| Literature DB >> 30996333 |
Jessica Z Kubicek-Sutherland1, Dung M Vu1, Aneesa Noormohamed1, Heather M Mendez2, Loreen R Stromberg1,2, Christine A Pedersen1, Astrid C Hengartner1, Katja E Klosterman1, Haley A Bridgewater1, Vincent Otieno3, Qiuying Cheng4, Samuel B Anyona5, Collins Ouma6, Evans Raballah7, Douglas J Perkins3,4, Benjamin H McMahon8, Harshini Mukundan9.
Abstract
Bacteremia is a leading cause of death in sub-Saharan Africa where childhood mortality rates are the highest in the world. The early diagnosis of bacteremia and initiation of treatment saves lives, especially in high-disease burden areas. However, diagnosing bacteremia is challenging for clinicians, especially in children presenting with co-infections such as malaria and HIV. There is an urgent need for a rapid method for detecting bacteremia in pediatric patients with co-morbidities to inform treatment. In this manuscript, we have developed and clinically validated a novel method for the direct detection of amphiphilic pathogen biomarkers indicative of bacteremia, directly in aqueous blood, by mimicking innate immune recognition. Specifically, we have exploited the interaction of amphiphilic pathogen biomarkers such as lipopolysaccharides (LPS) from Gram-negative bacteria and lipoteichoic acids (LTA) from Gram-positive bacteria with host lipoprotein carriers in blood, in order to develop two tailored assays - lipoprotein capture and membrane insertion - for their direct detection. Our assays demonstrate a sensitivity of detection of 4 ng/mL for LPS and 2 ng/mL for LTA using a waveguide-based optical biosensor platform that was developed at LANL. In this manuscript, we also demonstrate the application of these methods for the detection of LPS in serum from pediatric patients with invasive Salmonella Typhimurium bacteremia (n = 7) and those with Staphylococcal bacteremia (n = 7) with 100% correlation with confirmatory culture. Taken together, these results demonstrate the significance of biochemistry in both our understanding of host-pathogen biology, and development of assay methodology, as well as demonstrate a potential new approach for the rapid, sensitive and accurate diagnosis of bacteremia at the point of need.Entities:
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Year: 2019 PMID: 30996333 PMCID: PMC6470174 DOI: 10.1038/s41598-019-42502-5
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Overview of bacterial PAMP detection strategies. (a) Schematic representation of amphiphilic bacterial biomarkers in association with biochemically similar molecules either by forming micelles or interacting with host lipoprotein carriers. Black arrows indicate physiological associations, while orange arrows indicate experimental processes. In the absence of sequestration by a host lipoprotein carrier, bacterial PAMPs can be detected by (b) membrane insertion, which requires only one antibody. When associated with a host lipoprotein carrier, detection can be performed using (c) lipoprotein capture, which requires two antibodies, as well as prior knowledge of PAMP-lipoprotein carrier associations. Dimensions of the various layers are included in order to present the biophysical dimensions of assay performance within the evanescent field of the waveguide. Graphic representations are not drawn to scale.
Figure 2Assay optimization for the detection of LPS in human serum. (a) Representative measurement of LPS (25 ng/mL) incubated overnight at 4 °C in control human serum, with the specific signal (RFU) from the detection α-LPS antibody (25 nM) as a function of emission wavelength (nm). The background and non-specific signals are measured before the addition of LPS. (b) Detection using membrane insertion of 50 ng/mL of LPS derived from S. Typhimurium ATCC 14028 following dilution in PBS or overnight incubation in control human serum. Data are presented as the specific/non-specific (S/N) ratio. (c) Detection using lipoprotein capture of 50 ng/mL of LPS derived from S. Typhimurium ATCC 14028 following overnight incubation in control human serum using capture antibodies targeting HDL and/or LDL. (d) Concentration dependent detection of S. Typhimurium LPS using lipoprotein capture with 25 nM of the α-LPS antibody in ELISA format measured in absorbance at 450 nm. (e) Concentration dependent detection of S. Typhimurium LPS using lipoprotein capture in the LANL waveguide-based biosensor. All values given in (b–e) are the mean ± standard deviation derived from at least two independent determinations (n = 2). ELISA assays were performed in triplicate (n = 3). Statistical significance was determined by one-way ANOVA with Fisher’s least significant difference test used for post hoc analysis (**P < 0.01 or *P < 0.05).
Figure 3Assay optimization for the detection of LTA in human serum. (a) Membrane insertion assay using the 25 nM α-Gram+ antibody for the detection of S. aureus LTA (1 µg/mL) incubated in control human serum with 1 h incubation at room temperature (teal line), 24 h incubation overnight at 4 °C (dotted blue line), and 24 h incubation overnight at 4 °C followed by sample processing (blue line). The background and non-specific signals are measured before the addition of LTA. (b) Detection using lipoprotein capture with the 25 nM α-Gram+ antibody to detect 1 µg/mL of S. aureus LTA following overnight incubation in control human serum using capture antibodies targeting HDL and/or LDL. (c) Concentration dependent detection of S. aureus LTA using lipoprotein capture with 25 nM of the α-LTA antibody in ELISA format measured in absorbance at 450 nm. (d) Comparison of the sensitivity of lipoprotein capture (HDL and LDL together) and membrane insertion assays for the detection of 100 ng/mL S. aureus LTA using the cocktail of 25 nM α-Gram+ monoclonal and 25 nM of α-Sau polyclonal antibody. All values given in (b–d) are the mean ± standard deviation derived from at least two independent determinations (n = 2). ELISA assays were performed in triplicate (n = 3). Statistical significance was determined by one-way ANOVA with Fisher’s least significant difference test used for post hoc analysis (***P < 0.001 or **P < 0.01).
Summary of patient demographics and laboratory test results.
| Patient IDa | Sex | Age (months) | Malaria | Biosensor | Blood Culture IDb | Sequence Confirmationc (NCBI Accession No.) |
|---|---|---|---|---|---|---|
| 1 | F | 25 | + | + | ||
| 2 | F | 21 | + | + | ||
| 3 | F | 6 | + | + | − | |
| 4 | F | 15 | + | + | − | |
| 5 | F | 10 | + | + | ||
| 6 | F | 5 | + | + | ||
| 7 | F | 14 | n.d. | + | − | |
| 8 | M | 11 | − | negative | No growth | − |
| 9 | F | 4 | − | negative | No growth | − |
| 10 | F | 8 | − | negative | No growth | − |
| 11 | F | 17 | − | negative | No growth | − |
| 12 | M | 4 | − | + |
| − |
| 13 | M | 15 | + | + |
| |
| 14 | F | 11 | + | + |
| |
| 15 | M | 12 | + | + | − | |
| 16 | M | 18 | + | + | − | |
| 17 | M | 23 | + | + | − | |
| 18 | M | 10 | + | + | − | |
| 19 | M | 13 | + | negative | No growth | − |
| 20 | M | 6 | + | negative | No growth | − |
aPatient samples numbered 1–11 were tested for LPS, while patient samples numbered 12–21 were tested for LTA.
bCoagulase-negative Staphylococcus spp.
cSelect strains were further classified by whole genome sequencing with NCBI accession numbers included if available or bacterial strain ID if not available.
n.d. data not available.
Figure 4Detection of LPS and LTA directly in pediatric patient serum samples. Data are presented as the S/N ratio with a value above 2 indicating a positive result. (a) Detection of LPS in clinical serum samples using the lipoprotein capture assay. (b) Detection of LTA in clinical serum samples using both the lipoprotein capture (grey bars) and membrane insertion (black bars) assays.