Automated In Vivo Nano-sensing of Breath-borne Protein Biomarkers

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Automated In Vivo Nano-sensing of Breath-borne Protein Biomarkers Haoxuan Chen, Jing Li, Xiangyu Zhang, Xinyue Li, Maosheng Yao, and Gengfeng Zheng Nano Lett., Just Accepted Manuscript • DOI: 10.1021/acs.nanolett.8b01070 • Publication Date (Web): 11 Jul 2018 Downloaded from http://pubs.acs.org on July 12, 2018

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Automated In Vivo Nano-sensing of Breath-borne Protein

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Biomarkers

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Haoxuan Chen1, Jing Li1, Xiangyu Zhang1, Xinyue Li1, Maosheng Yao*,1 and Gengfeng Zheng*,2 1

State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China 2 Laboratory of Advanced Materials, Department of Chemistry and State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200438, China

Revision submitted to Nano Letters

* Corresponding Author: Maosheng Yao, Email: [email protected], Ph: +86 01062767282 State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China Gengfeng Zheng, Email: [email protected] Laboratory of Advanced Materials, Department of Chemistry and Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Fudan University, Shanghai 200032, China

June 21, 2018 Beijing, China

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Table of Contents Graphic

Non-invasive in vivo monitoring of physiological conditions onsingle singleprotein protein level level on IL-6 target response

Exhaled breath

Biomarkers

YYYYYYY Living rat

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SiNW sensor device

Real-time signal

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ABSTRACT

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Toxicology and bedside medical condition monitoring is often desired to be both

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ultrasensitive and noninvasive. However, current biomarker analyses for these

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purposes are mostly offline and fail to detect low marker quantities. Here, we report a

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system called dLABer (detection of living animal’s exhaled breath biomarker) that

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integrates living rats, breath sampling, microfluidics, and biosensors for the

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automated tracking of breath-borne biomarkers. Our data show that dLABer could

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selectively detect (online) and report differences (of up to 103-fold) in the levels of

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inflammation agent interleukin-6 (IL-6) exhaled by rats injected with different

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ambient particulate matter (PM). The dLABer system was further shown to have an

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up to 104 higher signal-to-noise ratio than that of the enzyme-linked immunosorbent

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assay (ELISA) when analyzing the same breath samples. In addition, both

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blood-borne IL-6 levels analyzed via ELISA in rats injected with different PM

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extracts and PM toxicity determined by a dithiothreitol (DTT) assay agreed well with

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those determined by the dLABer system. Video recordings further verified that rats

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exposed to PM with higher toxicity (according to a DTT assay and as revealed by

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dLABer) appeared to be less physically active. All the data presented here suggest that

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the dLABer system is capable of real-time, noninvasive monitoring of breath-borne

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biomarkers with ultrasensitivity. The dLABer system is expected to revolutionize

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pollutant health effect studies and bedside disease diagnosis as well as physiological

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condition monitoring at the single-protein level.

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Keywords: dLABer, Biomarker, Particulate matter, Toxicity, Biosensor, Real time, 3


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Disease monitoring, Physiological condition

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1. Introduction

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Epidemiological studies have shown that ambient air pollution is a leading

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contributor to the global disease burden, e.g., exposure to particulate matter (PM) with

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a diameter of 2.5 µm (PM2.5) is described to have resulted in 4.2 million deaths and

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103.1 million disability-adjusted life-years (DALYs) in 2015 (1, 2). For every 10 µg

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m−3 increase in PM10, the respiratory and cardiovascular daily mortality rates were

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estimated by the World Health Organization (WHO) to be increased by 1.3% (95% CI:

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0.5–2.09%) and 0.9% (95% CI: 0.5–1.3%), respectively (3, 4). However, these

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epidemiological studies strongly rely on the metric of PM mass concentration, while

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no direct correlation has been established between health outcomes and specific PM

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components (5-8). Typically, for air pollution health studies, people first collect air

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samples and store them for some time at low temperature and then conduct the health

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effect or toxicity studies by exposing the collected air samples to cells or animals

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(4,5,7-10). PM from different sources could have very different toxicity per unit of

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mass due to different compositions (9). On the other hand, toxicology studies use cells

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as subjects, and the results might not apply for humans (10). Although animal-based

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studies are more representative, biomarker analysis using current methods takes a

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long time, including taking of blood samples, and importantly, the results might not

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represent the health state at the time of exposure because biomarker levels evolve

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over time (11-13). Nonetheless, biomarker analysis is widely used in toxicological

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studies (14). For example, blood samples from animals are usually taken after 4


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exposure, and then, relevant biomarkers are typically analyzed offline (15, 16). This

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practice has caused significant problems when interpreting the in vivo health effects of

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environmental pollutants.

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Among these health studies, exhaled breath is increasingly being used as a

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non-invasive biomarker method compared to blood sample for exposure analysis

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(17-19). Exhaled breath contains a large number of slightly volatile (e.g., nitric oxide,

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carbon monoxide, hydrocarbons) and nonvolatile compounds (e.g., cytokines, lipids,

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adenosine, histamine) that can be used to assess the respiratory and systemic health

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status (20-22). Among the breath-borne substances, fractional exhaled nitric oxide

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(FeNO), 8-isoprostane, malondialdehyde, interleukins, and other compounds are

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widely used as markers of oxidative stress and airway inflammation resulting from

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occupational and daily exposure to air pollutants (23-27). Additionally, exhaled breath

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has been studied for early diagnosis of lung diseases, such as the use of FeNO for

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diagnosis and treatment of asthma (28). In many other studies, breath-borne proteins

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and various cytokines, such as interleukins, TNF-α and leptin, were shown to be

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associated with lung cancer and can possibly be used for early-stage disease screening

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(29-31). Technically, breath-borne volatile organic compounds (VOCs) are in the gas

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phase and can be directly analyzed via gas chromatography-mass spectrometry

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(GC-MS). Many studies have addressed analysis of breath-borne VOCs from living

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animal subjects using GC-MS or modified carbon nanotubes (32-34). However, with

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regard to nonvolatile organic compounds (e.g., proteins, nucleic acids, and viruses),

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current methods, such as ELISA, for measuring biomarkers take a long time, typically 5


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up to several hours. Recently, the silicon nanowire field effect transistor (SiNW FET)

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has emerged as a rapid and ultrasensitive tool in the nanoscience field and has already

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been used to detect many biomolecules, including small molecules, proteins, nucleic

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acids, viruses, and others (35-40). When detecting biological species, including

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disease protein biomarkers, the SiNW FET was shown to have a sensitivity up to

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several orders of magnitude greater than ELISA (41-44). In our previous work, we

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developed a real-time airborne virus monitoring system (GREATpa) by integrating air

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sampling, microfluidics and an SiNW sensor device (45). The system has been further

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successfully applied to detect viruses in exhaled breath condensates with high

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sensitivity (29 viruses/µl) and selectivity, and the results largely agreed with those

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from a reverse transcription quantitative polymerase chain reaction (RT-qPCR)

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analysis (46). Likewise, similar to virus detection, this same system provides an

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outstanding opportunity for tracking in situ PM exposure health effects through

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real-time monitoring of

biomarkers exhaled from animal or human subjects.

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Here, we report a new system called dLABer (detection of living animal’s

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exhaled breath biomarker) that integrates living animals, air sampling, and

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microfluidics as well as a biosensor for the real-time detection of breath-borne

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biomarkers. The system integrates technologies from various scientific fields, i.e.,

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medical, toxicology, environmental, and nanotechnology fields. To test the system,

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ambient PM collected from different countries were directly injected into rat blood

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circulation using a previously reported protocol (47) from our laboratory. IL-6 levels

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in exposed and control rat breath samples were then monitored in real time using the 6


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dLABer system. The IL-6 levels in collected breath samples were further measured

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using a standard ELISA for verification and sensitivity comparisons. In addition, IL-6

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levels in rat blood sera were also measured. As a confirmation step, the toxicities of

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PM samples from different cities were also measured using dithiothreitol (DTT). This

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work develops a frontier method that could potentially revolutionize pollutant health

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effect studies as well as bedside breath-borne disease diagnosis and monitoring.

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2. Materials and methods

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2.1 Detection of living animal’s exhaled breath biomarker (dLABer) system

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In this work, we developed an online PM toxicity analysis system named dLABer,

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as shown in Figure 1 and Supporting Information S1 (video). The system is composed

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of three major parts: exhaled breath biomarker collection from living rats, sample

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delivery, and a biomarker monitoring and analysis module based on a commercial

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nanobiosensor. For exhaled breath biomarker collection, we constructed a sampler

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based on the impinging principle that operated at 1 liter breath of air per minute. As

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observed in Figures 1 and S1, the rat cage was made in-house with only one air inlet

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(for supplying fresh air to the rats) and one air outlet (for sampling the biomarkers

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exhaled by the rats). The air was driven by a pump for unidirectional flow in the cage,

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and biomarkers exhaled by the rats were carried by the air flow and finally absorbed

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into the collection liquid phosphate-buffered saline (PBS) in a polypropylene conical

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tube. The conical tube was modified with an outlet in the bottom that allowed the

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peristaltic pump to automatically transport the sample to the nanobiosensor. The 7


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sample transport flow rate was set to 15 µl per minute and can be adjusted according

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to experimental need. The initial volume of PBS was 10 ml, and the liquid was

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automatically replenished by the peristaltic pump at the same speed as sample

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delivery to maintain a constant volume in the tube during the experiment. For

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biomarker monitoring and analysis, the commercialized SiNW FET Nanocard (Vista

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Therapeutics, Inc., USA) was used as the nanobiosensor. Before use, the SiNW was

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decorated in our laboratory with a rat-specific antibody obtained from an ELISA kit

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(Becton, Dickinson and Company). When the target antigen bound to the antibody on

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the nanowire, the conductance of the transistor changed proportionally to the antigen

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quantity. The detection signal was then programmed using a commercial system

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(Vista Therapeutics, Inc., USA). Detailed pictures of the biosensor chips used are

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shown in Figure 2.

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Exhaled breath Collection

Peristaltic pump

Detection signal

Rat cage

NanoBiosensor Signal amplifier PBS

Air

Computer Pump Biomarker collector

sample

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Nanobiosensor

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Fig. 1. Experimental sketch and photo of the dLABer system that integrates living rats,

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breath sampling, microfluidics and a commercial FET-based biosensor for the

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real-time detection of breath-borne biomarkers; the airborne biomarkers were directly

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exhaled by the exposed rats (a dLABer system video is provided in Supporting

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Information S1).

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2.2 PM sample collection and suspension preparation

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In this work, we applied the dLABer system to real-time analysis of the toxicity

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of ambient PM collected from different countries by monitoring the IL-6 level in the

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exhaled breath of rats exposed to the PM via injection. PM samples from different

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cities (Cities A, B, C and D; these four cities are from four different continents) were

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collected through automobile air conditioning filters as described in our previous

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work (48). Detailed analysis of the PM toxicity in the rat model will be reported

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elsewhere. In this work, the PM samples and the rats were mainly used for testing the

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dLABer system that was developed. A PM suspension was made by vigorously

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vortexing 2 mg of dust per ml deionized (DI) water for 20 min at a vortex rate of 3200

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rpm (Vortex Genie-2, Scientific Industries Co., Ltd.). The extract solution was then

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prepared by filtering the PM suspension through a nylon filter with an average pore

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size of 0.45 µm.

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2.3 Rat breeding and PM injection The jugular vascular catheterization (JVC) rat model described in our previous 9


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work (47) was used to test the dLABer system for the real-time monitoring of

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breath-borne biomarkers. Thirty male 10-week-old Wistar rats weighing 200–240 g

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who had undergone a jugular vein catheterization operation were purchased from

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Beijing Vital River Laboratory Animal Technology Co., Ltd. A flexible sterile catheter

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was embedded into the jugular vein with approximately 1 centimeter of catheter out

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of the skin and fixed onto the back of the rat with staples. All the rats were kept in an

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animal care facility under a natural 12 h light/12 h dark cycle and were fed a normal

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chow diet. After 1 week of acclimation, the rats were randomly divided into 5 groups

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(6 rats in each group) for exposure to PM from four different countries or normal

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saline (NS) as a control. All the groups were injected with the same volume ( 1 ml) of

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extract suspension or NS. After injection, one rat from each group was placed in the

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dLABer system for online exhaled breath biomarker IL-6 analysis, and blood samples

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were taken (1 ml) 1 hour after injection. The blood serum was separated immediately

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by centrifugation at 3000 rpm for 4 min, and the serum sample was kept at -20 °C for

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further analysis. PM extract injection and blood sampling were performed through the

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embedded catheter using sterile syringes with 23G flat-end needles. All rats were

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monitored by recording cameras, and the video records were used for analysis of

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animal behavior in response to different levels of PM exposure. All animal

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experiments were approved by the Institutional Review Board of Peking University,

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and relevant experiments were performed in accordance with ethical standards

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(approval # LA2017204).

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2.4 Real-time monitoring of breath-borne biomarkers from PM-injected rats

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Before performing experiments, the SiNW sensor (Nanocard) was activated and

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functionalized in our laboratory by binding an IL-6 antibody to the surface of the

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nanowires via a two-step procedure described previously (37). First, we used a 1%

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ethanol/ddH2O solution containing 10% v:v 3-(trimethoxysilyl)propyl aldehyde to

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react with SiOH groups for 40 min at room temperature; thereby, aldehyde groups that

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were used for the next step, i.e., the antibody linkage, were attached to the nanowire

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surface. The nanowires were washed with isopropanol at 3 µl/min for 20 min and

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dried under a gentle flow of nitrogen gas for 3-5 min until the entire surface appeared

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to be dry. Next, the Nanocards were heated overnight (approximately 16 hours) at

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40 °C under vacuum. Then, rat IL-6 antibody (Becton, Dickinson and Company) was

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diluted to 100 µg/ml in 10 mM Na-PBS at pH 8.4 containing 4 mM sodium

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cyanoborohydride and pulled by a peristaltic pump over the nanowires at 3 µl/min for

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five hours. Unreacted aldehyde groups on the surface were passivated by reaction

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with ethanolamine at 6 µl/ml in 10 mM Na-phosphate buffer, pH 8.4, containing 4

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mM sodium cyanoborohydride at 3 µl/min for two hours. Finally, Na-phosphate

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buffer was pulled over the nanowires for 45 min at 3 µl/min. A portable Vista

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NanoBioSensor unit and NanoBioSensor software (Vista Therapeutics, Inc., USA)

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were used for conductance signal processing. Recombinant rat IL-6 was serial diluted

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with PBS and used as a standard. As shown in Figs. 1 and S1, the exhaled breath from

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the rats was continuously collected using a homemade liquid sampler and transported

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to the biosensor for real-time breath-borne biomarker analysis. 11


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2.5 Measurements of IL-6 using an enzyme-linked immunosorbent assay

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In addition, for quality control, the IL-6 levels in exhaled breath samples and

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blood samples from the same rats were analyzed using traditional ELISA kits for rat

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IL-6 detection (Becton, Dickinson and Company) according to the manufacturer’s

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instructions. Briefly, solid-phase IL-6 antibody was prepared by coating microliter

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plate wells with purified rat IL-6 antibody. IL-6 standards, diluted blood serum or

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exhaled breath samples, detection antibodies (biotinylated), and horseradish

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peroxidase (HRP) reagent were added to coated wells step by step to form

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antibody-antigen-antibody-enzyme complexes. Then, 3,3’,5,5’-tetramethylbenzidine

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(TMB) substrate solution was added after the wells were washed. The TMB substrate

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turned blue after catalysis by HRP. The reaction was terminated by addition of a

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sulfuric acid solution, and the suspension finally turned yellow. The color change was

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measured spectrophotometrically at a wavelength of 450 nm, and the biomarker

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concentrations in the samples were then determined by comparing the optical density

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(OD) of the samples to a standard curve. In the ELISA, recombinant rat IL-6 was

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serially diluted with diluent from the assay kit and used as a standard, and a diluent

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assay and blood samples collected from rats injected with NS were used as controls.

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The ELISA results were further compared with those from the dLABer system.

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2.6 PM toxicity analysis using a DTT assay A DTT assay was used to analyze the oxidative potential of PM extract samples 12


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from different cities. Briefly, redox-active compounds catalyze the reduction of

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oxygen to superoxide by DTT, which is oxidized to disulfide. The remaining thiol is

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allowed to react with 5,5′-dithiobis-2-nitrobenzoic acid (DTNB), generating mixed

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disulfides and 5-mercapto-2-nitrobenzoic acid (TNBA), which is then measured based

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on its absorption at 412 nm. The measured ROS generation potentials are expressed as

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the normalized index of oxidant generation (NIOG) according to (49). The DTT

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analysis results for different PM samples were compared with those for breath and

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blood samples analyzed by the dLABer system and by ELISA. In addition, the

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water-soluble metal elements in PM extract solutions (i.e., Fe, Cu, Zn, Pb, Ni, V, Cr,

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Mn, Co, Mo, and Cd) were analyzed via inductively coupled plasma mass

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spectrometry (ICP-MS, Aurora M90, Bruker, Inc., Billerica, MA, USA). The PM

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extract samples for ICP-MS analysis were diluted 10:1 with Milli-Q water. To analyze

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PM toxicity, the bacterial community in PM samples from four cities was investigated

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by high-throughput sequencing. Briefly, 1.5 ml of each PM suspension was prepared

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for 16S rDNA bacterial amplicon sequencing using the Illumina Miseq 2×300 bp

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sequencing platform (Sangon Biotech, Inc., Shanghai, China). Microbial DNA was

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extracted from bacterial colony samples using an E.Z.N.A. Soil DNA Kit (Omega

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Bio-tek, Norcross, GA, U.S.) according to the manufacturer's protocol. The V3–V4

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region of the bacterial 16S ribosomal RNA genes was amplified by polymerase chain

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reaction (94 °C for 3 min; followed by 5 cycles at 94 °C for 30 s, 45 °C for 30 s, and

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62 °C for 30 s; 20 cycles at 94 °C for 20 s and 55 °C for 20 s; 72 °C for 30 s; and a

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final

extension

at

72

°C

for

5

min)

using

the

primers

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F 13


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5′-(CCCTACACGACGCTCTTCCGATCTG(barcode)CCTACGGGNGGCWGCAG)-

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3′

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5′-(GACTGGAGTTCCTTGGCACCCGAGAATTCCAGACTACHVGGGTATCTAA

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TCC)-3′. PCRs were performed in a 30 µL mixture containing 15 µL of 2× Taq master

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mix, 1 µL of each primer (10 µM), and 10-20 ng of template DNA. The second

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polymerase chain reaction round was carried out in the same 30 µl mixture (95 °C for

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3 min; followed by 5 cycles at 94 °C for 20 s and 55 °C for 20 s; 72 °C for 30 s; and a

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final extension at 72 °C for 5 min). After purification using the Agencourt AMPure

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XP system (Beckman Instruments, Inc., USA) and quantification using a Qubit2.0

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DNA detection kit (Life Technologies, Inc., USA), a mixture of amplicons was used

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for sequencing on an Illumina platform performed by Sangon Biotech, Inc., Shanghai,

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China.

and

805R

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3. Statistical analysis

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In this study, the SiNW FET conductance level data for all samples were not

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normally distributed; thus, the differences were analyzed via Kruskal-Wallis one-way

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analysis. Pairwise multiple comparisons (Dunn's method) were performed to analyze

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differences between all pairs of samples. In addition, the IL-6 concentrations in the

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blood sera of rats in different groups were analyzed via ELISA. Despite the

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occurrence of blood clotting in the catheters, at least 5 blood serum samples were

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obtained for all groups. Differences between groups were analyzed using an

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independent sample t-test. Differences between NIOG values of PM from different 14


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cities were analyzed using one-way ANOVA. The dLABer, ELISA and DTT analysis

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results were compared to further validate the accuracy and reliability of the dLABer

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system. All statistical tests were performed with the statistical component of

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SigmaPlot 12.5 software (Systat Software, Inc.), and a p value less than 0.05 indicated

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a statistically significant difference at a confidence level of 95%.

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4. Results and discussion

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4.1 Calibration of the dLABer system using IL-6 biomarker standards

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Recombinant rat IL-6 was serial diluted 10 times with PBS and used as a standard

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for evaluating the performance of the nanobiosensor. PBS and standard samples of

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different concentrations, ranging from 5×100 to 5×104 pg/ml, were delivered

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continuously and successively via a microfluidic channel to the Nanocard at a flow

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rate of 20 µl/min, which was controlled by the peristaltic pump. Fifteen SiNW FET

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circuits on the Nanocard conducted electricity, and the conductivity of the circuits

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changed in response to the amount of IL-6 attached to the SiNW FET surfaces. The

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SiNW FET conductance data were monitored and recorded in real time using signal

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collecting and amplifying equipment (NanoBioSensor and its software). The

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conductance vs time data of two good sensor circuits are shown in Figure 2 (A). When

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PBS flowed through the Nanocard, the conductance levels of SiNW FET remained at

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approximately 9.1×10-8 S for sensor #1 and 6.5×10-8 S for sensor #2. The conductance

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levels decreased rapidly when the Nanocard was held without liquid flow. The

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decrease was observed again when the system switched between two standard 15


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samples with different IL-6 concentrations. The conductance levels of SiNW FET

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increased to 8.4×10-8 S for sensor #1 and 6.3×10-8 S for sensor #2 when detecting

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IL-6 standard samples of 5 pg/ml, which was comparable to the levels of PBS. The

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small difference between the 5 pg/ml IL-6 standard sample and PBS might be caused

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by the different ionic strengths of the two solutions, because the recombinant rat IL-6

331

was reconstituted with DI water according to the manufacturer’s instructions before

332

being diluted in PBS. The difference between PBS and the standard sample of 5 pg/ml

333

was examined and found to be significant, with a p value < 0.05. As observed in

334

Figure 2 (A), IL-6 concentration levels of 5, 50, 500, 5000, and 50000 pg/ml

335

corresponded to average conductance levels of 8.4, 9.4, 9.7, 10.1, and 12.4 × 10-8 S

336

for sensor 1# and 6.3, 6.8, 7.0, 7.3, and 8.7 ×10-8 S for sensor #2. As observed in

337

Figure 2 (A), a 10-fold increase in IL-6 concentration resulted in an ~3-20% increase

338

in the conductance level. This quantitative relationship could vary with sensor chips

339

due to variations in fabrication and functionalization, and thus, the Nanocard should

340

be calibrated with standards and negative controls before use. The linear regression

341

curves for the calibration results are shown in Figure 2 (B). The regression curves

342

were shown to have reasonable linearity, with R2 values of 0.8744 and 0.8691 for

343

sensor #1 and sensor #2, respectively, indicating that the dLABer system can be used

344

for quantitative determination. As shown in Figure 2 (B), when the 50000 pg/ml IL-6

345

standard sample was delivered to the Nanocard, the conductance level increased to a

346

very high level, which was different from the conductance change induced by other

347

standard samples (5-5000 pg/ml). This might be partially due to the excessive ionic 16


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strength of the higher concentration standards. Overall, the calibration results showed

349

that the dLABer system has good linearity with respect to biomarker concentration

350

and the corresponding electrical conductance signal. (C)

(A)

Nanocard IL-6 Conc. pg/ml

5×104

Inlet 5×101

PBS

5×102

5×103

5×100

Outlet

BreathIL-6 analysis using Breath-borne ILantibodyantibody-coated FET (B)

(D)

With rats PBS

Exhaled breath sample PBS

Without rats PM+PBS 24 μg/ml

Selectivity test against particulate matter （PM PM））in the air

351 352

Fig. 2. (A) Detection of rat IL-6 standards using the dLABer system. Two parallel

353

conductance signals from two independent SiNW sensors (Vista Therapeutics, Inc.,

354

USA) were selected and are shown in the figure. The corresponding IL-6

355

concentration (logarithm-transformed) in every standard sample is labeled above the

356

curve in the figure (5×100~5×104 pg/ml); (B) Linear regression curves of normalized

357

conductance and IL-6 concentration (corresponding to the two conductance curves,

358

drawn from the detection results of rat IL-6 standards); (C) Detailed photos of the

359

commercialized SiNW sensor along with the flow tubes (Vista Therapeutics, Inc.,

360

USA); (D) Selectivity test against particulate matter (PM) in the air: detection of IL-6 17


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Page 18 of 37

361

in exhaled breath samples and PBS buffer solution, which was used to continuously

362

collect PM in the air. An exhaled breath sample was collected from 6 healthy rats

363

inside a cage kept in a lab on the Peking University campus during hazy days for 6

364

hours. The PM concentration in PBS buffer solution was approximately 24 µg/ml

365

(calculated as follows: 6 h × 6 L/min (air sampling rate) × 110 µg/m3 (average

366

ambient PM concentration during the experiments) / 10 ml (volume of PBS buffer)).

367

Two independent SiNW sensor conductance signals are shown in the figure.

368 369

As shown in Figure 2 (D), the particulate matter collected from the air did not

370

interfere with nanowire sensing. As shown in this work (described below), the PM in

371

the air also contained many different types of bacteria; and previous studies have also

372

shown that ambient PM contains many different types of viruses (50) and allergens

373

(proteins), such as Der p 1 and Der f 1 (up to 1282 ng/m3) and endotoxin (up to 83.6

374

ng/m3) (51,52). Despite the complex composition of air samples, the conductance

375

signals from the PM, shown in Figure 2 (D), were comparable to those from PBS

376

buffer without the presence of rats. Here, our main application of the technology is on

377

ambient air, thus the non-interferences from the ambient pollutants such as proteins

378

and endotoxin, and microbial particles are very critical. As shown in Figure 2 (A), the

379

sensor responded well to different levels of IL-6. Our ELISA data using the same

380

coating antibody also corresponded well with the dLABer system data (described

381

below). Overall, the system demonstrated outstanding selectivity against many

382

ambient components. 18


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383 384

4.2 Detection of IL-6 in exhaled breath samples

385

After calibration of the nanobiosensor using standards, the dLABer system was

386

used for real-time IL-6 detection in the exhaled breath of rats injected with NS and

387

PM from different cities (A, B, C, and D), as shown in Supporting Information S1.

388

Here, for stable analysis and validation, exhaled breath was first sampled using the

389

dLABer system for 1 hour, and IL-6 in exhaled breath was collected into

390

approximately 10 ml of PBS in collection tubes. After the collection process, the

391

samples were delivered to the nanobiosensor for detection. As shown in Figure 3 (A),

392

a Nanocard was first exposed to PBS, which served as the negative control. The

393

conductance levels were 10.4 ×10-8 S for sensor #1 and 7.3 × 10-8 S for sensor #2,

394

which were higher than the levels observed when PBS was introduced into the

395

Nanocard before calibration. This is largely due to residual attachment of IL-6 from

396

the high-concentration standard sample. Although PBS served as a cleaning solution

397

to detach IL-6 from the SiNW surface, the process required a long time to allow the

398

sensor to return to its original state. Additionally, the affinity between antibody and

399

antigen (IL-6) was an important factor affecting the direction of the reversible

400

reaction. The antibody used has a high K value (chemical equilibrium constant),

401

which indicates easy association and difficult dissociation of antibody and antigen

402

(53). Antibodies with proper affinity could be helpful for improving the reusability of

403

the Nanocard in future applications. A few minutes after the conductance level of PBS

404

became stable, the exhalation samples from rats injected with PM from different cities 19


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Page 20 of 37

405

were delivered to the Nanocard. As observed in Figure 3 (A), the conductance levels

406

of these samples varied significantly, indicating different IL-6 levels in exhaled breath

407

induced by PM from different cities. The conductance levels were converted into the

408

IL-6 concentration in exhaled breath samples by calculation via the standard curve

409

shown in Figure 2 (B). As shown in Figure 3 (B), rats injected with NS exhibited the

410

lowest IL-6 production. As presented in Figure 3 (B), the signal-to-noise ratios (city

411

PM vs NS rat injection) of breath-borne IL-6 measured with the dLABer system

412

ranged from ~10 for City B to ~104 for City D.

20


Page 21 of 37

(A)

-8

Conductance, 10 S

16

City D City A

14

City C City B

12

PBS

NS

10

PBS

8

Sensor #1 Sensor #2

6 4 0

500

1000 1500 2000 2500 3000 3500 4000 4500 5000

Time, s

(B) 1e+12

Concentration of IL-6, pg/ml

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Sensor #1 Sensor #2

1e+11 1e+10 1e+9 1e+8 1e+7 1e+6 1e+5 1e+4 1e+3 1e+2

NS

City A

City B

City C

City D

413 414

Fig. 3. (A) Detection of IL-6 in exhaled breath samples collected from rats injected

415

with normal saline (NS) and PM from different cities (Cities A-D). The exhaled

416

breath samples were collected 1 h after injection. Two independent SiNW sensor

417

conductance signals are shown in (B); IL-6 concentrations in exhaled breath samples 21


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418

that correspond to the conductance results are shown in (A) and were calculated using

419

the linear regression curves of IL-6 standards presented in Figure 1.

420 421

In our previous in vivo study of the toxic effects of PM, the inflammatory marker

422

IL-6 was shown to increase remarkably in serum after injection of PM compared with

423

negative controls injected with NS, indicating that a rapid inflammatory response was

424

induced by PM exposure (47). Other studies have also reported associations between

425

short-term exposure to air pollution and an acute increase in IL-6 (54, 55). As

426

observed in Figure 3 (A), when the exhaled breath sample labeled “City A” flowed

427

into the Nanocard, the conductance level immediately increased to 13 and 11 (x 10-8 S)

428

for approximately 7-8 min for sensor #1 and sensor #2, respectively. This conductance

429

fluctuation might be caused by the continuous flow and the fact that there are always

430

some antigens associating with or falling off the antibodies on the SiNW. Rats in each

431

group were injected with the same dose of PM extract (1 ml of 2 mg/ml PM

432

suspension), but the IL-6 levels were different in the exhaled breath of rats in different

433

groups, indicating that different levels of inflammatory responses were induced and

434

the toxicities of PM from different countries are not the same, due to the different

435

components and sources. The PM from City D induced the highest level of IL-6

436

production in the exhaled breath samples (highest conductance level), followed by

437

Cities A, C, and B. These results, along with those reported in Supporting Information

438

S1, suggest that the dLABer system can detect IL-6 exhaled by rats in real time and

439

thus can distinguish different PM toxicities. The two independent sensors generated 22


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440

consistent results, and thus, the results showed good repeatability.

441 442

Consistent with the above results, as shown in Figure 4 (A) and Supporting

443

Information S2 (videos) taken 1 h after injection, rats exposed to PM from Cities A, C,

444

and D appeared to be drowsy. They remained in the corner of the cage and did not

445

move after the PM injection, while the rats in the NS (control) and City B groups

446

remained relatively active. They moved around the cage and remained alert or curious

447

to external interruptions (e.g., knocking on the cage). Similar behavioral discrepancies

448

were observed between groups of rats injected with high and low doses of PM in our

449

previous study (47), suggesting that the PM injected into the blood circulation system

450

might have caused acute health effects, possibly including nerve injury, in the rats

451

within a short time. The results of this work suggest that the effects of PM from

452

different cities differ due to the PM components and other differences. Overall, the

453

dLABer system can be used for the real-time tracking of breath-borne biomarkers in

454

rats exposed (here, via injection) to PM samples.

455 456

23


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(A)

(B) City B

City A

200

IL-6 in exhaled breath sample

150

Concentration of IL-6, pg/ml

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 37

NS

100 50 NS

City A City B City C City D

(C) 300

IL-6 in blood serum

200

100

City C

City D

0 City A

457

City C

City D

458

Fig. 4. (A) Video snapshot of rats in groups injected with PM from different cities.

459

Rats in the NS and City B groups appeared to be more active than rats in the City A, C,

460

and D groups, which produced high IL-6 levels in exhaled breath. All related videos

461

are provided in Supporting Information S1. (B) IL-6 levels in the exhaled breath

462

samples from the same rats (analyzed using the dLABer system) assessed with a

463

traditional ELISA ; (C) IL-6 levels in the blood serum of rats injected with normal

464

saline (NS) and PM from different cities measured with a traditional ELISA. The

465

values represent the average concentration of 5 or 6 rats in one group, and error bars

466

indicate standard deviations.

467 468

To further validate our method and results obtained using the dLABer system, the

469

IL-6 levels in collected exhaled breath samples (the same samples that were analyzed

470

using dLABer) and blood sera from rats were analyzed via a standard ELISA. As

471

shown in Figure 4 (B), rats injected with PM from City D produced the highest levels

472

of IL-6, followed by Cities A, C, and B. In contrast, rats injected with NS exhibited 24


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473

the lowest IL-6 levels. These results were consistent with those obtained using the

474

dLABer system. As observed in Figure 3, the dLABer system had a signal-to-noise

475

ratio of 10-104, while the ELISA, shown in Figure 4, had a ratio of ~ 1.5-4 when

476

assessing the same breath samples. In addition to the exhaled breath samples, blood

477

samples were taken 1 h after intravenous PM injection, and IL-6 levels were then

478

measured using via ELISA. The average IL-6 levels in the blood samples (after 5-fold

479

dilution) from NS control group and City B group rats were below the detection limit

480

of the ELISA kit; the average IL-6 levels and standard deviations in other groups are

481

shown in Figure 4 (C). As shown in Figure 4 (C), the average IL-6 concentration in

482

blood serum from rats in the City D group was approximately 220 pg/ml, which was

483

higher than that in serum from rats in the City A and City C groups and,

484

unsurprisingly, higher than that in NS and City B group rat sera. In general, these

485

results matched the results obtained with the dLABer system. The PM extracts were

486

intravenously injected through a catheter and induced IL-6 release as a result of

487

systemic inflammation; the IL-6 concentration can increase rapidly in the blood, as

488

revealed in our previous work (47). The results suggested that the IL-6 in blood

489

circulation can be exhaled through pulmonary blood exchange. Upon IL-6

490

accumulation during sampling, IL-6 can be detected using our dLABer system in real

491

time, as shown in S1. In addition to the real-time breath-borne IL-6 monitoring

492

capability, the dLABer system was found to be more sensitive (up to 104 times higher

493

signal-to-noise ratio) than ELISAs when detecting small differences between samples,

494

such the difference between the City B and City C groups. In this work, we collected 25


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Page 26 of 37

495

airborne IL-6 from a confined space occupied only by rats, as shown in Supporting

496

Information S1 (video); thus, the biomarker would be collected into the liquid even if

497

it came from a different rat-related source. Here, we did not specifically differentiate

498

between potential IL-6 sources, but the IL-6 likely primarily comes from exhaled

499

breath, with a negligible contribution from sweat (56). In theory, the exhaled breath

500

samples were the same temperature as living rats, i.e., 37 °C, but in this work, they

501

were collected into DI water that had a temperature of approximately 20 °C.

502

Accordingly, the temperatures were the same for all breath samples collected and

503

analyzed and the sensors in this work. In the future, experiments could be designed to

504

study the effects of different temperature gradients on sensor responses when

505

analyzing the same breath samples.

506 507

Here, the ELISA blood-borne biomarker results agreed with the breath-borne

508

dLABer system results, showing that PM from different cities induced different levels

509

of IL-6 production and thus presented different toxicities. PM is a complex and

510

heterogeneous mixture, and its composition varies greatly with different locations

511

because the emission sources differ (4). Among PM contents, metals are generally

512

studied and have been shown in many studies to cause adverse health effects via ROS

513

generation (57). The metal concentrations in normal saline and PM extracts from

514

different cities in this work are shown in Figure 5 (A). Except for lead (Pb), all metal

515

concentrations in the PM extracts were found to be significantly higher than those in

516

normal saline. Previous studies noted that metals bound to PM2.5 could be the 26


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517

toxicants responsible for ROS generation (induction of oxidative stress) and

518

inflammatory injury (15, 57-59). In addition, one study showed that oxidant radical

519

generation and cytokine production (IL-6 and TNF-α) in airways were significantly

520

increased after administration of metal-rich ambient PM2.5 into contralateral lung

521

segments of healthy volunteers (60). The PM from City A and City D had relatively

522

higher Fe, Zn, Mo, and Co levels, while PM from City B had relatively high Mg, Cu,

523

V, and Ni levels. These differences in metal levels might cause different degrees of

524

toxicity, while the contribution of specific elements to toxicity and their possible

525

synergistic mechanisms need to be further investigated. In another study, PM2.5

526

samples collected from a traffic site containing higher concentrations of metals, such

527

as Fe, Cu, Ni, and Mn, e.g., were shown to exhibit higher oxidative ability using a

528

DTT assay (61). The NIOGs of PM from different cities determined by the DTT assay

529

are shown in Figure 5 (B). As observed in the figure, there are significant differences

530

between the NIOGs of the PM from four cities (p < 0.05). The PM from City D

531

yielded the highest NIOG, followed by Cities C and A, and the PM from City B

532

exhibited the lowest NIOG. The difference in metal components is shown in Figure 5

533

(A) and might partially explain the different PM toxicities; however, many chemical

534

and biological materials are present in PM, and their overall contribution to PM

535

toxicity are still not well understood. For example, the biological components, known

536

as bioaerosols, have been found to induce ROS production, and thus, the PM toxicity

537

might be modulated (62). As shown in Figure 5 (C), the bacterial communities in the

538

PM samples collected here varied greatly among the four cities. Among the top 10 27


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Page 28 of 37

539

bacteria phyla (listed in Supporting Information S3), the proportion of gram-negative

540

bacteria in City A-D samples was 57.15, 54.07, 68.19 and 62.59, respectively.

541

Endotoxins released by these gram-negative bacteria might also contribute to the total

542

toxicity of PM (63, 64).

543

The NIOG values provided here refer to the ability of the PM to induce oxidative

544

stress and damage, and this index might be a product of numerous factors (65). The

545

proinflammatory behavior of IL-6 in response to toxic compounds and its positive

546

relationship with the level of ROS generation have been well addressed previously

547

(59). Nonetheless, aside from the fact that the PM from City C exhibited a higher

548

NIOG than expected, the DTT assay results for other cities corresponded well with

549

the breath-borne IL-6 results obtained using the dLABer and ELISA methods.

550

28


Page 29 of 37

.025

1000 Normal saline City A City B City C City D

100

10

1

.020

NIIOGNIOG (toxicity)

concentration, ng/ml

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

.015

.010

.005

0.000

.1 Fe Mg Cu Zn Ti Mn V

Cr Mo Co Ni Pb

City A

City B

City C

City D

(C)

551 552

Fig. 5. (A) The measured metal levels in PM suspensions used for injection

553

determined by ICP-MS; (B) Normalized index of oxidant generation (NIOG)

554

determined by the DTT assay for (PM) air samples collected from different cities. The

555

values represent averages of at least 5 samples from each city, and error bars indicate

556

the standard deviation; (C) Culturable bacterial species distribution at the genus level

557

in PM samples from different cities. Different colors in the plot represent different

558

species names corresponding to the text on the right-hand side, and the length of the

559

color block represents the relative abundance of the species. The top 15 bacterial

560

phyla in PM samples from four cities are listed in Supporting Information S3.

561 29


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Page 30 of 37

562

Many epidemiological studies have already provided strong evidence that PM

563

pollution is responsible for a variety of diseases, including respiratory disease,

564

cardiovascular illness, and related morbidity and mortality (1). Among these studies,

565

animal model-based toxicology studies have been used to establish cause and effect

566

relationships for specific PM components by precise control of exposure variables.

567

The method typically includes PM exposure (inhalation or tracheal instillation) and

568

subsequent biological analyses, such as biomarker and histopathological analysis.

569

Biomarkers in blood and urine are usually used in both epidemiological and

570

toxicological studies for exposure analysis or pathological analysis. Overall, these

571

studies have led to a good mechanistic understanding of PM health effects. However,

572

the results are often impacted by delayed analysis of in situ responses to exposure in

573

human or animal subjects. Biomarkers in living systems are likely to evolve over time;

574

thus, current methods might miss the intermediate health endpoints resulting from

575

pollutant exposure. Compared with other bio-fluids, exhaled breath analysis is

576

noninvasive and more convenient for human subjects Therefore, it has received

577

significant attention in not only environmental health studies but also in other

578

biological and medical studies, such as drug monitoring, pharmacokinetics research

579

(66, 67), and diagnosis of lung disease (21, 68). For example, one study showed that

580

compared with healthy children (IL-4 = 35.7±6.2 pg/ml), children with asthma

581

problems had higher IL-4 levels (53.7±4.2 pg/ml) in exhaled breath condensate, and

582

the IL-4 levels decreased to (37.5±5.6 pg/ml) after steroid treatment (69). In other

583

studies, the IL-6 level increased in the exhaled breath condensate of patients with lung 30


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584

diseases, such as obstructive sleep apnea (OSA) (70), chronic obstructive pulmonary

585

disease (COPD) (71) and lung cancer (31). Currently, most biomarker analyses, such

586

as those of interleukin in blood, urine, and exhaled breath, are performed through an

587

ELISA. However, ELISAs are time consuming, offline, and not able to track

588

biomarker dynamics in real time. In addition, their sensitivity is relatively low

589

compared with emerging nanotechnology, e.g., field-effect-transistor (FET)-based

590

methods (43). Here, we developed a system called dLABer that integrates living

591

animals, breath sampling, microfluidics, and a FET-biosensor for the real-time

592

monitoring of breath-borne biomarkers. The system is able to overcome both the

593

offline and sensitivity limitations of the current methods. Our results showed that the

594

dLABer system is able to monitor breath-borne IL-6 from rats in real time and

595

provide direct in situ evidence of the health effects of PM exposure. Here, the PM

596

exposure level and rats were selected solely to test the developed dLABer system.

597

Undoubtedly, the system could also be used to monitor breath-borne biomarkers

598

exhaled by humans in various scenarios, such as epidemiological studies. Benefiting

599

from its real-time monitoring capability and high sensitivity, the dLABer system can

600

be further developed for evaluation of therapeutic response, pharmacokinetics studies

601

and even bedside monitoring of biomarker-based disease status in the future.

602 603

Conclusions

604

Here, we developed a novel system that allows us to track in real-time

605

breath-borne biomarkers from living subjects. Our work bridges the nanotechnology 31


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Page 32 of 37

606

field with the environmental, medical and other engineering fields in solving air

607

pollution problems that are often thought to be extremely difficult if not impossible.

608

To test the feasibility of the system, rats injected with PM from different cities were

609

used. The dLABer system results were further validated via ELISA of the breath

610

samples collected. In addition, analysis via ELISA of the blood samples collected

611

from rats injected with different PM samples (of the same mass) and the PM toxicity

612

analysis using the DTT method generally agreed well with the dLABer system results.

613

All the ELISA and DTT assay data and the rat behavior video recordings suggest that

614

the dLABer system is capable of tracking breath-borne biomarkers in real time, with

615

ultrasensitivity, as indicated by the 104 higher signal-to-noise ratio than that of the

616

ELISA. Breath-borne biomarkers (proteins), to the best of our knowledge, have not

617

been previously analyzed using nanotechnology, such as SiNW analysis. Thus far, in

618

the air pollution health effect field, no one has taken advantage of the latest

619

cutting-edge nanotechnology for analyzing associated biomarkers, especially for

620

online analysis. Biomarker levels can evolve over time; accordingly, current methods

621

(sample collection and storage for some time, followed by analysis via ELISA or

622

another technique) could miss intermediate health conditions or outcomes due to air

623

pollution exposure. Our work develops an integrated system that can noninvasively

624

monitor the health effects of air pollution in real time or online and, importantly, is

625

able to capture the dynamics of the effect of air pollution on health. Here, rats and PM

626

exposure were selected to test the dLABer system, but in the future, the system could

627

be used along with other types of sensors to detect biomarkers in humans in various 32


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628

scenarios. The system can be used to immediately monitor breath-borne biomarkers in

629

humans for disease status monitoring or tracking the effectiveness of medications at

630

the bedside. The dLABer system developed here holds great promise for

631

revolutionizing pollutant health effect studies and bedside disease diagnosis, as well

632

as physiological condition monitoring at the single-protein level.

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Associated Content

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Supporting information

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S1. Video of the dLABer system showing real-time breath-borne biomarker

637

monitoring

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S2. Video clip of rats 1 hour after injection with PM from different countries

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S3. Top 10 bacteria phyla in PM samples from four cities identified using

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high-throughput sequencing

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Acknowledgments

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This study was supported by the NSFC Distinguished Young Scholars Fund

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Awarded to M. Yao (21725701), the National Natural Science Foundation of China

644

(91543126, 21611130103, 21477003, and 41121004), and the Ministry of Science and

645

Technology (2016YFC0207102, 2015CB553401, and 2015DFG92040). A patent has

646

been filed for the dLABer system, and the authors declare no competing interests.

647 648 649 650 651 652

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Automated In Vivo Nano-sensing of Breath-borne Protein Biomarkers

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