LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection.

The diagnosis of celiac disease (CD) is currently based on serology and intestinal biopsy, with detection of anti-tissue transglutaminase (tTG) IgA antibodies recommended as the first-line test. Emphasizing the increasing importance of serological testing, new guidelines and evidence suggest basing the diagnosis solely on serology without confirmatory biopsy. Enzyme immunoassays (EIAs) are the established approach for anti-tTG antibody detection, with the existing point-of-care (POC) tests lacking sensitivity and/or specificity. Improved POC methods could help reduce the underdiagnosis and diagnostic delay of CD. We have previously developed rapid homogenous immunoassays based on time-resolved Förster resonance energy transfer (TR-FRET), and demonstrated their suitability in serodiagnostics with hanta- and Zika virus infections as models. In this study, we set out to establish a protein L -based TR-FRET assay (LFRET) for the detection of anti-tTG antibodies. We studied 74 patients with biopsy-confirmed CD and 70 healthy controls, with 1) the new tTG-LFRET assay, and for reference 2) a well-established EIA and 3) an existing commercial POC test. IgG depletion was employed to differentiate between anti-tTG IgA and IgG positivity. The sensitivity and specificity of the first-generation tTG-LFRET POC assay in detection of CD were 87.8% and 94.3%, respectively, in line with those of the reference POC test. The sensitivity and specificity of EIA were 95.9% and 91.9%, respectively. This study demonstrates the applicability of LFRET to serological diagnosis of autoimmune diseases in general and of CD in particular.

Introduction

The diagnosis of celiac disease (CD) is conventionally based on the combination of serology and duodenal biopsy, with detection of IgA anti-tTG antibodies recommended as the first-line test [1-3]. Total IgA is measured to avoid false negative results in patients with IgA deficiency [1-4]. Other serological markers of CD include antibodies against endomysium antigen (EMA) and deamidated gliadin peptides (DGP), however, somewhat laborious measuring techniques and subjective interpretation (EMA) or weaker specificity (DGP) hampers their use in diagnostics. Additionally, HLA (human leukocyte antigen) testing may aid in ruling out CD, as almost all patients with CD display HLA-DQ2.5 or -DQ8 [5]. Emphasizing the increasing importance of serology, European guidelines allow the diagnosis of symptomatic children to be based on serological markers only [4]. In fact, recent evidence suggests that serological diagnosis would suffice for adults and asymptomatic children [6, 7].

Enzyme immunoassays (EIA) and point-of-care (POC) tests serve as detection methods for anti-tTG antibodies. EIA, with its high sensitivity and specificity, is the most widespread method. However, it requires dedicated laboratory infrastructure, and the results are available at best within some hours. The majority of POC diagnostics is performed using lateral flow assays (LFA), which unlike EIA are rapid but suffer from lower sensitivity (91% vs. 94%, respectively) and specificity (95% vs. 97%, respectively) in detecting biopsy-confirmed CD [8, 9]. Lacking quantitation, the existing anti-tTG IgA POC tests cannot replace EIAs in the diagnostic algorithm of CD as per the European Society for Paediatric Gastroenterology Hepatology and Nutrition (ESPGHAN) [4]. Also, from the follow-up perspective, a quantitative result would be desirable.

Better POC tests could lower the testing threshold and help reduce the diagnostic delay and underdiagnosis of CD. It is estimated that 83–90% of CD patients remain undiagnosed [10], having a markedly reduced quality of life as compared to those diagnosed and treated [11]. Moreover, delayed diagnosis [12, 13] is associated with persistent symptoms [14] leading to increased use of healthcare services, and a decreased quality of life even after the diagnosis and treatment [15].

TR-FRET (time-resolved Förster resonance energy transfer) is a phenomenon occurring when two fluorophores, donor and acceptor, are in close proximity. Excitation of the donor leads to energy transfer to the acceptor, which then emits the energy at a characteristic wavelength. The TR-FRET efficiency depends inversely on the distance between the two fluorophores. Background autofluorescence is minimized by time-resolved measurement, enabled by chelated lanthanide fluorophores with a long fluorescence half-life. TR-FRET has been employed widely in research and diagnosis to investigate e.g. protein-protein interactions and disease markers [16].

We have previously developed a rapid wash-free TR-FRET -based method for antibody detection, termed protein L FRET assay (LFRET) [17]. LFRET employs a donor-labeled antigen, and an acceptor-labeled protein L that binds the kappa (κ) light chains of all immunoglobulin classes. If the clinical sample contains antibodies against the antigen, they will bring the fluorophores to close proximity. Thus, the TR-FRET signal tells that the sample contains the antibodies of interest. The LFRET signal can be measured without additional steps shortly after combining the sample with the reagent mix, allowing for rapid point-of-care diagnosis. We have provided proof-of-concept for the LFRET assay in serodiagnostics using hanta- and Zika virus infections as models [18, 19].

To achieve a test quicker than EIA and with a higher diagnostic utility compared to LFA, and to demonstrate the applicability of the LFRET approach to autoimmune diagnosis, we set out to establish an LFRET assay for the detection of IgA-class anti-tTG antibodies. Using a panel of serum/plasma samples from patients with biopsy-confirmed CD and healthy controls, we herein demonstrate that tTG-LFRET can indeed be utilized in serological diagnosis of CD with a performance comparable to existing POC tests.

Materials and methods

Samples

The study included serum and/or plasma samples of 74 Finnish patients, 43 children and 31 adults, with CD confirmed by a duodenal biopsy showing villous atrophy and crypt hyperplasia corresponding to Marsh classes 3A-C. HLA-DQ2.5 and -DQ8 molecules, encoded by the HLA-DQA1 and DQB1 alleles, were analyzed as described [20, 21]. DQ2.5, DQ8 or both were positive for 59, 5 and 4 patients, respectively. With 6 individuals, the HLA status was not analyzed.

The control group comprised serum and/or plasma samples from 70 healthy individuals, including 47 children and 23 adults. DQ2.5, DQ8 or both were positive for 34, 31 and 4 individuals, respectively.

The study was approved by the Ethics Committee of Kuopio University Hospital and written informed consent was obtained from all subjects (from parents/guardians of all children and the children themselves, if >10 years of age).

Proteins

Recombinant protein L (Thermo Scientific) was labeled with Alexa Fluor 647 (AF) to yield AF-labeled protein L (AF-L), as described [18]. Europium-labeled tTG (Eu-tTG) was generated by labeling baculovirus/Sf9-expressed tTG (Diarect AG) with QuickAllAssay Eu-chelated protein labeling kit (BN Products and Services) according to the manufacturer’s instructions. IgG-free bovine serum albumin (BSA) used in LFRET assay was from Jackson ImmunoResearch Inc.

tTG-LFRET assay

The LFRET assay principle has been described previously [17, 18], and is illustrated in Fig 1. Unlike in those papers, the results here are given as averages of normalized TR-FRET signal values, not divided by the TR-FRET signal of the negative control. To establish an LFRET assay for anti-tTG antibodies the concentrations of assay components were optimized by cross-titration, using panels of 5 to 15 samples shown anti-tTG-IgA positive or negative by FEIA (fluorescent enzyme immunoassay). The optimal on-plate serum dilution was found to be 1/100, and the optimal on-plate concentrations for AF-L and Eu-tTG, 250 nM and 5 nM, respectively. To determine the incubation time, measurements were done at 0, 7, 15, 22, 30, 45, 60 and 90 minutes after mixing the reagents. TR-FRET signals were measured with Wallac Victor2 fluorometer (PerkinElmer) and normalized as described previously [22].

Fig 1

Simplified protocol for tissue transglutaminase protein L TR-FRET assay.

Eu-tTG = Europium-labeled tissue transglutaminase, AF-L = Alexa Fluor™ 647 -labeled protein L; TR-FRET = time-resolved Förster resonance energy transfer; RT = room temperature. We used TBS-BSA (50mM Tris-HCl, 150mM NaCl, pH 7.4, 0.2% BSA) for all component dilutions. On-plate serum dilution was 1/100 and reagent concentrations were 250 nM for AF-L and 5 nM for Eu-tTG. For further details, see the previous publication [18].

IgG depletion

To distinguish between anti-tTG IgA- and IgG-class antibodies, GullSORB (Meridian Bioscience, Inc.) was used to deplete the samples of IgG, as described [18]. All samples were studied by tTG-LFRET with and without IgG depletion.

Reference methods and statistical analyses

The tTG IgA reference test was EliA Celikey IgA (Thermo Scientific, Phadia GmbH), a FEIA used widely by clinical laboratories. Total IgA was measured with an accredited in-house method of HUSLAB (Hospital District of Helsinki and Uusimaa, Laboratory Services, Finland). If the total IgA measurement was indicative of selective IgA deficiency, tTG IgG was measured by EliA Celikey IgG (Thermo Scientific, Phadia GmbH).

A commercial rapid lateral flow test (Celiac Disease Quick Test, Biohit) for anti-tTG antibodies performed according to the manufacturer’s instructions was used as an additional reference.

All statistical analyses were performed with R version 3.5.1.

Results

tTG-LFRET incubation time, cutoff values and performance

An LFRET assay for detection of anti-tTG antibodies (tTG-LFRET) was set up using recombinant Eu-labeled tTG antigen and AF-labeled protein L. The assay conditions were first optimized utilizing 15 selected samples (included in the 144-sample panel) known to be negative (n = 7) or positive (n = 8) for IgA-class anti-tTG antibodies. Then, using the optimized conditions, all 144 samples were tested with tTG-LFRET. While most of the CD patient samples were anti-tTG positive already in the first TR-FRET measurement immediately after mixing the reagents, the best balance between sensitivity, specificity and incubation time was obtained at 22 minutes’ assay time (S1 Fig and S1 Table).

To determine the assay cutoff we measured the tTG-LFRET signals for 67 tTG-antibody negative samples, and set the LFRET cutoff at mean plus two standard deviations (SD) (35.438 + 2 × 5.316 = 46.07 counts).

We then assessed the diagnostic performance of the tTG-LFRET assay by analyzing altogether 144 serum/plasma samples from 74 CD patients and 70 healthy controls with HLA-associated genetic risk for CD. The sensitivity and specificity of tTG-LFRET in detection of biopsy-proven CD were 87.8% (65/74) and 94.3% (66/70), respectively (Table 1).

Table 1

Sensitivity and specificity of LFRET, FEIA and LFA by age group and altogether.

	Group	Subjects	TP	FP	TN	FN	Sensitivity	Specificity
tTG-LFRET	Children	90	43	3	44	0	100.0%	93.6%
	Adults	54	22	1	22	9	71.0%	95.7%
	Total	144	65	4	66	9	87.8%	94.3%
FEIA	Children	90	43	6	41	0	100.0%	87.2%
	Adults	54	28	0	23	3	90.3%	100.0%
	Total	144	71	6	64	3	95.9%	91.4%
LFA	Children	90	43	3	44	0	100.0%	93.6%
	Adults	54	22	1	22	9	71.0%	95.7%
	Total	144	65	4	66	9	87.8%	94.3%

TP = true positive, FP = false positive, TN = true negative, FN = false negative. tTG-LFRET = tissue transglutaminase protein L–based Förster resonance energy transfer assay. FEIA = fluorescent enzyme immunoassay (Phadia EliA Celikey IgA). LFA = Lateral flow assay (Biohit Celiac Disease Quick Test).

Comparison of tTG-LFRET with FEIA and lateral flow

To compare tTG-LFRET performance with existing assays, we analyzed the above described sample panel using anti-tTG IgA FEIA and a commercial anti-tTG lateral flow assay. By applying the manufacturer-defined cutoffs and considering equivocal results as positive, the sensitivity of anti-tTG FEIA in detection of CD was 95.9% (71/74) and the specificity was 91.4% (64/70) (Table 1). The respective values for the commercial lateral flow assay were 87.8% (65/74) and 94.3% (66/70). The samples incorrectly identified by any of the methods have been listed in Table 2.

Table 2

Samples identified incorrectly by any of the methods used.

Sample	Group	CD status	LFRET (counts, mean of duplicates ± SD)	FEIA (U/ml)	LFA	Incorrectly identified by
1	Children	+	42 ± 8.1	12	+	LFRET
2	Adults	+	35 ± 6.1	1.4	-	LFRET, FEIA, LFA
3	Adults	+	35 ± 3.8	13	+	LFRET
4	Adults	+	36 ± 9.8	20	+	LFRET
5	Adults	+	41 ± 9.6	15	+	LFRET
6	Adults	+	43 ± 5.5	6.3	-	LFRET, FEIA, LFA
7	Adults	+	46 ± 1.7	15	-	LFA
8	Adults	+	37 ± 4.3	20	+	LFRET
9	Adults	+	34 ± 2.3	1	-	LFRET, FEIA, LFA
10	Adults	+	46 ± 1.1	13	-	LFA
11	Adults	+	48 ± 12.5	14	-	LFA
12	Adults	+	54 ± 4.6	33	-	LFA
13	Adults	+	43 ± 0.9	15	-	LFRET, LFA
14	Adults	+	42 ± 1.1	10	-	LFRET, LFA
15	Children	-	39 ± 5.3	10	-	LFRET, LFA
16	Children	-	47 ± 1.6	22	+	LFRET, FEIA, LFA
17	Children	-	47 ± 0.8	18	-	LFA
18	Children	-	36 ± 1.8	14	+	FEIA, LFA
19	Children	-	79 ± 9.9	35	-	LFRET, FEIA
20	Adults	-	27 ± 13.8	1	+	LFA
21	Adults	-	46 ± 0.3	1.7	-	LFRET

CD status = celiac disease (CD) status as defined by biopsy (+ = CD,— = no CD). LFRET (protein L TR-FRET assay) / FEIA (fluorescent enzyme immunoassay) / LFA (lateral flow assay) = CD status as suggested by each method, darker background indicating a result suggestive of CD. For LFRET and FEIA, quantitative results are included, as photons for LFRET and as U/ml for FEIA. Cutoffs for LFRET and FEIA are 45 counts and 7 U/ml, respectively.

Notably, all samples (n = 42) with a high FEIA result (above 70 U/ml) yielded positive tTG-LFRET results (Fig 2). The Pearson correlation between LFRET and FEIA results was 0.85.

Fig 2

Anti-tTG-IgA FEIA results (x-axis) compared to LFRET results (y-axis) without IgG depletion.

FEIA = fluorescent enzyme immunoassay. LFRET = protein L–based time-resolved Förster resonance energy transfer assay. FEIA result is expressed as U/ml. LFRET result is expressed as average of normalized acceptor wavelength emission counts from two replicates of the same sample, with two consecutive measurements from both replicates. Patients with biopsy-confirmed celiac disease (CD) are marked with a darker spot. The solid lines indicate cutoffs for FEIA and LFRET, with the area between 7 and 10 U/ml corresponding to an equivocal result for FEIA. FEIA cutoffs are set as determined by the manufacturer. LFRET cutoffs were determined by measuring the tTG-LFRET signals for 67 tTG-antibody negative samples (as defined by FEIA) and setting the LFRET cutoff at the mean LFRET signal plus two standard deviations (SD) (35.438 + 2 × 5.316 = 46.07 counts). Pearson correlation coefficient between FEIA and LFRET results is 0.85.

IgG depletion in tTG-LFRET

In an earlier study we employed IgG depletion to distinguish between IgM and IgG in an infectious disease application of LFRET [18]. Here we used the same approach to determine if the sample is anti-tTG IgA-positive or IgA-negative yet IgG-positive. After IgG depletion, using a constant cutoff (mean + 2 × SD, equal to 34.392 + 2 × 5.117 = 44.63 counts), the LFRET assay sensitivity and specificity would be 77.0% (57/74) and 95.7% (67/70), respectively (Fig 3).

Fig 3

Anti-tTG-IgA FEIA results (x-axis) compared to LFRET results (y-axis) with IgG depletion.

FEIA = fluorescent enzyme immunoassay. LFRET = protein L–based time-resolved Förster resonance energy transfer assay. FEIA result is expressed as U/ml. LFRET result is expressed as average of normalized acceptor wavelength emission counts from two replicates of the same sample, with two consecutive measurements from both replicates. Patients with biopsy-confirmed celiac disease (CD) are marked with a darker spot. The solid lines indicate cutoffs for FEIA and LFRET, with the area between 7 and 10 U/ml corresponding to an equivocal result for FEIA. FEIA cutoffs are set as determined by the manufacturer. LFRET cutoffs were determined by measuring the tTG-LFRET signals for 67 tTG-antibody negative samples (as defined by FEIA) and setting the LFRET cutoff at the mean LFRET signal plus two standard deviations (SD) (34.392 + 2 × 5.117 = 44.63 counts). The dashed line represents x10 upper limit of normal (ULN) for FEIA, and for LFRET a cutoff for detection of samples with a FEIA result above x10 ULN. Pearson correlation coefficient between FEIA and LFRET (with IgG depletion) results is 0.83.

The reduction in tTG-LFRET signal (in %) due to IgG depletion was determined for each of the 144 samples. The average reduction plus 2.5 × SD, corresponding to a 59% reduction in tTG-LFRET signal, was chosen as cutoff, with greater reduction taken as indication of IgG-class LFRET positivity. Hence, samples in which upon IgG depletion the tTG-LFRET signal both 1) fell down by >59% and 2) went beyond the cutoff of 44.63 counts, were considered anti-tTG IgG-positive yet IgA-negative. As no such samples were found in the panel, two of them were obtained from HUSLAB to validate the threshold. Upon IgG depletion, the tTG-LFRET signal levels for these samples decreased by 70% and 87% and went below the positivity cutoff; hence the samples were correctly identified as anti-tTG IgA-negative yet IgG-positive (Fig 4).

Fig 4

tTG-LFRET signal change with IgG depletion.

tTG-LFRET = tissue transglutaminase protein L–based time-resolved Förster resonance energy transfer assay. On the x-axis, x marks the LFRET signal without IgG depletion (by GullSORB treatment) and o marks the signal with IgG depletion. On the y-axis are all the studied samples, labels indicating the sample id. An algorithm for differentiation of IgG+/IgA- samples from IgA+ samples was defined as follows: First, the reduction in tTG-LFRET signal (in %) due to IgG depletion was calculated for each of the 144 study samples. The average reduction plus 2.5 × SD, corresponding to a 59% reduction in tTG-LFRET signal, was chosen as cutoff, with greater reduction taken as indication of IgG-class LFRET positivity. Second, to consider the samples IgA-negative, IgG depletion had to reduce the signal below the cutoff as determined by the mean LFRET signal plus two standard deviations (SD) (34.392 + 2 × 5.117 = 44.63 counts) of 67 tTG-antibody negative samples (as defined by FEIA). For the two anti-tTG IgA-/IgG+ samples (marked with arrows), IgG depletion reduces the LFRET signal by 1) more than 59% and 2) below the positivity cutoff. For the IgA-positive and -negative samples (all samples not marked with arrows), a similar phenomenon is not seen.

Discussion

We established a rapid LFRET assay for the detection of anti-tTG IgA-class antibodies (tTG-LFRET) for serological screening of celiac disease (CD). CD affects 1% of world population and the typical diagnostic delay is 5–10 years [12, 13]. In both developed and resource-poor countries, the vast majority of patients currently remain undiagnosed. Patients with undiagnosed and untreated CD suffer from decreased quality of life and increased risk of various conditions including neuropathy, liver disease as well as osteoporosis [2, 5]. Thus, low-threshold diagnostic testing and screening of risk groups such as first-degree relatives of CD patients is warranted. Reliable anti-tTG POC diagnostics could lower the threshold for CD screening and help overcome the diagnostic delay.

Herein we harnessed LFRET [17], previously applied in infectious disease diagnostics [18, 19], for an autoimmune disease identified by tTG-specific IgA antibodies. This paves way for development of LFRET assays for other autoimmune diseases. While in CD the tTG autoantigen is well-characterized, the less defined antigens in some other autoimmune diseases provide a challenge for POC diagnostics. Nevertheless, with well-defined autoantigens, e.g. ANCA-associated vasculitis, anti-GBM disease, pemphigus and pemphigoid could be suitable targets for LFRET-based assay development.

The sensitivity and specificity of tTG-LFRET for biopsy-confirmed CD were 87.8% and 94.3%, respectively. While the commercial LFA was equal to tTG-LFRET, FEIA exhibited higher sensitivity (95.9%) but lower specificity (91.9%). In line with our LFA results, the existing anti-tTG IgA POC tests have been shown to identify biopsy-confirmed CD with a pooled sensitivity and specificity of 90.5% (95% CI 82.3% –95.1%) and 94.8% (95% CI 92.5% –96.4%), respectively [9]. EIAs have been shown to perform with a slightly lower pooled sensitivity of 93.0% (95% CI 91.2% –94.5%), yet with a higher pooled specificity of 96.5% (95% CI 95.2% –97.5%) [8]. Interestingly, all of our CD patients anti-tTG negative by FEIA were likewise negative by tTG-LFRET and LFA (Table 2). Lowering the tTG-LFRET cutoff, for enhanced sensitivity of 93.2%, would decrease the specificity to 81.4%. In general, the somewhat lower sensitivity of tTG-LFRET compared to FEIA was confined to samples weakly positive in the latter assay (Fig 2), and might result from the europium label masking some of the tTG epitopes. Another contributing factor could be the variation in immunoglobulin light chain composition: the anti-tTG antibodies in some individuals might mostly have light chains of type λ, nonbinding protein L. Patients with a high-positive FEIA result of >70 U/ml, i.e., >10 times the upper limit of normal (ULN) were all correctly positive in tTG-LFRET, both with and without IgG depletion. This could reflect greater anti-tTG antibody repertoire with antibodies containing both κ and λ light chains. An anti-tTG IgA result of >10x ULN is among the requirements of ESPGHAN criteria for CD diagnosis without biopsy [4]. With IgG depletion, our tTG-LFRET cutoff could be set at 60 counts (Fig 3, dashed lines): A tTG-LFRET result higher than this equals a FEIA result of >10x ULN (> 70 U/ml) with 95% sensitivity (40/42 samples) and 100% specificity (142/142). Indeed, all of the patients exceeding this cutoff had biopsy-confirmed CD. Thus, individuals with an IgG-depleted tTG-LFRET result above 60 can be considered to have CD at a high degree of certainty, possibly without the need for biopsy. Importantly, such patients made up more than a half of those diagnosed with CD in the present study (40/74).

Interestingly, IgG depletion reduced the tTG-LFRET signal to a varying extent in most of the anti-tTG positive samples (Fig 4). This suggests that not only anti-tTG IgA, but also anti-tTG IgG contributes to the tTG-LFRET signal. Anti-tTG IgG contribution to tTG-LFRET signal in samples with low concentration of anti-tTG IgA could also explain the enhanced sensitivity of tTG-LFRET for CD diagnosis without IgG depletion (87.8% vs 77.0% with IgG depletion, Figs 1 and 2). In the study population, this does not decrease the specificity of the method for CD diagnosis. This is in line with previous studies showing that anti-tTG IgG has a high specificity for CD comparable to anti-tTG IgA, albeit lower sensitivity [23].

In conclusion, our study shows that the LFRET approach is applicable to detection of IgA autoantibodies and serological diagnostics of autoimmune diseases. The assay appears highly specific in detection of CD, yet somewhat less sensitive. A homogenous approach, the LFRET is considerably faster than EIA, paralleling LFAs in both time and diagnostic performance. Unlike the LFA used, the LFRET provides a numeric result.

Sensitivity and specificity (y-axis) of tTG-LFRET (tissue transglutaminase protein L TR-FRET assay) for CD (celiac disease) at different incubation times (x-axis).

We chose 22 minutes as the incubation time to achieve the best balance between sensitivity, specificity and assay time.

(TIF)

Click here for additional data file.

Sensitivity and specificity of tTG-LFRET (tissue transglutaminase protein L TR-FRET assay) for CD (celiac disease) at different incubation times.

We chose 22 minutes (bolded) as the incubation time to achieve the best balance between sensitivity, specificity and assay time.

(DOCX)

Click here for additional data file.

8 Oct 2019

PONE-D-19-23614

LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection

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Reviewer #1: In the manuscript “LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection”, the authors present the application of previous L-based time-resolved Foster energy transfer (TR-FRET) assay to detect anti-tissue transglutaminase antibody in patients.

In my opinion, this work is of interest for the readers of the Journal but I recommend the publication after a minor revisions. In particular:

- The application of TR-FRET assay from the authors and the comparing the sensitivity and specificity with other available test reported in this manuscript appears to be very promising to shed light on the individuation of point-of-care test. I know that in previous work the authors have described in details the approach, but could be an add value if they integrate in this manuscript a flow chart taht describe the assay. This will allow the reader to better understand the assay. Please the authors provide it.

- In the materials and methods section the paragraph “Reference methods” and “Statistically analysis” should be unified. Please, the authors provide it.

-Materials methods section the paragraph “tTG-LFRET assay” and “IgG depletion” could be unified. Please, the authors consider this option.

- In the paragraph “Sample” of the materials and method section, please add more information about the sample preparation before to perform the assays.

- All figure legends present in the manuscript lack of important details that allow the reader to understand the single figures. Please, the authors improve it.

- Please at line 48 clarify the abbreviation HLA

Reviewer #2: In the present paper, Dr. Juuso Rusanen and co-workers exploited a recombinant Eu-labeled tTG antigen and AF-labeled protein L to develop a TR-FRET-based immunoassay (named LFRET) for the detection of anti-tTG antibodies in celiac disease patients.

They validated the assay on serum samples form 74 celiac patients and 70 healthy subjects, finding a good correlation between the LFRET assay and current immunoassays (both fluorescence enzyme immunoassay (FEIA) and lateral flow assay (LFA)).

The new LFRET assay is conceived as a point of care test, with the advantage of being quantitative, compared to LFA. Despite the data are quite solid, certain aspects are not clear and need to be revised.

Specific comments:

1) In the methods section a description of the LFRET assay is necessary; the authors should at least mention how serum/plasma samples are processed, how the assay is performed, and what instrument they use for fluorescence acquisition and analysis.

2) It is not clear how the FRET signal is shown (figure 1 and figure 2). The authors state that “ LFRET signal is expressed as average of normalized acceptor wavelenght emission counts from two replicats of the same sample (with 2 consecutive measurements from both replicates)”. But, since counts are “not divided by the TR-FRET signal of the negative control”, what normalization has been done? On the x-axis “LFRET signal, counts, log scale” is reported, but as I can understand the scale is not in log10? Reported numbers are referred to counts x103? The rationale for the cut off value and the Pearson correlation coefficient should be reported in the figure legend.

3) In figure 2 the authors report the results of the LFRET assay after IgG depletion, correlating them with results of the FEIA assay (that is specific for IgA). It is not clear how the cutoff for FEIA is calculated. In addition, no correlation coefficient is reported.

4) In figure 3 the LFRET counts of the samples before and after IgG depletion are shown, in order to demonstrate that the new system is able to detect anti-tTG IgA-negative yet IgG-positive samples. A threshold for identifing these samples was established, and validated on two samples taken from the HUSLAB bank (laboratory), outside of the sample collection of the study. In practice, these samples serve as controls to prove the validity of the treshold, but this point should be explained more clearly in the text. In addition, also for figure 3 it is not clear how the cutoff of counts was calculated.

5) The first results section is intitled tTG-LFRET incubation time, cutoff and performance but no data are shown about the incubation time. The title should be changed.

6) Since the results from FEIA and from LFA are reported in the second paragraph I suggest to move the last sentence of the first section (line 152-154, and the discussion of the figure 1) to the second section. Also, the title of the second paragraph should indicate a comparison between the reference methods and the new one. Table 2 should be commented in this results section.

7) In table 2 it should be more correct to report mean ±SD of the duplicates samples for LFRET and FEIA.

Minor points

1) Use always the same acronim for FEIA (or EIA)

2) Table 1 is subdivided in three subtables that should be combined in a unique one.

3) How are considered the samples between 7 and 10 U/ml in the FEIA assay? This should be specified in the methods/results interpretation.

4) Raw 230: insert the reference as a number

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Reviewer #2: No

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2 Nov 2019

Response to Reviewers Juuso Rusanen 2.11.2019

Dear Dr. Juuso Rusanen:

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

[…]

Kind regards,

Sabato D'Auria

Academic Editor

PLOS ONE

-> Our warmest thanks for the opportunity to revise our manuscript according to journal requirements and reviewers’ comments, for which point-by-point replies are included below.

Journal Requirements

When submitting your revision, we need you to address these additional requirements.

[…]

1. We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

-> Thank you for the remark and our sincere apologies for not noticing this when first submitting the manuscript. We have now added supporting information files including the data referred to in the part of the manuscript in question.

Reviewer #1

In the manuscript “LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection”, the authors present the application of previous L-based time-resolved Foster energy transfer (TR-FRET) assay to detect anti-tissue transglutaminase antibody in patients.

In my opinion, this work is of interest for the readers of the Journal but I recommend the publication after a minor revisions. In particular:

- The application of TR-FRET assay from the authors and the comparing the sensitivity and specificity with other available test reported in this manuscript appears to be very promising to shed light on the individuation of point-of-care test. I know that in previous work the authors have described in details the approach, but could be an add value if they integrate in this manuscript a flow chart taht describe the assay. This will allow the reader to better understand the assay. Please the authors provide it.

-> We are very happy to hear that the reviewer considers the manuscript very promising, and agree that a flowchart would help better understand the assay. Thus, we have added one (Fig 1).

- In the materials and methods section the paragraph “Reference methods” and “Statistically analysis” should be unified. Please, the authors provide it.

-> We have unified the sections accordingly.

-Materials methods section the paragraph “tTG-LFRET assay” and “IgG depletion” could be unified. Please, the authors consider this option.

-> We agree with the reviewer that unifying these sections would make sense, and tried this option. However, we found that unifying these sections and placing the second paragraph (comparison of methods) as last would perhaps disturb the flow of the manuscript more than the current order of paragraphs, which we thus chose to keep. For clarity, we have renamed the section ”IgG depletion” to ”IgG depletion in tTG-LFRET”.

- In the paragraph “Sample” of the materials and method section, please add more information about the sample preparation before to perform the assays.

-> We have added a flowchart (Fig 1), which also describes the sample preparation.

- All figure legends present in the manuscript lack of important details that allow the reader to understand the single figures. Please, the authors improve it.

-> We fully agree, and therefore have added significantly more information to figure legends, including but not limited to clarifying all non-standard abbreviations used.

- Please at line 48 clarify the abbreviation HLA

-> We have clarified this abbreviation.

Reviewer #2

In the present paper, Dr. Juuso Rusanen and co-workers exploited a recombinant Eu-labeled tTG antigen and AF-labeled protein L to develop a TR-FRET-based immunoassay (named LFRET) for the detection of anti-tTG antibodies in celiac disease patients.

They validated the assay on serum samples form 74 celiac patients and 70 healthy subjects, finding a good correlation between the LFRET assay and current immunoassays (both fluorescence enzyme immunoassay (FEIA) and lateral flow assay (LFA)).

The new LFRET assay is conceived as a point of care test, with the advantage of being quantitative, compared to LFA. Despite the data are quite solid, certain aspects are not clear and need to be revised.

-> Thank you.

Specific comments:

1) In the methods section a description of the LFRET assay is necessary; the authors should at least mention how serum/plasma samples are processed, how the assay is performed, and what instrument they use for fluorescence acquisition and analysis.

-> We agree with comment and have added a flowchart illustrating how the samples are processed and the assay performed (Fig 1). Furthermore, the instrument used for fluorescence measurements has been named in the methods section.

2) It is not clear how the FRET signal is shown (figure 1 and figure 2). The authors state that “ LFRET signal is expressed as average of normalized acceptor wavelenght emission counts from two replicats of the same sample (with 2 consecutive measurements from both replicates)”. But, since counts are “not divided by the TR-FRET signal of the negative control”, what normalization has been done? On the x-axis “LFRET signal, counts, log scale” is reported, but as I can understand the scale is not in log10? Reported numbers are referred to counts x103? The rationale for the cut off value and the Pearson correlation coefficient should be reported in the figure legend.

-> We appreciate the points raised by reviewer #2. For clarification, we have added a reference regarding normalization to this paper to the materials and methods section, line 131. To further clarify, normalization here refers to normalizing the acceptor (Alexa Fluor 647, AF647) signal measured at 665 nm with respect to the donor (Europium) emission at 665 nm. This is done according to the following equation (from Saraheimo et al. 2013): AF647N = AF647–k*Eu, where AF647N = normalized AF647 fluorescent counts, AF647 = unnormalized A647 counts (at 665 nm), k = Eu emission at 665 nm/Eu emission at 615 nm and Eu = Eu fluorescent counts (at 615 nm).

The x axis scale is logarithmic, but the axis labels are indeed arbitrarily set to best cover the signal area (25-300). Alternatively, we could use e.g. log2 axis labels, but in our opinion this would make the figure more difficult to perceive (see Figs i & ii in the file "Response to Reviewers"). To clarify this part, we now mention in the axis titles that axis labels are arbitrary.

We have added the rationale to the cutoff as well as Pearson correlation coefficients to the figure legends (Figs 2 and 3).

3) In figure 2 the authors report the results of the LFRET assay after IgG depletion, correlating them with results of the FEIA assay (that is specific for IgA). It is not clear how the cutoff for FEIA is calculated. In addition, no correlation coefficient is reported.

-> We have added Pearson correlation coefficient to the figure legend. The cutoff of FEIA assay is manufacturer-defined.

4) In figure 3 the LFRET counts of the samples before and after IgG depletion are shown, in order to demonstrate that the new system is able to detect anti-tTG IgA-negative yet IgG-positive samples. A threshold for identifing these samples was established, and validated on two samples taken from the HUSLAB bank (laboratory), outside of the sample collection of the study. In practice, these samples serve as controls to prove the validity of the treshold, but this point should be explained more clearly in the text. In addition, also for figure 3 it is not clear how the cutoff of counts was calculated.

-> Thank you for these helpful remarks, we have clarified this point in the text accordingly. Furthermore, we now explain the algorithm for differentiating between IgG+/IgA- and IgA+ samples in the figure legend.

5) The first results section is intitled tTG-LFRET incubation time, cutoff and performance but no data are shown about the incubation time. The title should be changed.

-> We now have added data on incubation time (S1 Fig and S1 Table in Supplementary data).

6) Since the results from FEIA and from LFA are reported in the second paragraph I suggest to move the last sentence of the first section (line 152-154, and the discussion of the figure 1) to the second section. Also, the title of the second paragraph should indicate a comparison between the reference methods and the new one. Table 2 should be commented in this results section.

-> Thank you, we have amended the manuscript accordingly.

7) In table 2 it should be more correct to report mean ±SD of the duplicates samples for LFRET and FEIA.

-> We now have corrected the table to refer to means ± SD of duplicates for LFRET. For FEIA, no duplicate measurements were taken.

Minor points

1) Use always the same acronim for FEIA (or EIA)

-> In the manuscript, we refer to EIA as a more general concept in the abstract, introduction and conclusions, as also non-fluorescent EIAs are used for anti-tTG antibody determination. We use the word FEIA only when specifically referring to the reference EIA we used in this study (which is a fluorescent EIA, or FEIA). We hope that this adequately explains why we consider it justified to use the acronyms separately.

2) Table 1 is subdivided in three subtables that should be combined in a unique one.

-> Thank you for the excellent suggestion, we have combined the three subtables into a single table.

3) How are considered the samples between 7 and 10 U/ml in the FEIA assay? This should be specified in the methods/results interpretation.

-> In this manuscript, results equivocal in FEIA (between 7 and 10 U/ml) are considered positive. There were two samples of this range, one true and one false positive. We have added a mention of this on page 8, line 179.

4) Raw 230: insert the reference as a number

-> We now have added the reference.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

14 Nov 2019

LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection

PONE-D-19-23614R1

Dear Dr. Juuso Rusanen,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Sabato D'Auria

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

19 Nov 2019

PONE-D-19-23614R1

LFRET, a novel rapid assay for anti-tissue transglutaminase antibody detection

Dear Dr. Rusanen:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Sabato D'Auria

Academic Editor

PLOS ONE