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Rapid phenotyping towards personalized malaria medicine

Abstract

Malaria is major public health concerns which continues to claim the lives of more than 435,000 people each year. The challenges with anti-malarial drug resistance and detection of low parasitaemia forms an immediate barrier to achieve the fast-approaching United Nations Sustainable Development Goals of ending malaria epidemics by 2030. In this Opinion article, focusing on the recent published technologies, in particularly the nuclear magnetic resonance (NMR)-based diagnostic technologies, the authors offer their perspectives and highlight ways to bring these point-of-care technologies towards personalized medicine. To this end, they advocate an open sourcing initiative to rapidly close the gap between technological innovations and field implementation.

Background

Malaria continues to claim the lives of more than 435,000 people each year. The challenges with anti-malarial drug resistance and detection of low parasitaemia form immediate barriers to achieve the fast-approaching United Nations Sustainable Development Goals of ending malaria epidemics by 2030 [1].

Critical for the control and elimination of malaria is an accurate diagnosis of the disease. Malaria infection often goes asymptomatic due to undetectable low parasitaemia is in fact inevitably underestimating the number of malaria carriers. Detecting and treating these infections are of utmost importance to ensure patient health and to block disease transmission, since they are a reservoir for future infections. Light microscopy (LM) remains the standard of practice for malaria diagnosis in febrile patients at health facilities, nevertheless this method requires well-trained personnel and does not adequately detect low parasitaemia (detection limit: ~ 50 parasite/μL of blood) [2]. Alternatively, rapid diagnostic test (RDTs), based on immunochromatographic test are ready-to-use assays and have facilitated access to malaria diagnosis even at the community level. Its simplicity to perform and interpret, allowed a significant increase of the proportion of patients suspected of having malaria in receiving a malaria diagnostic test (59% from 2015– 2017, up from a median of 33% for the period 2010–2012) [1].

Nonetheless, RDTs are not more sensitive than LM and, similarly, cannot detect the low-level blood-stage malaria infections that can otherwise be identified by genetic methods [3]. Nucleic acid amplification-based tests (NAATs), such as polymerase chain reaction (PCR) and loop mediated isothermal amplification (LAMP) have been emerging as conceivable option with much greater sensitivity (down to 1 parasite/µL of blood) in diagnosis [4]. Nevertheless, it still requires minimal laboratory conditions, advanced staff training, relatively long time-to-results (30–60 min) and high costs, limiting its usefulness in resource-limited settings. In response to this needs, highly sensitive point-of-care tests such as ultra-sensitive RDTs [5] (already commercially available), paper-based microfluidics for deoxyribonucleic acid (DNA) detection [6] or even nuclear magnetic resonance (NMR)-based hemozoin detection [7,8,9,10], has been developed for malaria diagnostics. The use of this highly sensitive point-of-care tests are crucial to support malaria elimination and have been considered and discussed under the Malaria Policy Advisory Committee [11]. In this Opinion article, we focus on the NMR-based hemozoin detection technologies as diagnostic test that not only can deliver sensitivity but also its potentiality towards malaria personalized malaria medicine.

NMR-based hemozoin detection

A rapid malarial screening has been recently reported based on point-of-care NMR system [7, 9, 10, 12]. NMR spectroscopy is a well-established, non-invasive technique for biochemical, structural studies and a powerful approach in characterizing metabolic responses in biological samples. NMR-based malaria detection is centered on recognizing the paramagnetic susceptibility of malaria hemozoin crystals, which conditions a differential proton nuclear magnetic resonance signature of the infected erythrocyte. This in turn allows a quantitative determination of the parasitaemia. Being parasite survival dependent on hemozoin formation as a by-product of haem detoxification process upon haemoglobin degradation, makes this natural marker, a good unique feature to identify parasites presence in patients’ blood.

As shown in mice studies, the micro NMR system has ‘hypersensitivity’ with a detection limit of less than 10 parasite/µL of blood [7]. This could be a game-changer in resource limited-settings since advance in technology made it portable, needs only one drop of blood (same as microscopy or RDT sample test), and results in less than 10 min. The research team further demonstrated that low-cost, and much stable detection baseline was possible by concentrating the less deformable infected red blood cells using microfluidic separation technique. This high level of sensitivity challenges its usefulness to single out asymptomatic patients or to conduct large randomized screening in the field. In malaria pre-elimination setting, detection of asymptomatic parasite carriers is detrimental since this often low parasite density infections, constitute a large proportion of the parasite reservoirs. Clearing this parasite reservoir is critical for malaria elimination as these individuals still remain infectious to the mosquito promoting the disease transmission. Therefore, NMR-based technology revealed with high potential to be used as high-throughput sensitive diagnostic tool capable to be used in field limited settings.

Sensitivity versus specificity

While good NMR sensitivity (‘true positive rate’) has been reported, the issue of specificity (‘false positive rate’) remains elusive [7, 8]. Hemozoin is also the signature of other blood-borne parasites (e.g., Schistosoma), favoring their difference in disease manifestation symptoms to distinguish them. One far more relevant problem would be to distinguish Plasmodium species once treatment is usually administered based on the Plasmodium species detected. There are five Plasmodium species that can infect humans, being Plasmodium falciparum responsible for the highest mortality rate [13] and Plasmodium vivax responsible for more than 2.5 billion people at risk of infection [1, 14]. The process of haemoglobin degradation, in all Plasmodium species, right from the starting of parasites invasion in the intraerythrocytic cycle leads to hemozoin crystals formation, but their shape and condensation differs [15].

The process of hemozoin formation is mediated heavily by the transfer of electron. Sienkiewicz had shown using multi-frequency high field electron paramagnetic resonance (EPR) that the spectra obtained for hemozoin and synthetic β-haematin can only correspond to a high spin Fe-III (S = 5/2) [16]. The presence of unpaired electrons can be used as EPR-marker to unveil possibly much more intermediate steps, in this poorly understood arena. There is a window of opportunity in which one can manipulate the electron spin resonance using EPR along with the current NMR detection [17] or any of the electron-nuclei double resonance (ENDOR) variants [18]. The small but significant hyperfine interactions from the electron-nuclear coupling allows enormous information to be mapped out. Thus, the use of EPR, ENDOR or multidimensional NMR spectroscopy should have the capacity to differentiate the detailed structure of hemozoin [19] leading to species identification.

Towards the NMR-based personalized malaria medicine

Taking NMR technology beyond parasite detection, this technology has high potential to address another important factor that hampers the control and elimination of malaria i.e., the rapid parasite drug resistance acquisition. Scaling up to higher dimension (e.g., two- or multi-dimensional), NMR spectroscopy may provide the capability of detecting parasite ‘phenotypic variation’. Multi-dimensional representation would essentially means obtaining multifactorial markers (a panel of associated biomarkers) in a single snapshot which in return increases the accuracy of diagnostic [20, 21]. Obtaining time- and patient-unique ‘molecular fingerprint’ is the first step towards personalized malaria medicine, which has vast implication to the malaria elimination programme due the increasingly rate of phenotypic variations in the field [21].

In good time, multi-dimensional NMR techniques are well developed within the NMR community. With the development of fast and highly efficient multidimensional Inverse Laplace decomposition algorithm [22,23,24], and the recent demonstration of two-dimensional low-field NMR relaxometry applications [24,25,26] maybe the answer. By decomposing the multiple proton relaxation reservoirs arising from the water-protein interactions in red blood cells (RBCs), one could hypothetically capture the unique phenotypic expression (e.g., physiological patterns) at every stage of infection. Considering valid this hypothesis, there are a number of significant implications, and they are as follow;

Anti-malarial drug resistance has been correlated with specific genetic mutations in the parasite, offering a tool for the development of diagnostic tests to monitor resistance. But the analysis of the genetic maker, usually through nucleic acid amplification and detection systems, demands technical handling expertise and generally above 1-h turnaround time, precluding, up to today, the development of a device/tool that could provide this information at the point-of-care settings. On top of this, there are anti-malarial drugs such as the artemisinin, for which mechanism of action and resistance is yet to be fully disclosed owning to the possible epigenetic involved. As an example, mutations at the P. falciparum k13 gene does not explain some cases of phenotypic variations, such as parasite clearance time upon artemisinin-based combination therapy (ACT) treatment within the same gene [27, 28]. These phenotypic variations could be based on geographical location or differential transmission setting or even the different ring developmental stage or other genetic factors that needs to work together to reveal a phenotype [29]. Therefore, the NMR or other spectroscopic technologies [25, 30, 31] could aid with the challenges we are facing in detecting anti-malarial drug resistance providing more meaningful information as rapid phenotyping rather than genotyping.

As an outcome of the above mentioned, the anti-malarial drug resistance could hypothetically be captured by multidimensional spectroscopy without a priori knowledge (hypothesis free) on the genetic markers or even independent of other -omics details. Anti-malarial target different features of the parasite’s biology leading to changes in metabolic responses. We hypothesized that the alteration of protein chemistry in the infected RBCs with different anti-malarial susceptible parasites could lead to a distinctive spectrum due to the sensitivity of water-protein interactions in the time-domain multidimensional NMR.

Future outlook: the silver lining

Parasites were first detected under the microscope in 1884 by Alphonse Laveran, a military doctor in France’s Health Service of the Armed Forces. It has passed now almost a century and a half since its discovery and imposingly, microscopy continues to be the recommended method for malaria diagnosis in the field.

Spectroscopic techniques (e.g. NMR, surface enhanced Raman spectroscopy (SERS)), and ultralow cost microfluidic chip [6, 10, 32,33,34,35] are starting to gain the momentum in this joint multidisciplinary expertise to deliver much more sensitive and rapid field malaria detection. We herein disclose the potentiality of going beyond detection and detail some NMR characteristics that could take us towards personalized malaria medicine in low resources settings. In fact, these technologies visioning point of care devices are also moving towards the tantalizing idea of non-invasive, needle free detection. Characteristics such as reliably diagnose with no skin puncture and consequently with no disposable wastes, meets the growing field use medical and environment demands [36]. Conceptualizing the NMR as point of care device, a low-cost wearable device (e.g., pulse oximetry) or compact body fluids analyser for monitoring may become feasible in near future but remain a foreseen test. This may be possible if engineers can step up the game by using the radio/microwave or infrared spectrum as transducer, in analogous to the existing (and already viable) technologies of micro magnetic resonance imaging [37] or SERS [38], respectively.

Far too often, we found ideas and proposal being thrown off beyond publications in this tight funding environment, and unwillingness of investors to put in their money in what often dubbed as the ‘poor-man disease’. In order to accelerate this cause, we need researchers to open-source code (e.g., hard/software) and open-source the ideas/solutions, so that it will continue to spark innovation in the place where the technologies are needed most. With ubiquitous access to internet as meeting place (e.g., open access articles), and low-cost fabrication of hardware (e.g., Arduino, 3D printing), more practical solution can be brought to doorstep. The OPENCORE NMR project [39] by K. Takeda for example, has lowered the barrier of building NMR spectrometer tremendously. The emergence of software-defined-radio (SDR) [21, 40, 41] is making what once used to be expensive radio pulser/receiver within the reach of hobbyist now. SDR enables the replacement of traditional hardware of radio-frequency components with software-based signal processing. Such a movement has the potential to shift the research community and society at large towards technology democratization, departing from the (over)-dependency on expensive commercial spectrometers.

There is a silver lining in this: having low-cost instrumentation with ultra-low-cost assays for malaria diagnostic (and monitoring), will then immediately translate the know-how (e.g., spectroscopic techniques, or discovery of new markers) for other infectious diseases or even other chronic diseases aka the ‘rich-man diseases’ (e.g., diabetes mellitus [31], and cancer [42]) in developed countries.

Conclusion

Accurate diagnosis of malaria and the resilient capacity that the malaria parasite has in acquiring resistance to anti-malarial drugs form immediate barriers to the control and elimination of this disease. Researchers in the field are beginning to see more cases of phenotypic variations. These phenotypic variations could be based on geographical location or differential transmission setting or even the different ring developmental stage [28, 30]. In these regards, we discussed the recent advances in spectroscopic-based technologies which is able to reveal unique ‘molecular fingerprint’, and thus providing the much needed rapid phenotyping (rather than genotyping) platform in the field [20, 40].

Data availability statements

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Abbreviations

NMR:

Nuclear magnetic resonance

LM:

Light microscopy

RDTs:

Rapid diagnostic test

NAATs:

Nucleic acid amplification-based tests

PCR:

Polymerase chain reaction

LAMP:

Loop mediated isothermal amplification

DNA:

Deoxyribonucleic acid

EPR:

Electron paramagnetic resonance

ENDOR:

Electron-nuclei double resonance

RBCs:

Red blood cells

ACT:

Artemisinin-based combination therapy

SERS:

Surface enhanced Raman spectroscopy

SDR:

Software-defined-radio

References

  1. WHO. World malaria report 2018. Geneva: World Health Organization; 2018.

    Google Scholar 

  2. World Health Organization. Malaria diagnosis: memorandum from a WHO meeting. Bull World Health Organ. 1988;66:575–94.

    Google Scholar 

  3. Morris U, Aydin-Schmidt B, Shakely D, Mårtensson A, Jörhagen L, Ali AS, et al. Rapid diagnostic tests for molecular surveillance of Plasmodium falciparum malaria -assessment of DNA extraction methods and field applicability. Malar J. 2013;12:106.

    Article  Google Scholar 

  4. Aydin-Schmidt B, Morris U, Ding XC, Jovel I, Msellem MI, Bergman D, et al. Field evaluation of a high throughput loop mediated isothermal amplification test for the detection of asymptomatic Plasmodium infections in Zanzibar. PLoS ONE. 2017;12:e0169037.

    Article  Google Scholar 

  5. Das S, Peck RB, Barney R, Jang IK, Kahn M, Zhu M, et al. Performance of an ultra-sensitive Plasmodium falciparum HRP2-based rapid diagnostic test with recombinant HRP2, culture parasites, and archived whole blood samples. Malar J. 2018;17:118.

    Article  Google Scholar 

  6. Reboud J, Xu G, Garrett A, Adriko M, Yang Z, Tukahebwa EM, et al. Paper-based microfluidics for DNA diagnostics of malaria in low resource underserved rural communities. Proc Natl Acad Sci USA. 2019;116:4834–42.

    Article  CAS  Google Scholar 

  7. Peng WK, Kong TF, Ng CS, Chen L, Huang Y, Bhagat AA, et al. Micromagnetic resonance relaxometry for rapid label-free malaria diagnosis. Nat Med. 2014;20:1069–73.

    Article  CAS  Google Scholar 

  8. Han J, Peng WK. Reply to ‘Considerations regarding the micromagnetic resonance relaxometry technique for rapid label-free malaria diagnosis’. Nat Med. 2015;21:1387–9.

    Article  CAS  Google Scholar 

  9. Thamarath SS, Xiong A, Lin P-H, Preiser PR, Han J. Enhancing the sensitivity of micro magnetic resonance relaxometry detection of low parasitemia Plasmodium falciparum in human blood. Sci Rep. 2019;9:2555.

    Article  Google Scholar 

  10. Kong TF, Ye W, Peng WK, Hou HW, Marcos, Preiser PR, et al. Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection. Sci Rep. 2015;5:11425.

    Article  CAS  Google Scholar 

  11. WHO. Technical consultation on research requirements to support policy recommendations on highly sensitive point-of care diagnostics for P. falciparum malaria. Report No.: WHO/CDS/GMP/MPAC/2018.1. https://www.who.int/malaria/mpac/mpac-october2018-session7-report-high-sensitive-poct.pdf.

  12. Peng WK, Chen L, Han J. Development of miniaturized, portable magnetic resonance relaxometry system for point-of-care medical diagnosis. Rev Sci Instrum. 2012;83:095115.

    Article  Google Scholar 

  13. Weiss DJ, Lucas TCD, Nguyen M, Nandi AK, Bisanzio D, Battle KE, et al. Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000–17: a spatial and temporal modelling study. Lancet. 2019;394:322–31.

    Article  Google Scholar 

  14. Gething PW, Elyazar IRF, Moyes CL, Smith DL, Battle KE, Guerra CA, et al. A long neglected world malaria map: Plasmodium vivax endemicity in 2010. PLoS Negl Trop Dis. 2012;6:e1814.

    Article  Google Scholar 

  15. Egan TJ. Hemozoin formation. Mol Biochem Parasitol. 2008;157:127–36.

    Article  CAS  Google Scholar 

  16. Sienkiewicz A, Krzystek J, Vileno B, Chatain G, Kosar AJ, Bohle DS, et al. Multi-frequency high-field EPR study of iron centers in malarial pigments. J Am Chem Soc. 2006;128:4534–5.

    Article  CAS  Google Scholar 

  17. Tan KO, Yang C, Weber RT, Mathies G, Griffin RG. Time-optimized pulsed dynamic nuclear polarization. Sci Adv. 2019;5:eaav6909.

    Article  Google Scholar 

  18. Murphy DM, Farley RD. Principles and applications of ENDOR spectroscopy for structure determination in solution and disordered matrices. Chem Soc Rev. 2006;35:249–68.

    Article  CAS  Google Scholar 

  19. Pisciotta JM, Scholl PF, Shuman JL, Shualev V, Sullivan DJ. Quantitative characterization of hemozoin in Plasmodium berghei and vivax. Int J Parasitol Drugs Drug Resistance. 2017;7:110–9.

    Article  Google Scholar 

  20. Dupré A, Lei K-M, Mak P-I, Martins RP, Peng WK. Micro- and nanofabrication NMR technologies for point-of-care medical applications—a review. Microelectron Eng. 2019;209:66–74.

    Article  Google Scholar 

  21. Peng WK, Paesani D. Omics meeting Onics: towards the next generation of spectroscopic-based technologies in personalized medicine. J Pers Med. 2019;9:E39.

    Article  Google Scholar 

  22. Song Y-Q, Venkataramanan L, Hürlimann MD, Flaum M, Frulla P, Straley C. T1–T2 correlation spectra obtained using a fast two-dimensional Laplace inversion. J Magn Reson. 2002;154:261–8.

    Article  CAS  Google Scholar 

  23. Berman P, Levi O, Parmet Y, Saunders M, Wiesman Z. Laplace inversion of low-resolution NMR relaxometry data using sparse representation methods. Concepts Magn Reson Part A Bridg Educ Res. 2013;42:72–88.

    Article  Google Scholar 

  24. Ahola S, Zhivonitko VV, Mankinen O, Zhang G, Kantola AM, Chen HY, et al. Ultrafast multidimensional Laplace NMR for a rapid and sensitive chemical analysis. Nat Comm. 2015;6:8363.

    Article  CAS  Google Scholar 

  25. Curti E, Carini E, Cobo MF, Bocher T, Vittadini E. The use of two-dimensional NMR relaxometry in bread staling: a valuable tool? Food Chem. 2017;237:766–72.

    Article  CAS  Google Scholar 

  26. Jeoh T, Karuna N, Weiss ND, Thygesen LG. Two-dimensional 1H-nuclear magnetic resonance relaxometry for understanding biomass recalcitrance. ACS Sustainable Chem Eng. 2017;5:8785–95.

    Article  CAS  Google Scholar 

  27. Hastings IM, Kay K, Hodel EM. How robust are malaria parasite clearance rates as indicators of drug effectiveness and resistance? Antimicrob Agents Chemother. 2015;59:6428–36.

    Article  CAS  Google Scholar 

  28. Silva M, Ferreira PE, Otienoburu SD, Calçada C, Ngasala B, Björkman A, et al. Plasmodium falciparum K13 expression associated with parasite clearance during artemisinin-based combination therapy. J Antimicrob Chemother. 2019;74:1890–3.

    Article  CAS  Google Scholar 

  29. Gibbons J, Button-Simons KA, Adapa SR, Li S, Pietsch M, Zhang M, et al. Altered expression of K13 disrupts DNA replication and repair in Plasmodium falciparum. BMC Genomics. 2018;19:849.

    Article  CAS  Google Scholar 

  30. Hills BP. Applications of low-field NMR to food science. Annu Rep NMR Spectroscopy. 2006;58:177–230.

    Article  CAS  Google Scholar 

  31. Peng WK, Chen L, Boehm BO, Han J, Loh TP. Molecular phenotyping of oxidative stress in diabetes mellitus with point-of-care NMR system. bioRxiv. 2019;565325. https://doi.org/10.1101/565325.

  32. Liu C, Mauk MG, Hart R, Bonizzoni M, Yan G, Bau HH. A low-cost microfluidic chip for rapid genotyping of malaria-transmitting mosquitoes. PLoS ONE. 2012;7:e42222.

    Article  CAS  Google Scholar 

  33. Guan G, Chen PCY, Peng WK, Bhagat AA, Ong CJ, Han J. Real-time control of a microfluidic channel for size-independent deformability cytometry. J Micromech Microeng. 2012;22:105037.

    Article  Google Scholar 

  34. Toh RJ, Peng WK, Han J, Pumera M. Direct in vivo electrochemical detection of haemoglobin in red blood cells. Sci Rep. 2015;4:6209.

    Article  Google Scholar 

  35. Tu T-Y, Wang Z, Bai J, Sun W, Peng WK, Huang RY, et al. Rapid prototyping of concave microwells for the formation of 3D multicellular cancer aggregates for drug screening. Adv Healthcare Mater. 2014;3:609–16.

    Article  CAS  Google Scholar 

  36. Lukianova-Hleb EY, Campbell KM, Constantinou PE, Braam J, Olson JS, Ware RE, et al. Hemozoin-generated vapor nanobubbles for transdermal reagent- and needle-free detection of malaria. Proc Natl Acad Sci USA. 2014;111:900–5.

    Article  CAS  Google Scholar 

  37. Cooley CZ, Stockmann JP, Armstrong BD, Sarracanie M, Lev MH, Rosen MS, et al. Two-dimensional imaging in a lightweight portable MRI scanner without gradient coils: Lightweight MRI Scanner without Gradient Coils. Magn Reson Med. 2015;73:872–83.

    Article  Google Scholar 

  38. Chen K, Yuen C, Aniweh Y, Preiser P, Liu Q. Towards ultrasensitive malaria diagnosis using surface enhanced Raman spectroscopy. Sci Rep. 2016;6:20177.

    Article  CAS  Google Scholar 

  39. Takeda K. OPENCORE NMR: Open-source core modules for implementing an integrated FPGA-based NMR spectrometer. J Magn Reson. 2008;192:218–29.

    Article  CAS  Google Scholar 

  40. Asfour A, Raoof K, Yonnet J-P. Software Defined Radio (SDR) and Direct Digital Synthesizer (DDS) for NMR/MRI instruments at low-field. Sensors. 2013;13:16245–62.

    Article  Google Scholar 

  41. Krishnan R, Babu RG, Kaviya S, Kumar N, Rahul C, Raman SS, et al. Software defined radio (SDR) foundations, technology trade offs: a survey. In: 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). 2017;2677–82.

  42. Cruz A, Peng WK. Perspective: cellular and molecular profiling technologies in personalized oncology. J Pers Med. 2019;9:44.

    Article  Google Scholar 

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Acknowledgements

W. K. Peng would like to acknowledge INL Start Up and INL Seed Grant 2019.

Funding

This work was supported by INL Start Up and INL Seed Grant 2019, the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (NORTE-01-0145-FEDER-000013) and by the Fundação para a Ciência e Tecnologia (FCT) (M.I.V. is founded through DL 57/2016 (CRP)).

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MIV and WKP is an expert in microbiology and technological innovations, respectively. Both authors contributed equally in analysing the manuscript. Both authors read and approved the final manuscript.

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Correspondence to Weng Kung Peng.

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Veiga, M.I., Peng, W.K. Rapid phenotyping towards personalized malaria medicine. Malar J 19, 68 (2020). https://doi.org/10.1186/s12936-020-3149-4

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