Lab on a Chip - Erickson Lab @ Cornell University · Personalized nutrition diagnostics at the point-of- ... dietary supplements to assess one's nutritional status, their ... age,

Lab on a Chip

FRONTIER

Cite this: Lab Chip, 2016, 16, 2408

Received 24th March 2016,Accepted 31st May 2016

DOI: 10.1039/c6lc00393a

www.rsc.org/loc

Personalized nutrition diagnostics at the point-of-need

Seoho Lee,ab Balaji Srinivasan,bc Sasank Vemulapati,a Saurabh Mehta*bc andDavid Erickson*ab

Micronutrient deficiency is widespread and negatively impacts morbidity, mortality, and quality of life glob-

ally. On-going advancements in nutritional biomarker discovery are enabling objective and accurate as-

sessment of an individual's micronutrient and broader nutritional status. The vast majority of such assess-

ment however still needs to be conducted in traditional centralized laboratory facilities which are not

readily accessible in terms of cost and time in both the developed and developing countries. Lab-on-a-

chip (LOC) technologies are enabling an increasing number of biochemical reactions at the point-of-need

(PON) settings, and can significantly improve the current predicament in nutrition diagnostics by allowing

rapid evaluation of one's nutritional status and providing an easy feedback mechanism for tracking changes

in diet or supplementation. We believe that nutrition diagnostics represents a particularly appealing oppor-

tunity over other PON applications for two reasons: (1) healthy ranges for many micronutrients are well de-

fined which allows for an unbiased diagnosis, and (2) many deficiencies can be reversed through changes

in diet or supplementation before they become severe. In this paper, we provide background on nutritional

biomarkers used in nutrition diagnostics and review the emerging technologies that exploit them at the

point-of-need.

Introduction

Micronutrient deficiency is prevalent worldwide and is associ-ated with an increased risk of developing numerous healthcomplications.1–3 Iron deficiency for example is responsiblefor many of the 2 billion cases of anaemia, which in turn con-tributes to 20% of all maternal deaths.4 Vitamin B12 defi-ciency is the leading cause of cognitive decline in the elderly,and affects a high percentage of the vegetarian and veganpopulations whose dietary constraints prevent them from asufficient B12 intake.5–7 Vitamin A deficiency is also wide-spread and is the primary cause of blindness globally.4 It isreported that 77% of the US adults are considered to be vita-min D insufficient,8 and face increased risks of developingbone diseases,9 cardiovascular diseases10 and infections.11–13

Tackling micronutrient deficiencies has been identified bythe Copenhagen Consensus as one of the most cost-effectiveintervention to further global development and progress.14

Furthermore, numerous international agencies have identifiedthe development of tools to efficiently measure micronutrientdeficiencies as a priority (e.g. Gates Foundation15). Despite

these, effective intervention for micronutrient deficiency hasbeen a challenge as this often requires information about themicronutrient status of the population at the individual level.Unfortunately, most people around the globe have limitedknowledge about their micronutrient status which is largelydue to the difficulty in obtaining nutritional status measure-ments. The current standard methods of nutritional analysisneed to be performed in centralized lab facilities, and thus aretime consuming, labour intensive and can be even morechallenging in resource-limited settings where the risks ofmicronutrient deficiencies are typically higher.16 The prob-lem is further complicated by the fact that deficiencies are of-ten asymptomatic, resulting in patients who are unaware ofthe severity of their deficiencies until complications develop.

We believe that recent advancements in “lab-on-a-chip(LOC)” devices can be applied to nutritional diagnostics andhelp tackle the micronutrient deficiency problem by makingdeficiency and tracking tests more accessible. The LOC de-vices have been used to carry out complex sample processingand biochemical reactions on-chip, effectively serving as por-table laboratories at the point-of-need (PON) settings.17–19 Inaddition to being globally prevalent and having significanthealth consequences, micronutrient deficiency has twounique traits that make their PON diagnosis particularly ap-pealing. First, unlike many other biomarkers found in bodilyfluids, the healthy ranges for nutritional biomarkers have

2408 | Lab Chip, 2016, 16, 2408–2417 This journal is © The Royal Society of Chemistry 2016

a Sibley School of Mechanical and Aerospace Engineering, Cornell University,

Ithaca, NY 14853, USA. E-mail: [email protected] Institute for Nutritional Sciences, Global Health, and Technology (INSiGHT),

Cornell University, Ithaca, NY 14853, USA. E-mail: [email protected] Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853, USA

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http://dx.doi.org/10.1039/c6lc00393a

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Lab Chip, 2016, 16, 2408–2417 | 2409This journal is © The Royal Society of Chemistry 2016

been well studied and well defined, which enables one to of-ten make more explicit and unbiased nutritional diagnosis.Second, many cases of micronutrient deficiencies can be re-versed through simple changes in diet (e.g. supplementation,food fortification and food diversification) and/or behaviourmodification before the condition becomes severe. Thismeans that the effect of deploying a simple PON tool thatcan inform people of their micronutrient deficiencies canalso make relatively simple therapeutic recommendationsand the outcomes can be tracked with far fewer confounders.

In this paper, we outline the role of nutritional biomarkersin nutritional analysis and the factors that may complicatetheir detection, and the PON technologies that have emergedto help address the world's micronutrient deficiency prob-lem. We then discuss the challenges and opportunities facingthe PON nutrition diagnosis at the consumer level.

Nutritional biomarker considerations for diagnostic devicedesign

Nutritional biomarkers are biochemical indicators found inbodily fluids that provide objective and specific means to as-sess one's micronutrient status.31 They play a particularly im-portant role in the diagnosis of micronutrient deficiencies forwhich patients are often asymptomatic and therefore not ob-servable using common screening approaches based on an-thropometric indicators (i.e. body measurements and clinicalsymptoms).32 Since the concept of nutritional biomarkers wasfirst introduced more than 30 years ago by Solomons et al.,33

the importance of nutritional biomarkers in assessing one'snutritional status has been well recognized and investigated.Prior to reviewing the technological state of the art, we firstpresent a selection of standard biomarkers that can be usedas detection targets of common micronutrient deficiencies.We then discuss how the diagnosis reliant on the biomarkerlevels alone could lead to misleading diagnosis, as each bio-marker level could be affected differently by various factorsincluding the presence of inflammation or infection, risk pro-file of the patient and timing relative to dietary exposure.While our review focuses on detection of micronutrient defi-ciencies from bodily fluids, interested readers may refer to arecent review article34 on the role of LOC devices and micro-fluidics technology in macronutrient analysis (i.e. carbohy-drate, protein, and fat)35–37 and nutrient analysis in food sam-ples.38,39 When using nutrient content/intake from food ordietary supplements to assess one's nutritional status, theirinterplay with human hosts for varying degrees of nutrient ab-sorption, distribution, metabolism and excretion becomescrucial; interested readers are encouraged to refer to recentwork in nutrikinetics40,41 and nutridynamics.42,43

Standard biomarkers. Selecting nutritional biomarkersthat accurately and reliably reflect the nutrient exposure, sta-tus and effect is challenging and there is currently a limitedavailability of these biomarkers.2 This has been identified bythe Institute of Medicine (IOM) as a knowledge gap that re-quires further research, and is being addressed by the Na-tional Institute of Child Health and Human Development

(NICHD) through the creation of the Biomarkers of Nutritionfor Development (BOND) program.44 Despite the challenges,the tremendous progress in the areas of nutritional bio-markers, medicine, metabolism and genetics has led to thediscovery of useful nutritional biomarkers over the years.Table 1 briefly outlines the standard biomarkers that havebeen studied and widely accepted for use in the status assess-ment of micronutrients such as iron, zinc, vitamins A, D, andB12 (Table 1). A more comprehensive information can befound elsewhere.20

Sample types and naturally occurring form of biomarkers.Following the selection of a proper biomarker, the PON deviceshould consider the sample type in which the biomarker ref-erence values are defined. As such they should often be ableto process blood samples, which are complex to work withbut contains the richest level of physiological information.Nonetheless, there are other bodily fluids like urine, saliva,breast milk, and sweat that could be suitable for assessmentof certain biomarkers (see Table 1). Further, many nutrientsare under homeostatic control in blood and their concentra-tion in blood may not be indicative of true status or reflectshorter time periods of intake, necessitating analysis in otherbody fluids or tissues. For example, decreased levels of folatein serum (<7 nM) may indicate vitamin B9 deficiency, how-ever deficiency is more accurately diagnosed by looking forRBC folate levels below 305 nM.20 As there exist different pro-cessing requirements for each sample type, the diagnostic de-vice should be developed accordingly. Another key consider-ation should be on what natural form the biomarkers arefound in within the sample. For example, blood 25-hydroxyvitamin D [25(OH)D] exist 95–99% bound to the vita-min D binding proteins (VDBP).45 As this hinders the immu-noassay interactions that most vitamin D tests are based on,an essential sample processing to liberate the 25(OH)D fromthe VDBP has to be incorporated into the diagnostic devicedesign.

Presence of infection or inflammation. Biomarker levels ofcertain micronutrient deficiencies will be affected by the pres-ence of infection or inflammation in the patient. The failureto take this into account has caused major problems in thecurrent methods used to identify vitamin A and iron deficien-cies. Being acute phase reactants, the RBP and ferritin concen-trations change (i.e. RBP levels decrease and ferritin levels in-crease) during an infection or any underlying inflammation.46

Therefore without accurate assessment of inflammation, theestimates of iron and vitamin A deficiency are biased – falseoverdiagnosis of iron deficiency and underdiagnosis of vita-min A deficiency. For the detection of such micronutrients,the PON device design should eliminate false outputs by incor-porating inflammation and infection markers such asC-reactive protein (CRP) or α1-acid glycoprotein (AGP).30,47

Risk group. Health consequences of some micronutrientdeficiencies could represent a higher threat for certain popu-lation groups based on gender, age, race, or location. As such,cut-off values and reference ranges of nutritional biomarkerlevels may be defined differently for each population group.

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For example, iron deficiency is defined by serum ferritin con-centrations below 12 ng mL−1 and 15 ng mL−1 in children lessthan five years of age and adults, respectively.48 Such under-standing should be incorporated in the design of the diagnos-tic device for more accurate diagnosis of one's nutritionalstatus.

Timing relative to dietary exposure. Biomarkers can beclassified into short term (representing intake over pasthours/days), medium-term (representing intake over weeks/months) and long-term markers (representing intake overmonths/years).49 As such the knowledge of the user's recent/usual micronutrient intake, as well as acute/chronic exposureshould be incorporated into the operation timing of the nutri-tional diagnostic devices. For example, analysis of seleniumin urine provides information on recent intake, and that in

hair or toenails gives a more reliable assessment of long-termselenium status.20

State-of-the-art PON devices for nutritional biomarkers

Currently there is a need for the development of accurate andreliable PON devices for nutrition diagnostics that can: (1) de-tect nutritional biomarkers directly from bodily fluids with amatching performance to that of the gold standard methods,where the device's limit-of-detection and sensitivity can pro-vide an in-depth, quantitative information about one's nutri-tional status, and (2) multiplex the detection to a handful ofbiomarkers, in which the device is able to autonomously pro-cess and deliver the samples/reagents to and from the regionsof appropriate biochemical events as required for the detec-tion of each biomarker. Realization of such aims in PON has

Table 1 Summary of micronutrients, biomarkers & levels of deficiency/insufficiency, and health consequences20

Micronutrient BiomarkerLevels ofdeficiency/insufficiency

Compatiblesample types Health consequences

Vitamin A Retinol,Retinol-bindingprotein

<0.7 μM: deficiency;<1.05 μM: insufficiency21

Blood,breastmilk

Night blindness, delayed growth, ocularlesions and xerophthalmia, impairedimmune functions

Vitamin B7 Biotin <140 pM in serum: deficiency;140–365 pM; normal range22

Blood, urine Dermatitis, depression, alopecia, seizures,developmental delay, poor skin and hair quality

Vitamin B9 Folate (serum orRBC),

<7 nM in serum: insufficiency Blood Tiredness, loss of appetite, megaloblastic anaemia,neural tube defects<305 nM in RBC: insufficiency

Vitamin B12 Serum vitamin B12, <150 pM: deficiency;<221 pM: insufficiency

Blood Neurological (paraesthesia, cognitive impairment)and hematological (anaemia) disorders

Methylmalonic acid, >376 nM: insufficiencyHomocysteine >21.3 μM: insufficiency

Vitamin C Vitamin C <11 μM in plasma: deficiency;<28 μM: insufficiency

Blood, urine Scurvy, vitamin C hypovitaminosis

Vitamin D Serum25-hydroxyvitamin D,

<50 nM: deficiency;<75 nM: insufficiency

Blood Rickets in children, osteomalacia in adults,osteoporosis

Serum vitamin Dbinding proteina

300–600 μg ml−1: normal range;23

direct correlation to D deficiencyhas not yet been determined

Vitamin E Serum vitamin E <5 μg ml−1: deficiency;5–20 μg ml−1: normal range24

Blood Neuromuscular and neurological disorders,retinopathy, anaemia

Zinc Zinc <10.7 μM in serum: deficiency25 Blood, hair Anorexia, lethargy, diarrhoea, growth restriction(delayed bone maturation), impaired immunefunction

Iron Serum ferritin, <12 ng mL−1: deficiency in childrenunder 5 years of age; <15 ng mL−1:deficiency in adults

Blood Anaemia, insufficient energy metabolism, impairedmuscle strength and endurance, impaired collagensynthesis, increased anxiety, impaired memory,low birth weight and premature delivery(pregnant women)

Serum solubletransferrin receptor

>4.4 μg ml−1: deficiency26

<110 mg mL−1: deficiency inpregnant women; <120 mg mL−1:deficiency in non-pregnant women;<130 mg mL−1: deficiency in men(>15 years)

Hemoglobina

Iodine Urinary iodine, <99 ng mL−1 in: insufficiency inchildren; <150 ng mL−1:insufficiency in pregnant women

Urine, blood Goiter, impaired mental function, hypothyroidism,delayed physical development

Serum TSH >5 IU mL−1: deficiencySelenium Selenium <80 ng mL−1 in serum or plasma:

deficiency;27 >1 μg mL−1: excess28Blood, urine,toe nails, scalphair29

Selenosis (excess selenium; hair loss, brittle nails,nausea, diarrhea, fatigue), Keshan disease(deficient selenium)

CRP,b Serum CRP >5 μg mL−1:30 inflammation Blood Increased risk of diabetes and cardiovasculardisease (chronic inflammation); presence ofinfection and/or trauma (acute inflammation)

AGPb Serum AGP >1 mg mL−1:30 inflammation

a Non-specific markers. b Inflammation markers needed for accurate iron and vitamin A status evaluation.

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been the idea behind the development of LOC devices ormicrofluidic based diagnostics technology,17 and there re-cently have been demonstrations of such devices for the rapidbiochemical detection of some nutritional biomarkers includ-ing: iron, vitamins A, B7, B12 and zinc. In the following sec-tions we review the technological state of the art, while cate-gorizing them by the underlying biochemical detectionprinciple. While immunoreactions represent the standardmethod of detection for many, special molecular characteris-tics of some biomarkers enable their detection through otherapproaches using electrochemical, affinity-based and chemi-luminescent reactions. We also discuss how the recent ad-vancements of smartphone technology could facilitate thePON deployment of many of these LOC sensor systems.

Immunosensing of nutritional biomarkers in PON.Immunoreactions (i.e. specific binding interactions betweenthe biomarkers and their respective antibodies) have been theunderlying detection principle of many gold standardmethods including enzyme-linked immunosorbent assays(ELISA) and immunofluorescence assays (IFA). Thebiomarker-to-antibody interactions are easily transferrableonto the miniaturized features on LOC platforms, which haveled to their widespread use in the PON detection of nutri-tional biomarkers.

Labelled immunosensors. Labelled immunoassays arecharacterized by the use of detection labels on the antigen orantibody for producing discernible signals in an immunoreaction,and may be further classified by the specific label type (e.g.fluorescent, colorimetric, enzymatic, chemiluminescent etc.).Fig. 1A shows a disposable microfluidic fluorescent immunoassayfor the 5-plex detection of ferritin, CRP and other blood proteinsin human serum samples.50 In this work, in-parallel detection of5 different target molecules is achieved on-chip by the incorpora-tion of: the micromechanical values for controlling the reagent

flow by pressure, the microchannels for directing thereagents within the chip, and the microchambers for hostingthe fluorescent sandwich immunoassay. The device can sen-sitively measure serum ferritin levels in the range of 350–3500 pg ml−1, which could be combined with its CRP mea-surements to provide an accurate iron deficiency diagnosis.While this represents a promising step towards a PON detec-tion of multiple nutritional biomarkers, there remained ma-jor limitations including the absence of on-chip filtrationmechanism for blood samples, and the requirement for alaboratory-scale microscope and computing platform for thefluorescent signal analysis. To overcome these challenges inthe near term, this system could be integrated with recentdemonstrations of portable fluorescent reader systems,51,52

as well as on-chip blood filtration systems based on variousmicrofluidic strategies.53–55

Rapid diagnostic tests (RDTs), widely known for their lateralflow detection principles, are another example of a labelledimmunosensor where gold nanoparticles (AuNP) are used asthe colorimetric detection labels in an immunoreaction. Theyhave been successfully deployed at the consumer level for thediagnosis of various diseases and medical conditions (e.g.ref. 56), but their application in nutrition has been limited. Therecent development of a RDT for vitamin D (Test4D™; Nano-speed Diagnostics) demonstrates the growing demand forthese tests which are rapid, cheap, and capable of acceptingwhole blood samples directly for autonomous processing,transport and biochemical analysis. Here the Test4D™ caneffectively act as a PON binary test using 32 ng ml−1 of25(OH)D levels as the vitamin D deficiency cut-off. More re-cently our group has demonstrated a novel lateral flow assayfor vitamin B12 (Fig. 1B) that achieves the detection of sub-ngml−1 levels of vitamin B12 through the use of silver enhance-ment and the “spacer pad” that increases the duration of a

Fig. 1 Immunosensing of nutritional biomarkers (A) microfluidic fluorescent immunoassay for the 5-plex detection of ferritin, CRP and other bloodproteins (B) lateral flow colorimetric immunoassay for vitamin B12 detection in PON (C) ITO-based label-free electrochemical immunosensor for RBPdetection. Figures adapted with permission from: (A) ref. 50 Copyright 2009 John Wiley and Sons, (C) ref. 62 Copyright 2014 John Wiley and Sons.


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key immunoreaction.57 This has the potential to extend theapplicability of RDTs for the detection of other key nutri-tional biomarkers that are physiologically found in sub-ngml−1 concentrations (e.g. vitamin B7 or biotin; 140–365 pM).Despite their exceptional suitability for PON applications andthe recent performance advancements, the RDTs are typicallylimited in two main ways. First is the binary nature of the re-sults which are insufficient for fully describing one's micro-nutrient status. Second is the simple one-directional natureof the sample/reagent flow which hampers the multiplexingof distinctly different biomarkers that demand varying levelsof sample processing, biochemical reaction and/or signalamplification.

Label-free immunosensors. Detection of nutritional biomarkerscan also be achieved using label-free immunosensors based on thetransduction of biomarker-to-antibody binding events into measur-able signals that may be electrochemical, optical, piezoelec-tric or thermometric.50,58,59 Among the methods based ondifferent transduction schemes, electrochemical label-freeimmunosensors have shown the biggest potential for PONsensing applications as they are low-cost, highly sensitive,biocompatible, and easily miniaturized.60,61 Recently a dis-posable, label-free electrochemical immunosensor for vita-min A deficiency diagnosis was reported.62 As shown inFig. 1C, indium tin oxide (ITO) surface with an immobilizedlayer of anti-RBP acted as the transducer that changed its im-pedance in response to the binding events between the anti-RBP and the sample RBP. Analysing the impedance datausing the single frequency impedance technique, Şimşeket al. quantified purified RBP in artificial serum samples witha limit-of-detection of 2.5 ag mL−1. While the presentedimmunosensor required laboratory infrastructure for its oper-ation, ultrasensitive electrochemical immunosensors that arebetter suited for PON nutrition diagnostics may be developedby integrating the sensors into compact microfluidics sys-

tems as demonstrated in other works for the detection ofnon-nutritional biomarkers.63,64

Chemical sensing of nutritional biomarkers. Special mo-lecular characteristics of some nutritional biomarkers offeradditional sensing strategies to be exploited even when theassociated antibodies are non-existent or not readily available.These are often minerals and water-soluble vitamins that caneasily be incorporated into: a part of known protein–ligand af-finity interactions, or a chain of chemical reactions as reac-tants or catalysts. In the following sections we discuss howthese principles have been used to enable the PON detectionof biotin (vitamin B7), zinc and cobaltĲII) ions in vitamin B12.

Protein–ligand affinity sensors. Extremely high affinitybetween biotin and streptavidin has been well known andexploited in numerous purification and sensing applicationsby tagging biotin to target proteins and subsequentlycapturing them with streptavidin modified with variousreporters (e.g. enzymes, fluorophores).65 For the special casewhere biotin is the target molecule itself, its detection usingstreptavidin can be more convenient and direct. Dimov et al.has previously demonstrated a “stand-alone self-powered inte-grated microfluidic blood analysis system (SIMBAS)” whichused the biotin-streptavidin affinity pair to quantify pM ofbiotin levels in whole blood.66 As shown in Fig. 2A, thePDMS-based SIMBAS system has 3 key parts: the filter that ex-tracts plasma from whole blood samples by sedimentation,detector that captures sample biotin via an immobilized layerof streptavidin, and suction chamber that sucks in and drivesthe sample flow with the vacuum pressure created bydegassing. For operation, the authors ran SIMBAS with bloodsamples spiked with various concentrations of fluorescentlytagged biotin, and demonstrated quantification of biotindown to 1.5 pM after 10 min. The effective use of micro-fluidics in SIMBAS has led to numerous advantages including:the low sample volume requirement of 5 μl, rapidity, self-

Fig. 2 Chemical sensing of nutritional biomarkers (A) SIMBAS system exploiting streptavidin–biotin affinity pair for detection of biotin (B)electrochemical sensor for detection of zinc (C) chemiluminescent sensor for detection of cobaltĲII) ions in vitamin B12. Figures adapted withpermission from: (A) ref. 66 Copyright 2011 The Royal Society of Chemistry, (B) ref. 77 (direct link: http://pubs.acs.org/doi/abs/10.1021/ac500277j)Copyright 2014 The American Chemical Society, (C) ref. 78 Copyright 2012 The Royal Society of Chemistry.


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powered blood sample processing and flow activation, andthe ability to run 5 in-parallel tests. Despite the strengths, thekey limitation of the SIMBAS is that it required the fluores-cent labels to be on the biotin for quantitation, whereas thenaturally occurring biotin in human blood will be without la-bels. Furthermore, the future application of the SIMBAS toother biomarkers necessitates the detection using other affin-ity pairs that likely have weaker interactions than those be-tween biotin and streptavidin, which will evidently lead to re-duced sensor performance. For this prototype SIMBASsystem, the requirement for a microscope to analyse fluores-cence signals at the end hampered its deployment for PONquantification of biotin, which could be addressed by its inte-gration with portable fluorescent reader systems as previouslydiscussed.

Electrochemical sensors. Several nutritional biomarkers ofthe ionic form may be detected using an electrochemicalprinciple known as anodic stripping voltammetry (ASV).Recently, a disposable copper-based electrochemical sensorthat uses the ASV method for the PON detection of zinc in se-rum was demonstrated.77 As shown in Fig. 2B, the zinc in thesample undergoes two steps, namely: preconcentration stepin which zinc is electroplated on a copper electrode of theelectrochemical sensor, and stripping step in which zinc is ox-idized to generate current that can be measured and corre-lated with sample zinc concentrations. Their novel sensorshowed a limit-of-detection of 140 nM zinc and operated inthe physiologically relevant range of 10–15 μM zinc with a to-tal analysis time under 15 min. Furthermore, the presentedsensor has a number of attributes that make it attractive forPON applications including: the choice of low-cost copper asthe new electrode material, sensor integration with miniaturepotentiostat/galvanostat system, and disposability. However,the sensor operation in this work was limited by thelaboratory-based sample extraction, and could be advanced byincorporating microfluidics technology to perform sampleprocessing on-chip as previously mentioned. Additionally,copper as a working electrode may not be as robust as thecarbon-based electrode choices.

Enzymatic sensors. On the other hand, some nutritionalbiomarkers may be known catalysts of reactions that emitdetectable signals of various forms including chemiluminescence.Recently, a continuous-flow microfluidic LOC device basedon luminol-peroxide chemiluminescent reactions was demon-strated for the determination of vitamin B12.

78 In this work,Lok et. al exploited the finding that the cobaltĲII) ions in vita-min B12, when liberated via acidification, are effective cata-lysts for the oxidation of luminol in the presence of hydrogenperoxide (H2O2) under alkaline conditions. The chemilumi-nescent signal produced could be correlated to the cobalt(II)ion concentrations, which are directly correlated to the sam-ple B12 concentrations.79 As shown in Fig. 2C, the microchipdevice contains two passive micromixers with 5 inlets (corre-lating to vitamin B12 sample, hydrochloric acid (HCl), sodiumhydroxide (NaOH), luminol and H2O2), and double spiralmicrochannels as optical detection regions. In operation,

sample B12 and HCl were inputted into the micromixer in or-der to free the cobalt(II) ions from the B12 via acidificaiton,subsequently followed by the supplies of NaOH, luminol andH2O2 which initiated the chemiluminescent signal produc-tion. While the device has demonstrated an excellent LOD of0.368 pg mL−1 B12, the performance was only demonstratedusing B12 supplements and egg yolk which were processedand prepared off-chip as samples. Furthermore, the require-ments for laboratory-scale detector system and infusionpumps represented hurdles for its PON vitamin B12 determi-nation. Beyond incorporating the portable chemilumines-cence analyzers,51,80 this system could benefit from the re-cent advancements in on-chip microfluidic pumpingstrategies based on pneumatics,81,82 electrokinetics,83 magne-tohydrodynamics84 and acoustics.85

In Table 2, we summarize the different biosensing tech-nologies for the PON detection of the nutritional biomarkerspresented in Table 1, along with their main challenges andfuture outlook. While there may exist numerous other bio-sensing schemes that can be used to detect these biomarkers,we present the technologies that we believe to have highprospects for enabling PON applications.

Smartphone enabled sensing of nutritional biomarkers inPON. Detection of nutritional biomarkers in PON settings isbeing enabled by the technological advancements in LOC sen-sor systems based on various biochemical phenomena, how-ever obtaining quantitative results from these systems still re-quires the sensor outputs to be read and interpreted using asophisticated instrument. While recent technological advance-ments have successfully transformed some of the laboratorybased instruments into portable units, the cost of such sys-tems become prohibitively high for their widespread adoptionby consumers who typically only require sporadic nutrition di-agnostic measurements.86 The smartphone technology can bea convenient yet powerful alternative to these instruments, asthe vast majority of the complexity required to make andinterpret such measurements is already embedded insmartphones.86,87 Furthermore, as smartphones are becomingincreasingly ubiquitous both domestically and abroad,88

smartphone based PON devices could face significantlylowered barriers to entry into the consumer diagnostics mar-ket. The efficacy of smartphone based platforms in nutri-tional analysis was previously demonstrated by our group forvitamin D deficiency diagnosis.89 In that work, we presentedthe “vitamin D AuNP immunoassay device (vitaAID)” systemshown in Fig. 3A which used the smartphone's imaging andcomputational capabilities to read and analyse colorimetricsignals from a novel AuNP-based immunoreaction on thevitaAID test strips. The system accurately quantified serum25(OH)D with an accuracy of 15 nM and a precision of 10 nMwithout the use of conventional laboratory equipment (i.e.spectrophotometer). More recently we presented the NutriPh-one system, a mobile platform for personalized diagnosis ofvitamin B12 deficiency.

57 This system improved upon the limi-tations of the vitaAID system by incorporating a custom RDTfor vitamin B12 capable of processing and analysing whole


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blood samples on-chip in less than 15 min. The effectivenessof the NutriPhone system was validated in a domestic humantrial in which it was used to correctly diagnose the B12 statusof human participants. Here the use of smartphone technol-ogy enabled our system to obtain quantitative B12 informationfrom conventionally qualitative RDT systems in PON settings.As such detection principle could be applied to other RDTsystems, NutriPhone system could be expanded for the diag-nosis of other micronutrient deficiencies simply by develop-ing additional RDT technologies.

Fig. 3B demonstrates another example in which a simple pa-per based microfluidics technology was empowered to performcomplex PON nutrition diagnostics by being integrated with thesmartphone technology. In this work, Lee et al. presented the“electronics enabled microfluidic paper-based analytical device(EE-μPAD)” which consists of: a paper-based microfluidics de-

vice for immunodetection of ferritin, RBP and CRP in wholeblood samples, and an optoelectronics system that measureslight transmission through the detection regions on the paper-based device and wirelessly transmits the data to a smartphonefor processing the data and communicating the results.90

Outsourcing of the computing power and connectivity ofsmartphones enable the EE-μPAD to assess vitamin A, iron andinflammation status by allowing the quantification of RBP, fer-ritin and CRP, respectively, in the physiologically relevantranges. The efficacy of the EE-μPAD was further demonstratedthrough a clinical trial where it showed comparable perfor-mance to the gold standard ELISA method in assessing 95whole blood samples. The partial reliance on smartphoneswherein sensing is achieved by a separate optoelectronicscomponent adds costs to the EE-μPAD, however presents ben-efits including its universal compatibility with different types

Table 2 Summary of challenges and future perspectives for biosensing of nutritional biomarkers at the PON

Biosensing technology* Target biomarker Main challenges Future perspectives

ImmunosensorsMicrofluidic enzyme-linkedimmunosorbent assay(ELISA); fluorescentimmunosensors; lateral flowimmunosensors; label-freeelectrochemical immunosensor

RBP Large performance dependence (i.e.accuracy, sensitivity, reproducibility,cross-reactivity) on quality of antibodies,and the difficulty in obtaining highquality antibodies;Probability for steric hindrance of antibodybinding (e.g. VDBP interfering in vitamin Dimmunoassays)

Immunoassay performance standardizationthrough adoption of External QualityAssessment (EQA) schemes;67

Heavier reliance on monoclonal antibodies(vs. polyclonal antibodies) and theirrecombinant production;68

Incorporation of sample pre-treatment (e.g.liberation of 25(OH)D from VDBP)

25(OH)DVitamin B12

Vitamin EFerritin/transferrinFolate (Vitamin B9)CRP/AGP69

Affinity pair sensorsBiotin-to-streptavidin pair Biotin (vitamin B7) Requirement for biotin pre-treatment as

demonstrated in a recent work66Assay scheme modification (e.g.pre-treatment of streptavidin instead),adaptation of electrochemical methods70)

Electrochemical sensorsAnodic strippingvoltammetry

Zinc Poor long-term stability and susceptibilityto interferents of copper electrode;High cost of gold/platinum electrode

Investigation into use of new electrodematerials such as graphite73 or carbonVitamin C71

Selenium72

Cyclic voltammetry Iodine74 Reduced performance in comparison tolaboratory methods75

Biosensor optimization (e.g. optimizationof thin-film thickness in a recent work74)

Enzymatic sensorsChemiluminescent CobaltĲII) ions High pH and/or temperature dependence76 Incorporation of performance calibration

in working pH and temperature ranges

Fig. 3 Smartphone enabled sensing of nutritional biomarkers (A) vitaAID system for PON diagnosis of vitamin D deficiency (B) EE-μPAD system fordiagnosis of vitamin A and iron deficiencies and inflammation. Figures adapted with permission from: (A) ref. 89 Copyright 2014 The Royal Societyof Chemistry, (B) ref. 90 Copyright 2015 John Wiley and Sons.


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of smartphones, and easier automation of the deviceoperations.

Summary and future perspectives

Micronutrient deficiencies are globally prevalent and respon-sible for the suboptimal health of the world population, mostof whom lack access to proper nutrition diagnostic systems.Development of rapid, cheap and easy-to-use system for accu-rate evaluation of nutritional biomarkers in PON settings hasthe potential to address the challenges with current labora-tory based methods, and allow for more effective manage-ment of micronutrient deficiencies. The on-going advance-ments in nutritional biomarkers are establishing ways tomore accurately diagnose micronutrient deficiencies, whichcan foster the development of such diagnostic systems.

Various systems for PON diagnosis of numerous micronu-trient deficiencies have been realized by miniaturizing differ-ent biochemical sensing approaches on LOC devices, whichnecessarily incorporate microfluidics and/or filtering mecha-nisms to process and handle the complex bodily fluids on-chip. While most of the aforementioned work are still limitedto laboratory use due to the persisting requirements for so-phisticated analytical tools and off-chip sample processing,we have shown that the technological solutions (e.g. portableanalyzer systems) to these challenges have already been dem-onstrated for other applications, and could be incorporatedin the near future to enable developments of truly PON toolsfor nutrition diagnostics. Despite the clear roadmap for thedevelopment of these PON devices, major challenges remainin their deployment to the consumers market as adoption ofportable analytical tools that are necessary for making accu-rate nutrition diagnostics can significantly increase the de-vice cost. Fortunately, new generation of analyzer systemsbased on smartphone technology with growing ubiquity, pow-erful sensing, computing and communication capabilities arereplacing such equipment in PON settings. So far, in the fieldof PON nutrition diagnostics, smartphone technology hasbeen coupled with simple paper-based test strips,empowering them to diagnose several micronutrient deficien-cies based on quantitative biomarker measurements. How-ever, smartphone technology can also enable other types ofLOC devices such as fluorescent or chemiluminescent basedsystems for PON nutrition diagnostics, as has been demon-strated in recent works for similar applications.91,92 Beyondtheir roles as analytical systems, the smartphone based PONdiagnostic systems have the potential to effectively store andcommunicate micronutrient status data for better epidemio-logical understanding and management of the micronutrientdeficiencies.

Acknowledgements

D. E. and S. M. acknowledge funding support through Na-tional Science Foundation Awards 1343058 as well as supportfrom the Micronutrient Initiative. In addition, S. L. acknowl-edges the support of the National Science and Engineering

Research Council of Canada (NSERC) through a Postgraduatescholarship.

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