1. Microbiology and Infectious Disease
Download icon

Smartphone screen testing, a novel pre-diagnostic method to identify SARS-CoV-2 infectious individuals

  1. Rodrigo M Young  Is a corresponding author
  2. Camila J Solis
  3. Andres Barriga-Fehrman
  4. Carlos Abogabir
  5. Alvaro R Thadani
  6. Mariana Labarca
  7. Eva Bustamante
  8. Cecilia V Tapia
  9. Antonia G Sarda
  10. Francisca Sepulveda
  11. Nadia Pozas
  12. Leslie C Cerpa
  13. María A Lavanderos
  14. Nelson M Varela
  15. Alvaro Santibañez
  16. Ana M Sandino
  17. Felipe Reyes-Lopez
  18. Garth Dixon
  19. Luis A Quiñones  Is a corresponding author
  1. Diagnosis Biotech, Chile
  2. Institute of Ophthalmology, University College London, United Kingdom
  3. Grupo Oncológico Cooperativo Chileno de Investigación, Chile
  4. Laboratorio de Especialidad, Clínica Dávila, Chile
  5. Laboratory of Chemical Carcinogenesis and Pharmacogenetics (Chilean Health Council Diagnostic Covid19 Laboratory), Department of Basic and Clinical Oncology, Faculty of Medicine, University of Chile, Chile
  6. Centro de Biotecnología Acuícola, Facultad de Química y Biología, Chile
  7. Programa Disciplinario de Inmunología, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Chile
  8. Departamento de Biología, Facultad de Química y Biología, Universidad de Santiago de Chile, Chile
  9. Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, Spain
  10. Facultad de Medicina Veterinaria y Agronomía, Universidad de Las Américas, Chile
  11. Department of Microbiology, Virology and Infection Control, Hospital National Health Service Foundation Trust, United Kingdom
  12. National Institute for Health Research Biomedical Research Centre at Great Ormond Hospital for Children National Health Service Foundation Trust and University College, United Kingdom
Tools and Resources
  • Cited 0
  • Views 3,044
  • Annotations
Cite this article as: eLife 2021;10:e70333 doi: 10.7554/eLife.70333

Abstract

The COVID-19 pandemic will likely take years to control globally, and constant epidemic surveillance will be required to limit the spread of SARS-CoV-2, especially considering the emergence of new variants that could hamper the effect of vaccination efforts. We developed a simple and robust – Phone Screen Testing (PoST) – method to detect SARS-CoV-2-positive individuals by RT-PCR testing of smartphone screen swab samples. We show that 81.3–100% of individuals with high-viral-load SARS-CoV-2 nasopharyngeal-positive samples also test positive for PoST, suggesting this method is effective in identifying COVID-19 contagious individuals. Furthermore, we successfully identified polymorphisms associated with SARS-CoV-2 Alpha, Beta, and Gamma variants, in SARS-CoV-2-positive PoST samples. Overall, we report that PoST is a new non-invasive, cost-effective, and easy-to-implement smartphone-based smart alternative for SARS-CoV-2 testing, which could help to contain COVID-19 outbreaks and identification of variants of concern in the years to come.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, has had a massive impact on human lives, health, and quality of life, challenging countries’ healthcare systems and their economies worldwide. Several countries are now facing a second or third wave of COVID-19 cases. Moreover, the development of this pandemic is still difficult to predict considering the emergence of SARS-CoV-2 mutations located in the receptor-binding domain of the surface spike protein, which creates a new hazard as evolved viral strains may be more infectious or evade the immune response and hinder vaccination efforts (CDC, 2021a; Collier et al., 2021; Greaney et al., 2021a; Volz et al., 2021; Wang et al., 2021; Wibmer et al., 2021). Particularly, the more infectious Alpha variant (B.1.1.7, Frampton et al., 2021; Rambaut et al., 2020), together with the Beta variant (B.1.351, Tegally et al., 2020), Delta (B.1617.2, Torjesen, 2021) and Gamma variant (P.1, Faria et al., 2021 ), considered variants of concern by CDC, which share the antigenic drift and/or signature mutations E484K, L452R,K417N and N501Y in the region of the spike protein that is recognised by neutralising antibodies (Collier et al., 2021Tchesnokova et al., 2021; Greaney et al., 2021b; Wang et al., 2021; Wibmer et al., 2021).

Early in the pandemic, the RNA sequence of the SARS-CoV-2 virus was made available (Wu et al., 2020), enabling the testing of infected patients by reverse transcription (RT)–PCR (Arnaout et al., 2020; Corman et al., 2020). Regular and broad testing of SARS-CoV-2 seems essential to contain the propagation of SARS-CoV-2, as many infected individuals express no symptoms, inadvertently spreading the infection (Ferretti et al., 2020; Kronbichler et al., 2020; Petersen and Phillips, 2020; Pollock and Lancaster, 2020; Sayampanathan et al., 2021). Therefore, successful epidemiological surveillance strategies required to monitor the spread of SARS-CoV-2 and the outbreak of new strains should include large-scale screening methods that enable periodic and continuous testing of the general population.

However, testing capacity has been limited, hampering attempts to control the spread of SARS-CoV-2. One obstacle is that reliable nasopharyngeal sampling and RT-PCR testing is highly invasive and requires both specialised staff and appropriate conditions for the manipulation and transport of the samples to comply with clinical standards and protocols expected by regulatory bodies (CDC, 2021b; UK-Government U, 2021). Lateral flow device antigen tests are cheaper, accurate when detecting individuals with high viral load, and an epidemiologically effective option to identify SARS-CoV-2 contagious people (Dinnes et al., 2021; Pavelka et al., 2021; Wagenhäuser et al., 2021). Yet, correct testing also requires nasopharyngeal sampling. Therefore, regular large-scale testing is difficult because accurate tests are either too invasive, expensive, or logistically complicated to implement, which make them unviable for the task.

To provide a simple alternative to identify SARS-CoV-2-infected individuals, we designed and validated a method by which SARS-CoV-2 RNA can be RT-PCR detected from samples taken from a person’s smartphone screen. This Phone Screen Testing (PoST) method shows high sensitivity (81–100%) compared to nasopharyngeal RT-PCR SARS-CoV-2 test results from individuals with a high viral load, making the smartphone screen a good proxy of the health status of contagious individuals. Furthermore, the SARS-CoV-2 variants present in PoST samples with low RT-PCR Ct value were successfully identified. Overall, our results provide a new, non-invasive, cost-effective, and efficient method to identify COVID-19 contagious infected cases and limit the transmission of the disease.

Results

PoST pilot to identify COVID-19-positive cases

SARS-CoV-2 RNA can be detected from many different kinds of surfaces, places, and devices, including phones (Marshall et al., 2020; Santarpia et al., 2020; Ye et al., 2020; Zhou et al., 2020). Furthermore, active SARS-CoV-2 virus is more likely to be recovered from some surfaces when expelled from individuals with seemingly high viral load (Bullard et al., 2020; Jefferson et al., 2020; Sonnleitner et al., 2021). Smartphones are personal objects that are constantly exposed to peoples’ mouths, their screens becoming a likely contaminated surface. Therefore, we hypothesised that COVID-19 contagious individuals will regularly deposit aerosols, droplets of saliva, or upper respiratory tract secretions containing shed SARS-CoV-2 virions, over the screen of their phone, which could then be sampled and detected by RT-PCR.

To facilitate test-trace and isolating strategies of COVID-19-infected individuals, we assessed the RT-PCR detection of SARS-CoV-2 RNA from smartphone screen swab samples via PoST. The presence of SARS-CoV-2 RNA in phone screens was then correlated with clinical COVID-19 nasopharyngeal RT-PCR-positive diagnosis of the phones’ owner. The cohort sample in this pilot study consisted of both symptomatic and asymptomatic or pre-symptomatic individuals who required SARS-CoV-2 testing due to a suspected SARS-CoV-2 infection, close contact to SARS-CoV-2-positive individuals, or return to work and travel authorisation requests in Santiago, Chile, between September and October 2020 (3.81% ± 1.0 average positivity rate in Santiago, Figure 1—figure supplement 1C–E).

Polyester swabs embedded in saline solution were used by a member of our team to sweep the bottom half of smartphone screens of individuals (Figure 1A). Of 540 individuals, 51 tested positive for SARS-CoV-2 by nasopharyngeal RT-PCR detection (9.4% positivity rate, Figure 1B [whole bar], Figure 1—figure supplement 1A, Source data 1). Remarkably, all samples with low Ct value, under 20, also tested positive for PoST (n = 15, Figure 1B [blue segment of bars], Figure 1C, Source data 1). Our results suggest that the ability for PoST to correctly identify positive nasopharyngeal individuals, sensitivity, is 100% in individuals with high viral load, Ct value under 20. As shown in Figure 1C (red line, Source data 1), the accumulated sensitivity of PoST in nasopharyngeal samples with medium Ct values below 30 is 89.7% (n = 29, medium and low viral load). Therefore, our results suggest that testing samples from smartphone screens is effective in identifying COVID-19-positive patients with low and medium Ct RT-PCR result values, which are thought to be actively contagious and expelling virus particles (Bullard et al., 2020; Jefferson et al., 2020; Sonnleitner et al., 2021). The study was performed in double-blind conditions such that the PoST and the nasopharyngeal RT-PCR tests were carried out in different laboratories by independent teams, which were not aware of each other’s result outcome.

Figure 1 with 2 supplements see all
Phone Screen Testing and RT-PCR can identify individuals with high SARS-CoV-2 viral load.

(A) Schematic of smartphone sampling. Swabbing follows the dashed line indicated trajectory. (B, D) Histograms showing the distribution of individuals on ranges of clinical RT-PCR Ct value results for the pilot cohort (B, full dataset in Source data 1) and validation cohort (D, full dataset in Source data 2). For example, bar Ct value 11 corresponds to samples with Ct between [11–13 [interval]]. Whole bar, all individuals with positive nasopharyngeal RT-PCR result. Blue bar section, those individuals also PoST positive. (C, E) Bars represent the accumulated number of individuals with positive RT-PCR clinical results under the Ct value number associated with the bar for, (C) pilot cohort, and (E) validation cohort. Red line in both plots depicts the sensitivity observed relative to clinical nasopharyngeal RT-PCR testing at the corresponding accumulated Ct value results. Left axis, percentage of sensitivity; right axis, number of accumulated individuals under the corresponding Ct value.

Of all the PoST and nasopharyngeal-positive samples in this cohort, 76% (n = 22/29) corresponded to individuals with no specific COVID-19 symptoms (Figure 1—figure supplement 1E, Source data 1). Therefore, testing smartphone screens is effective in identifying COVID-19-infected individuals regardless of their symptoms at the time of testing.

The overall ability of PoST to correctly identify a negative nasopharyngeal test, specificity, in this pilot was 98.8% (Figure 1—figure supplement 1A, Source data 1). Of this cohort, six samples were identified as PoST-positive/nasopharyngeal-negative, which could be interpreted as PoST false positives (Figure 1—figure supplement 1, Source data 1). However, in two cases that were contacted after testing, the individuals had three clear COVID-19 symptoms (Source data 1), suggesting that rather than a PoST false positive, these cases could be a nasopharyngeal false-negative result.

To further evaluate the apparent bimodal distribution observed in the Ct values from this cohort of positive COVID-19 clinical samples, we analysed the RT-PCR Ct dataset results of SARS-CoV-2-positive cases from the Davila Clinic (Santiago, Chile) adding up to over seven thousand samples (Figure 1—figure supplement 2A-H, Source data 3). When this data set was grouped in month intervals, we did observe a specific distribution of Ct values consistent with the pilot data at the months this cohort was tested (Figure 1B, Figure 1—figure supplement 2G-H).

The results of our pilot study were encouraging and suggested that the PoST method could be a good alternative to more invasive tests with similar sensitivity, like lateral flow antigen test screening (Dinnes et al., 2021; Jääskeläinen et al., 2021; Wagenhäuser et al., 2021). Therefore, validation with higher sample number was required to generate more conclusive evidence.

Validation of phone screen testing in a high-positivity-rate cohort

To further validate the PoST method, we increased the sample size by testing a new set of 764 individuals at the same clinic and similar cohort kind as before, between the 5 and 16April 2021. At this time, Santiago presented a high positivity rate (12.4% ± 2.2, Chilean Department of Health, 2021) as a consequence of the second COVID-19 wave in the country, which enabled identifying 182 SARS-CoV-2-positive individuals (24% positivity rate in this cohort at the clinic), by nasopharyngeal swabbing (Figure 1D, Figure 1—figure supplement 1B). The distribution of RT-PCR results in this study is unimodal and tends towards lower Ct values compared to the distribution observed in the pilot study (Figure 1B,C).

Similar to what was observed in the pilot cohort, the sensitivity of PoST ranges between 81.3% and 100% in nasopharyngeal samples with low Ct value, under 20 (high viral load, Figure 1D,E), and the sensitivity decays at higher Ct values (Figure 1E, red line). In this cohort, 35% of PoST- and nasopharyngeal-positive samples corresponded to COVID-19 asymptomatic or pre-symptomatic individuals at the time of testing (n = 43/122, Source data 2). This validation study was also performed in the same double-blind conditions as the pilot study described above.

The overall specificity of PoST during this validation was 97.6% (Figure 1—figure supplement 1B); 14 SARS-CoV-2-negative nasopharyngeal samples were identified positively by PoST (Figure 1—figure supplement 1B, Source data 2). Of these cases, we could contact four individuals, of which three had clear COVID-19 symptoms, one of which tested positive when the nasopharyngeal sample was repeated (Source data 2). This suggests that some of the discrepancies may be due to nasopharyngeal false-negative test results.

Early in the pandemic, the notion that SARS-CoV-2 could spread via surfaces made regular disinfection of surfaces a common practice (Goldman, 2020). We therefore evaluated whether cleaning smartphone screens before PoST sampling could affect the test results. Of all the SARS-CoV-2 PoST- and nasopharyngeal-positive samples where the screen had been cleaned within 24 hr (n = 23), 22% (5/23) were taken from phones that had been sanitised the same day (<6 hr), and 48% (8/23) less than 2 hr before the PoST sample was taken (Source data 3). This suggests that sanitising or cleaning the smartphone before the PoST sampling may not affect the detection of SARS-CoV-2 traces on the phone screen.

This validation study confirms that the PoST method shows a high sensitivity when identifying SARS-CoV-2-infected individuals with a low RT-PCR Ct value, regardless of their symptoms, providing a new valuable tool to tackle the COVID-19 pandemic.

SARS-CoV-2 variant identification in PoST samples

The current challenge in COVID-19 diagnostics is to find ways to distinguish the specific SARS-CoV-2 variant present in the tested samples to aid in containing outbreaks of variants with higher virulence or infectivity. To aid this task, we performed a screen to address whether SARS-CoV-2 variants can be identified from PoST samples. Fluorescent probe-based multiplexed or single RT-PCR reactions in 69 PoST samples from the 2021 cohort was used to identify the following variations in the Spike (S) SARS-CoV-2 gene: del69/70, K417N/T, E484K, N501Y, P681H. From this analysis, 36 samples fulfilled the criteria of amplifying SARS-CoV-2 control genes S and N. Out of this group, seven samples tested positive for at least one SNP associated with new SARS-CoV-2 variants. Two samples had all three variations described to be present in Beta (B.1.351-South African) or Gamma (P.1-Brasilian) variants (K417T, E484K, N501Y). Another three samples showed variations E484K and N501, which are only found together in Gamma and Beta variants. Even though these samples did not test positive for K417T, it is still likely that the virus in these samples corresponds to either Beta or Gamma, as the combination of variations that tested positive have only been found together in these two SARS-CoV-2 variants. One sample only tested positive for SNP K417T, which is only found in Gamma and Beta SARS-CoV-2 variants. Lastly, we identified one sample with variation del69/70 and P681H, which are only found together in the Alpha (B.1.1.7- UK) SARS-CoV-2 variant. The remaining 28 samples showed no variation, and hence are likely to contain original Wuhan SARS-CoV-2.

Our results imply that the capacity to identify SARS-CoV-2 RNA by the primer/probe set we used for PoST is not affected by the mutations described for the variant of concern we identified. The capacity of identifying SARS-CoV-2 variants from PoST samples differentiates this assay from lateral flow device antigen testing, which can only identify the presence of the virus and not discriminate specific variants.

Discussion

A recent study suggests that socioeconomic status and delay in testing for SARS-CoV-2 was a significant factor in the high mortality rate observed during 2020 in Santiago, Chile (Mena et al., 2021). Therefore, finding new methods to enhance epidemiological surveillance strategies are necessary to limit the struggle generated by the COVID-19 pandemic.

Our study suggests that the PoST method could be an effective non-invasive way to rapidly identify COVID-19-positive contagious individuals who actively spread the virus, regardless of their symptoms. This method does not require specialised operators or conditions for sampling. Furthermore, because PoST is an environmental test, the protocols and reagents required to manipulate and process the samples for RT-PCR have been optimised to make PoST substantially more cost-effective, circumventing the need for clinical-grade reagents and standards. All which makes PoST a good alternative for large-scale population testing.

Interpretation of the PoST method results

PoST-positive tests correlate with nasopharyngeal samples with low RT-PCR Ct values, which suggests that individuals with low Ct clinical RT-PCR results are probably passing through the peak of a COVID-19 infection and are contagious, shedding SARS-CoV-2 viral particles that can be detected on their smartphone screens. The Ct value of RT-PCR results from nasopharyngeal samples may present a level of variability that is intrinsic to the nature of the technique, the sampling process, and because the results are not standardised to an internal reference (Dahdouh et al., 2021). However, considering these inherent limitations, correlations have been found between nasopharyngeal samples with low RT-PCR Ct value results and the level of infectivity assessed by the capacity to propagate the SARS-CoV-2 virus in vitro from such samples (Bullard et al., 2020; Jefferson et al., 2020; Sonnleitner et al., 2021). Our results add support to the possibility that patients with low Ct RT-PCR results from nasopharyngeal samples present a high viral load and are actively shedding SARS-Cov-2, which can be detected on the screen of smartphones.

Of all the PoST-positive samples, most of which had low nasopharyngeal RT-PCR Ct results, 76% of the pilot and 35% in the validation study were asymptomatic or pre-symptomatic at the moment of testing (Figure 1—figure supplement 1E, Source data 1, 2). Suggesting that PoST is effective in identifying COVID-19-positive individuals regardless of their symptoms.

SARS-CoV-2 variant identification is required to further enhance epidemiological surveillance to contain the spreading of variants of concern that are more pathogenic or infective, to contain and isolate their dissemination. We successfully identified one PoST sample that presented all three polymorphisms present in Beta (B.1.351) and Gamma (P.1) variants. The rest of the tests did not unequivocally show which SARS-CoV-2 variant was present in the sample but was enough to conclude the nature of the variant present in the sample. Even though optimisation will be required to enhance SARS-CoV-2 variant identification in PoST samples, our results are encouraging, and could make PoST a viable option to screen for variants of concern. In this scenario, and although the output of results would take longer, PCR and sequencing will likely enhance the performance of variant detection in PoST samples.

Regarding nasopharyngeal RT-PCR results with a high Ct value (i.e., lower-viral load), these are probably in transition, and either starting or ending a COVID-19 infection. Therefore, they are less likely to shed SARS-CoV-2 virions that can be detected by PoST. This transition is the reason why periodic regular testing is required to identify those infected individuals once they enter a contagious phase.

To a lesser extent and against the overall trend we observe for PoST detection, PoST-positive results were identified in this high Ct value nasopharyngeal RT-PCR results group. Given the unstable nature of the SARS-CoV-2 virus on surfaces (Goldman, 2020), and the pervasive activity of RNases that are ubiquitously present in the environment (Probst et al., 2006), it is unlikely that these positive PoST results are due to the detection of long-lasting virus or RNA on the phone screen surface. Hence, we could exclude the possibility that these PoST-positive results are the consequence of detecting RNA from when individuals were passing through a moment of higher COVID-19 infection. Therefore, one could speculate that these results are the consequence of suboptimal nasopharyngeal sampling, which would explain the low amount of virus in the sample and hence, a high Ct value. Alternatively, it is plausible that these samples belong to individuals with a low viral load that are still actively contagious, which is against the observed trend (Bullard et al., 2020; Jefferson et al., 2020; Sonnleitner et al., 2021), but cannot be excluded as a possibility. It will be interesting to perform a follow-up study on these individuals as they could be part of a group with a higher capacity to shed SARS-CoV-2 along their infectious cycle, potentially explaining the COVID-19 superspreading capacity observed in some people (Lewis, 2021).

The distribution profile of the nasopharyngeal RT-PCR Ct test results in our study was different in the pilot and validation cohorts. The pilot Ct results presented an apparent bimodal distribution with low and high Ct value populations (Figure 1B). On the other hand, in the validation study, the distribution was unimodal and most samples tended towards low RT-PCR Ct results (Figure 1D). We speculate that this stark difference could be due to an inherent characteristic of these cohorts related to the positivity rates in the population of Santiago at the time of sampling. In fact, the distribution profile of the pilot nasopharyngeal Ct values is similar to that corresponding to samples taken when the pilot sampling was performed (Figure 1—figure supplement 2G–H). At the time the pilot study was performed, Santiago, Chile, presented a low average positivity rate (3.8% ± 1.0, Chilean Department of Health, 2021), and was recovering from the first COVID-19 wave. Likewise, the distribution profile of the validation cohort nasopharyngeal Ct results was similar to when Santiago was passing through the middle of first the COVID-19 wave, at a high average positivity rate (9.5–26.4%, Figure 1—figure supplement 2B–D). This observation suggests that the RT-PCR Ct value results distribution could show specific profile signatures that express the epidemiological status of the population. Confirming this observation will further require a deeper analysis of this kind of dataset.

Advantages and limitations of the PoST method

Cost effective

One of the main advantages of PoST is its low cost compared to clinical nasopharyngeal tests. Excluding staff and premises, the net cost of a nasopharyngeal test in Chile ranges between 20 and 35 USD, which includes sample tube, transport media, swab, RNA extraction kit, and RT-PCR kit. Because PoST does not use clinical-grade consumables and reagents, its net cost for the same items ranges between 2 and 3 USD when it is the result of a single sample tested RT-PCR reaction. This net cost can go below $1 USD when PoST samples are pooled and groups of 5 and a single RT-PCR is performed, which we have shown to produce reliable results for PoST samples (data not shown).

Besides PoST not using clinical-grade consumables and reagents, one key optimisation is that PoST does not require an RNA extraction step, which reduces the cost by approximately $7 USD. Furthermore, instead of purchasing an RT-PCR kit specifically designed for SARS-CoV-2 detection, we assembled a combination of off-the-shelf probe/primers to detect the SARS-CoV-2 gene ‘N’ together with a generic RT-PCR kit. All together this optimisation enables a 10-fold price reduction of the net cost of PoST compared to a regular nasopharyngeal RT-PCT test.

High sensitivity and specificity

The PoST method has a similar sensitivity and specificity, compared to antigen lateral flow devices, which are extensively used for routine testing (Dinnes et al., 2021; Jääskeläinen et al., 2021; Wagenhäuser et al., 2021). Clinical-grade diagnostic RT-PCR kits include the detection of three SARS-CoV-2 genes, plus a human positive control, either multiplexed or individually detected. The specificity reached by PoST in this study was achieved only when detecting the ‘N’ SARS-CoV-2 gene. This could explain why PoST can miss identifying some positive nasopharyngeal RT-PCR samples in the low Ct range. A study adding the detection of two or three SARS-CoV-2 genes in the PoST protocol to assess whether a higher sensitivity is achieved would enable us to calculate whether this trade-off is enough to justify increasing the net cost of the PoST assay. Especially considering that the sensitivity described in this study is already high enough to detect COVID-19-positive individuals to affect limiting the transmission of the SARS-CoV-2 virus (Kennedy-Shaffer et al., 2021; Larremore et al., 2021; Mina et al., 2020).

Sampling speed and result turnaround of PoST

One other advantage of the PoST method is that the sampling process takes around a minute at most and does not require a particular setup besides having a sterile swab and sample tube. To maximise the speed and minimise errors in the PoST processing of samples, we developed a barcode-based smartphone application (unpublished), which enables the efficient tracking of the samples through the testing pipeline, ending with the delivery of results to the tested individuals’ smartphone via SMS. Moreover, pooling samples can reduce the number of RT-PCR required to process, further decreasing the time to deliver results, when the positivity rate is below 5% to justify pooling. With all this in place, a minimal non-automatised laboratory setup with one 96-well plate real-time PCR machine has the potential to deliver 940 test results per day, when processed by two technicians, and working on two rounds of 470 samples.

Altogether, this enables an efficient turnaround of results such that after the samples arrive at the lab, the results of 940 can be delivered in approximately 5.5 hr, if no SARS-CoV-2-positive samples are found, and 6.5 hr if positive individual samples are to be identified from pools. These times consider two technicians processing the samples to feed one 96-well plate real-time PCR machine. Therefore, under these conditions, results for 940 tests could be provided within the same day of sampling, which is ideal to isolate contagious cases, and effectively curb the spreading of COVID-19.

PoST as an alternative self-testing method

Due to its high sensitivity, specificity, and rapid result turnaround time, lateral flow device antigen testing has become widely used to screen for COVID-19 cases operated by trained staff (Pavelka et al., 2021) and self-administered (Riley et al., 2021). Because this method uses highly invasive nasopharyngeal swabbing, trained operators are the preferred option to deliver accurate and reliable results from these tests. From this point of view, the PoST method offers a valuable alternative for accurate self-test results as it is much easier and more reliable to effectively swab the screen of a smartphone than performing a self-administered nasopharyngeal test. This, together with the fact that SARS-CoV-2 variants can be identified in PoST samples, gives this method further advantages compared to lateral flow antigen testing.

Penetration of smartphone use in the population

One aspect that is important to mention is that although it is estimated that there are around 3.8 billion smartphones in the world and their penetration is very high among the young and adult population, their global distribution is not equitable (Turner, 2021). While penetration is almost total among adults in developed countries, in countries such as India or Bangladesh it does not exceed 33% of the population (Berenguer et al., 2016). On the other hand, among senior citizens, who are precisely a vulnerable population, even in developed countries some do not use a telephone or have older devices.

Overall, this study was aimed to validate PoST as method to identify COVID-19-infected cases by using the smartphone as a proxy from which traces of the SARS-CoV-2 virus of the owner can be detected. We propose that this highly sensitive, non-invasive, and cost-effective method could well be used for mass testing and help to contain the spreading of other airborne contagious diseases and outbreaks when tackling future epidemics. This could be particularly useful as an early warning system for rapid detection of respiratory pathogens in public health efforts to contain local outbreaks to prevent further escalating to other areas.

Materials and methods

Smartphone screen swab sampling, sample processing, and RT-PCR

Request a detailed protocol

Informed consent and consent to publish was obtained from all the individuals that participated in this study before performing the sampling process. Dacron swabs were briefly dipped in Weise medium (Merck, 1.09468.0100) and then used to swab the bottom half of mobile phone screens by a member of our team as shown in Figure 1A. Swabs were then introduced in sterile conical tubes containing Weise medium and briefly hand spun. Samples were processed for RT-PCR within 8 hr.

Aliquots of swab samples were incubated at 70°C for 10 min as previously described (Miranda et al., 2020). Samples were left to cool at room temperature and 3.3-µl aliquots were used for RT-PCR using Promega GoTaq Probe 1-Step RT-qPCR system (A6121) according to the manufacturer instructions and supplemented with SARS-CoV-2 N2 probes and primers (IDT#10006606) on an Illumina Eco Real-Time PCR System. We considered a test as positive if the PCR amplification obtained followed the expected standard sigmoidal kinetics of amplification.

Clinical sampling and RT-PCR

Request a detailed protocol

For each patient, nasopharyngeal swabs were collected using standard technique, as recommended by the manufacturer (AllplexTM 2019-nCoV Assay insert) and transported to the laboratory in viral transport medium (prepared according to the standard operating procedure of the CDC, USA). For all samples, RNA extraction was performed using STARmag kit (Seegene, Korea), and following the manufacturer’s instructions. For the analysis of the pilot cohort samples, target gene amplification of SARS-Cov-2 was performed using the AllplexTM 2019-nCoV Assay kit (Seegene, Korea), according to the manufacturer’s procedure. The RT-qPCR preparation was carried out in the Starlet equipment (Hamilton, USA, distributed by Seegene) and the qPCR amplification in a CFX-96 thermal cycler (Bio-Rad, USA). The AllplexTM 2019-nCoV Assay kit detects three viral genes (N, RdRP, and E). We considered a test as positive if PCR amplification was obtained with N gene and RdRP. If only the E gene was amplified, the test was considered presumably positive, thus requiring repetition by another extraction instrument (MagNAPure Compact System, Roche).

Identification of SARS-CoV-2 variants

Request a detailed protocol

The detection of different SARS-CoV-2 single nucleotide and deletion variants was performed using the Applied Biosystems TaqMan SARS-CoV-2 Mutation Panel kit (ThermoFisher) according to the conditions recommended by the manufacturer, on the AriaMx Real-time PCR system (Agilent Technologies) thermal cycler for fluorescence detection on VIC (reference sequence) and FAM channels (mutation sequence), and the AccuPower SARS-CoV-2 Variants ID Real-Time RT-PCR kit (Bioneer) according to manufacturer conditions, on the Exicycler 96 V4 Real Time thermal cycler (Bioneer) to detect fluorescence on the TET, TexasRed, FAM, TAMRA, and Cyanine5 channels.

Data availability

All the data used generated by this study was provided in the uploaded manuscript and source files.

References

  1. Conference
    1. Berenguer A
    2. Goncalves J
    3. Hosio S
    4. Ferreira D
    5. Anagnostopoulos T
    6. Kostakos V
    (2016)
    Are smartphones ubiquitous?
    IEEE Consum Electron Mag. pp. 104–110.

Decision letter

  1. Joshua T Schiffer
    Reviewing Editor; Fred Hutchinson Cancer Research Center, United States
  2. Jos WM van der Meer
    Senior Editor; Radboud University Medical Centre, Netherlands
  3. Joshua T Schiffer
    Reviewer; Fred Hutchinson Cancer Research Center, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Phone Screen Testing of SARS-CoV-2 complemented by a computer-based strategy to effectively tackle the COVID-19 pandemic" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Jonathan Dushoff (Reviewer #2); Ben S Cooper (Reviewer #3).

We are sorry to say that, after consultation with the reviewers, we have decided that your work will not be considered further for publication by eLife.

All reviewers agreed that the testing of mobile phone screens is highly novel and this study demonstrates that it could be potentially useful to expedite more widespread testing. The major reservations related to the mathematical modeling and the lack of specific consideration about implementation issues. Reviewer two pointed out the these included models are "neither necessary or sufficient to evaluate the possible usefulness of this testing method." It would be necessary to describe the specifics of a screening plan based on smartphone testing how it might interact with other interventions, or possible disadvantages due to displacing other tests that may have higher sensitivity or specificity. Testing smartphones at scale requires a plan, and an assessment of costs, including opportunity costs.

The modeling while robust, does not account for these real world issues and is not specifically calibrated to any specific COVID epidemiology data or parameters. Moreover, the effects in the model are mediated mostly by the quarantine associated with testing, whereas the greatest utility of this testing approach would require linkage to contact tracing.

A final comment on the cell phone testing strategy was that the sample size is small, with only 51 SARS-CoV-2 individuals (by nasopharyngeal swab). Overall, this presents as an extremely promising pilot study which needs further validation in a larger cohort.

Reviewer #1:

Strengths of the study are:

– A novel and potentially extremely useful approach to testing;

– Exciting data showing that cell phone swabbing can clearly be used to detect most people who remain contagious;

– The key variable for this approach is turnaround time of the assay and this is addressed in the mathematical model.

Areas for potential improvement are:

– The model has not been linked to real epidemic data such that estimates of the daily percentage of people who must be tested to achieve epidemic control are likely not reliable.

– The model links testing to quarantine which is compatible with current clinical and public health practice even if testing is generally catered to people who are at risk for infection based on symptoms or contacts rather than mass screening. In that sense, the model is really capturing the effect of mass testing and quarantine. The more realistic implementation would be use of this approach in a focused test and trace model.

– In general, a more detailed and realistic model is needed to assess the degree of implementation required in order to flatten or eliminate subsequent epidemic curves.

My opinion is that the assay portion of the paper alone would do well as a short report. However, the modeling lacks sufficient link to data and details of an implementation plan to truly inform public health policy or practice.

Reviewer #2:

The technology proposed is interesting and may well have potential.

The authors argue for smartphone testing as a component of a COVID screening strategy. They have done a small pilot study that shows promising results. They add two sensible mathematical models which contain a lot of assumptions, at least some of which should be better justified. Crucially, these mathematical models are neither necessary or sufficient to evaluate the possible usefulness of this testing method. The authors do not discuss what a screening plan based on smartphone testing might look like, how it might interact with other interventions, or possible disadvantages due to displacing other tests that may have higher sensitivity or specificity.

The pilot study is very small. The results are certainly promising, but should not be over-interpreted. The authors do not say if the k-means based partitioning was pre-planned.

The authors dismiss their method's low sensitivity for samples with low viral loads too lightly: in particular, the claim that "only" individuals with Ct<30 expel culturable virions is not supported by the cited studies. Even less is known about "infectiousness". The authors also state that individuals early in infection are not likely to be infectious without discussing the fact that these people are likely to become infectious in reality, but not in the authors' model world, where they are not infected.

Testing smartphones at scale requires a plan, and an assessment of costs, including opportunity costs. The authors seem to assume that everyone in the population can be tested this way, either at random in the ODE model, or sequentially in the ABM. They do not discuss questions of access or of equity (which populations don't have smartphones?). The authors discuss the difficulty of nasopharyngeal testing (L60) but could provide more details about the relative advantages of smartphone testing.

The presented models are not a substitute for a clear plan or for a larger confirmatory study. There is nothing specific in the models to smartphone-based surveillance. In particular, the models do not incorporate the putative sharp difference in sensitivity to high vs. low viral loads, nor take into account how viral loads might vary through time in an infection. There are many models available to do what the authors' models do, but they are not discussed. The authors' models may well have new features, but absent a relevant literature review, the reader cannot judge.

The authors should avoid post hoc analysis pathways (like using k-means to divide into two clusters). It's probably OK to report that 26/28 high or medium-load samples were positive, but this proportion should be reported with confidence intervals and (unless the authors had a clearly written plan beforehand to not do this) the overall proportion should be reported with confidence intervals as well.

It's pretty well known that better surveillance techniques would be better. If the authors want to do their own models, they need a clear reason (one is suggested above), and they need to situate their models in the universe of similar models already available.

What is needed to make this paper convincing is more data (or better scepticism about the existing data) and more discussion about logistics.

I don't understand the claim at L123.

Not sure if this is in the reviewer's ambit, but I dislike the explanations surrounding the conflict of interest. The authors should state the facts, they don't need to state that they wish to state them, nor to judge their own conflicts.

Reviewer #3:

The authors describe a novel approach for detecting individuals infected with SARS-CoV-2 which avoids the need to do nasopharyngeal swabs: swabbing smartphones and testing for the virus (with RT-PCR) in the swabs. The main advantage of swabbing phones rather than the nasopharynx, the authors argue, is that costs would be lower and testing could be faster.

The authors demonstrate feasibility of such an approach by applying their smartphone screening protocol to 540 individuals, 51 of whom are positive SARS-CoV-2 (by RT-PCR) from nasopharyngeal swabs. They demonstrate remarkable concordance between the nasopharyngeal and smartphone screening results. They then perform two model-based analyses, first using a simple deterministic model with homogeneous mixing, and second using an idealised individual based model (with transmission occurring on a 100x100 grid), and show that under the model assumptions daily smartphone testing of 10% of all individuals would be able to suppress transmission of the virus provided screening results are acted on between 0 and 3 days after the swabs are taken.

Strengths:

A major strength of the work is its novelty: I am not aware of other attempts to detect SARS-CoV-2 infection routinely by screening smartphones, and if the very high concordance with nasopharyngeal swabbing achieved here could be demonstrated in a larger and better-characterised cohort the results could have considerable significance given the lower costs and greater ease with which smartphones can be screened (it could, for example, be mechanised reducing costs further).

Secondly, quite apart from whether the findings do have potential to be used in routine screening as the authors suggest, the finding concerning the agreement between results from screening phones and nasopharynx has infection control implications which, though not mentioned by the authors, may be of potential importance in some contexts.

Weaknesses:

The sample size is small, with only 51 SARS-CoV-2 individuals (by nasopharyngeal swab) so this must be considered a pilot study rather than a large-scale evaluation of the approach. Clearly, if the approach is to gain any traction a much larger study is needed.

The claimed advantages over conventional nasopharyngeal screening are lower costs and faster turnaround times, but no attempt to quantify these are given. This information seems crucial for comparison with other testing approaches (e.g. PCR-based tests of nasopharyngeal swabs and lateral flow tests which are now widely used).

While the modelling seems to be done with competence, conclusions are based on idealised assumptions. For example, models assume once isolated infected individuals do not contribute to further transmission. At least in settings where isolation occurs at home (which is most parts of the world) this is not a realistic assumption. Other aspects of the models also lack biological realism (for example, the assumption that infectivity does not change over the course of an infection and exponential sojourn times in model compartments). For these reasons, the claim that "iterative testing over 10% of the population [daily] could effectively suppress the spread of COVID-19" applies only to the hypothetical idealised world of the model, and the work tells us little about how such at an approach would work in practice (accounting for the fact that isolation will not stop within-household transmission and that isolation will be imperfect etc).

Comments for the authors:

1. Some of the terminology used is non-standard. For example "quarantine" traditionally applies to isolation of those considered at risk of being infected but who have not yet been shown to be infected. "isolation" would be a better term for what the authors are describing.

2. I don't think the comparison with influenza in 1918/19 and talk of the "third wave" (as a universal occurrence) is helpful – it's a very different pathogen, and different countries may experience different numbers of "waves" due to the timing of interventions, emerging variants and seasonal factors.

3. To better make the case for the advantages of the approach over nasopharyngeal screening, some numbers are needed: costs, turnaround times etc.

4. Very little information is given on how those screened are selected. This information would strengthen the paper.

5. To make the case for the value of the approach in a specific population information on smartphone ownership in different age groups is needed.

6. Another potential advantage over nasopharyngeal swabbing is the lack of physical discomfort. This could lead to greater acceptance of the approach. In future work, it would be interesting to explore this.

7. Clearly, if the remarkable findings reported are to translate into a real-world intervention a much larger study with a better characterised population is needed. In future work the authors could also consider exploring RT-PCR versus lateral flow testing of the phone swabs.

8. While the models reported are adequate for a rough back-of-the envelope assessment, a more thorough model-based assessment would require models that have a stronger biological basis (i.e. more realistic assumptions about how infectivity changes over time, see for example, Grassly et al. Lancet Inf Dis 2020), and also more realistic assumptions about isolation (i.e. adherence and transmission in isolation settings).

9. In line with the approach in Grassly et al., I think it would be more informative to report modelling results as % reductions in transmission, as baseline transmissibility varies widely between settings (due to variation in climate, behaviours, pathogen lineage etc).

10. Very few results are reported from the agent-based model (only the kurtosis plots). It wasn't clear to me why this model wasn't explored more fully.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Smartphone Screen Testing, a novel pre-diagnostic method to identify SARS-CoV-2 infectious individuals" for consideration by eLife. Your article has been reviewed by Joshua T Schiffer as the Reviewing Editor and Reviewer #1 and Jos van der Meer as the Senior Editor.

The Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) Please provide a more balanced comparison of cell phone screening versus lateral flow antigen testing.

Reviewer #1:

This manuscript presents cell phone swabbing as a potentially useful method for SARS-CoV-2 diagnosis.

The revised version of this paper does a nice job of adding more samples and clarifying certain analyses. The removal of the mathematical modeling strengthens the manuscript. The paper demonstrates that self-phone sampling for SARS-CoV-2 appears to be a promising diagnostic approach, worthy of more study.

One criticism is that the advantages relative to lateral flow antigen testing are overstated. Antigen tests offer similar sensitivity and specificity with more rapid turnaround time. This should be mentioned.

https://doi.org/10.7554/eLife.70333.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

All reviewers agreed that the testing of mobile phone screens is highly novel and this study demonstrates that it could be potentially useful to expedite more widespread testing. The major reservations related to the mathematical modeling and the lack of specific consideration about implementation issues. Reviewer two pointed out the these included models are "neither necessary or sufficient to evaluate the possible usefulness of this testing method." It would be necessary to describe the specifics of a screening plan based on smartphone testing how it might interact with other interventions, or possible disadvantages due to displacing other tests that may have higher sensitivity or specificity. Testing smartphones at scale requires a plan, and an assessment of costs, including opportunity costs.

The modeling while robust, does not account for these real world issues and is not specifically calibrated to any specific COVID epidemiology data or parameters. Moreover, the effects in the model are mediated mostly by the quarantine associated with testing, whereas the greatest utility of this testing approach would require linkage to contact tracing.

A final comment on the cell phone testing strategy was that the sample size is small, with only 51 SARS-CoV-2 individuals (by nasopharyngeal swab). Overall, this presents as an extremely promising pilot study which needs further validation in a larger cohort.

We thank the reviewers for their very helpful comments, all of which have been taken on board in this new improved manuscript. Besides removing the computational modelling section from the manuscript, the three main changes in the new version are:

1. In addition to the 51 nasopharyngeal SARS-CoV-2 RT-PCR positive samples, 182 new cases were added to the study.

2. We show that SARS-CoV-2 ‘variants of concern’ can be identified from the samples taken from smartphone screens.

3. We have extensively elaborated on the interpretation and limitations of our results in the Discussion section of the new manuscript.

In the following rebuttal, we have only addressed the comments of reviewers regarding the SARSCoV-2 phone screen testing method. Below, we provide a more detailed description of our responses to the reviewer comments.

Reviewer #1:

[…] My opinion is that the assay portion of the paper alone would do well as a short report. However, the modeling lacks sufficient link to data and details of an implementation plan to truly inform public health policy or practice.

We have removed the modelling data from the manuscript.

Reviewer #2:

[…] The pilot study is very small. The results are certainly promising, but should not be over-interpreted. The authors do not say if the k-means based partitioning was pre-planned.

We took on board this and other reviewers’ comments regarding sample number and, as mentioned above, we have increased the sample number by 182 nasopharyngeal positive RT-PCR results. Also following this and other reviewers’ suggestions we have further elaborated on many aspects in the discussion of this new version and have also removed the k-means portioning as based on the new data, we decided it is no longer necessary.

[…] The authors should avoid post hoc analysis pathways (like using k-means to divide into two clusters). It's probably OK to report that 26/28 high or medium-load samples were positive, but this proportion should be reported with confidence intervals and (unless the authors had a clearly written plan beforehand to not do this) the overall proportion should be reported with confidence intervals as well.

The k-means post hoc analysis has been removed from the manuscript.

[…] What is needed to make this paper convincing is more data (or better scepticism about the existing data) and more discussion about logistics.

We have increased the SARS-CoV-2 Rt-PCR positive sample number four times and also extensively elaborated on the implications and potential of this new method in the discussion.

I don't understand the claim at L123.

This has been removed from the current manuscript.

Not sure if this is in the reviewer's ambit, but I dislike the explanations surrounding the conflict of interest. The authors should state the facts, they don't need to state that they wish to state them, nor to judge their own conflicts.

We agree with the reviewer and have now just stated the facts.

Reviewer #3:

[…] The sample size is small, with only 51 SARS-CoV-2 individuals (by nasopharyngeal swab) so this must be considered a pilot study rather than a large-scale evaluation of the approach. Clearly, if the approach is to gain any traction a much larger study is needed.

As mentioned above, we have significantly increased the sample number of SARS-CoV-2 positive individuals tested by nasal swabbing and RT-PCR. We expect this is enough for the referees to now consider this a validated method.

The claimed advantages over conventional nasopharyngeal screening are lower costs and faster turnaround times, but no attempt to quantify these are given. This information seems crucial for comparison with other testing approaches (e.g. PCR-based tests of nasopharyngeal swabs and lateral flow tests which are now widely used).

We thank the reviewer for pointing this out. Based on these suggestions we have made significant additions to the discussion which now includes arguments and quantification backing up the lowcost and quick turnaround times we claim for the phone screen testing method.

[…] Comments for the authors:

1. Some of the terminology used is non-standard. For example "quarantine" traditionally applies to isolation of those considered at risk of being infected but who have not yet been shown to be infected. "isolation" would be a better term for what the authors are describing.

This comparison was removed from the introduction.

2. I don't think the comparison with influenza in 1918/19 and talk of the "third wave" (as a universal occurrence) is helpful – it's a very different pathogen, and different countries may experience different numbers of "waves" due to the timing of interventions, emerging variants and seasonal factors.

As mentioned above, this has now been included in the discussion.

3. To better make the case for the advantages of the approach over nasopharyngeal screening, some numbers are needed: costs, turnaround times etc.

As the reviewer has noticed, to maximise the number of tested individuals, there was no selection criteria and all the people who arrived at the Davila Clinic (Santiago, Chile) for a SARS-CoV-2 test were recruited for the study.

[…] 5. To make the case for the value of the approach in a specific population information on smartphone ownership in different age groups is needed.

We have included studies for geographical and age distribution of smartphone usage in the discussion.

6. Another potential advantage over nasopharyngeal swabbing is the lack of physical discomfort. This could lead to greater acceptance of the approach. In future work, it would be interesting to explore this.

We agree with the reviewer and the non-invasive advantage of the phone screen testing method was enhanced in this new version of the manuscript.

7. Clearly, if the remarkable findings reported are to translate into a real-world intervention a much larger study with a better characterised population is needed. In future work the authors could also consider exploring RT-PCR versus lateral flow testing of the phone swabs.

We agree with the reviewer and we are currently embarked on a study comparing lateral flow device antigen testing and phone screen testing results. Comparisons between both methods have also been elaborated in the discussion of this current version of the manuscript.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Reviewer #1:

The revised version of this paper does a nice job of adding more samples and clarifying certain analyses. The removal of the mathematical modeling strengthens the manuscript. The paper demonstrates that self-phone sampling for SARS-CoV-2 appears to be a promising diagnostic approach, worthy of more study.

One criticism is that the advantages relative to lateral flow antigen testing are overstated. Antigen tests offer similar sensitivity and specificity with more rapid turnaround time. This should be mentioned.

We agree with the reviewer and when referring to lateral flow antigen testing, we have replaced:

“Lateral flow device antigen testing has become widely used to screen for COVID-19 cases operated by trained staff (Pavelka et al., 2021), and self-administered (Riley et al., 2021).”

For:

“Due to its high sensitivity, specificity, and rapid result turnaround time, lateral flow device antigen testing has become widely used to screen for COVID-19 cases operated by trained staff (Pavelka et al., 2021), and self-administered (Riley et al., 2021).”

https://doi.org/10.7554/eLife.70333.sa2

Article and author information

Author details

  1. Rodrigo M Young

    1. Diagnosis Biotech, Santiago, Chile
    2. Institute of Ophthalmology, University College London, London, United Kingdom
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing, R.Y. conceived the Phone Screen Testing method
    For correspondence
    1. ryoung@diagnosis-bt.com
    2. rodrigo.young@ucl.ac.uk
    Competing interests
    co-founder of Diagnosis Biotech
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5765-197X
  2. Camila J Solis

    Diagnosis Biotech, Santiago, Chile
    Contribution
    Data curation, Formal analysis, Supervision, Validation, Investigation, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7195-523X
  3. Andres Barriga-Fehrman

    Diagnosis Biotech, Santiago, Chile
    Contribution
    Conceptualization, Formal analysis, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    co-founder of Diagnosis Biotech
  4. Carlos Abogabir

    Diagnosis Biotech, Santiago, Chile
    Contribution
    Formal analysis, Methodology, Project administration
    Competing interests
    co-founder of Diagnosis Biotech
  5. Alvaro R Thadani

    Diagnosis Biotech, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2541-1709
  6. Mariana Labarca

    Diagnosis Biotech, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6455-3569
  7. Eva Bustamante

    Grupo Oncológico Cooperativo Chileno de Investigación, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3125-8608
  8. Cecilia V Tapia

    Laboratorio de Especialidad, Clínica Dávila, Santiago, Chile
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6234-2100
  9. Antonia G Sarda

    Laboratorio de Especialidad, Clínica Dávila, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  10. Francisca Sepulveda

    Laboratorio de Especialidad, Clínica Dávila, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8144-0096
  11. Nadia Pozas

    Laboratorio de Especialidad, Clínica Dávila, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  12. Leslie C Cerpa

    Laboratory of Chemical Carcinogenesis and Pharmacogenetics (Chilean Health Council Diagnostic Covid19 Laboratory), Department of Basic and Clinical Oncology, Faculty of Medicine, University of Chile, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9525-389X
  13. María A Lavanderos

    Laboratory of Chemical Carcinogenesis and Pharmacogenetics (Chilean Health Council Diagnostic Covid19 Laboratory), Department of Basic and Clinical Oncology, Faculty of Medicine, University of Chile, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6167-0508
  14. Nelson M Varela

    Laboratory of Chemical Carcinogenesis and Pharmacogenetics (Chilean Health Council Diagnostic Covid19 Laboratory), Department of Basic and Clinical Oncology, Faculty of Medicine, University of Chile, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5229-3007
  15. Alvaro Santibañez

    1. Centro de Biotecnología Acuícola, Facultad de Química y Biología, Santiago, Chile
    2. Programa Disciplinario de Inmunología, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Santiago, Chile
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9330-2961
  16. Ana M Sandino

    1. Centro de Biotecnología Acuícola, Facultad de Química y Biología, Santiago, Chile
    2. Departamento de Biología, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago, Chile
    Contribution
    Investigation, Methodology, Project administration
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3862-3743
  17. Felipe Reyes-Lopez

    1. Centro de Biotecnología Acuícola, Facultad de Química y Biología, Santiago, Chile
    2. Departamento de Biología, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago, Chile
    3. Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, Bellaterra, Spain
    4. Facultad de Medicina Veterinaria y Agronomía, Universidad de Las Américas, Providencia, Chile
    Contribution
    Investigation, Methodology, Writing - original draft, Project administration
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5001-457X
  18. Garth Dixon

    1. Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, Bellaterra, Spain
    2. Department of Microbiology, Virology and Infection Control, Hospital National Health Service Foundation Trust, London, United Kingdom
    3. National Institute for Health Research Biomedical Research Centre at Great Ormond Hospital for Children National Health Service Foundation Trust and University College, London, United Kingdom
    Contribution
    Investigation, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8165-3094
  19. Luis A Quiñones

    Laboratory of Chemical Carcinogenesis and Pharmacogenetics (Chilean Health Council Diagnostic Covid19 Laboratory), Department of Basic and Clinical Oncology, Faculty of Medicine, University of Chile, Santiago, Chile
    Contribution
    Supervision, Funding acquisition, Investigation, Methodology, Project administration
    For correspondence
    lquinone@uchile.cl
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7967-5320

Funding

Moorfields Eye Hospital NHS Foundation Trust (001155)

  • Rodrigo M Young

Moorfields Eye Hospital NHS Foundation Trust (GR001210)

  • Rodrigo M Young

Agencia Nacional de Investigación e Innovación (ANID-Covid0789)

  • Luis A Quiñones

Agencia Nacional de Investigación e Innovación (ANID-Covid1038)

  • Ana M Sandino
  • Felipe Reyes-Lopez

FONDECYT (1211841)

  • Felipe Reyes-Lopez

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We are very grateful for the help from the following colleagues: Rachel Aguilar Montes, Prof. Miguel Allende, José Aramburó, Mauricio Daza, Dr Carmen Feijóo, Camila Gonzalez Badilla, Itziar Linazaroso, Dr Jaime Mañalich, Dr Gonzalo Mena, Emiliana Montes, Dr Gareth Powell, Rodrigo Prieto, Esteban Quiñones, Dr Cristian Undurraga, Whitmy Valdés Araneda, Dr Carlos Vega, Mr Timothy Best, Dr Kathryn Harris, Dr Julianne Brown and Healthcare Scientists at Great Ormond Street Hospital Microbiology Department RY was supported by a Moorfields Eye Charity Career Development Award and a Springboard Award. LQ was partially supported by ANID-Covid0789. FER-L and AMS were supported by ANID-Covid1038. FER-L was supported by Fondecyt 1211841.

Ethics

Human subjects: Informed consent and consent to publish was obtained from all the individuals that participated in this study before performing the sampling process. This has been made explicit in the materials and methods section of the article. Ethical approval was obtained by the Ethics and Scientific Committee of Clinica Davila (Santiago, Chile) under the approval titled: "Identificación de marcadores de riesgo asociados a la severidad del Covid-19 en el microbioma respiratorio".

Senior Editor

  1. Jos WM van der Meer, Radboud University Medical Centre, Netherlands

Reviewing Editor

  1. Joshua T Schiffer, Fred Hutchinson Cancer Research Center, United States

Reviewer

  1. Joshua T Schiffer, Fred Hutchinson Cancer Research Center, United States

Publication history

  1. Received: May 16, 2021
  2. Accepted: June 21, 2021
  3. Accepted Manuscript published: June 22, 2021 (version 1)
  4. Version of Record published: July 12, 2021 (version 2)

Copyright

© 2021, Young et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,044
    Page views
  • 315
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

  1. Further reading

Further reading

    1. Microbiology and Infectious Disease
    Jaeeun Park et al.
    Research Article Updated

    Modification of the outer membrane charge by a polymyxin B (PMB)-induced PmrAB two-component system appears to be a dominant phenomenon in PMB-resistant Acinetobacter baumannii. PMB-resistant variants and many clinical isolates also appeared to produce outer membrane vesicles (OMVs). Genomic, transcriptomic, and proteomic analyses revealed that upregulation of the pmr operon and decreased membrane-linkage proteins (OmpA, OmpW, and BamE) are linked to overproduction of OMVs, which also promoted enhanced biofilm formation. The addition of OMVs from PMB-resistant variants into the cultures of PMB-susceptible A. baumannii and the clinical isolates protected these susceptible bacteria from PMB. Taxonomic profiling of in vitro human gut microbiomes under anaerobic conditions demonstrated that OMVs completely protected the microbial community against PMB treatment. A Galleria mellonella-infection model with PMB treatment showed that OMVs increased the mortality rate of larvae by protecting A. baumannii from PMB. Taken together, OMVs released from A. baumannii functioned as decoys against PMB.

    1. Microbiology and Infectious Disease
    Elisa De Crignis et al.
    Research Article

    The molecular events that drive Hepatitis B virus (HBV)-mediated transformation and tumorigenesis have remained largely unclear, due to the absence of a relevant primary model system. Here we propose the use of human liver organoids as a platform for modeling HBV infection and related tumorigenesis. We first describe a primary ex vivo HBV-infection model derived from healthy donor liver organoids after challenge with recombinant virus or HBV-infected patient serum. HBV infected organoids produced cccDNA, HBeAg, expressed intracellular HBV RNA and proteins, and produced infectious HBV. This ex vivo HBV infected primary differentiated hepatocyte organoid platform was amenable to drug screening for both anti-HBV activity as well as for drug-induced toxicity. We also studied HBV replication in transgenically modified organoids; liver organoids exogenously overexpressing the HBV receptor NTCP after lentiviral transduction were not more susceptible to HBV, suggesting the necessity for additional host factors for efficient infection. We also generated transgenic organoids harboring integrated HBV, representing a long-term culture system also suitable for viral production and the study of HBV transcription. Finally, we generated HBV-infected patient-derived liver organoids from non-tumor cirrhotic tissue of explants from liver transplant patients. Interestingly, transcriptomic analysis of patient-derived liver organoids indicated the presence of an aberrant early cancer gene signature, which clustered with the HCC cohort on the TCGA LIHC dataset and away from healthy liver tissue, and may provide invaluable novel biomarkers for the development of HCC and surveillance in HBV infected patients.