. Routine clinical samples (blood, urine, respiratory secretion, pus, and other body fluids) were collected for culture. We documented time taken for diagnosis, and mortality at day 28 of follow-up. We also performed CRISPR-BP34 detection on clinical specimens collected from 330 patients with suspected melioidosis and compared its performance with the current gold-standard culture-based method. Discordant results were validated by three independent qualitative PCR tests. This study is registered with the Thai Clinical Trial Registry, TCTR20190322003.

Findings

Between Oct 1, 2019, and Dec 31, 2022, 876 patients with culture-confirmed melioidosis were admitted or referred to Sunpasitthiprasong Hospital, 433 of whom were alive at diagnosis and were enrolled in this study. Median time from sample collection to diagnosis by culture was 4·0 days (IQR 3·0–5·0) among all patients with known survival status at day 28, which resulted in delayed treatment. 199 (23%) of 876 patients died before diagnosis and 114 (26%) of 433 patients in follow-up were treated, but died within 28 days of admission. To test the CRISPR-BP34 assay, we enrolled and collected clinical samples from 114 patients with melioidosis and 216 patients without melioidosis between May 26 and Dec 31, 2022. Application of CRISPR-BP34 reduced the median sample-to-diagnosis time to 1·1 days (IQR 0·7–1·5) for blood samples, 2·3 h (IQR 2·3–2·4) for urine, and 3·3 h (3·1–3·4) for respiratory secretion, pus, and other body fluids. The overall sensitivity of CRISPR-BP34 was 93·0% (106 of 114 samples [95% CI 86·6–96·9]) compared with 66·7% (76 of 114 samples [57·2–75·2]) for culture. The overall specificity of CRISPR-BP34 was 96·8% (209 of 216 samples [95% CI 93·4–98·7]), compared with 100% (216 of 216 samples [98·3–100·0]) for culture.

Interpretation

The sensitivity, specificity, speed, and window of clinical intervention offered by CRISPR-BP34 support its prospective use as a point-of-care diagnostic tool for melioidosis. Future development should be focused on scalability and cost reduction.

Funding

Chiang Mai University Thailand and Wellcome Trust UK.