CFNT: Cell Fluorescence Neutralization Test is a testing method that measures the level of neutralizing antibodies against specific serotypes of Dengue virus (DENV) in the serum of test subjects. The commonly used test for quantifying pre-existing neutralizing antibodies is the Plaque Reduction Neutralization Test (PRNT). However, one of its drawbacks is that it is labor-intensive and not suitable for high throughput, making it unsuitable for large-scale surveillance and vaccine trials []. Furthermore, PRNT requires the use of actual DENV (BSL2), which must be conducted in a certified laboratory, and experimenters are exposed to risks []. Therefore, we developed the safe and high-throughput neutralization test CFNT, taking inspiration from research conducted by Dr. Suzuki at the National Institute of Infectious Diseases [].

CFNT uses DENV-like Single-round Infectious Particles (SRIP) (BSL1) instead of actual DENV. This ensures the safety of experimenters. It employs infection-detecting cells that express infection using two types of fluorescence on a multi-well plate, resulting in high throughput. We will now detail the production of SRIP, the behavior of infection-detecting cells, and the procedure for the actual neutralization test.

SRIP Production

First, let me explain the production of SRIP. Our SRIP, similar to DENV, is produced using human embryonic kidney-derived HEK293T cells. Its genome encodes the C-terminal fragment of Cre recombinase, which induces the fluorescence switching of infection-detecting cells, C-Cre gene [].

The reason SRIP is single-cycle infectious lies in the fact that the SRIP genome is derived from a virus genome with structural protein deletions. In other words, even if SRIP infects a cell, it cannot replicate internally, leading to its single-cycle infectivity.

The SRIP we produce is based on the Yellow Fever Virus (YFV), which belongs to the same Flaviviridae family as DENV []. A illustrates the entire process of SRIP production(A). Firstly, the Flaviviridae genome, as represented in the Degue/Yellow Fever Virus Genome inA, can be broadly divided into structural protein and non-structural protein regions []. SRIP's genome is a version lacking the structural protein region. Therefore, to produce SRIP, we need to simultaneously and separately produce the YFV capsid protein, DENV's precursor membrane and envelope protein (prME), and SRIP's genome. InA, linearized pCAG YF-C produces the YFV capsid protein, pCAG D1-YG1-prME or pCMV-prME (DENV-2/3/4) produces the respective DENV prME protein for each serotype, and pCMV YF-C-Cre-rep produces YFV's non-structural proteins (essential for SRIP formation) and the SRIP genome. When the structural proteins and genome of SRIP are produced, SRIP is assembled within HEK293T cells and released into the extracellular environment.

B shows the structure of SRIP, with the outermost protein corresponding to the prME of each DENV serotype, which acts as an epitope(B). In other words, SRIP can be used as a light source corresponding to each DENV serotype. On the other hand, the internal part of SRIP consists of YFV's envelope and a ssRNA(+) genome with a deleted structural protein. Additionally, the SRIP genome encodes the C-Cre gene, which has a nuclear localization signal (: NLS), instead of the structural protein.

Fig. 0 |

A: The Production of SRIP The production of Sigle-round Infectious Particles is performed by HEK293T cells. First, yellow fever virus capsid, dengue virus precursor membrane and envelope protein (: prME) are produced in the cells. Then, these structural proteins assemble with the ssRNA(+) yellow fever virus genome, which lacks structural proteins and in which the C-Cre gene is inserted. Capsid is produced from pCAG YF-C and prME from pCAG D1-YG1-prME or pCMV-prME. However, pCAG D1-YG1-prME produces prME from DENV1 and pCMV-prME from DENV2, 3 and 4, respectively. These plasmids are linearized and co-transfected into HEK293T cells.
B: Single-round infectious particle (SRIP) SRIP, which mimics real DENV, has prMEs corresponding to each DENV serotype. The capsid is also derived from yellow fever virus. The SRIP genome is ssRNA (+), which means that the structural protein gene is missing from the yellow fever virus genome and the C-Cre gene has been inserted. Therefore, SRIP is not replication competent.

Infection Detecting Cells

Next, let me explain the behavior of infection-detecting cells. Infection-detecting cells typically produce green fluorescent protein EGFP, but in response to SRIP infection, they start producing red fluorescent protein mCherry. This switch is mediated by the assembly of two split Cre recombinase units: split Cre [], which triggers Cre-Lox Recombination().

Firstly, the infection-detecting cells possess a genetic circuit in their genome, as shown in the figure, from the CMV Promoter, loxP sequence, NLS+N-Cre gene, IRES sequence, EGFP gene, loxP sequence, mCherry gene, polyA signal, Neo^R/Kan^R gene. Therefore, transcription usually occurs from the Promoter to the polyA signal, leading to the translation of NLS+N-Cre (N-terminal fragment of Cre recombinase) primarily from the 5'-cap and EGFP from IRES (please note that mCherry is not produced at this stage). Consequently, infection-detecting cells exhibit green fluorescence when not infected by SRIP. However, when SRIP infects the cell, the SRIP genome is translated into the cytoplasm, resulting in the production of C-Cre. Both N-Cre and C-Cre carry NLS, enabling them to localize in the nucleus and function as Cre recombinase by coming together. This means they recognize the loxP sequences in the infection-detecting cell's genome and initiate Cre-Lox Recombination. As a result of this recombination, NLS+N-Cre gene, IRES sequence, and EGFP gene are entirely lost, and the genes below the CMV Promoter become loxP sequence, mCherry gene, Neo^R/Kan^R gene. This allows the transcription and translation of the mCherry gene.

Therefore, the infection-detecting cells switch from producing green fluorescent protein to red fluorescent protein in response to SRIP infection through the mechanism described above.

Fig. 0 |

Infection Detecting Cell Infection detecting cells have two states: green fluorescence and red fluorescence. Normal infection detecting cells produce N-Cre and the green fluorescent protein EGFP. However, when SRIP infects infection detecting cells, C-Cre is produced intracellularly, and since N-Cre and C-Cre have NLS, they associate in the nucleus to form Cre recombinase. It recognizes loxP sequences in the infection detecting cell genome and converts Cre-Lox recombination. This homologous recombination causes the infection detecting cells to switch from production of N-Cre and EGFP to production of the red fluorescent protein mCherry.

The Mechanism of Cre-Lox Recombination

Neutralization Test

CFNT (Cell Fusion Neutralization Test) quantify the neutralizing antibodies against DENV (Dengue virus) in the serum of subjects, using the two components explained earlier: SRIP and infection-detecting cells. The neutralizing antibody titer is determined by the dilution factor of the subject's serum that can prevent SRIP infection.

First, the mechanism of the neutralization assay is based on the principle that when SRIP is neutralized by neutralizing antibodies in the subject's serum, the infection-detecting cells emit green fluorescence, while if it is not neutralized, they emit red fluorescence (). This test is performed by creating a dilution series of the subject's serum. Initially, the serum is diluted and mixed with SRIP of each serotype, and the mixture is incubated for approximately 2 hours(). During this time, SRIP and, if present, the neutralizing antibodies in the serum, undergo antigen-antibody reactions to neutralize SRIP. Next, the mixture of these serum dilution series and SRIP is added to infection-detecting cells cultured in a 96-well plate, and they are incubated for 1-3 days.

As a result, based on the infection and neutralization status of SRIP, both green and red fluorescence become visible. Therefore, by quantifying the ratio of the two fluorescence intensities, it becomes possible to determine whether the infection-detecting cells in that well have been infected by SRIP or, in other words, whether there were sufficient neutralizing antibodies in the serum(). The reciprocal of the lowest serum dilution at which SRIP infection can be prevented is defined as the neutralizing antibody titer [].

Considering the fluorescence patterns in the figure, it can be observed that the DENV1 serotype has relatively high neutralizing antibody titers, while other serotypes exhibit lower neutralizing antibody titers. However, for serotype 3, there seems to be some cross-reactivity with serotype 1.

Fig. 0 |

The Mechanism of Neutralization Test Neutralization test using infection detecting cells and SRIP is performed by detecting neutralizing antibodies in the subject's serum. The collected subject serum is mixed with SRIP and inoculated into the infection-detecting cells. SRIP prevents infection of the infection detecting cells if there are sufficient neutralizing antibodies in the subject serum, and the event is detected as green fluorescence. On the other hand, if there are not enough neutralizing antibodies in the subject's serum, SRIP will infect the infection detecting cells and the event will be detected as red fluorescence.

Fig. 0 |

Serum Dilution Series and SRIP mix adding to Infection Detecting Cell The subjects' serum are prepared in dilution series and mixed with SRIP of the respective serotypes. The mixture is then added to the Infection Detecting Cell. Initially, the cells fluoresce green, but when infected with SRIP, they fluoresce red.

Fig. 0 |

Infection Detecting Cell (Green and Red Fluorescence) The ratio of green to red fluorescence emitted by infection-detecting cells depends on the amount of neutralizing antibodies in the subject's serum.



3D-PCR is a testing method used to detect DENV (Dengue virus) genomes in the serum of subjects, distinguishing them by serotype. Existing methods for detecting DENV in serum include antigen tests and RT-qPCR, but these methods are known for their low accuracy and high costs, making them less suitable for accurate and cost-effective surveillance on a broad scale.

Therefore, we conducted a meeting with Professor Matsumoto from the Tokyo Institute of Technology. Based on Professor Matsumoto's advice, we decided to focus on improving the high-accuracy but cost-prohibitive RT-qPCR method and undertook the validation of the innovative 3D-PCR approach.

This method is primarily conducted on 960 samples, a task that would typically require RT-qPCR for all 960 samples. However, with 3D-PCR, we can identify potential positive cases using just 30+α samples through an innovative approach. The process involves the three-dimensional pooling of the 960 collected samples, resulting in 30 combined samples. These combined samples are then subjected to PCR to identify potential positive cases. Only these candidates undergo retesting. This approach significantly reduces testing time and costs.

In summary, 3D-PCR is a high-accuracy, cost-effective method for detecting DENV genomes in a large number of samples, allowing for efficient and accurate surveillance. For more detailed information, please refer to the Proof of Concept page.

How to do 3D-PCR

Sample Collection and Plate Preparation: Serum samples are collected from the 960 individuals and distributed into 96-well plates, with a total of 10 plates being used.

Three-Dimensional Pooling: The samples from each well of each plate are combined in three dimensions, accounting for the x, y, and z axes. This results in the creation of a single tube for each combination of x, y, and z coordinates, generating a total of 30 combined samples, denoted as M^x_1, M^x_2, …, M^x_12, M^y_1, M^y_2, …, M^y_8, M^z_1, M^z_2, …, M^z_10().

RNA Extraction and RT-qPCR: RNA is extracted from each of these combined samples, followed by RT-qPCR for each of the four DENV serotypes. The identification of positive samples via RT-qPCR indicates the presence of DENV in the samples, suggesting the existence of positive individuals within the same well plate.

Positive Candidate Determination: Positive individuals are found at the intersections of multiple well plates that tested positive. These intersections among the M^x, M^y, and M^z samples become regions for positive candidate identification. Subsequent retesting is conducted on these candidate samples to pinpoint the specific positive individuals.

This method enables the efficient identification of positive individuals within a large cohort, resulting in significant reductions in testing time and costs. For specific examples, please refer to Example1 and Example2 provided at the bottom of the page.

Fig. 0 |

How to mix Samples
A: Mixing samples by aspect
3D-PCR combines subject sera in each plane in the x-, y-, and z-axis directions.
B: 30 Samples mixed by aspects
The number of subject sera collected for each plane in the x-, y-, and z-axis directions will eventually reach 30, denoted M^x_i (i = 1, 2, ..., 12), M^y_j (j = 1, 2, ..., 8), and M^z_k (k = 1, 2, ..., 10), respectively.


In this example, let's assume that out of the 30 combined samples, M^x_4, M^y_7, and M^z_3 tested positive(). This implies that the intersection of planes x=4, y=7, and z=3 corresponds to a positive candidate. There is only one such point, which is (4, 7, 3). Therefore, there is only one positive case at the coordinates (4, 7, 3).

Fig. 0 |

Example 1
If M^x_4, M^y_7 and M^z_3 are positive in 30 Mixed sample, the positive well is (4, 7, 3).


In this scenario, let's assume that out of the 30 combined samples, M^x_4, M^x_8, M^y_4, M^y_7, M^z_3, and M^z_7 tested positive(). This means that the intersections of planes x=4, x=8, y=4, y=7, z=3, and z=7 represent positive candidate regions. There are eight such points: (4, 4, 3), (4, 4, 7), (4, 7, 3), (4, 7, 7), (8, 4, 3), (8, 4, 7), (8, 7, 3), and (8, 7, 7).

Consequently, there are eight potential positive cases, and these candidates undergo retesting. If, for instance, (4, 4, 3) and (8, 7, 3) test positive upon retesting, this would mean that two individuals are confirmed as positive().

Fig. 0 |

Example 2 Step 1
If M^x_4, M^x_8, M^y_4, M^y_7, M^z_3, and M^z_7 are positive in 30 Mixed sample, the positive candidates are (4, 4, 3), (4, 4, 7), (4, 7, 3), (4, 7, 7), (8, 4, 3), (8, 4, 7), (8, 7, 3), (8, 7, 7).

Fig. 0 |

Example 2 Step 2
Truly positive subjects (4, 4, 3), (8, 7, 3) can be identified by retesting these eight positive candidates, (4, 4, 3), (4, 4, 7), (4, 7, 3), (4, 7, 7), (8, 4, 3), (8, 4, 7), (8, 7, 3), (8, 7, 7).


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