Rapid Diagnosis of Infectious Diseases

by Orobola Olajide

Introduction

Millions of hospitalizations and thousands of deaths each year are reported in the United States due to infectious diseases such as urinary tract infections, respiratory infections, and foodborne illnesses. Projections indicate that bacterial infections will cause 10 million deaths per year by 2050 due to antibiotic resistance (AMR). The main cause of AMR is inaccurate administration of antibiotics and delayed treatment, which increases the mortality rate. Therefore, we need fast and accurate infectious diseases diagnostic methods to intervene in time, administer antibiotics properly, increase the cure rate, and shorten hospital stays.

Diagnostic methods should be fast, but current methods for disease diagnosis are time-consuming, mainly because of extensive and expensive processes of sample preparation. Sample preparation involves the conversion of a biological sample such as blood, urine, etc. into a form that can be easily analyzed by analytical instruments. Current steps in sample preparation include sample extraction, reaction with certain chemicals, dilution, and so on. Since these steps are tedious, an alternative method, called the ambient ionization technique, has been introduced, in which samples are analyzed directly in their original state with minimal or no sample preparation. An example of such a technique is paper spray, in which the sample, such as blood, is dabbed onto a triangular piece of paper and its chemical information is captured through the application of spray solvents and high voltage. In addition to being quick, diagnostic methods must also be accurate. Just as each person's fingerprint is unique for accurate identification, microorganisms that cause infectious diseases have compounds in their cell membranes that allow for accurate identification. Historical chemical identification techniques have often relied on distinguishing compounds by their mass, but these compounds, or metabolites, are structurally complex, meaning that multiple metabolites with the same mass but different structures and sizes may exist. Therefore, an analytical method is needed to distinguish these structurally complicated metabolites. 

Ion mobility spectrometry (IMS) provides the right solution to these problems because it can distinguish isomers (metabolites with similar mass but different structures). IMS allows us to “fingerprint” infectious organisms that might have structurally and chemically similar metabolites, which are often found in distinct, but closely related, bacteria species or strains. For example, Bacillus subtilis and Bacillus velezensis belong to the same genus but are two different species, while Bacillus velezensis AP46 and Bacillus velezensis AP215 belong to the same species but are two different strains. These different bacterial species and strains might have metabolites that are of similar masses but different structures, which would require the use of IMS to distinguish them. This is particularly important because different strains and species can cause different diseases, but due to their high biological similarity, traditional identification techniques might misidentify them, leading to inaccurate therapeutic administration. These challenges highlight the importance of ion mobility spectrometry to reveal different metabolites that can be used as biomarkers to distinguish different species and strains of microorganisms.

The paper spray technique provides speed, while ion mobility spectrometry provides accurate discrimination. Hence, due to the clinical importance of early detection and accurate discrimination, we coupled the paper spray technique with IMS to distinguish five microorganism species in less than two minutes with a 100% prediction rate. Currently, we are exploring the coupled techniques as a diagnostic method to differentiate seven strains of microorganisms. Further research is being conducted to develop a portable diagnostic device that is inexpensive, accurate, and fast.

Acknowledgement: This material is based upon work supported by the National Institute of Health (NIH), grant #1R35GM147225. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding organizations.