key: cord-0802264-1l92yq48
authors: Francis, Rania; Le Bideau, Marion; Jardot, Priscilla; Grimaldier, Clio; Raoult, Didier; Bou Khalil, Jacques Yaacoub; La Scola, Bernard
title: High-speed large-scale automated isolation of SARS-CoV-2 from clinical samples using miniaturized co-culture coupled to high-content screening
date: 2020-09-23
journal: Clin Microbiol Infect
DOI: 10.1016/j.cmi.2020.09.018
sha: 66a90ffca6aed92801ff1f8b3731ae666103b8e1
doc_id: 802264
cord_uid: 1l92yq48

OBJECTIVES: A novel coronavirus, SARS-CoV-2, is responsible for the current COVID-19 global pandemic. Only a few laboratories routinely isolate the virus, which is because the current co-culture strategy is highly time-consuming and requires working in a biosafety level 3 laboratory. This work aimed to develop a new high-throughput isolation strategy using novel technologies for rapid and automated isolation of SARS-CoV-2. METHODS: We used an automated microscope based on high-content screening (HCS), and we applied specific image analysis algorithms targeting cytopathic effects of SARS-CoV-2 on Vero E6 cells. A randomized panel of 104 samples, including 72 that tested positive by RT-PCR and 32 that tested negative, were processed with our HCS strategy and were compared to the classical isolation procedure. RESULTS: The isolation rate was 43% (31/72) with both strategies on RT-PCR-positive samples and was correlated with the initial RNA viral load in the samples, in which we obtained a positivity threshold of 27 Ct. Co-culture delays were shorter with the HCS strategy, where 80% (25/31) of the positive samples were recovered by the third day of co-culture, compared to only 26% (8/30) with the classic strategy. Moreover, only the HCS strategy allowed us to recover all the positive samples (31 with HCS versus 27 with classic strategy) after 1 week of co-culture. CONCLUSIONS: This system allows the rapid and automated screening of clinical samples with minimal operator workload, which reduces the risk of contamination, thus paving the way for future applications in clinical microbiology, such as large-scale drug susceptibility testing.

An outbreak caused by a novel coronavirus (SARS-CoV-2) occurred in late December 2019 in 40 Wuhan, China; it then spread worldwide and was declared a pandemic by the WHO on the 12 th of 41

March 2020 [1] , [2] , [3] . Laboratory diagnosis is mainly based on molecular biology using specific 42 RT-PCR systems to detect the virus in clinical samples [4] , [5] , [6] . However, during such pandemics, 43 strain isolation is important, as having the particle represents the key to all in vitro research, such as 44 drug susceptibility testing and vaccine development [7]. Furthermore, culture allows access to all 45 viral genomes since whole-genome sequencing techniques performed directly on samples have their 46 limitations in terms of sensitivity 47

. A first application of this strategy was used by our group to evaluate the risk of contagiousness of 48 patients for discharge from the infectious diseases ward [8] . However, the current co-culture strategy 49 is tedious and time consuming, especially due to the large number of samples to be cultured. An ideal 50 solution would be an automated system allowing the rapid screening and monitoring of co-cultures at 51 large scale. 52

In previous works, we developed a screening strategy based on high-content screening microscopy 53 (HCS) for the isolation of environmental giant viruses in amoeba and the strict intracellular 54 bacterium Coxiella burnetii [9], [10] . In this work, we used the same automated high-throughput 55 method and adapted it for SARS-CoV-2 isolation from clinical samples with the objective to discard 56 the negative co-cultures after one week and omit blind subcultures. Specific algorithms were applied 57 to detect cytopathic effects in co-cultures at high throughput, which eliminates the subjectivity 58 related to manual observations by the laboratory personnel. This strategy exhibited a similar isolation 59 rate but a lower co-culture delay when compared to the classic technique routinely used for isolation, 60 as we were able to detect all positive co-cultures in one week.

locally isolated SARS-CoV-2 strain IHUMI-3. This viral strain was previously isolated in our lab 65 from a nasopharyngeal swab, as previously described [11] . The viral titer was calculated by the 66 TCID50 method. Briefly, we cultured Vero E6 cells in black 96-well microplates with optical 67 bottoms (Nunc, Thermo Fischer) at a concentration of 2×10 5 cells/ml and a volume of 200 µl per 68 well in transparent MEM supplemented with 4% fetal calf serum and 1% glutamine. Plates were 69 incubated for 24 hours at 37°C in a 5% CO 2 atmosphere to allow cell adhesion. Infection was then 70 carried out with 50 µl of the viral stock suspension diluted up to 10 -10 . The plates were centrifuged 71 for 1 hour at 700xg, and the total volume per well was adjusted to 250 µl with culture medium. 72

Uninfected cells were considered negative controls. 73

DNA staining was performed with NucBlue™ Live ReadyProbes™ reagent (Molecular Probes, Life 75 Technologies, USA). A concentration of 4 ng/ml was used (equivalent to 10 µl per well directly from 76 stock solution), and a different well was stained each day to avoid photobleaching and possible 77 cytotoxicity, as previously described [10] . 78

Image acquisition and analysis were performed using the automated CellInsight™ CX7 High-79 Content Analysis Platform coupled with an automation system including an Orbitor™ RS Microplate 80 mover and an incubator Cytomat™ 2C-LIN (Thermo Scientific). The HCS Studio 3.1 software was 81 used to set up acquisition parameters using a 20x objective (0.45 NA) and to define image analysis. 82 developed in R Studio® for the detection of the intracellular bacteria, Coxiella burnetii [10] . We 88 optimized this application for the detection of cytopathic effects caused by Briefly, a database consisting of negative (uninfected cells) and positive (infected cells) controls was 90 generated. The data were used to define specific features allowing the discrimination between the two 91 groups. The following features were selected: the average, total and variation of the nuclear 92 fluorescence intensity per cell, the nuclear area, the skewness of the brightfield intensity distribution, 93 the kurtosis of the brightfield intensity distribution and the total intensity of the brightfield within the 94

ROI_SkewIntenCh3, ROI_KurtIntenCh3 and ROI_TotalIntenCh3 respectively). These parameters 96 were used to generate two clusters using the K-means clustering algorithm, and the percentage of 97 injured cells per well was calculated as previously described [10] . We then compared the percentage 98 of injured cells obtained to the total cell count in each well to detect cell lysis. 99

We applied this strategy for the detection of SARS-CoV-2 in 104 randomly chosen, anonymized 101 nasopharyngeal swab samples. Initial RT-PCR ranged from 12 Ct to 34 Ct in 72 samples, and 32 102 samples with negative initial PCR were used as negative controls. All samples except five were from 103 hospitalized patients. Sample preparation and co-culture were performed as previously described 104 isolation strategy based on the manual observation of cytopathic effects under an inverted microscope 112 to validate our strategy [11], [8] , [12] . For this strategy, co-cultures showing no cytopathic effects after 113 one week were sub-cultured at days 7 and 14 onto a fresh monolayer of cells for a complete 114 observation of three weeks. 115

Positive co-cultures were processed with both scanning electron microscopy (SEM) and RT-PCR 117 directly from culture supernatant to validate the presence of COVID-19 viral particles. Briefly, SEM 118 was performed using the SU5000 microscope (Hitachi High-Tech Corporation, Tokyo, Japan) 119 allowing a rapid observation in approximately 10 minutes without time-consuming sample 120

preparations [12] . The RT-PCR protocol was performed as previously described by Amrane et al., 121 targeting the E gene [13] . This RT-PCR was applied to wells showing a cytopathic effect to confirm 122 that this effect was due to SARS-CoV-2 and to negative wells to confirm that the lack of cytopathic 123 effect was not due to microscopically undetectable minimal viral growth. 124

The R Studio® and XLSTAT software programs were used to perform all statistical tests included in 126 this paper. P values were calculated to search for significant differences between the positivity rates 127 obtained on a daily basis of co-culture using the HCS and the classic isolation strategies. ROC curves 128

were also calculated to determine a positivity threshold for strain isolation related to the initial viral 129 Fig. 1 -140 a, b) compared to advanced stages of infection and cell lysis (Supplementary Fig. 1 -g, h, i, j, k) . 

The data extracted from the images were analyzed in the dedicated application in R Studio. The 149 database of negative and positive controls served as training data for the clustering algorithm, and a 150 baseline of 2 to 3% injured cells was predicted in the negative training data compared to a value of 50 151 to 55% injured cells in the positive training data. The percentage of injured cells in each condition 152 was predicted and then divided by the total cell count per well. This ratio allowed us to distinguish 153 positive wells, showing cytopathic effects or cell lysis, from the negative control wells consisting of 154 uninfected cells (Figure 1-a) . Cytopathic effects were detectable up until the dilution 10 -4 after 6 155 days of culture for the strain IHUMI-3 used in this study, which corresponds to the viral titer 156 obtained by TCID50.

linked to the HCS microscope. A screening process was predefined, thus allowing the proper 160 incubation of the plates followed by the automated handling of the screening process at each 161 specified time point. 162

Among the panel of 104 samples processed on the CX7 microscope, 32 samples had a negative initial 164 PCR and were considered controls for the system's sensitivity; therefore, the corresponding co-165 cultures were negative. Among the remaining 72 samples, we managed to isolate the virus from 31 166 samples using our automated detection system. The detection delay ranged from 24 hours to 3 days 167 for most samples and was prolonged to 6 days for samples with low viral load. In this work, we were able to co-culture a large amount of clinical samples and monitor them with a 194 fully automated system, which reduced the workload and time required from laboratory technicians. 195 Similar isolation rates were obtained with both isolation strategies, which validated the efficiency of 196 our new automated system. Moreover, this isolation rate was obtained in one week with the HCS 197 strategy without any further subcultures, contrary to the classic technique with weekly subcultures for 198 a total incubation time of three weeks. The main advantage of this technique relies in the automation, 199 as it limits the risks of exposure or contamination of the personnel, since plate monitoring and data 200 analysis can be carried out from a distance, thus avoiding direct contact and manual observations of 201 co-cultures. Furthermore, since the loss of virus cultivability in samples allows us to consider the 202 patients at low risk of contamination, it therefore helps in the decision making to discharge them 203 from the infectious diseases wards [8] . The use of the HCS isolation strategy allowed us to answer 204 this question in one week. This is especially critical at the beginning of an epidemic or when PCR 205 detection systems have to be modified. Moreover, several studies showed that assessing the duration 206 of SARS-CoV-2 infectivity is based on viral cell culture or secondary infection rates 207 [12] , [14] , [15] , [16] , [17] , [18] , [19] . Therefore, our automated isolation system allows answering this 208 question faster than any other tool, and viral infectivity can be assessed several times during the 209 outbreak to search for modifications, such as reduced transmissibility or effect of antiviral therapy. 210

Furthermore, the greater the number of strains isolated, the better the understanding of the genetic 211 diversity of this virus, especially since genome sequencing directly from samples is limited to the 212 viral load, and a very poor genome assembly is obtained when the viral load is greater than 19 Ct 213

[20], [19] . Subsequently, developing an automated viral isolation technique was necessary to 214 overcome the subjective and time-consuming manual microscopic observations. This new strategy is 215 therefore applicable during the current crisis to recover strains from suspected samples in a safe and 216 rapid way. Further work is underway to apply this technique for the large-scale drug susceptibility 217 testing of SARS-CoV-2 strains isolated from patients. Finally, the algorithms used here could be 218 adapted and applied for the detection and isolation of other viruses from clinical samples in cases of 219 known and emerging viral diseases. 220

Authors would like to declare that Didier Raoult is a consultant for Hitachi High-Tech Corporation. 

WHO Director-General's opening remarks at the Mission briefing on COVID-19 -12

Severe acute respiratory syndrome coronavirus 242 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the 243 challenges

A novel coronavirus from patients 245 with pneumonia in China

The Laboratory Diagnosis of COVID-19

Infection: Current Issues and Challenges

Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia

Improved 253 molecular diagnosis of COVID-19 by the novel, highly sensitive and specific

Viral RNA 260 load as determined by cell culture as a management tool for discharge of SARS-CoV-2 261 patients from infectious disease wards

High-throughput isolation of giant viruses 264 using high-content screening

Reliable System for Coxiella burnetii Isolation from Clinical Samples

Hydroxychloroquine 269 and azithromycin as a treatment of COVID-19: results of an open-label non-randomized 270 clinical trial

Ultrarapid diagnosis, 272 microscope imaging, genome sequencing, and culture isolation of SARS-CoV-2

COVID-19 patients with hydroxychloroquine and azithromycin: A retrospective analysis of 287 1061 cases in Marseille, France

SARS-CoV-2 from diagnostic samples

Shedding of infectious virus in hospitalized patients with coronavirus disease

COVID-19): duration and key determinants

Clinical immunological and virological 296 characterization of COVID-19 patients that test re-positive for SARS-CoV-2 by

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