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Clin Microbiol Infect。2020 Sep；26（9）：1248-1253。
Published online2020Jun23。 doi:10.1016/j.cmi.2020.06.009
PMCID:PMC7308776
PMID:32585353

SARS-CoV-2检测

R.Ben-Ami单击功能区上，1，纪念册 A.Klochendler单击功能区上，1，纪念册 .Seidel单击功能区上，2，纪念册 T.Sido单击功能区上，3 O.Gurel-Gurevich单击功能区上，4个 .Yassour单击功能区上，5，6个 E.Meshorer单击功能区上，7 G.Benedek单击功能区上，8个 I.Fogel单击功能区上，8个 E.Oiknine-Djian单击功能区上，8个 A.Gertler单击功能区上，8个 Z.Rotstein单击功能区上，8个 B.Lavi单击功能区上，8个 Y.Dor单击功能区上，1，∗∗∗∗ D.G.Wolf单击功能区上，8，9，∗∗∗ .Salton单击功能区上，10，∗∗ Y.Drier单击功能区上，9，∗and The Hebrew University-Hadassah COVID-19 Diagnosis Team，on behalf of
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关联数据

辅助材料

Abstract

基础，基础

Testing for active SARS-CoV-2 infection is a fundamental tool in the public health measures taken to control the COVID-19pandemic。Because of the overwhelming use of SARS-CoV-2reverse transcription（RT）-PCR tests worldwide，the availability of test kits has become a major bottleneck and the need to increase testing throughput is rising。We aim to overcome these challenges by pooling samples together，and performing RNA extraction and RT-PCR in pools。

Methods

We tested the efficiency and sensitivity of pooling strategies for RNA extraction and RT-PCR detection of SARS-COV-2。We tested184 samples both individually and in pools to estimate the effects of pooling。We further implemented Dorfman pooling with a pool size of eight samples in large-scale clinical tests。

结果，结果

We demonstrated pooling strategies that increase testing throughput while maintaining high sensitivity。A comparison of 184 samples tested individually and in pools of eight samples showed that test results were not significantly affected。Implementing the eight-sample Dorfman pooling to test26576samples from asymptomatic individuals，weidentified31（0.12%）SARS-CoV-2positive samples，achieving a7.3-fold increase in throughput。

Discussion

Pooling approaches for SARS-CoV-2testing allow a drastic increase in throughput while maintaining clinical sensitivity。We report the successful large-scale pooled screening of asymptomatic populations。

Keywords:COVID-19，诊断，组测试，Infectious diseases，RT-PCR

基础，基础

An emerging novel severe acute respiratory syndrome-related coronavirus，SARS-Cov-2，is the virus behind the global COVID-19pandemic。Among the foremost priorities to facilitate efficient public health interventions is areliable and accessible diagnosis of an active SARS-CoV-2 infection。The standard laboratory diagnosis of COVID-19 involves three main steps，namely viral inactivation and lysis of the nasopharyngeal swab sample，extraction（or purification）of viral RNA and reverse transcription（RT）-PCR。Because of the rapid spread of the virus and the increasing demand for tests，the limited availability of test reagents，mainly RNA extraction kits，has become（and will likely continue to be）a major bottleneck as the pandemic expands[1个单击功能区上，2]。

Of particular importance is the ability to survey large asymptomatic populations（1）to trace asymptomatic COVID-19 carriers who are otherwise difficult to identify and isolate；（2）to assure key personnel（e.g.healthcare personnel）are not contagious；（3）to screen high-risk populations（such as nursing homes）to help protect them；（4）toaccurately estimate the spread of infection and the effectiveness of community measures and social distancing；and（5）to allow and monitor a safe return to work.Effficient and higher throughput diagnostic approaches are needed to support such efforts。While some of these applications（e.g.no.4）may be achieved with less-sensitive detection approaches，most applications do require adhering to the current high standards of RT-PCR。

Several attempts to address this challenge have been recently reported，and can be categorized into three major approaches。The first approach is to replace PCR-based methods by other direct diagnostic methods such asloop-mediated isothermal amplification[[3]单击功能区上，[4]单击功能区上，[5]单击功能区上，[6]CRISPR-基础诊断工具[[7]单击功能区上，[8]单击功能区上，[9]]。The second approach involves serological surveys[[10]单击功能区上，[11]单击功能区上，[12]单击功能区上，[13]]，and the third approach involves the improvement in the capacity of PCR methods by optimization and automation[1个单击功能区上，14单击功能区上，15]orby reducing the required number of tests via pooling samples together，known as group testing。

Group testing is a field of research in the intersection of mathematics，computer science and information theory，with applications in biology，communication and more。A group testing algorithm is a testing scheme directed towards minimizing the number of tests conducted on a setof samples by using the ability to test pooled subsets of samples。If a pool ofnsamples tests negative，all samples must be negative，and therefore their status has been determined in only one test instead ofnindividual tests。Various group testing algorithms exist，with different assumptions and constraints[16单击功能区上，第十七节：]。While many such algorithms，most notably binary splitting，may be very efficient in theory，they might be unsuitable because of practical limitations。Some key constrains are（1）a limit on the number of stages due to the importance of delivering a test result quickly，exemplified by the urgent clinical context of COVID-19 diagnosis；（2）a limit on the ability to dilute samples and still safely identify a single positive sample in a pool；and（3）favourability of simple algorithms which may minimize human error in a laboratory setting。

SARS-COV-2detection have been suggested recently[2单击功能区上，[18]单击功能区上，[19]单击功能区上，[20]单击功能区上，[21]单击功能区上，[22]]，these studies mostly discussed theoretical considerations。Here we describe and demonstrate practical pooling solutions that save time and reagents by performing RNA extraction and RT-PCR on pooled samples。We offer two such pooling approaches，based either on simple（Dorfman）pooling or matrix pooling[23单击功能区上，第二十四节：]，and demonstrate their efficiency and sensitivity in the daily reality of COVID-19。

Methods

取样，取样

At the Hadassah Medical Centre（HMC），two distinct populations are tested for SARS-Cov-2at present。First，we receive samples from symptomatic patients，from the hospital and from the community。In these samples，about10%of SARS-CoV-2tests are positive。Second，we receive samples from prospectively screened asymptomatic populations such ashospital employees and workers in essential industries。According to the Israeli Ministry of Health guidelines all samples were collected using a single swab for combined deep nasal and oropharyngeal collection from the same patient。Nasopharyngeal swab samples were collected in2mL of Viral Transport Medium（VTM）or collected directly to 2mL of Zymo lysis buffer。

RNA extraction and RT-PCR detection for individual tests

For sample lysate preparation220μL of sample VTM was added to 280μL of Zymo lysis buffer。RNA was extracted using MagNA Pure96 kit（Roche Lifesciences）using the Roche platform and eluted in 60μL.A10-μRNA was used in 30μL of reaction using real-time fluorescent RT-PCR kit（BGI）。We followed kit instructions with thermocycler protocol:one cycle at 50℃for 20min；one cycle at 95℃for 10min；40cycles at 95℃for15s；one cycle at60°C for30s。According to the clinical guidelines of the Israeli Ministry of Health at the time experiments were conducted，a sample was defined as定位，定位if the viral genome was detected at threshold cycle（Ct）values≤35，asindeterminateat Ct values>35and≤38，and asnegativeat Ct values＞38。

定位装置，定位装置

first pooling strategy is a simple two-stage testing algorithm know as Dorfman pooling[25]。在first stage，the samples are divided into disjoint pools ofnsamples each，and each such pool is tested。Anegative result implies that all samples in the pool are negative，while a positive result implies that at least one sample in the pool is positive。In the second stage，the samples of each pool that tested positive are individually tested。

要解决的问题需要解决的问题[23单击功能区上，第二十四节：]，wheren 2总厂，总厂，总厂n已重命名nmatrix.Each row and each column are pooled，resulting in2ntests，1个2ntimes fewer tests than individual testing。If either the number of positive rows or columns is one，the positive samples can be uniquely identified at the intersections of the positive rows and columns。Otherwise，if both the number of positive rows and columns is greater than one，intersections of positive rows and columns will be retested individually。

测试功率表

Individual barcoded samples were received at the laboratory，inactivated by alysis buffer and pooled on a Tecan liquid-handling robot。电力电力电力供应量为450μL and used MagNA Pure96kit（Roche Lifesciences）using the Roche platform。For eight-sample pools，we used QIAsymphony DSP Virus/Pthogen kit on a QIAsymphony platform。四角形焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝焊缝μL.Positive pools were validated by individual tests as described above。Both Qiagen kits were used with Zymo lysis buffers，and therefore we skipped the lysis and Proteinase K step。RNA was eluted into60μL；10μL of RNA was used for a30-μLreaction using real-time fluorescent RT-PCR kit（BGI）。To reduce the risk of contamination，daily ultraviolet irradiation of RNA extraction robots was performed，and different rooms for processing before and after PCR were setup，without mixing personnel or machines between the two compartments。

Note that analysis of pool results requires close attention to indeterminate-result pools，as these may contain individual positive samples。Therefore，all pools detected with Ct≤39 were retested（seeTable2，batch3），while maintaining standard criteria for the individual tests when retesting。

Table2

Three pooled tests run at the Hadassah Medical Centre

止动装置，止动装置No.of samplesNo.of poolsNo.of positive pools固定电源No.of positive individual samples in the positive pools固定式配电装置No.of total testsNo.of tests saved，compared to single sample tests（%）
1个720901个21.81个19.498622（86.4%）
2720900———90630（87.5%）
3728913positives，1indeterminate25.39222.05,28.72123605（83.1%）
37.441个37.67a
35.261个34.66
38.67 indeterminate038.24

Ct，cycle threshold。

aAccording to Hadassah Medical Centre's protocol for indeterminate values，reverse transcription-PCR was repeated with a different kit，and eventually was determined as positive。

切向功率和参数

We define theefficiencyof a pooling algorithm as the total number of samples divided by the expected number of tests conducted on them。We assume all samples are independent and identically distributed，and denote the probability of a sample to be positive byp（prevalence of detectable COVID-19 patients in the relevant population）and the pool size byn.The efficiency of the algorithms described above depends on bothpand，andn.The best theoretical efficiency is在-什么plog2在p）-什么在1个-什么p）log2在1个-什么p））-什么1个单击功能区上26]。Dorfman pooling is在1个+1个n-什么在1个-什么p）n）-什么1个单击功能区上25]。We chose a pool size ofn=8 samples asit allows a low false-negative rate（Fig.1）和高efficiency for a wide range of COVID-19 prevalence（Table1and，andTable S1）。可检测COVID-19 in asymptomatic population is estimated to be considerably below1%[27]，and indeed of the 26576samples tested in the present study only0.12%were found positive。Therefore，efficiency is likely to be5-7.5。高功率功率功率发生器Table1and supplementary material）。We provide a tool（https://github.com/matanseidel/pooling_optimization）to help choose the approach and pool size based on the prevalence。

Table1

多门和matrix pooling with pool sizen=8 compared with optimal efficiency

Prevalence（p）0.1%1%2%5%10%20%
最大尺寸efficiency87.712.47.13.52.131.39
Dorfmann=8efficiency7.54.93.62.21.441.04
Matrixn=8efficiency4.03.93.62.61.681.05
Fig.1

Pooling eight lysates retains clinical sensitivity。第23 pooling experiments，with eight lysates in each pool；15 pools with positive samples indeed come up positive（pools1-15），three pools without positive samples come up negative（pools20,21,21,23）and four out of five pools containing a single indeterminate sample detected as indeterminate（pools16,17,18,19,22）；Pools containing one or two samples with low amount of SARS-CoV-2are detected at a similar Ct（pools9-18），showing clinical sensitivity is retained and the risk of false negatives is minimal。Ct，threshold cycle。

止动阀

These studies were part of the approved diagnosis optimization and validation procedures at the HMC，and therefore no additional Institutional Review Board approvals were required。

结果，结果

akey requirement of pooled RNA extraction and RT-PCR tests is to retain sufficient sensitivity。Theoretically，pooling eight samples should elevate the Ct of a single positive sample by three cycles。However，reproducibility of RNA extraction and RT-PCR might be affected by other factors。We therefore empirically tested assay sensitivity，when multiple negative samples and one positive sample were mixed at the lysate stage。We tested the pooling of 184 samples into23pools of eight samples each，and also tested in parallel each sample individually。This approach yield highly accurate results，with no loss of diagnostic assay sensitivity:each of the pools that contained one or more positive samples was found to be positive，and all the pools that contained only negative samples were found to be negative（Fig.1）。Of the five pools that contained one individual sample with an‘indeterminate’result（in each pool），one was found to be negative per definition of individual tests，but still with Ct<39，which allows pool retesting。

5×5 matrices，and identified all positive samples accurately（Fig.2）。Importantly，the positive samples were detected in both the row and the column pools at a similar cycle in all three tested matrices，suggesting the pooling scheme is robust。

Fig.2

Matrix pooling。（a）Scheme for5×5matrix pooling。Twenty-five samples sorted in a5×5mtrix and each row and each column is pooled into a total of ten pools，on which RNA extraction，reverse transcription and qPCR are performed。In this illustration row B and column3are positive（black stars），hence sample B3is the only positive sample。If more than one row and one column are positive then all samples in intersections need to be retested，as some may be negative。（b）Three5×5pool matrices were generated（30pools from75lysates）。Each matrix（25lysates that were previously tested individually）included a single lysate positive for SARS-COV-2。As expected，only six pools（one row and one column per matrix）were positive for SARS-COV-2，while24pools had threshold cycle（Ct）>40（Undetected）。Reverse transcription-PCR Ct values of positive pools were nearly identical in the column pool（green）and the row pool（blue），and similar to the values of the individual test of the positive sample（grey）。

从nasopharyngeal swab samples到screened asymptomatic pooling protocol of 1:8 and employed it，employees of essful validation of both pooling strategies，and the low prevalence in asymptomatic healthcare personnel，and residents and employees of nursing homes。

在first three batches run at the HMC（Table2）we tested2168samples by pooling，using311RNA extraction and RT-PCR reactions（amese14%of kits that would have been used in the full individual testing，an increase of sevenfold in throughput）。Among these samples，we have identified and individually validated five positive samples，corresponding to a rate of 0.23%。We have then implemented the method in a routine clinical diagnosis setting of asymptomatic populations，testing a total of 26576 samples with7.3-fold increase in throughput，identifying a total of 31 positives（0.12%）。

Discussion

We demonstrate in areal-life situation the usefulness of pooled sampling starting at the early lysate stage。The simplicity of the method，similarity to currently approved procedures and the fact that we do not require special sample handling or additional information make it easily adoptable on a large scale。This saves time，work and reagents，allowing aconsiderable throughput increase of clinical diagnostic laboratories and opening the door for efficient screening of large asymptomatic populations for the presence of SARS-Cov-2infection。

An important consideration before implementing group testing is the expected rate of false-positive and false-negative results。从asymptomatic individuals，we did not encounter any false positives in the pools（see）Fig.1and，andTable2）。False negatives are in principle more worrisome when testing in pools，because samples that failed at the RNA extraction step will be missed（while our individual testing includes amplification of ahuman transcript serving asan internal control for proper RNA extraction and RT-PCR of each sample）。To define the magnitude of this potential problem，we examined a set of 13781 individual tests done at the HMC，which were all expected to show a signal for a human gene serving as internal assay control。Amplification of the human gene failed in 52 samples（0.38%）。Thus，we estimate that our current protocol of pooled sampling carries a risk of missing0.38%of the positive samples。In a population of1000individuals tested，of which1000are positive（rate of 0.1%），this predicts that four positive individuals will be missed when using pools。We posit that this is a tolerable situation，particularly given the potentially much higher rates of false-negative results due to swab sampling and other errors upstream。Large-scale implementation of the pooling scheme should be carefully done to assure pre-analytical influences（e.g.inadequate sampling，transport time，temperature influences）do not lead to significant loss of signal，which may further increase the risk of false negatives。

Increase in throughput applies to RNA extraction and RT-PCR，but not to viral inactivation and lysis or reporting of results。Reporting at the HMC is automated and was adapted to the pooling scheme and therefore does not require additional work.Viral inactivation and lysis typically take 30min while RNA extraction and RT-PCR4-5hr，and thereforefore7.3-fold increase in efficiency translates to~4.5 increase in efficiency of the flow，ormore if efficiency of viral inactivation is increased by other means（e.g.automation）。

The increase in efficiency allowed the HMC to survey healthcare personnel and multiple nursing homes，and identify a nursing home with16positive individuals，helping to stop the spread at that centre。Specifically，we have demonstrated that pooling lysates from five or eight nasopharyngeal swab samples retains sufficient sensitivity of viral RNA detection，allowing identification of SARS-CoV-2-positive individuals，while increasing throughput fivefold to 7.5-fold。

The prevalence of COVID-19in the tested population is not always known，which could affect the optimal pool size。This could be addressed either by external estimates，such asa previous run of individual samples，rate of symptomatic patients，oralternative methods such as serological screening or wastewater titres monitoring[28单击功能区上，29]。Alternatively，it is possible to dynamically adapt pooling sizes，when the measured rate of positive samples is different than expected。Finally，some group testing algorithms（reviewed in[第十七节：）estimate the number of positive samples while using a relatively small（logarithmic）number of tests，and may be adapted to clinical constraints and parameters。If samples are not independent，and we have information regarding their dependency，we can further improve efficiency by grouping together dependent samples，that is，samples that are likely all positives or all negatives，such as members of the same family，or samples that are likely to all negatives ory。This will increase the number of negative pools，and therefore decrease the overall number of tests conducted。Future improvement of the sensitivity of the test，such as better sets of primers and improved sample collection will allowretaining sensitivity even when pooling a large number of sample lysates together。This will enable further improving efficiency，especially when prevalence is low，by increasing the pool size。

Author contributions

Concept and design:E.Meshorer，Y.Dor，D.Wolf，M.Salton and Y.Drier。Acquisition，analysis，or interpretation of data:R.Ben-Ami，A.Klochendler，M.Seidel，T.Sido，O.Gurel-Gurevich，M.Yassour，E.Meshorer，Y.Dor，D.Wolf，M.Salton and Y.Drier。Software:M.Seidel。Visualization:T.Sido，M.Yassour。Resources:the Hebrew University-Hadassah COVID-19diagnosis team，G.Benedek，I.Fogel，E.Oiknine-Djian，A.Gertler，Z.Rotstein，B.Lavi，Y.Dor，D.Wolf。Writing original draft，review and editing:Y.Dor，D.Wolf，M.Salton and Y.Drier。Supervision:Y.Dor，D.Wolf，M.Salton and Y.Drier。All authors approved the final manuscript。

传输控制

All authors disclose no conflicts of interest。

Acknowledgements

Y.Drier is supported by an Alon Fellowship and the Concern Foundation/American Friends of the Hebrew University Young Professorship Award。The following people are members of the Hebrew University-Hadassah Medical School COVID-19 diagnosis team and have contributed to the development of the pooled testing pipeline:A.Klochendler，A.Eden，A.Klar，A.Geldman，A.Arbel，A.Peretz，B.Shalom，B.Ochana，D.Avraz.Netim，an，D.Steinberg，D.Ben Zvi，E.Shpigel，G.Atlan，H。Klein，H.Chekroun，H.Shani，I.Hazan，I.Ansari，I.Magenheim，J.Moss，J.Magenheim，L.Peretz，L.Feigin，M.Saraby，M.Sherman，M.Bentata，M.Avital，M.Kott，M.Peyser，M.Weitz，M.Shacham，M.Grunewald，N.Sasson，Walln.AzzaN。rum，O.Fridlich，R.Sher，R.Condiotti，R.Refaeli，R.Ben Ami，R.Zaken-Gallili，R.Helman，S。Ofek，S.Tzaban，S.Piyanzin，S.Anzi，S.Dagan，S.Lilenthal，T.Sido，T.Licht，T.Friehmann，Y.Kaufman，A.Pery，A.Saada，A.Dekel，A.Yeffet，A.Shaag，A.Michael-Gayego，E.Shay，E.Arbib niel，L.Natan，M.Hamdan，M.Rivkin，M.Shwieki，O.Vorontsov，R.Barsuk，R.Abramovitch，R.Gutorov，S.Sirhan，S.Abdeen，Y.Yachnin，Y.Daitch。

注释，注释

编辑器：F.Allerberger

Footnotes

Appendix ASupplementary data to this article can be found online athttps://doi.org/10.1016/j.cmi.2020.06.009。

内容信息

The Hebrew University-Hadassah COVID-19 Diagnosis Team:

A.Klochendler单击功能区上，A.Eden单击功能区上，A.Klar单击功能区上，A.Geldman单击功能区上，A.Arbel单击功能区上，A.Peretz单击功能区上，B.Shalom单击功能区上，B.L.Ochana单击功能区上，D.Avrahami-Tzfati单击功能区上，D.Neiman单击功能区上，D.Steinberg单击功能区上，D.Ben Zvi单击功能区上，E.Shpigel单击功能区上，G.Atlan单击功能区上，H.Klein单击功能区上，H.Chekroun单击功能区上，H.Shani单击功能区上，I.Hazan单击功能区上，I.Ansari单击功能区上，I.Magenheim单击功能区上，J.Moss单击功能区上，J.Magenheim单击功能区上，L.Peretz单击功能区上，L.Feigin单击功能区上，.Saraby单击功能区上，.Sherman单击功能区上，.Bentata单击功能区上，.Avital单击功能区上，.Kott单击功能区上，.Peyser单击功能区上，.Weitz单击功能区上，.Shacham单击功能区上，Grunewald单击功能区上，N.Sasson单击功能区上，N.Wallis单击功能区上，N.Azazmeh单击功能区上，N.Tzarum单击功能区上，O.Fridlich单击功能区上，R.Sher单击功能区上，R.Condiotti单击功能区上，R.Refaeli单击功能区上，R.Ben Ami单击功能区上，R.Zaken-Gallili单击功能区上，R.Helman单击功能区上，S.Ofek单击功能区上，S.Tzaban单击功能区上，S.Piyanzin单击功能区上，S.Anzi单击功能区上，S.Dagan单击功能区上，S.Lilenthal单击功能区上，T.Sido单击功能区上，T.Licht单击功能区上，T.Friehmann单击功能区上，Y.Kaufman单击功能区上，A.Pery单击功能区上，A.Saada单击功能区上，A.Dekel单击功能区上，A.Yeffet单击功能区上，A.Shaag单击功能区上，A.Michael-Gayego单击功能区上，E.Shay单击功能区上，E.Arbib单击功能区上，H.Onallah单击功能区上，K.Ben-Meir单击功能区上，L.Levinzon单击功能区上，L.Cohen-Daniel单击功能区上，L.Natan单击功能区上，.Hamdan单击功能区上，.Rivkin单击功能区上，.Shwieki单击功能区上，O.Vorontsov单击功能区上，R.Barsuk单击功能区上，R.Abramovitch单击功能区上，R.Gutorov单击功能区上，S.Sirhan单击功能区上，S.Abdeen单击功能区上，Y.Yachnin，andY.Daitch

Appendix A.（Supplementary data）

The following are the Supplementary data to this article:

Multimedia component1:
Click here to view。（57K，pdf）Multimedia component1

Multimedia component2:
Click here to view。（13K，xlsx）Multimedia component2

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