April 13, 2022

COVID-19 is not going away, we don’t say this to scare you, but to prepare you.

The coronavirus has baffled scientists, virologists, and immunologists alike since its emergence in 2019. Two and a half years later the advancement of this virus is still surprising experts. This is due to its rapid evolution, methods of transmission, and short/long-term effects of infection not just in humans, but in other species as well.

As COVID cases rise in 26 states, and hospitalizations rise in 10, there are quite a few indicators that we may be heading into a tsunami-sized outbreak in the coming months.

1. New spikes in COVID-19 Cases worldwide
2. Decreasing mask mandates, travel restrictions, and other COVID policies
3. A virus that is growing more contagious and mutating at remarkable speeds
4. COVID Tests that decrease in accuracy as said virus evolves
5. An upcoming season of large gatherings and festivals
6. A world of people that desperately want to get back to normal

Based on all of these factors, Clear Health Pass’s Co-Founder and CEO John Cataldi doesn’t expect for things to return to normal until maybe 2024: “It’s going to continue, the next wave will be here in full force by around October or November and make the prior waves look small”.

With all these battles we are currently facing, continued and consistent COVID testing is vital to helping experts track and understand this virus. This not only helps them develop treatments and therapies but also gives all of us the information we need to make decisions to keep our family and loved ones safe.

We are all carrying the weight of the world on our shoulders, but Clear Health Pass hopes to ease some of that burden in the near future by offering a COVID test that is astronomically more comfortable, user-friendly, accessible, and affordable. We hope that this will hugely impact the willingness of consumers to get tested early and often.  

Visit us at our website here:

www.clearhealthpass.com

Read more about why testing is so important here:

https://www.bloomberg.com/news/articles/2022-04-10/covid-19-could-be-spreading-undetected-in-u-s

COVID Case Statistics as of 4/13/22 here:

https://www.beckershospitalreview.com/public-health/covid-19-cases-tick-up-in-9-states.html

Clear Health Pass Covid Pandemic Update: December 06, 2022

The B.1.1.529 variant was first reported to the World Health Organization (WHO) from South Africa on November 24, 2021. The epidemiological situation in South Africa has been characterized by three distinct peaks in reported cases, the latest of which was predominantly the Delta variant. In recent weeks, infections have increased steeply, coinciding with the detection of the B.1.1.529 variant. The first known confirmed B.1.1.529 infection was from a specimen collected on November 09, 2021. The variant as of December 05, 2021, has now been found in 16 states as hospitals prepare for a potentially massive spike in hospitalizations. 

Omicron has 50 mutations, 30 of which are in the spike protein. Specifically changes to amino Acids 333 to 527, which contain ACE2. One study in March 2020, demonstrated that ACE2 was the dominant area for receptor binding of antibodies.  These changes represent one of the most dramatic variant mutations to date whereas approximately, representing a greater than 15% change in the surface area of the spike protein. Ten of those mutations are within that amino acid range (438-506). Given that monoclinic antibodies bind in a 3-dimensional space (aka lock and key), there is a high probability that the overall surface change will inhibit viral neutralization, due to lack of binding receptor availability via the body’s immune system, monoclonal antibody therapeutics, and potentially greatly reduced efficacy of current vaccines.  In addition, there may be an increase in T-cell response once an infection is onset, which may also cause inflammation that may trigger complications, like long-haulers, even post-infection. 

Omicron is now designated by the WHO and the European Center for Disease Prevention and Control classification as a Variant of Concern (VOC) based on epidemiological data indicating an increase in infections in South Africa in recent weeks and the virus ability immune escape and potentially increased transmissibility compared to the Delta variant and have raised its classification status as a Variant of Concern (VOC).  

Breakthrough Variants Still Cause Spread, Illness, Hospitalization, and Death in the Vaccinated

On June 25th, Dr. Chevy Levy Israel’s Director General of Health Ministry stated during a radio interview that 40-45% breakthrough rates reported SARS-Co-2, from those previously vaccinated. According to Reuters, as of December 04, 2022, Israel is one of the global leaders in vaccinations and early variant detection with approximately 89.6% of Israeli adults being vaccinated, with 57% being fully vaccinated, which is on par with the United States. In August, the Israeli Minister of Health Nitzan announced that it became the first nation to offer a third dose of vaccine to people as young as age 50. Since then, the breakthrough rate has continued to climb according to their health ministry. Though the unvaccinated will have an overall higher infection, hospitalization, and mortality rate, the rate of breakthrough infection data strongly suggests that Sar-Cov-2 variants will inevitably outpace the deployment of new vaccines and boosters. What is clear is that “breakthrough” cases are not the rare events the term implies. According to Israel’s Health Ministry, in an article on August 15, 2021, 514 Israelis were hospitalized with severe or critical COVID-19, a 31% increase from just 4 days earlier. Of the 514, 59% were fully vaccinated. Of the vaccinated, 87% were 60 or older. “There are so many breakthrough infections that they dominate and most of the hospitalized patients are actually vaccinated,” says Uri Shalit, a bioinformatician at the Israel Institute of Technology and an advisor for the county’s Covid task force.

Asymptomatic SARS-CoV-2 Super Spreaders: What you Don’t See My Harm 

In an August 2021, a PNAS research article, Asymptomatic SARS-CoV-2 infection, researchers cross-referenced data sets of PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020, and April 2, 2021, to identify studies that reported silent infections at the time of testing, whether pre-symptomatic or asymptomatic. At the time of testing, 42.8% of cases exhibited no symptoms, a group comprising both asymptomatic and pre-symptomatic infections. Epidemiologists, those that study and analyze the distribution (who, when, and where), patterns, and determinants of health and disease conditions usually observe a “20/80 rule” or the “1:4 ratio” in the way that infectious diseases are transmitted within a population. For clarity, 1 infected person will infect 4 healthy persons. This “1:4 ratio” applies to many transmissions of infectious pathogens among different species. A COVID-19 epidemic model with a latency period follows the same 1:4 ratio, but new variants have also created an asymptomatic carrier, which can spread the virus, but themselves show little to no sign of infection. This dramatically changes the current Covid-19 epidemic modeling of a typical 1:4 ratio to that of a “Super-spreader”. Super-spreaders can transmit pathogens disproportionately to more than an average number of secondary cases and are likely to promote the speed and scale of outbreaks. Usually, super-spreaders transmit at least ten individuals, sometimes even up to 100 secondary cases, and exponentially increase infections by a factor of 10+ every 24-48 hours, without testing or quarantine in effect.  Thus, asymptomatic super-spreaders of COVID-19 can be extremely dangerous and must be handled time-efficiently. Prior pandemic data suggests that “Symptomatic” Super Spreaders (E.g., EBOLI & SARS) transmit from 10-100x secondary cases. In a JAMA study released as of January 11, 2021, 59% of all transmission came from the asymptomatic transmission, comprising 35% from pre-symptomatic individuals and 24% from individuals who never develop symptoms. Under a broad range of values for each of these assumptions, at least 50% of new SARS-CoV-2 infections were estimated to have originated from exposure to individuals with infection but without symptoms.

The US is 38 of 130 countries in Genetic Variant Testing

According to the Global Influenza Surveillance System (“GISAID”), which collaborates, supplies, and syndicates, genomic data sets concerning SARS-CoV-2 variants to the CDC, the World Health Organization (“WHO”), the U.S. Department of Health (“DOH”), the European Union, other world governments and tens of thousands of researchers worldwide reports that the United States gnomically identifies less than 1.6% or 0.29% as a global genomics contributor of its positive COVID-19 cases a month.   This ranks the U.S. as 38th out of 130 countries in terms of sequencing Positive COVID-19 cases, which is the only current defense against identifying potentially variant strains. According to the WHO, the United States is doing so little of the genetic sequencing needed to detect new variants of the coronavirus—like the ones first identified in Great Britain and South Africa—that such mutations are probably proliferating quickly, undetected.  At one time, BUT NOT DEEMED as VOC, the coronavirus variant known as B.1.1.7, which studies show is both more deadly and transmissible than the original version of SARS-CoV-2, first identified in December 2020, now serves as one of the most common strains circulating in the United States, and its growing prevalence alarms prominent epidemiologists.  

Relaxed Travel Bans in Allowing the Vaccinated and potentially the Infected into the United States 

On October 25, President Biden announced a Presidential Proclamation titled “A Proclamation on Advancing the Safe Resumption of Global Travel During the COVID-19 Pandemic.”  This proclamation, which took effect at 12:01 am Eastern Standard Time on November 8, 2021, ended the travel restrictions under Presidential Proclamations (P.P.) 9984, 9992, 10143, and 10199 as they relate to the suspension of entry into the United States of persons physically present in Brazil, China, India, Iran, Ireland, the Schengen Area, South Africa, and the United Kingdom.  In place of these restrictions, the President announced a global vaccination requirement for all adult foreign national travelers. Unfortunately, the South American variant has already made entry into the US in much larger numbers, given the estimated breakthrough rates of over 50%+ of vaccinated, which may potentially lead to the vaccinated, asymptomatic super spreader. 

Key Take Always: 

1. If the variant is sufficient to cause regional to national outbreaks, vaccine breakthrough is likely.

2. Thus, vaccines and antiviral treatments will be reduced in the overall effectiveness.

3. Vaccines may still help reduce long-term hospitalization and mortality. 

4. Changes in the virus may also cause systemic complications due to inflammation caused by overactive T-cells. 

Departing advice: 

1. Mask up 

2. Wash hands

3. Avoid large gatherings especially during the holiday season

4. Get vaccinated or a booster is available 

About Clear Health Pass™ (CHP): 

Clear Health Pass ™ is a diagnostic, telehealth enabled bioinformatics platform that provides Telehealth, Testing, Treatment, and Bioinformatics Platform that provides a next generation Rapid Covid & Variant Saliva Test, antigen of VOCs and Unknown variants. Its Bioinformatics platform facilitates an early warning of direct and indirect health issues for legal syndication of test data to authorized agencies, platforms, and persons. Clear Health Pass ™ is a Portfolio Partner of the Native American Venture Fund (NAVF), The Sage Community Development Corporation, and the Blue Lake Rancheria Economic Development Corporation. Clear Health Pass ™ is a Minority / Veteran Operated Organization in Partnership as Tribal Representative with Federally Recognized Native American Tribes under 25 U.S.C. § 476. Clear Health Pass ™ is being clinical trials pending pre-qual FDA submittal under its tribal status.  Clear Health Pass ™ is registered as Clear Health Pass Holdings, LLC and has filed with the US Securities and Exchange Commission under 506c, 144 Reg D Offering. 

 For more information on Clear Health Pass ™ as an investment opportunity Click or Call the Native American Venture Fund at 212-634-4300. 

Monocytes are a group of immune cells that originate in bone marrow and are released into peripheral blood, where they circulate for several days^1,2. They belong to the mononuclear-phagocyte system, which also include macrophages, dendritic cells and their bone-marrow precursors^3,4,5. Monocytes represent 5–10% of peripheral leucocytes and are probably best known for serving as a systemic reservoir of myeloid precursors that are needed for the renewal of tissue macrophages and dendritic cells^6,7,8,9. However, they also have other well documented functions in immune response against infection^10,11,12,13 and in pathogenesis of several inflammatory disorders. Although initially perceived as a homogeneous population, it has become increasingly apparent that monocytes display considerable heterogeneity with respect to their phenotype and function^1,2,14,15.

Abstract

Given the importance of monocytes in pathogenesis of infectious and other inflammatory disorders, delineating functional and phenotypic characterization of monocyte subsets has emerged as a critical requirement. Although human monocytes have been subdivided into three different populations based on surface expression of CD14 and CD16, published reports suffer from contradictions with respect to subset phenotypes and function. This has been attributed to discrepancies in reliable gating strategies for flow cytometric characterization and purification protocols contributing to significant changes in receptor expression. By using a combination of multicolour flow cytometry and a high-dimensional automated clustering algorithm to confirm robustness of gating strategy and analysis of ex-vivo activation of whole blood with LPS we demonstrate the following: a. ‘Classical’ monocytes are phagocytic with no inflammatory attributes, b. ‘Non-classical’ subtype display ‘inflammatory’ characteristics on activation and display properties for antigen presentation and c. ‘Intermediate’ subtype that constitutes a very small percentage in circulation (under physiological conditions) appear to be transitional monocytes that display both phagocytic and inflammatory function. Analysis of blood from patients with Sepsis, a pathogen driven acute inflammatory disease and Systemic Lupus Erythmatosus (SLE), a chronic inflammatory disorder validated the broad conclusions drawn in the study.

Introduction

In humans, monocytes have been divided into three subtypes based on relative surface expression of LPS co-receptor CD14 and FCγIII receptor CD16^16,17. The most predominant of the three, termed “classical monocytes”, express high levels of CD14 on their surface, are devoid of surface CD16 and account for approximately 80% of the total monocyte population. The remaining 20% express CD16 and have been further classified into two subtypes. The more abundant “nonclassical monocytes”, are characterized by very low expression of surface CD14 and high levels of CD16, whereas the third monocyte subtype, called “intermediate monocytes”, express high levels of both the receptors^16,17.

Over the years, a number of studies, often contradictory, aimed at functional characterization of the three monocyte subsets have been undertaken by different research groups^{18,19,20,21,22,23,24,25,26}, which has sparked an interest to investigate proportions of monocyte subsets in a wide variety of diseases. Relative percentages of monocyte subsets has been reported to understand pathogenesis of several infectious and metabolic diseases viz., sepsis^27,28,29, chronic liver disease^30,31,32, rheumatoid arthritis³³, atherosclerosis³⁴, filariasis³⁵ and obesity³⁶. However, lack of consistent gating strategies for quantification by flow cytometry has been a major limitation, leading to lack of reproducibility. Since CD16 is highly expressed on neutrophils and NK cells, these cell types need to be excluded from analysis for reproducible quantification and to avoid confounders. The other major limiting factor is that all functional studies so far have been performed with purified monocytes, contributing to highly variable results depending on method of isolation employed³⁷.

In this study, we used a combination of multicolour flow cytometry, multiparameter imaging cytometry and a high-dimensional automated clustering algorithm to confirm robustness of our gating strategy. Further, we have addressed these controversies on analysis of functional phenotype of human monocyte subsets in circulation. We demonstrate that gradient purified monocytes are significantly different from cells analysed in whole blood for receptor expression. Our findings suggest that ficoll purification of blood monocytes leads to a decrease in number of CD14+/CD16- classical monocytes with a concomitant expansion of CD14dim/CD16+ nonclassical monocytes. Moreover, gradient separation also contributed to increased surface expression of CD16. Therefore, in order to retain physiologically relevant monocyte function, we adopted whole blood stimulation and staining protocol. Using this method we show distinct phenotype and function of monocyte subsets in circulation with respect to inflammation, antigen presentation and phagocytosis. We unequivocally demonstrate that nonclassical and not intermediate subtype are the primary inflammatory monocytes and further validate by studying patients suffering from sepsis and systemic lupus erythematous (SLE).

Discussion

Existence of heterogeneity in human peripheral blood monocytes based on size and density was reported almost three decades ago, showing that human monocytes in circulation consisted principally of two subtypes – a large and a small sized one – that differed in their phagocytic and inflammatory capabilities^{42,43,44,45,46,47}. Later, with the advent of flow cytometry, a more robust identification of blood monocyte subsets was performed based on differential expression of surface CD14 and CD16⁴⁸. This initial study showed existence of at least two distinct monocyte subsets – CD14+/CD16- and CD14+/CD16+- that were strikingly different in their function. Subsequently, the CD16+monocytes were shown to be further composed of two different populations¹⁴. One was shown to express equal levels of CD14 and CD16 (CD14+/CD16+), while the other population was characterized by very low surface expression of CD14 (CD14dim/CD16+).Given the importance of monocytes in immune function and their role in pathogenesis of a wide variety of diseases, it became essential to precisely characterize human blood monocyte subsets. To this end, a large number of studies were undertaken by different research groups with a view to functionally characterize blood monocyte subsets^{18,19,20,21,22,23,24,25,49}. However, there exists little consensus among most of published literature. One of the reasons is lack of a consistent gating strategy for immunophenotyping by flow cytometry. This issue was addressed by a recent review that proposed a common gating strategy to identify monocyte subpopulations in human circulation¹⁶. Accordingly, in the current study, a negative gating strategy was used to sequentially exclude neutrophils, NK cells, B cells and T cells from analysis followed by inclusion of HLA-DR+++monocytes that were further discriminated on a bivariate scatterplot of CD14 vs. CD16 to finally yield three clearly distinguishable monocyte subpopulations. According to proposed nomenclature^16,17, they were classified as ‘classical’ (CD14+/CD16-), ‘intermediate’ (CD14+/CD16+) and ‘nonclassical’ (CD14dim/CD16+). In accordance with previously published reports, classical monocytes were the most numerous, constituting about 80–90% of blood monocytes, with intermediate and nonclassical subtypes making up the rest.

A contentious issue with analysis of high dimensional flow cytometry data is the use of manual gating which is subjective and relies on visual inspection that varies between users leading to errors^50,51. This problem is especially evident during identification of rare cell types. Therefore, to validate our gating strategy we employed an automated clustering algorithm called spanning tree progression analysis of density-normalized events (SPADE)³⁸. SPADE involves density-dependent downsampling of raw flow cytometry data followed by agglomerative clustering based on relative expressions of different cellular antigens. This leads to construction of minimum spanning trees connecting the clusters that allows easy visualization of rare events. The similarities between bivariate plots created through SPADE and manual gating validated our manual gating strategy. A further confirmation of robustness of manual gating was obtained through high resolution imaging cytometry in which each individual population of cell was visualized and were clearly distinguishable via a combination of cell surface marker expression and nuclear morphology.

A growing body of opinion suggests that the primary reason for discrepancies between previously published reports on monocyte subset function is use of in vitro purified monocytes in culture and that whole blood stimulation and analysis could be a better alternative^39,40. A number of studies have shown benefits of whole blood culture and stimulation over purified cells for in vitro analysis of immune cell function^{37,52,53,54,55}. In the present study, we observed that purification of peripheral blood mononuclear cells (PBMCs) by ficoll-density gradient centrifugation led to considerable changes in relative percentages of monocyte subtypes – classical monocytes decreased with a simultaneous increase in percentage of nonclassical monocytes. When compared with whole blood analysis, our results provide evidence to the notion that gradient purification of monocytes can lead to experimental artefacts that can confound analysis of monocyte function.

Analysis of surface molecules on monocyte subpopulations revealed differential expression of toll-like receptors (TLRs), scavenger receptors and co-stimulatory molecules among the three monocyte subsets. Intermediate and nonclassical monocyte subsets expressed more TLRs 2, 4, 5, co-stimulatory molecules CD80, CD86 and HLA-DR than the classical subset, suggesting their role in antigen presentation. On the other hand, higher expression of scavenger receptors CD36 and CD163 on classical monocytes was suggestive of their predominantly phagocytic function. Our observation that CD80 and CD86 is differentially expressed among monocyte subsets is in disagreement with an earlier published report²³ that showed no difference in expression of CD80 and CD86 in purified monocyte subsets. Interestingly, the observed difference in expression of these two molecules within monocyte subsets was no longer present following stimulation of monocytes with LPS, suggesting that the earlier observation may have been a consequence of activation during purification process.

A constant source of controversy regarding function of subsets of human monocyte the type of cytokines produced by them. While inflammation is a complex phenomenon involving several receptors, mediators and pathways, monocytes that synthesize molecules such as TNF-α, IL-1β, IL-6 etc. have been classified and designated as ‘inflammatory subtype’ by us in this manuscript. The current study demonstrates that nonclassical monocytes are the primary producers of TNF-α and IL-1β upon activation as shown by intracellular cytokine staining. This observation is markedly different from an earlier observation²¹ that classified intermediate monocytes to be primarily responsible for inflammatory cytokine production while the non-classical monocytes showed patrolling behaviour. It is pertinent to note that these authors had used bead purified monocytes in vitro and measured released cytokines in supernatants. Another interesting observation was increased IL-10 production by intermediate subsets, which differs from earlier studies that demonstrated classical monocytes as principal producers of IL-10^21,23. While whole blood assays performed in this study is closer to physiological condition (unlike bead purified monocyte subsets) the discrepancy between earlier studies^21,23 and our current observation could also be due to difference in the assay system adapted for measuring cytokines. While the previous reports had measured secreted cytokines by ELISA in the current study we have quantified intracellular cytokines by flow cytometry. Intracellular cytokines do not necessarily correlate with secreted cytokines, particularly in the case of IL-1β secretion which is tightly regulated. Thus the observed differences in TNF-α, IL-1β and IL-10 positive monocyte subsets could be a result of the two different assay systems used in the investigations. Another probable cause could be a result of observations made at different time points as most studies reported in literature were all 18 hour stimulations followed by analysis of cytokines whereas our observations were at much earlier times points.

There was concordance between scavenger receptor expression and functional phagocytosis in different monocyte subsets. Classical and intermediate monocytes were found to be highly phagocytic while nonclassical monocytes were poorly phagocytic, an observation in agreement with previous reports²¹. Our data also provide circumstantial evidence to the hypothesis that intermediate monocytes may not be a distinct endpoint of differentiation rather a developmental stage between classical and nonclassical subsets. Principal components analysis and hierarchical clustering revealed the intermediate and classical monocytes to be closely linked whereas the nonclassical subset formed a distant cluster. This close relationship between intermediate and classical subsets has been suggested earlier²¹. It would be of interest to investigate if intermediate monocytes can switch to-and-fro between classical and nonclassical subtypes, i.e. between a predominantly phagocytic and a primarily inflammatory phenotype depending on different activation cues.

Flow cytometry-based detection of immune cell types in the context of various diseases is a useful way to diagnose severity and outcome in a clinical setting. We validated our findings in two inflammatory disease conditions, viz. sepsis and SLE. Our results indicate that expansion of CD16+ monocytes can be used to determine an inflammatory condition that is consistent with published reports^27,28,29,33. However, a question that remained unanswered was which one of the CD16+ monocyte subsets expand during inflammation? Our data show that while in an acute inflammation like sepsis both subsets increase in percentage with a concomitant decrease in classical monocyte percentage, in a chronic inflammatory situation like SLE, only the nonclassical subset is expanded. Although it is not clear whether such increase in inflammatory cell types is a cause or consequence of disease, it tends to suggest that increase in intermediate monocytes could be a differentiating factor between acute and chronic inflammation.

We conclude that ‘Classical’ monocytes are phagocytic with no inflammatory attributes, ‘Non-classical’ subtype display ‘inflammatory’ characteristics on activation and exhibit properties for antigen presentation while ‘Intermediate’ monocytes constitute a very small percentage in circulation (under physiological conditions) and appear to be a minor transitional subset that displays both phagocytic and inflammatory function. Given the importance of understanding monocyte subtypes in several human diseases (infectious as well as metabolic) very large number of reports have begun to clutter medical literature using un-validated flow cytometric assays. This highly validated phenotypic and functional characterization of Human monocyte subtypes should bring clarity to investigators in human immunology.

Immunoglobulin G (IgG) antibody subclasses play major roles in the control of bacterial and viral infections, the killing of tumour cells during antibody therapy and the pathological destruction of healthy tissues in autoimmune diseases. As a result of their potency and range of actions, antibodies have become one of the most rapidly growing classes of human therapeutics in recent years, particularly in cancer treatments.

Abstract

Antibody-dependent cellular cytotoxicity (ADCC) is exerted by immune cells expressing surface Fcγ receptors (FcγRs) against cells coated with antibody, such as virus-infected or transformed cells. CD16, the FcγRIIIA, is essential for ADCC by NK cells, and is also expressed by a subset of human blood monocytes. We found that human CD16− expressing monocytes have a broad spectrum of ADCC capacities and can kill cancer cell lines, primary leukemic cells and hepatitis B virus-infected cells in the presence of specific antibodies. Engagement of CD16 on monocytes by antibody bound to target cells activated β2-integrins and induced TNFα secretion. In turn, this induced TNFR expression on the target cells, making them susceptible to TNFα-mediated cell death. Treatment with TLR agonists, DAMPs or cytokines, such as IFNγ, further enhanced ADCC. Monocytes lacking CD16 did not exert ADCC but acquired this property after CD16 expression was induced by either cytokine stimulation or transient transfection. Notably, CD16+ monocytes from patients with leukemia also exerted potent ADCC. Hence, CD16+ monocytes are important effectors of ADCC, suggesting further developments of this property in the context of cellular therapies for cancer and infectious diseases.

Introduction

Antibodies mediate their anti-tumour effects directly, by interfering with tumor cell growth, or indirectly by activating immune-mediated complement-dependent cytotoxicity (CDC) or antibody-dependent cellular cytotoxicity (ADCC). A growing body of evidence suggests that ADCC may be the dominant mechanism operating in vivo^1,2,3,4,5. The process of ADCC begins with recognition of an antigen expressed on the target cell surface by specific immunoglobulins. The Fc domain of these antibodies is then bound by Fcγ receptors (FcγRs) expressed on immune effector cells, which triggers the release of cytotoxic granules towards the target cell or upregulates death receptors expression on the cell surface. In murine cancer models, both rituximab and trastuzumab efficacy has been shown to completely depend on activating FcγRs^6,7, in particular FcγRI and/or FcγRIV^8,9. This appears to be similar in humans where polymorphisms in either FcγRIIa or FcγRIII that affect their affinity for IgG influence the clinical success of rituximab^10,11, trastuzumab^{1,2,3,12,13,14} and cetuximab^4,5,6 treatment for B-cell lymphoma, breast cancer and colorectal cancer, respectively.

NK cells are considered to be the main mediators of ADCC both in physiological and therapeutic settings. However, NK cells are present only in low numbers in the microenvironment of colorectal^7,8, renal^9,10, liver, skin, breast and lung carcinomas^11,12,13,14. Defects in their cytotoxic function due to changes in activating and inhibiting receptor expression, upregulation in MHC class I expression, decreased expression in the signal transducing ζ chain, CD16 and cytotoxic machinery has been reported in numerous studies^15,16,17. A recent study further showed that cross-linking of CD16 on NK cells promoted a phenomenon known as NK cell abnormalities (NKCA), which not only included CD16 down-regulation, but also an increased in the frequency of apoptotic NK cells as well as enhanced depletion of NK cells in the presence of leukemic cells¹⁸. Apparently, this NKCA can be overcome by inhibiting MMP activation with TIMP3¹⁸. Notably, trastuzumab treatment was more effective in mice lacking the inhibitory FcγRIIb⁷, which is not expressed by NK cells, implying the involvement of other immune cell populations. Using target cell depletion approaches in mice, several studies have demonstrated that monocytes and macrophages to be the principal mediators of ADCC against α-CD20-coated B cells in vivo^4,19.

In both mice and humans, subsets of blood monocytes exhibit differential surface expression of the various FcγRs²⁰. FcγRIIIA (CD16) distinguishes human monocytes into two major subsets (i.e. CD16+ and CD16−) and they can be further subdivided using additional surface markers such as CD56^21,22. The minor subset that expresses low level of CD56 is mostly CD16− and is expanded in numbers under inflammatory conditions like Crohn’s disease and rheumatoid arthritis^23,24. While both the CD16+ and CD16− monocyte populations express similar levels of FcγRIIA (CD32), FcγRI (CD64) is preferentially expressed on the CD16− subset²⁰. The infiltration of monocytes into tumours has been widely observed. Interestingly, a recent study showed that tumour infiltration of CD16+ myeloid was associated with improved survival of colorectal cancer patients⁸. Whether CD16 expression on monocytes could promote cytotoxicity like it does in NK cells is unknown. In this study, we determine the capacity of human monocyte subsets to perform ADCC, and specifically assessed the role of CD16 in this function.

Discussion

Our data show that the human blood monocyte subsets that express CD16 possess the capacity to exert ADCC on cell lines, primary tumor cells and virally infected cells. ADCC by CD16+ monocytes was as efficient as that of NK cells. The CD16− subset when acquired CD16 expression could promote ADCC, revealing that this subset intrinsically possessed the machinery required to promote cytolysis of antibody-coated targets. ADCC activity could be further enhanced upon stimulation of CD16+ monocytes with TLR agonists, cytokines such as IFNγ and DAMPs. Cell-cell contact was essential and target cells lysis occurred through a TNFα-mediated mechanism. CD16+ monocytes from B-CLL patients did not exhibit discernible dysfunctions and showed ADCC activity similar to that of CD16+ monocytes from healthy individuals.

The involvement of other immune cell types in mediating ADCC has been clearly evident in numerous preclinical studies. These mouse studies demonstrated that monocytes and/or macrophages and not NK cells are the principal mediators of ADCC against α-CD20-coated B cells in vivo^4,19 further supporting the importance of monocyte in eradicating antibody-coated cells in vivo.

Our observation that the capacity for ADCC is unique to the CD16+ subset of human monocytes, is in line with recent findings both in humans³⁶ and in mice¹⁹. Mice deficient in FcγRIV, the murine homolog of human CD16³⁷ exhibit defects in several models of ADCC³⁸. In our study, the engagement of CD16 and potentially CD32, but not CD64, was necessary to trigger ADCC, which was similar to that reported for SLAN+ DC²⁹. However, unlike the data by Schmitz et al.²⁹ showing equal contribution of both CD32 and CD16 to ADCC by DC, our study showed that blocking CD16 inhibited lysis to a greater extent than CD32. CD16− monocytes were unable to exert ADCC despite the expression of CD64 and CD32 unless CD16 expression was enforced. Their differential ADCC could not be explained by the expression of CD32 isoforms, i.e. CD32a (activating) and CD32b (inhibiting) since CD32a expression is similar on both monocyte subsets and CD32b expression is higher on CD16+ monocytes^20,39 and unpublished data. Furthermore, the fact that the level of ADCC activity of these cells positively correlated with the level of CD16 expression further confirms the essential role played by CD16. Functional polymorphisms in the coding regions of the different FcγR s are known to impact their affinity for IgG. In fact, many studies correlating FcγR polymorphisms, particularly for CD32 and CD16 with clinical response, suggest a role for FcγR-mediated effector functions in antibody therapy. In both rituximab and trastuzumab treatments for follicular lymphoma and metastatic breast cancer respectively, polymorphism in both CD16 (i.e. FcγRIIIa-158V/F) and CD32 (i.e. FcγRIIa -131H/R) were shown to correlate with clinical responses^1,11. Another study in metastatic breast cancer found homozygosity for FcγRIIa-131H alone to be significantly associated with a stronger anti-tumour response and progression free survival when patients are treated with trastuzumab⁴⁰. These further support a predominant role of myeloid cells including monocytes in antibody therapy.

Panitumumab, an EGF receptor antibody, currently the only approved human IgG2 antibody, has been shown to promote ADCC by myeloid cells including monocytes as effectively as the IgG1 antibody at low doses⁴¹. Unlike IgG1, they bind CD32 with higher affinity⁴². With our study demonstrating that CD32 together with CD16 are involved in ADCC provide support for the potential application of IgG2 antibody in immunotherapy.

Impaired NK cell function has been reported in various types of malignancy. Alterations in the expression of activating and inhibiting receptors, increased MHC class I expression, down-regulated expression in the signal transducing ζ chain, CD16 and cytotoxic machinery were reported to contribute to NK cell dysfunction^15,16,17. Although reduced expression of CD16 on NK cells was commonly observed in many malignancies, there was no significant down-regulation of CD16 expression on NK cells from B-CLL patients in our study (data not shown). Nevertheless, these cells still exhibited a reduced ADCC ability compared to NK cells from healthy individuals possibly due to other factors mentioned above. On the contrary, CD16+ monocytes from these patients were as capable as CD16+ monocytes from healthy individuals in terms of ADCC.

Unlike NK cells where IL-12 and IL-15 activates and enhances their cytolytic ability, the ADCC capacity of CD16+ monocytes was unaffected by these cytokines. A previous study showed that IFNγ could enhance monocyte/macrophage ADCC activity but only via FcγRI⁴³. While TLR agonists such as CpG can enhance the cytolytic ability of NK cells⁴⁴, LPS and R848, which ligate TLR4 and TLR7/8 respectively, specifically enhanced the ADCC activity of CD16+ monocytes. R848 has been shown to activate NK cell cytotoxicity after 18 hrs⁴⁵ but no enhancing effect was detected at the 5 hr time point used in our study. TLR8 agonist, in particular, promoted ADCC by monocytes through a IL-12-induced granzyme B expression and secretion after 12 hrs⁴⁶. However, no granzyme B protein was detectable when CD16+ monocytes were treated with R848 for 5 hrs in our study (data not shown) and IL-12 treatment also did not enhance ADCC at this time-point. Both HMGB1 and S100A9 are self-derived molecules well-known as damage-associated molecular patterns (DAMPs), which are released at sites of tissue damage or regions of necrotic cells⁴⁷. Treatment of cancer with therapeutic antibodies is routinely performed in conjunction with chemotherapy or surgery, which leads to tissue damage and death in the tumour environment. As such, monocytes recruited to the tumour site and activated locally by DAMPs might then be able to promote killing of the remaining cancer cells coated with the therapeutic antibody. Both HMGB1 and S100A9 as well as TLR agonists and IFNγ could also activate monocytes to release pro-inflammatory cytokines including TNFα^48,49,50. Specifically, IL-10 and TGF-β over-production were shown to decrease NK cell mediated functions including ADCC, down regulation of CD16 expression and IFNγ production^16,51,52, our data however showed that the enhancement of CD16 expression on CD16− monocytes by these mediators conferred these monocytes with ADCC activity, which might be favorable for cancer immunotherapy.

Previous studies showed that FcγR engagement can induce β2-integrin activation on murine macrophages for optimal phagocytic activity but played no role in ADCC by in vitro differentiated human macrophages^53,54. However, β2-integrin appears to be involved in ADCC by CD16+ monocytes in our study. Besides promoting the release of proinflammatory cytokines, stimuli like LPS and S100A9 may potentially be enhancing ADCC activity of CD16+ monocytes through regulating the activity of CD11b, the binding partner of β2-integrin^55,56.

The production of TNFα by activated macrophages and monocytes has been well described. The involvement of TNFα in ADCC by macrophages through antibody neutralization assay had also been reported in numerous studies²⁹. Nevertheless, the exact mechanism is still unclear. The TNFα secreted by CD16+ monocytes upon engagement of the FcγR could be involved in the activation of b2-integrins in an autocrine fashion similar to that reported for neutrophils⁵⁷. In addition, as shown for breast cancer cells, the secreted TNFα also induced ICAM1 expression on the tumor cells in our study (data not shown)⁵⁸. Together, these would result in further cell-cell interaction to promote target cell lysis. Most importantly, only target cells in direct contact with the CD16+ monocytes will undergo ADCC because the clustering of antigens on the target cell surface through engaging the FcγR on the CD16+ monocytes promoted TNFR surface expression, predisposing these target cells to TNFα-mediated cell death. A finding that has not yet been reported.

Moreover, CD16+ monocytes have been reported to expand during infection, autoimmune disease and certain cancers such as colorectal, gastric and breast^59,60. It will therefore be interesting to understand how this biological observation might link with clinical outcomes, and in particular whether higher numbers of CD16+ monocytes might favor better responses to therapeutic antibody treatment. Interestingly, a study by Romano et al. showed that melanoma patients who responded to treatment with ipilimumab had a significantly higher proportion of CD16+ monocytes as compared with non-responding patients³⁶. Another study showed that CD16+ myeloid cells infiltration into the tumour mass in colorectal cancer patients represents a strong, novel and independent prognostic prosurvival factor⁸. Further studies are required to determine how the preferential expansion of this subset influences the progress of the different diseases. Moreover, we have shown the potential for human CD16+ monocytes to be effective mediators of ADCC against a range of cell types in vitro and therefore exploration of ways to exploit this potential in vivo could prove valuable in the clinical setting.

Covid-19 can involve multiple organs including the nervous system. We sought to characterize the neurologic manifestations, their risk factors, and associated outcomes in hospitalized patients with Covid-19.

Methods

We examined neurologic manifestations in 509 consecutive patients admitted with confirmed Covid-19 within a hospital network in Chicago, Illinois. We compared the severity of Covid-19 and outcomes in patients with and without neurologic manifestations. We also identified independent predictors of any neurologic manifestations, encephalopathy, and functional outcome using binary logistic regression.

Results

Neurologic manifestations were present at Covid-19 onset in 215 (42.2%), at hospitalization in 319 (62.7%), and at any time during the disease course in 419 patients (82.3%). The most frequent neurologic manifestations were myalgias (44.8%), headaches (37.7%), encephalopathy (31.8%), dizziness (29.7%), dysgeusia (15.9%), and anosmia (11.4%). Strokes, movement disorders, motor and sensory deficits, ataxia, and seizures were uncommon (0.2 to 1.4% of patients each). Severe respiratory disease requiring mechanical ventilation occurred in 134 patients (26.3%). Independent risk factors for developing any neurologic manifestation were severe Covid-19 (OR 4.02; 95% CI 2.04–8.89; P < 0.001) and younger age (OR 0.982; 95% CI 0.968–0.996; P = 0.014). Of all patients, 362 (71.1%) had a favorable functional outcome at discharge (modified Rankin Scale 0–2). However, encephalopathy was independently associated with worse functional outcome (OR 0.22; 95% CI 0.11–0.42; P < 0.001) and higher mortality within 30 days of hospitalization (35 [21.7%] vs. 11 [3.2%] patients; P < 0.001).

Interpretation

Neurologic manifestations occur in most hospitalized Covid-19 patients. Encephalopathy was associated with increased morbidity and mortality, independent of respiratory disease severity.

As of 8 September 2020, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has led to over 26.5 million confirmed infections and 875,000 deaths from coronavirus disease-2019 (Covid-19) worldwide.¹

Like most infections caused by members of the coronavirus family, SARS-CoV-2 manifests itself with upper respiratory tract infections and flu-like symptoms of varying severity.² However, Covid-19 is unique in its ability to cause a multi-organ disease, with involvement of the central and peripheral nervous system in some individuals.

Indeed, a wide range of neurologic manifestations of SARS-CoV-2 infection have been recognized, and evidence of their severity and persistence is increasing.^3–10 However, the frequency of those manifestations and associated risk factors remain unclear. We sought to characterize the incidence of neurologic manifestations, in patients with confirmed Covid-19 and identify factors associated with the development of neurologic manifestations in hospitalized patients with both severe and non-severe respiratory disease. Furthermore, neurologic manifestations, especially encephalopathy, have been associated with worse clinical outcomes in other systemic illnesses including sepsis and may even lead to significant disability.^11, 12 Therefore, we sought to identify if encephalopathy was associated with greater morbidity in hospitalized patients with Covid-19.

Discussion

This study highlights the high frequency and range of neurologic manifestations, which occurred in more than four fifths of Covid-19 patients hospitalized in our hospital network system. These results expand findings of neurologic manifestations in 36.4% of hospitalized Covid-19 patients in China and 57.4% in Europe^16, 17, albeit with increased prevalence in our US cohort. Differences in frequencies may be caused by genetic factors including polymorphism in expression of the viral receptor angiotensin-converting enzyme 2 (ACE 2) in the nervous system, and possibly, SARS-CoV-2 strain variations.¹⁸ In addition, our hospital network system was never stressed beyond capacity due to surge preparation and most patients had moderate disease, with only one quarter developing severe respiratory distress requiring mechanical ventilation.¹⁹ This may have allowed for more detailed evaluation and identification of neurologic manifestations.

The fact that any neurologic manifestations as a whole were more likely to occur in younger people is surprising, and could potentially be explained by greater clinical emphasis on the risk of respiratory failure than other symptoms in older patients. Alternatively, early neurologic manifestations such as myalgia, headache, or dizziness may have prompted earlier medical care. In contrast, encephalopathy was more frequent in older patients. Risk factors for encephalopathy also included severe Covid-19 disease and history of any neurological disorder or chronic kidney disease. This is consistent with recent literature identifying higher rates of mortality in Covid-19 patients with pre-existing chronic neurological disorders.²⁰

The increased morbidity and mortality associated with encephalopathy, independent of respiratory severity, parallels previous literature in sepsis-associated encephalopathy and delirium-associated mortality^11, 21 and emphasizes its relevance in Covid-19. We also found that encephalopathy in Covid-19 was associated with triple the hospital length of stay. Broad recognition and screening for encephalopathy as a contributor to disease severity in Covid-19 may have utility in resource allocation and potential to improve patient outcomes. Furthermore, our findings emphasize the broader need to develop interventions that target encephalopathy as a component of multi-organ system medical illness.

The cause of encephalopathy could not be determined with certainty given the lack of extensive diagnostic neurologic testing for most patients in this study due to ongoing pandemic restrictions. However, the most likely etiology of encephalopathy in patients with Covid-19 is multifactorial, including systemic disease and inflammation, coagulopathy, direct neuroinvasion by the virus, endotheliitis and possibly post-infectious auto-immune mechanisms.⁵ Additionally, traditional risk factors associated with intensive care unit delirium and encephalopathy also need to be taken into account, including sedation and analgesia doses, disruption of sleep/wake cycles, and infectious complications.^22, 23 Critical illness encephalopathy, in general, can result from multiple mechanisms or combinations of mechanisms that remain an unresolved area of basic science research.²⁴

Our hospital network system includes an AMC and nine other hospitals. There was no meaningful difference in severity of disease between the AMC and the other hospitals, but patients at the AMC had better functional outcomes and lower 30-day mortality. One potential explanation for this finding may be related to specialty care, access to resources, and lower rates of do not resuscitate/intubate and comfort measures-only orders. Our AMC is also the largest hospital within the NMHC system with the greatest number of ICU beds, which may confer a survival benefit to critically ill patients with Covid-19.²⁵ A similar difference has been observed in patients with sepsis, who had better outcomes and lower mortality when treated by tertiary versus non-tertiary hospitals.²⁶ Early adoption and implementation of uniform treatment protocols across hospital networks driven by AMCs may be a means to improve outcome and lower mortality of Covid-19 patients that deserves further investigations.

Our study has limitations, including its retrospective nature, and the fact that fewer than 6% of patients were evaluated by neurologists or neurosurgeons. Since most patients were admitted to dedicated Covid-19 wards or ICUs with strict infection control precautions in place, access to brain CT or MRI was not as readily available as for other patients with neurologic diseases. This limited a more complete neurologic work up in many Covid-19 patients. Additionally, patients were cared for at 10 different hospitals and there may have been varying rates of local geographic infection severity. However, this provided us with a more generalized view of the neurologic manifestations in Covid-19 patients and could identify opportunities for regionalized resource allocation and preparedness protocols in a large hospital network system.

Only 9 months into the pandemic, the long-term effects of Covid-19 on the nervous system remain uncertain. Our results suggest that, of all neurologic manifestations, encephalopathy is associated with a worse functional outcome in hospitalized patients with Covid-19, and may have lasting effects.¹² Long-term follow-up is necessary to assess the true burden of encephalopathy in these patients. Whether milder forms occur in non-hospitalized individuals with Covid-19 who complain of protracted inability to concentrate or decreased short term memory (referred to as ‘brain fog’) warrants further evaluation.²⁷ Prospective cognitive and neurologic-focused evaluations through specialized clinics dedicated to further diagnostic assessment and tailored rehabilitation needs could play a significant role in recovery from this pandemic.

Optical biosensors have led to significant advancements in virus detection and imaging capabilities. Coupled with advanced instrumentation, they have enabled higher sensitivities while increasing the rate at which samples can be tested. These techniques can be developed into point-of-care (POC) diagnostics for viral detection and are promising alternatives to detect COVID-19.

Abstract

The recent pandemic of the novel coronavirus disease 2019 (COVID-19) has caused huge worldwide disruption due to the lack of available testing locations and equipment. The use of optical techniques for viral detection has flourished in the past 15 years, providing more reliable, inexpensive, and accurate detection methods. In the current minireview, optical phenomena including fluorescence, surface plasmons, surface-enhanced Raman scattering (SERS), and colorimetry are discussed in the context of detecting virus pathogens. The sensitivity of a viral detection method can be dramatically improved by using materials that exhibit surface plasmons or SERS, but often this requires advanced instrumentation for detection. Although fluorescence and colorimetry lack high sensitivity, they show promise as point-of-care diagnostics because of their relatively less complicated instrumentation, ease of use, lower costs, and the fact that they do not require nucleic acid amplification. The advantages and disadvantages of each optical detection method are presented, and prospects for applying optical biosensors in COVID-19 detection are discussed.

Introduction

The novel coronavirus disease 2019 (COVID-19) has caused an unprecedented surge in virus research, in particular improving testing and diagnostics. The rapid global spread of COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and slow and sometimes inaccurate testing has highlighted the need for more advanced imaging and detection techniques. The current standards for virus imaging include computed tomography (CT), single photon emission computed tomography (SPECT), and positron emission tomography (PET).¹ These methods are costly, have low resolution, and in the case of CT can only detect signs of virus infection (i. e., pneumonia or lung lesions),² although recently CT has been used as an additional technique for COVID-19 diagnosis.³ Often enzyme-linked immunosorbent assay (ELISA) or reverse-transcription polymerase chain reaction (RT-PCR) are linked with immunofluorescence to detect pathogens and viruses.⁴ Currently, RT-PCR is the gold standard for SARS-CoV-2 detection; however, this is a multi-step technique which involves purification, nucleic acid amplification, and fluorescence detection.⁵ The process is laborious, requires a trained operator, can report a number of false-negatives, and has limited availability in resource-limited settings.⁶ A comparison between different molecular imaging modalities is shown in Figure 1.

Optical biosensors present an alternative method for virus detection due to their safe, straight-forward use, and cost-effective technology, including eliminating the need for nucleic acid amplification.⁷ Fluorescence, surface plasmons, and colorimetry techniques have all been used previously for the detection of HIV, Ebola, norovirus, and influenza virus, amongst others.⁸ These techniques have been used in nano-biosensors to allow for targeted virus detection and single virus imaging.⁹ Optical biosensors can also be used as point-of-care (POC) diagnostic tools. POC diagnostics use collected samples without the need for sample preparation, require low costs of test manufacturing, and do not require trained personal or expensive analysis equipment.¹⁰ To the best of our knowledge, only a handful of optical biosensors are currently on the market for virus detection, most comprising of lab-on-a-chip (LOC) techniques that amplify nucleic acids for fluorescent analysis.¹¹ Improving optical imaging, in particular single virus imaging, has the potential to be used to track and monitor virus replication, cell interaction, and termination in order to more quickly and efficiently develop treatment options. Ongoing research to apply these imaging techniques to detect COVID-19 has already begun;¹² however, further work is necessary to bring these technologies from benchtop to market. This minireview examines multiple optical techniques and their applications in virus detection and presents a perspective on their potential use to detect SARS-CoV-2.

Methods of Optical Biosensing

Optical biosensing can combine detection and imaging which can provide a deeper understanding of a pathogen in addition to detecting it in biological samples.¹⁴ Optical bioimaging combines advanced optical methods with pathogen-specific tracers, allowing for targeting and detection of abnormalities in a disease pathway at the molecular stage. Some of the advantages of optical bioimaging over conventional imaging methods like MRI, CT and PET include femtomolar sensitivity, high spatial resolution, non-invasive and non-ionizing imaging, low equipment/personnel cost, ease of mobilization, quantitative results and short processing time.^7, 15 While useful for ex vivo diagnostics of processed biological samples, direct imaging without sample preparation has many challenges: the presence of dense tissues in biological samples introduces loss of light directionality that results in a higher degree of scattering.¹⁶ The dense biological tissues have high absorbance that reduces the light intensity, resulting in a subsequent decrease in the signal-to-noise ratio. The scattering and absorbing effects of these biological samples can be overcome by employing excitation and emission wavelengths in the near-infrared window (NIR 1) (700–900 nm)¹⁷ or a second NIR window (NIR 2; 1.0–1.7 μm).¹⁸ Recent research involving fluorescence, surface plasmon and surface enhanced Raman scattering (SERS)-based detection and imaging has advanced the field of optical imaging to be employed as testing mechanisms for various viral pathogens.

Fluorescence

Fluorescence-based sensing and imaging offers unique advantages such as good sensitivity, high temporal resolution, availability of biocompatible imaging agents, and noninvasive characteristics that make it relevant in research and clinical settings.¹⁹ Fluorescence-based optical biosensors are the single largest group of sensors at present, owing to the commercial availability of numerous fluorescent probes, high quality optical fibers and suitable optical instruments.²⁰ High excitation power is not required for fluorescence, making it a cheap, readily available tool. Wei et al. demonstrated successful imaging of fluorescent nanoparticles and viruses (100 nm and 160–272 nm, respectively) using a setup that fits on a smartphone.²¹ While a viable biological imaging technique, there are certain limitations such as fluorophore blinking,²² photobleaching and orientation of the transition dipoles (causing artifacts), and the inability for many target molecules to exhibit detectable fluorescence signals²³ that need to be overcome before it can be used for virus detection.

Fluorescent biosensors have various parameters like intensity, energy transfer, lifetime and, quantum yield that can be exploited for virus detection.²⁴ One mechanism that is often used in these biosensors to detect close interactions (<10 nm) between an analyte and a fluorophore is Förster resonance energy transfer (FRET). FRET is the process where incident radiation is absorbed and nonradiatively transferred from a donor to an acceptor by means of long-range dipole-dipole coupling.²⁵ Recent improvements in FRET research and advancements in optical instrumentation have established FRET microscopy as an effective tool for biological imaging and detection applications.²⁶

The fluorescence emission of sensors can be classified as up-converting or down-converting based on their excitation and emission wavelengths. Up-conversion is when the emitted wavelength is shorter than the excitation wavelength (anti-Stokes shift). Up-conversion of the above mentioned NIR 1 excitation wavelengths to shorter visible wavelengths enables minimal autofluorescence, deeper sample penetration depth, higher signal-to-noise ratio, and high chemical and physical stability during biosensing.²⁷ Down-conversion is the more common mode of linear fluorescence that can exploit NIR 2 by emitting longer wavelengths than the excitation wavelengths.

There are multiple different light-emitting materials (fluorophores) used in fluorescence-based optical biosensors including inorganic semiconductor quantum dots (QDs), carbon dots (CDs), graphene nanostructures and organic conjugated polymer nanoparticles as shown in Figure 2. QDs, also known as colloidal semiconductor nanocrystals, are small particles (1–10 nm in size in all three dimensions), with unique optical and electronic properties.²⁸ Due to quantum confinement effects, the emission wavelengths of QDs can be tuned from UV to NIR.²⁹ Compared to small-molecule organic dyes, QDs are superior in many aspects, such as high quantum yield, photostability, emission wavelength tunability, Stokes shift, and absorption and emission profiles.³⁰ They are one of the more commonly investigated materials for fluorescence sensing at present with multiple reports that study their suitability in fluorescent biosensors. For example, their bright photoluminescence, broad size-tunable emission spectrum, and photochemical stability have been successfully applied for single-virus tracking in vitro.^19a Pan et al. replaced the native hydrophobic ligands of QDs with multidentate polymer ligands bearing imidazole pendant groups to obtain water-dispersible azido-derivatized NIR QDs that were used for tracking and imaging of avian influenza H5N1 pseudotype virus (H5N1p; Figure 2A).^19a The virus particles were labeled with the water soluble QDs through biorthogonal chemistry, a biocompatible chemical reaction that can occur without interfering with native biochemical processes. This labeling enabled non-invasive tracking of respiratory viral infection in vivo. In another study, a bionic assay was developed for thrombin activity detection (indicator of diseases such as thrombosis, hemophilia, atherosclerosis, and inflammation) based on peptide-modulated CdTe QD aggregation, where the surface charge of CdTe QDs is regulated by the hydrolysis of a thrombin substrate peptide.³¹ However, QDs are mainly made with toxic chemical elements and thus their long-term toxicity in vivo is a major concern.³⁰ This has led to the development of more biocompatible light-emitting nanomaterials, such as conjugated polymer nanoparticles (CP NPs) and CDs.³² However, imaging is more challenging with these materials.³³

Conjugated polymers (CPs) are macromolecules containing backbones with extended π-conjugated structural units resulting in enhanced light-harvesting and effective transport of excitons compared to organic dyes. They are an important class of materials due to their signal amplification in therapeutic activities³⁴ and their reduced photo toxicity by promoting light-controlled photodynamic therapy.³⁵ In order to reduce the toxicity of CPs, new water-soluble CPs have been designed and synthesized, and significant advances in biological applications of these water-soluble CPs have been made.³⁶ Bai et al. used the change in fluorescence intensity observed when polythiophene/cucurbit[7]uril (PT/CB[7]) CP formed a supramolecular structure with tobacco mosaic virus (TMV) for virus and other pathogen detection (Figure 2B).⁴ Change in fluorescence intensity was observed upon formation of supramolecular structure enabling the detection of TMV virus. This strategy has the potential to detect multiple types of viruses and other pathogens by altering the polythiophene backbone.³⁹ Due to their capability to undergo conformational changes⁴⁰ and encapsulate emitters,⁴¹ CPs are suitable for optical biosensors using FRET.⁴² Wang et al. synthesized supra-dots from poly(9,9-dioctylfluorene (PFO) nanoparticles (p-dots) and dicyanomethylene-4H-pyran (DCM) dye molecules (Figure 2C).³⁷ The supra-dots bind to the hemagglutinin of influenza virus resulting in a drastic decrease of FRET signal. The size of CP NPs is important in order to be useful in clinical applications as renal particle filtration is highly dependent on particle size. Kidneys quickly filter out particles smaller than 6 nm, whereas particles larger than 8 nm remain in circulation.³⁰ To increase the size of small CP NPs, a targeting biomolecule can be linked to particles smaller than 6 nm using cleavable bonds. After imaging, the CP NPs can be released from the biomolecule and excreted through urine. Polymer NPs can be used for ex vivo virus detection using fluorescence detector flow strips conjugated with antibodies and dendrimer bioconjugated latex (polystyrene conjugated with aliphatic amines) NPs (Figure 2D).³⁸

Surface plasmons

Surface plasmons are collective oscillations of the electron cloud at the surface of a metal excited by incident electromagnetic radiation. There are different types of surface plasmons that are associated with different metal structure types. For example, propagating surface plasmon polaritons (SPPs) are supported by metal films while localized surface plasmon resonances (SPRs or LSPRs) are supported by metal NPs. One of the drawbacks of planar surface plasmon sensors based on SPPs is their extended surface area that requires relatively large sample volumes and large numbers of molecular interactions to generate a detectable signal. A logical approach to overcome these limitations is the use of plasmonic NPs, which exhibit a reduced surface area compared to a metallic film.⁴³ The development of synthetic methods to control the shape of plasmonic NPs with relatively narrow size distribution has been extensively reported. The shape and size specificity of the SPRs of plasmonic NPs results in homogeneous plasmon line widths and near-field enhancements, which are crucial to reliable single-NP and single-molecule plasmon sensors.

SPR detection can be modulated on the basis of changes in intensity,⁴⁴ refractive index,⁴⁵ wavelength,⁴⁶ and resonance angle,⁴⁷ as shown in Figure 3. SPR is sensitive to phase changes which increases the sensitivity and resolution of SPR detection as compared to conventional methods involving angular and wavelength modulations.⁴⁸ The SPR intensity and wavelength can be a function of shape, size, and dielectric constant of plasmonic NPs as well as of the surrounding environment making it an effective tool that can be tailored to imaging and detection of single biomolecules and cells.⁴⁹ In 1983, Liedberg et al. created the first plasmonic biosensor by depositing a silver film on glass.⁵⁰ Upon adsorption of human γ-globulin, a shift in the resonance angle of the SPR was observed due to the change in refractive index. The concept of conjugating antibodies with metals has resulted in developing modified DNA-AuNP aggregates into biosensors that enable detection of nucleic acids of several pathogens.⁵¹ Intensity-based SPR imaging is the more common commercially available type,⁴⁸ employed by companies such as Biosensing Instrument Inc. (http://biosensingusa.com) and Carterra (https://carterra-bio.com), which detects antibodies, single cells, viruses, proteins, and drug molecules. Ashiba et al. employed a dual antibody trapping system to detect norovirus by adding antibody functionalized QDs to a biosensor modified with virus antibodies.⁵² Surface plasmons on an Al film were used to detect the QD intensity as virus particles became trapped between the biosensor antibody and the QD antibody (Figure 3A). Liu et al. took advantage of silver’s strong localized SPR light-scattering signals to prepare thiol-linked HIV DNA AgNPs.⁵³ A change in scattering intensity was observed with DNA-AgNPs hybridized with HIV DNA (Figure 3B). Changes in resonance angle of surface plasmons was utilized by preparing an antibody modified polymer sensor film coated on a gold film that binds dengue virus-E protein at low detection limits (Figure 3C).⁵⁴ The biosensor exhibited an increased shift in the resonance angle upon binding of the virus, due to a change in the refractive index of the environment surrounding the Au film. SPR sensors can provide real-time 2D resolution of high-throughput micro-arrays by combining spectra and phase-shift investigations.⁴⁸ The challenges for SPR detection involve the requirement of high excitation power, toxicity (except gold), and high fabrication costs.

Plasmon-enhanced fluorescence

Plasmon-enhanced fluorescence (PEF) was first investigated in the 1970s by Weber et al. and Knoll et al. using high-quantum-yield dye molecules.⁵⁵ PEF has been extensively investigated in the context of bioimaging by coupling surface plasmons to periodic corrugations like grating. This coupling yielded enhancement of fluorescent signals over three orders of magnitude.⁵⁶ For biological samples Koh et al. reported an enhancement of fluorescence by 20- to 30-fold in the NIR 1 window using a nanostructured plasmonic gold chip.⁵⁷ This enables improved detection and bioimaging by fluorescence of biocompatible fluorophores that exhibit relatively low quantum yields.⁵⁸ PEF has been frequently used on microfluidic chips for detection and imaging of biomolecules.^56a, 59 Additionally, PEF is versatile in terms of detecting various types of viruses while improving the detection limits.⁶⁰

Surface-enhancing Raman scattering

The discovery of the SERS effect in the 1970s demonstrated that Raman scattering efficiency can be enhanced by factors of up to 10⁶ when the sample is located on or near nano-textured surfaces of plasmonic metals.⁶¹ This enhanced Raman scattering efficiency holds great promise as an optical bioimaging technique, which under optimal conditions, enables deep and high-resolution volumetric imaging of biological tissues.⁶² Solid substrates covered with metal-coated nanostructures were developed and proposed as efficient and reproducible SERS-active media.⁶³ SERS offers higher sensitivities and chemical specificities than most modes of optical detection;²³ and has been used to detect influenza, Adeno, West Nile, and rift valley fever virus amongst others.⁶⁴ However, SERS-based bioimaging is underdeveloped^64a due to the lack of specialized Raman instruments tailor-made for volumetric bioimaging,⁶⁵ toxicity challenges, and poor stability of SERS probes due to enzymatic degradation or desorption.⁶⁶

Colorimetry

Colorimetric biosensors can detect the presence of particular compounds through a color change easily observable with the naked eye or by a simple optical detector.⁶⁷ Due to their ease of use and the fact that they do not require expensive analysis instrumentation, colorimetric biosensors are ideal candidates for POC diagnostics.⁶⁸ Smart materials causing visible color change have been developed using noble metal NPs, metal oxide NPs, carbon nanotubes, and CPs,^40b, 69 as shown in Figure 4. Metal oxide NPs (such as Fe₃O₄ and CeO₂) and carbon nanotubes can produce a color change due to catalyzing the reaction of a peroxidase substrate or their intrinsic peroxidase activity, respectively.^69b–70 Several CPs (i. e., polydiacetylene and polythiophenes) can also exhibit a color change that arises from conformational transitions or agglomeration.⁷³ AuNP are another candidate material for colorimetric biosensors because their color can be manipulated by particles being in an aggregated or non-aggregated orientation.⁷⁴ Extensive research has been performed to modify AuNPs by incorporating various functional acceptors onto their surfaces.⁷⁵ However, a major problem with AuNPs is their intrinsic desire to aggregate when in high ionic strength environments or in the presence of impurities.⁷⁶ By balancing the interparticle attractive and repulsive forces, and colloidal stability, aggregation can be more easily controlled.⁷⁷ Yen et al. used multicolored Au nanoplates (triangular in shape) conjugated with virus specific antibodies to distinguish between dengue, yellow fever, and Ebola viruses.⁷¹ A sandwich hybridization formed between the antibody-Au nanoplate, virus particle, and a surface-adhered virus-specific antibody (Figure 4A). In 1993, Charych et al. proposed that human influenza virus (H1N1) can be detected colorimetrically at lower detection limits by using a polydiacetylene (PDA) bilayer.⁷⁸ Since then, PDA bilayers have undergone several modifications in an effort to create a POC testing method.⁷⁹ Song et al. introduced a peptide functionalization of PDA that increased the colorimetric detection limit to 10⁵ PFU or 0.2 HAU, similar to the rapid antigen test kits (Figure 4B).⁷²

Virus Detection with Optical Detection Techniques

Each optical detection technique outlined above presents its own advantages and disadvantages, and all have been previously used for virus detection (Figure 5, Table 1). Optical nano-biosensors dramatically improve the possibilities to monitor in vivo processes that enhance our understanding of cellular functions.⁸³ NPs, QDs, and CPs are the most common types of imaging probes that overcome the limitations of organic dyes.³⁰ Their ability to undergo surface modifications to increase their hydrophilic or hydrophobic nature is crucial for their use in in vivo measurements.⁸⁴

One common approach of optical virus detection is using biomolecules (antibodies, aptamers, DNA) unique to a specific virus as shown in Figure 6. Although this technique has a high selectivity and can be used for a variety of detection modalities, the biomolecules need to be readily available and affordable to be a cost-effective technique. Boltovets et al. investigated the quantification of the inhibition effect of polysaccharide glucuronoxylomannan (GXM) on the infection efficiency of TMV.⁸⁵ This study demonstrated a shift in the wavelength of surface plasmons due to the change in refractive index of the environment induced by the presence of TMV (Figure 6A). Another method by Zengin et al. used SERS to detect DNA representative of hepatitis B on a temperature responsive silicon chip.^80d AuNPs were modified with a hepatitis B DNA-capture probe and were adhered to the surface of a chip. DNA reporter strands labeled with indocyanine green were coupled to a different set of AuNPs (Figure 6B). The two sets of AuNPs sandwich hepatitis B DNA making the sandwich complex optically active. The chip was able to be regenerated for multiple uses by a simple sulfate solution washing step. Zhan et al. proposed employing SERS-based imaging in combination with enzyme immunoassay for the detection of respiratory syncytial virus (RSV).⁸⁸ Firstly, a peroxidase solid substrate was modified with 3,3′,5,5′-tetramethylbenzidine (TMB), a Raman molecule. RSV was captured with a specific antibody on a solid substrate and subsequently bound by another horseradish peroxidase (HRP) labeled antibody to form a sandwich complex. AgNPs were capped with citrate that makes them negatively charged. These negatively charged AgNPs form aggregates upon coming in contact with the positively charged TMB resulting in an enhancement of Raman signal that originates from TMB. LSPR was used by Nasrin et al. who developed a peptide linker conjugated with both a QD and a AuNP which altered the intensity of absorption when influenza virus particles were present (Figure 6C).⁸⁶ Shojae et al. have conjugated CdTe QDs with antibodies specific to Citrus tristeza virus (CTV) and AuNPs with the antigen coat protein of CTV.⁸⁷ The fluorescence signal from the antibody conjugated QDs was significantly reduced due to FRET from QDs to the AuNPs. For the infected samples, there was a significant increase in the fluorescence signal from the QDs due to the absence of FRET, which resulted in optical detection of CTV.

Microfluidics-based LOC devices have been identified as lead candidates for in-field POC diagnostics due to their ease of use and low-cost analysis⁸⁹ as shown in Figure 7. Fluorescence enhanced SPR has been shown to detect Ebola virus using a chip prepared with both microfluidic and optofluidic capabilities (Figure 7A).^80b Oligonucleotide functionalized magnetic microbeads were used to target Ebola RNA for signal amplification, followed by fluorescent labeling and detection, which occurs in under ten minutes. The high specificity, low limit of detection, quick analysis time, and ability to perform multiple runs using a single chip yields a highly desirable method of analysis. Hwang et al. designed a lateral flow assay (LFA) capable of detecting Tamiflu-resistant influenza virus by using oseltamivir hexylthiol (OHT) AuNPs that selectively bind to Tamiflu resistant virus (TRV).⁹⁰ A detection and a control line were prepared with anti-influenza A virus nucleoprotein antibody and Tamiflu resistant neuraminidase protein respectively (Figure 7B). OHT-AuNPs bind to TRV particles which bind to the test line antibodies causing a color change due to the conjugation of the AuNPs. The proposed LFA does not require sample preparation and produces results within 10 minutes.

Nano-biosensors are especially useful as site specific imaging tools to detect where virus particles reside, which is useful for assisting with therapeutic delivery tactics. Recently, Ueki et al. published the first protocol for in vivo analysis of lung virus infiltration using a multicolor two-photon imaging device for influenza virus in mice.^9b They focused on intravenously administering fluorochrome-conjugated antibodies to visualize the virus particles in the lungs using two-photon excitation laser microscopy. This technique allows for viral pathogenicity studies useful for understanding host response mechanisms. Despite their success, the protocol for this technique is laborious and faces several challenges including the lungs constant movement and a limited observation depth of ∼70 μm which is not deep enough for bronchial imaging. An alternative method for single virus tracking uses coherent brightfield (COBRI) microscopy in tandem with fluorescence to track vaccinia virus particles starting before the virus lands on the cell.^9a A scattering approach is used by shining a continuous wave laser beam at a single wavelength at an aqueous solution containing cells and virus particles and collecting both COBRI and fluorescent images. Both imaging modalities were important because fluorescence confirmed the location of the virus particles as seen on COBRI images. COBRI images could then be used to estimate the x,y,z planar positions to determine when a single virus particle is interacting with a cell surface. They were able to successfully capture a single virus particle diffusing in the aqueous solution and landing on the cell plasma membrane. This work is extremely useful for studying the delivery of nanoparticles or therapeutics into cells. Studying viruses in their physiological environments, provides insight into host response mechanisms assisting in developing more direct therapeutic targeting.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiology of coronavirus disease 2019 (COVID-19), is readily transmitted person to person. Optimal control of COVID-19 depends on directing resources and health messaging to mitigation efforts that are most likely to prevent transmission, but the relative importance of such measures has been disputed.

Key Points

Question  What proportion of coronavirus disease 2019 (COVID-19) spread is associated with transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from persons with no symptoms?

Findings  In this decision analytical model assessing multiple scenarios for the infectious period and the proportion of transmission from individuals who never have COVID-19 symptoms, transmission from asymptomatic individuals was estimated to account for more than half of all transmission.

Meaning  The findings of this study suggest that the identification and isolation of persons with symptomatic COVID-19 alone will not control the ongoing spread of SARS-CoV-2.

Objective  To assess the proportion of SARS-CoV-2 transmissions in the community that likely occur from persons without symptoms.

Design, Setting, and Participants  This decision analytical model assessed the relative amount of transmission from presymptomatic, never symptomatic, and symptomatic individuals across a range of scenarios in which the proportion of transmission from people who never develop symptoms (ie, remain asymptomatic) and the infectious period were varied according to published best estimates. For all estimates, data from a meta-analysis was used to set the incubation period at a median of 5 days. The infectious period duration was maintained at 10 days, and peak infectiousness was varied between 3 and 7 days (−2 and +2 days relative to the median incubation period). The overall proportion of SARS-CoV-2 was varied between 0% and 70% to assess a wide range of possible proportions.

Main Outcomes and Measures  Level of transmission of SARS-CoV-2 from presymptomatic, never symptomatic, and symptomatic individuals.

Results  The baseline assumptions for the model were that peak infectiousness occurred at the median of symptom onset and that 30% of individuals with infection never develop symptoms and are 75% as infectious as those who do develop symptoms. Combined, these baseline assumptions imply that persons with infection who never develop symptoms may account for approximately 24% of all transmission. In this base case, 59% of all transmission came from asymptomatic transmission, comprising 35% from presymptomatic individuals and 24% from individuals who never develop symptoms. Under a broad range of values for each of these assumptions, at least 50% of new SARS-CoV-2 infections was estimated to have originated from exposure to individuals with infection but without symptoms.

Conclusions and Relevance  In this decision analytical model of multiple scenarios of proportions of asymptomatic individuals with COVID-19 and infectious periods, transmission from asymptomatic individuals was estimated to account for more than half of all transmissions. In addition to identification and isolation of persons with symptomatic COVID-19, effective control of spread will require reducing the risk of transmission from people with infection who do not have symptoms. These findings suggest that measures such as wearing masks, hand hygiene, social distancing, and strategic testing of people who are not ill will be foundational to slowing the spread of COVID-19 until safe and effective vaccines are available and widely used.Introduction

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus that causes coronavirus disease 2019 (COVID-19), began to spread globally, it became apparent that the virus, unlike the closely related SARS-CoV in the 2003 outbreak, could not be contained by symptom-based screening alone. Asymptomatic and clinically mild infections were uncommon during the 2003 SARS-CoV outbreak, and there were no reported instances of transmission from persons before the onset of symptoms.¹ SARS-CoV-2 spread faster than SARS-CoV, and accumulating evidence showed that SARS-CoV-2, unlike SARS-CoV, is transmitted from persons without symptoms. However, measures to reduce transmission from individuals who do not have COVID-19 symptoms have become controversial and politicized and have likely had negative effects on the economy and many societal activities. Optimal control of COVID-19 depends on directing resources and health messaging to mitigation efforts that are most likely to prevent transmission. The relative importance of mitigation measures that prevent transmission from persons without symptoms has been disputed. Determining the proportion of SARS-CoV-2 transmission that occurs from persons without symptoms is foundational to prioritizing control practices and policies.

Transmission by persons who are infected but do not have any symptoms can arise from 2 different infection states: presymptomatic individuals (who are infectious before developing symptoms) and individuals who never experience symptoms (asymptomatic infections, which we will refer to as never symptomatic). Early modeling studies of COVID-19 case data found that the generation interval of SARS-CoV-2 was shorter than the serial interval, indicating that the average time between 1 person being infected and that person infecting someone else was shorter than the average time between 1 person developing symptoms and the person they infected developing symptoms.^2–5 This finding meant that the epidemic was growing faster than would be expected if transmission were limited to the period of illness during which individuals were symptomatic. By the time a second generation of individuals was developing symptoms, a third generation was already being infected. Epidemiological data from early in the pandemic also suggested the possibility of presymptomatic transmission,^6,7 and laboratory studies confirmed that levels of viral RNA in respiratory secretions were already high at the time of symptom onset.^8–10

Asymptomatic SARS-CoV-2 transmission also occurs because of individuals with infection who are never symptomatic (or who experience very mild or almost unrecognizable symptoms). The proportion of individuals with infection who never have apparent symptoms is difficult to quantify because it requires intensive prospective clinical sampling and symptom screening from a representative sample of individuals with and without infection. Nonetheless, evidence from household contact studies indicates that asymptomatic or very mild symptomatic infections occur,^11–14 and laboratory and epidemiological evidence suggests that individuals who never develop symptoms may be as likely as individuals with symptoms to transmit SARS-CoV-2 to others.^9,15,16

Discussion

The findings presented here complement an earlier assessment²¹ and reinforce the importance of asymptomatic transmission: across a range of plausible scenarios, at least 50% of transmission was estimated to have occurred from persons without symptoms. This overall proportion of transmission from presymptomatic and never symptomatic individuals is key to identifying mitigation measures that may be able to control SARS-CoV-2. For example, if the reproduction number (R) in a given setting is 2.0, then at least a 50% reduction in transmission is needed to drive the reproductive number below 1.0. Given that in some settings R is likely much greater than 2 and more than half of transmissions may come from individuals who are asymptomatic at the time of transmission, effective control must mitigate transmission risk from people without symptoms.Limitations

This study has limitations. First, we used a simplistic model to represent a complex phenomenon, ie, the average infectiousness of SARS-CoV-2 infections over time. We used this model deliberately to test assumptions about the timing of peak infectiousness and transmission among asymptomatic individuals so that we could vary only these 2 critical parameters and assess their relative effects. Therefore, these results lack quantitative precision, but they demonstrate the qualitative roles of these 2 components and show that across broad ranges of possible assumptions, the finding that asymptomatic transmission is a critical component of SARS-CoV-2 transmission dynamics remains constant.

As discussed here, the exact proportions of presymptomatic and never symptomatic transmission are not known. This also applies to the incubation period estimates, which are based on individual exposure and onset windows that are difficult to observe with precision and therefore include substantial uncertainty even when leveraging estimates across multiple studies. Moreover, they likely vary substantially in different populations. For example, older individuals are more likely than younger persons to experience symptoms,²⁰ so in populations of older individuals, never asymptomatic transmission may be less important. However, specific age groups are rarely exclusively isolated from other age groups, so asymptomatic transmission risk is still important in those groups and even more so in younger age groups, in which transmission may be even more dominated by asymptomatic transmission.²⁰

Real-world transmission dynamics are also not entirely dependent on the individual-level dynamics of infectiousness over time. Now that COVID-19 is widely recognized, individuals with COVID-19 symptoms are more likely to isolate themselves and further reduce the proportion of transmission from symptomatic individuals, shifting a greater proportion of transmission to those who do not have symptoms. In this sense, the estimates here represent the lower end of the proportion of asymptomatic transmission in the presence of interventions to reduce symptomatic transmission.Conclusions

Under a range of assumptions of presymptomatic transmission and transmission from individuals with infection who never develop symptoms, the model presented here estimated that more than half of transmission comes from asymptomatic individuals. In the absence of effective and widespread use of therapeutics or vaccines that can shorten or eliminate infectivity, successful control of SARS-CoV-2 cannot rely solely on identifying and isolating symptomatic cases; even if implemented effectively, this strategy would be insufficient. These findings suggest that effective control also requires reducing the risk of transmission from people with infection who do not have symptoms. Measures such as mask wearing and social distancing empower individuals to protect themselves and, if infected, to reduce risk to their communities.²¹ These measures can also be supplemented by strategic testing of people who are not ill, such as those who have exposures to known cases (eg, contact tracing) or are at high risk of exposing others (eg, congregate facility staff, those with frequent contact with the public). Multiple measures that effectively address transmission risk in the absence of symptoms are imperative to control SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has caused a global pandemics. To facilitate the detection of SARS-CoV-2 infection, various RT-LAMP assays using 19 sets of primers had been developed, but never been compared. 

We performed comparative evaluation of the 19 sets of primers using 4 RNA standards and 29 clinical samples from COVID-19 patients. Six of 15 sets of primers were firstly identified to have faster amplification when tested with four RNA standards, and were further subjected to parallel comparison with the remaining four primer sets using 29 clinical samples. Among these 10 primer sets, Set-4 had the highest positive detection rate of SARS-CoV-2 (82.8%), followed by Set-10, Set-11, and Set-13 and Set-17 (75.9%). Set-14 showed the fastest amplification speed (Tt value < 8.5 min), followed by Set-17 (Tt value < 12.5 min). Based on the overall detection performance, Set-4, Set-10, Set-11, Set-13, Set-14 and Set-17 that target Nsp3, S, S, E, N and N gene regions of SARS-CoV-2, respectively, were determined to be better than the other primer sets. Two RT-LAMP assays with the Set-4 primers in combination with any one of four other primer sets (Set-14, Set-10, Set-11, and Set-13) were recommended to be used in the COVID-19 surveillance.

Introduction

Coronavirus disease 2019 (COVID-19), caused by the newly discovered coronavirus SARS-CoV-2^1, 2, is rapidly spreading throughout the world, posing a huge challenge to global public health security. As of 20 September, 2020, it has infected over 30.6 million people, and resulted in at least 950,000 deaths globally. In the absence of effective antiviral drugs or efficacious vaccines, early diagnosis of SARS-CoV-2 infection is essential for the containment of COVID-19^3,4, without which it is impossible to timely implement intervention and quarantine measures, and difficult to track contacts in order to limit virus spread.

Nucleic acid testing of various approaches are widely used as the primary tool for diagnosing COVID-19^3,4. Among them, reverse transcription quantitative PCR (RT-qPCR) methods have been set as the gold standard for laboratory confirmation of SARS-CoV-2 infection because of their proven track record as being the most robust technology in molecular diagnostics^4,5,6. However, the RT-qPCR assay relies on sophisticated facilities with reliable supply of electricity and well-trained personnel in large general hospitals and health care facilities, or government labs (such as CDC), and it is relatively time-consuming (about 1.5–2 h). These limit its capacity in point-of-care settings. Moreover, visiting a clinical setting for testing increases the risk of spreading the virus. Therefore, an alternative, fast, simple, and sensitive point-of-care testing (POCT) is highly needed to facilitate the detection of SARS-CoV-2 infection in resource-limited settings^3,7.

Loop-mediated isothermal amplification (LAMP) is a promising POCT method with high sensitivity, specificity, and rapidity, and it is easy-to-use⁸. To overcome the limitation of RT-qPCR assay, a number of RT-LAMP assays using at least 19 sets of different primers had been developed in the last few months for the detection of SARS-CoV-2^{9,10,11,12,13,14,15,16,17,18,19}. Although these assays had proven sensitive and effective for the detection of SARS-CoV-2, how do they compare with each other have not been evaluated. In this study, we compared all 19 sets of SARS-CoV-2-specific RT-LAMP primers using the mismatch-tolerant LAMP system that is faster and more sensitive than the conventional ones^20,21, and screened the high-efficiency RT-LAMP assays for use in the detection of SARS-CoV-2.

Discussion

SARS-CoV-2 transmission mainly occurs in the early and progressive stages of COVID-19 disease during which the patients and virus carriers have higher viral load than that in recovery stage^22,23,24, and are generally more infectious. To contain the spread of the virus, early diagnosis is essential^3,4. It helps to trigger timely intervention (e.g. quarantine, lockdown, and contact tracing), and facilitates to optimize clinical management. It is clear that serological assays are not suitable for this purpose, because detectable antibodies always appear several days after infection. Therefore, viral RNA testing is the primary method for early diagnosis of COVID-19. Despite being the most robust diagnostic tests, RT-qPCR-based assays are more centralized in core facilities, and they are not amenable for large-scale monitoring for asymptomatic and pre-symptomatic virus carriers in point-of-care settings (e.g. community and home). Therefore, community- and/or home-based nucleic acid assays that allow individuals to test in the community, at home, or other point-of-care sites without having to visit hospitals are convenient tools for the detection of SARS-CoV-2 infection by the general public^3,7.

RT-LAMP assays are such needed tools^8,20,21. In fact, various LAMP assays have been developed that included at least 19 sets of primers targeting to different genomic regions of SARS-CoV-2, with reported high detection sensitivity ranging from 1 to 1200 copies per 25 µL reaction^{9,10,11,12,13,14,15,16,17,18,19}. However, these primers are never formally evaluated with clinical samples. The sensitivity and performance of a RT-LAMP assay are mainly determined by the primers, because other components of the reaction system are optimized and stable. Therefore, assessing the optimal RT-LAMP primer sets for the detection of SARS-CoV-2 infection is important for the selection of the best assay format to use for large field screening of COVID-19 patients.

Recently, the reaction system of RT-LAMP was further optimized to have higher sensitivity and faster amplification speed, even allowing the presence of few mismatched bases between primer and templates in a mismatch-tolerant version^20,21. The new optimized reaction system containing an additional 0.15 U of high-fidelity DNA polymerase is called as mismatch-tolerant LAMP. The inclusion of an additional amount of high-fidelity DNA polymerase makes it a higher applicability to highly variable viruses, and a 10–15 min faster reaction speed than the conventional LAMP method. Using this new version, we assessed 19 sets of SARS-CoV-2 RT-LAMP primers. Six sets of primers showing faster amplification speed were firstly selected from 15 sets of primers using 4 RNA standards, and then tested with other 4 primer sets using 41 clinical samples. Eight sets of primers showed either comparable or better performance than the other 2 sets of primers (Set-1 and Set-18) as determined by positive detection rate. Of the 8 sets of primers, six were further selected based on high positive detection rate and/or overall faster amplification speed (with mean Tt value less than 13 min). The six primer sets are Set-4, Set-10, Set-11, Set-13, Set-14 and Set-17 that correspond to Nsp3, S, S, E, N, and N genes of SARS-CoV-2, respectively.

Among selected assays, the N gene-based RT-LAMP assays (Set-14 and Set-17) had the fastest amplification speed, followed by Orf, S and E gene-based assay (Set-4, Set-10, Set-11 and Set-13). This result suggested that the N gene-based RT-LAMP assay was more sensitive in detecting SARS-CoV-2 than that based on other genes, consisting with results of RT-qPCR assays⁵. In this study, Set-4 had the highest positive detection rates than all other primer sets, and had a LOD of 3 copies per 25 µL reaction, obviously more sensitive than the previously reported sensitivity of more than 100 copies per 25 µL reaction (Table 1 and Fig. 4)^12,14. The sensitivity of Set-4 was comparable with highly sensitive primer sets Set-13 and Set-14 (less than 3 copies per 25 µL reaction)^16,17. In addition, the sensitivity of primer Set-11 was less than 50 copies per 25 µL reaction (data not shown), obviously low 200 copies/25 µL reaction reported in previous study¹². These indicated the mismatch-tolerant method significantly improved the detection sensitivity of RT-LAMP²⁰. In addition, two of our previously reported primers, Set-8 and Set-18, exhibited high sensitivities of 3–20 copies per 25 µL reaction and good performance in the detection of clinical samples under the mismatch-tolerant reaction condition^9,10, but they did not show better performance than other nine primer sets in this study. A reason might be that the use of the mismatch-tolerant reaction system generally improved the amplification efficiency of the primers reported by other groups²⁰.

The analyzed primer sets showed high specificity in that they did not amplify any SARS-CoV-2 negative clinical samples. Sequence alignment analyses further supported that the six sets of optimal primers had good specificity to SARS-CoV-2, albeit they might generate non-specific amplification for SARS-CoV due to a high degree of sequence identity. However, given the lethal nature of both SARS-CoV-2 and SARS-CoV²⁵, a non-specific positive result for SARS-CoV might also be of clinical importance.

Two nucleic acid assays targeting to different genes are suggested to be used in the detection of SARS-CoV-2 to avoid potential false-negative results⁵. Based on comparable performances, any two of the six optimal primer sets (Set-4, Set-10, Set-11, Set-13, Set-14 and Set-17) were recommend to be used in the detection of SARS-CoV-2. However, simultaneous use of Set-10 and Set-11, or Set-14 and Set-17 should be avoided because the former two sets target to the same S gene and the latter two sets target to the same N gene. In addition, because of highest positive detection rate and high sensitivity, Set-4 was strongly encouraged to be preferentially selected for the diagnosis of COVID-19 patients. Apart from the six recommend primer sets, other primers such as Set-2 and Set-5 also had good performance, and can also be used in the monitoring of COVID-19 infections.

Another advantage of our version of the RT-LAMP assay is that the results are easily visualized with a pH-sensitive indicator dye (e.g. cresol red and neutral red)²⁶. Moreover, a combination of a nucleic acid extraction-free protocol and a master RT-LAMP mix containing all reagents (enzymes, primers, magnesium, nucleotides, dye and additives), except the template, enables the development of a simple kit that can be used at home, or a community-based diagnosis center for the detection of COVID-19 infection^3,27.

In summary, we evaluated and selected six optimal primer sets from 19 sets of SARS-CoV-2 RT-LAMP primers through a comparative evaluation with clinical RNA samples from COVID-19 patients. Two RT-LAMP assays with the Set-4 primers and any one of the other four primer sets (Set-10, Set-11, Set-13 and Set-14) were recommended to be used in the COVID-19 surveillance to facilitate the early finding of asymptomatic and pre-symptomatic virus carriers in clinical and point-of-care settings, and the monitoring of environmental samples in the field.

Lateral flow devices for asymptomatic mass testing are proving controversial. At the heart of the matter is a flawed process, with the decision to implement society-wide “Moonshot” testing made before robust field evaluations of the tests were completed. Subsequent selective emphasis of unrealistic performance estimates has caused confusion. Little surprise we are now in a mess.

Tests have to be fit for the purpose to which they are put. Innova lateral flow assays for repeat asymptomatic testing are being distributed to care homes, universities, NHS staff, public health teams, and now schools. Ministers and other proponents have stated that negative results will show who is free from infection.456 The tests appeal because they are cheap, do not need a laboratory, give results in 30 minutes, and are easy to distribute. But their performance as a “test to enable” is lacking.

The government commissioned the University of Oxford and Public Health England’s Porton Down laboratory to evaluate rapid tests for covid-19, including Innova’s.7 The two relevant field studies recruited people from NHS test and trace centres, mainly those with symptoms. Detection rates (sensitivity) were 73% (95% confidence interval 64% to 85%) when tested by skilled NIHR research nurses and 79% (73% to 85%) when tested by Porton Down laboratory scientists.89 But testing by test centre employees (following written instructions) achieved sensitivity of just 58% (52% to 63%). This is important, because it is closest to the circumstances for staff, student, visitor, and community testing.

Government announcements have described sensitivity as “high,” quoting detection rates of “76.8%”3 or “nearly 80%,”10 obtained by pooling results from two groups of highly experienced staff and excluding test centre staff. When questioned, the secretary of state for health said he “was not familiar” with the 58% figure.11 The government press release announcing the results of the evaluation says that over 95% of cases with high viral loads were detected, although it confusingly also includes a statement that all were detected.3

Preliminary data from mass screening of largely asymptomatic people shows even lower sensitivity. Tucked into annex B of a government guide to community testing12 is the statement: “In the field evaluation in Liverpool, compared to PCR tests, these tests picked up 5 out of 10 of the cases PCR detected and more than 7 out of 10 cases with higher viral loads, who are likely to be the most infectious.”

If a test misses 50% of infections, people with a negative result are not in the clear—their chances of active infection are simply half what they were before the test. Nobody can be considered free of risk of transmitting infection. Failing to identify 30% of people with high viral loads is six times worse than the almost 5% missed in the Porton Down/Oxford evaluation, and of particular concern.

Allowing half of infected people, and one third of those with high viral loads, to unwittingly take the virus into hospitals, family homes, and care homes will not reduce the spread of the infection and could put lives at risk. Diligent maintenance of social distancing, personal protection, and other infection prevention control measures remains vital for people with a negative result.

Uncertainties remain about who is actually infectious. “High viral load” has wrongly become synonymous with “infectious,” with tests being described equally wrongly as tests of infectiousness. Both scientists and politicians have used this wording, with the prime minister stating that lateral flow tests would “identify people who are infectious … allowing those who are not infectious to continue as normal.”5

The assumption that people with a negative lateral flow test cannot be infectious, is also embedded in a key simulation model used to promote mass testing.13 It’s still unclear how viral load and ease of viral culture from people with PCR positive results relate to level of infectivity. Although evidence suggests that virus can be more easily cultured from people with higher viral loads,14 it can also be cultured from people with lower viral loads.15 Also, detected viral load varies according to how much biological material is caught on a swab,16 and it is not yet clear whether SARS-CoV-2 can be spread when virus cannot be cultured at all.

Innova’s poor sensitivity in asymptomatic people in field settings should have been expected. The largest and most realistic study within the Porton Down/Oxford evaluation (of tests done by test centre employees) reported only a 58% detection rate, even in mainly symptomatic people. Innova recommends use of the test only in people with symptoms and states: “Negative results do not rule out SARS-CoV-2 infection and should not be used as the sole basis for treatment or patient management decisions, including infection control decisions.”17 The World Health Organization says negative antigen rapid diagnostic test results “should not remove a contact from quarantine requirements.” 18

Whatever decision making process the UK government used, it ignored key evidence and dismissed expert international advice. The result is a considerable burden on care home staff, universities, NHS staff, public health teams, and schools, with minimal additional safety compared with existing risk mitigation measures. Asymptomatic lateral flow testing is an unhelpful diversion from the important task of vaccination rollout.19