Background Yersinia pestis is the causative agent of plague, a zoonosis associated with small mammals. Plague is a severe disease, especially in the pneumonic and septicemic forms, where fatality rates approach 100% if left untreated. The bacterium is primarily transmitted via flea bite or through direct contact with an infected host. The 2017 plague outbreak in Madagascar resulted in more than 2,400 cases and was highlighted by an increased number of pneumonic infections. Standard diagnostics for plague include laboratory-based assays such as bacterial culture and serology, which are inadequate for administering immediate patient care for pneumonic and septicemic plague. Principal findings The goal of this study was to develop a sensitive rapid plague prototype that can detect all virulent strains of Y. pestis. Monoclonal antibodies (mAbs) were produced against two Y. pestis antigens, low-calcium response V (LcrV) and capsular fraction-1 (F1), and prototype lateral flow immunoassays (LFI) and enzyme-linked immunosorbent assays (ELISA) were constructed. The LFIs developed for the detection of LcrV and F1 had limits of detection (LOD) of roughly 1–2 ng/mL in surrogate clinical samples (antigens spiked into normal human sera). The optimized antigen-capture ELISAs produced LODs of 74 pg/mL for LcrV and 61 pg/mL for F1 when these antigens were spiked into buffer. A dual antigen LFI prototype comprised of two test lines was evaluated for the detection of both antigens in Y. pestis lysates. The dual format was also evaluated for specificity using a small panel of clinical near-neighbors and other Tier 1 bacterial Select Agents. Conclusions LcrV is expressed by all virulent Y. pestis strains, but homologs produced by other Yersinia species can confound assay specificity. F1 is specific to Y. pestis but is not expressed by all virulent strains. Utilizing highly reactive mAbs, a dual-antigen detection (multiplexed) LFI was developed to capitalize on the diagnostic strengths of each target.

Melioidosis is very challenging to diagnose. There is a clear need for a point-of-care assay for the detection of B. pseudomallei antigen directly from patient samples.

The 2013-2016 Ebola virus (EBOV) outbreak in West Africa and the ongoing cases in the Democratic Republic of the Congo have spurred development of a number of medical countermeasures, including rapid Ebola diagnostic tests. The likelihood of transmission increases as the disease progresses due to increasing viral load and potential for contact with others. Early diagnosis of EBOV is essential for halting spread of the disease. Polymerase chain reaction assays are the gold standard for diagnosing Ebola virus disease (EVD), however, they rely on infrastructure and trained personnel that are not available in most resource-limited settings. Rapid diagnostic tests that are capable of detecting virus with reliable sensitivity need to be made available for use in austere environments where laboratory testing is not feasible. The goal of this study was to produce candidate lateral flow immunoassay (LFI) prototypes specific to the EBOV glycoprotein and viral matrix protein, both targets known to be present during EVD. The LFI platform utilizes antibody-based technology to capture and detect targets and is well suited to the needs of EVD diagnosis as it can be performed at the point-of-care, requires no cold chain, provides results in less than twenty minutes and is low cost. Monoclonal antibodies were isolated, characterized and evaluated in the LFI platform. Top performing LFI prototypes were selected, further optimized and confirmed for sensitivity with cultured live EBOV and clinical samples from infected non-human primates. Comparison with a commercially available EBOV rapid diagnostic test that received emergency use approval demonstrates that the glycoprotein-specific LFI developed as a part of this study has improved sensitivity. The outcome of this work presents a diagnostic prototype with the potential to enable earlier diagnosis of EVD in clinical settings and provide healthcare workers with a vital tool for reducing the spread of disease during an outbreak.

Francisella tularensis is the causative agent of tularemia, a zoonotic bacterial infection that is often fatal if not diagnosed and treated promptly. Natural infection in humans is relatively rare, yet persistence in animal reservoirs, arthropod vectors, and water sources combined with a low level of clinical recognition make tularemia a serious potential threat to public health in endemic areas. F. tularensis has also garnered attention as a potential bioterror threat, as widespread dissemination could have devastating consequences on a population. A low infectious dose combined with a wide range of symptoms and a short incubation period makes timely diagnosis of tularemia difficult. Current diagnostic techniques include bacterial culture of patient samples, PCR and serological assays; however, these techniques are time consuming and require technical expertise that may not be available at the point of care. In the event of an outbreak or exposure a more efficient diagnostic platform is needed. The lipopolysaccharide (LPS) component of the bacterial outer leaflet has been identified previously by our group as a potential diagnostic target. For this study, a library of ten monoclonal antibodies specific to F. tularensis LPS were produced and confirmed to be reactive with LPS from type A and type B strains. Antibody pairs were tested in an antigen-capture enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay format to select the most sensitive pairings. The antigen-capture ELISA was then used to detect and quantify LPS in serum samples from tularemia patients for the first time to determine the viability of this molecule as a diagnostic target. In parallel, prototype lateral flow immunoassays were developed, and reactivity was assessed, demonstrating the potential utility of this assay as a rapid point-of-care test for diagnosis of tularemia.

We report centrifugally-driven, orthogonal flow immunocapture (cOFI) of Zaire Ebola virus-like particles with an accompanying rich, colorimetric image analysis approach that does not require commercial ‘strip readers’ or custom analysis algorithms.