Opportunities and challenges when pooling milk samples using ELISA

Accuracy of testing strategies using antibody-ELISA tests on repeated bulk tank milk samples and/or sera of individual animals for predicting herd status for Salmonella dublin in dairy cattle

There is currently no perfect test for determining herd-level status for Salmonella Dublin in dairy cattle herds. Our objectives were to evaluate the accuracy, predictive ability, and misclassification cost term of different testing scenarios using repeated measurements for establishing the S. Dublin herd status. Diagnostic strategies investigated used repeated bulk tank milk antibody-ELISA tests, repeated rounds of blood antibody-ELISA tests on non-lactating animals or a combination of both approaches. Two populations hypothesized to have different S. Dublin prevalences were included: (i) a convenience sample of 302 herds with unknown history of infection; and (ii) a cohort of 58 herds that previously tested positive to S. Dublin. Bulk milk samples were collected monthly for 6-7 months and serum were obtained from 10 young animals on two occasions, at the beginning and end of bulk milk sampling period. A series of Bayesian latent class models for two populations and comparing two tests were used to compare bulk milk-based to serum-based strategies. Moreover, Monte Carlo simulations were used to compared diagnostic strategies combining both types of samples. For each diagnostic strategy, we estimated the predictive values using two theoretical prevalences (0.05 and 0.25). Misclassification cost term was also estimated for each strategy using these two prevalences and a few relevant false-negative to false-positive cost ratios. When used for screening a population with an expected low prevalence of disease, for instance for screening herds with no clinical signs and no previous S. Dublin history, a diagnostic strategy consisting of two visits at 6 months interval, and with herd considered positive if bulk milk PP% ≥ 35 and/or ≥ 1/10 animals are positive on one or both visits could be used to confidently rule-out S. Dublin infection (median negative predictive value of 0.99; 95% Bayesian credible intervals, 95BCI: 0.98, 1.0). With this approach, however, positive results should later be confirmed with more specific tests to confirm whether S. Dublin is truly present (median positive predictive value of 0.36; 95BCI: 0.22, 0.57). The same diagnostic strategy could also be used confidently to reassess the S. Dublin status in herds with a previous S. Dublin history. When use for such a purpose, the predictive value of a positive result could be greatly improved, from 0.78 (95BCI: 0.65, 0.90) to 0.99 (95BCI: 0.94, 1.0) by requiring ≥ 1 positive result on both visits, rather than at any of the two visits.

Detection of Low MAP Shedder Prevalence in Large Free-Stall Dairy Herds by Repeated Testing of Environmental Samples and Pooled Milk Samples

Simple Summary

Paratuberculosis is a disease which affects ruminants worldwide. Many countries have implemented certification and monitoring systems to control the disease, particularly in dairy herds. Monitoring herds certified as paratuberculosis non-suspect is an important component of paratuberculosis herd certification programs. The challenge is to detect the introduction or reintroduction of the infectious agent as early as possible with reasonable efforts but high certainty. In our study, we evaluated different low-cost testing schemes in herds where the share of infected animals was low, resulting in a low within-herd prevalence of animals shedding the bacteria that causes paratuberculosis in their feces. The test methods used were repeated pooled milk samples and fecal samples from the barn environment. Our study showed that numerous repetitions of different samples are necessary to monitor such herds with sufficiently high certainty. In the case of herds with a very low prevalence, our study showed that a combination of different sampling approaches is required.

Abstract

An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.

Variation in the Performance of Different Batches of Two Mycobacterium avium Subspecies paratuberculosis Antibody ELISAs Used for Pooled Milk Samples

Simple Summary

This article explores variation in the performance of different batches of tests for the detection of antibodies against the ruminant pathogen Mycobacterium avium subspecies paratuberculosis (MAP) in milk. The results indicate that variation is present and that it has sources mainly in the manufacturing process of the test kits and, to a lesser degree, in the test laboratories.

Abstract

Regionally, the monitoring of paratuberculosis at the herd level is performed by the detection of specific antibodies in pooled milk samples by ELISA. The negative/positive cut-off S/P values applied for pooled milk samples are low and particularly vulnerable to variation in the test performance. In this study, a batch variation in the test performance of two ELISA tests was assessed to identify consequences for sample classification. A total of 72 pooled milk samples (50 from MAP-infected herds, 22 from one MAP-non-infected herd) were analyzed using three different batches, each of two different MAP antibody ELISA tests (A and B). Receiver operating characteristic (ROC) analysis was performed, with the results of each batch, S/P values of the samples and optical density (OD) readings of the negative and positive control samples included in the kits being compared between the batches of one test. ROC analysis revealed a considerable variation in the test performance of the batches of the two individual tests, caused by differences in the S/P values of the samples and resulting in different sensitivities at a specificity of 100%. Major sources of variation originate from the manufacturing processes of test batches. These sources have to be better controlled, and the test performance has to be revisited regularly.

When to use one-dimensional, two-dimensional, and Shifted Transversal Design pooling in mycotoxin screening

While complex sample pooling strategies have been developed for large-scale experiments with robotic liquid handling, many medium-scale experiments like mycotoxin screening by Enzyme-Linked Immunosorbent Assay (ELISA) are still conducted manually in 48- and 96-well plates. At this scale, the opportunity to save on reagent costs is offset by the increased costs of labor, materials, and risk-of-error caused by increasingly complex pooling strategies. This paper compares one-dimensional (1D), two-dimensional (2D), and Shifted Transversal Design (STD) pooling to study whether pooling affects assay accuracy and experimental cost and to provide guidance for when a human experimentalist might benefit from pooling. We approximated mycotoxin contamination in single corn kernels by fitting statistical distributions to experimental data (432 kernels for aflatoxin and 528 kernels for fumonisin) and used experimentally-validated Monte-Carlo simulation (10,000 iterations) to evaluate assay sensitivity, specificity, reagent cost, and pipetting cost. Based on the validated simulation results, assay sensitivity remains 100% for all four pooling strategies while specificity decreases as prevalence level rises. Reagent cost could be reduced by 70% and 80% in 48- and 96-well plates, with 1D and STD pooling being most reagent-saving respectively. Such a reagent-saving effect is only valid when prevalence level is < 21% for 48-well plates and < 13%-21% for 96-well plates. Pipetting cost will rise by 1.3-3.3 fold for 48-well plates and 1.2-4.3 fold for 96-well plates, with 1D pooling by row requiring the least pipetting. Thus, it is advisable to employ pooling when the expected prevalence level is below 21% and when the likely savings of up to 80% on reagent cost outweighs the increased materials and labor costs of up to 4 fold increases in pipetting.

Tests in short supply? Try group testing

Christopher R. Bilder, Peter C. Iwen, Baha Abdalhamid, Joshua M. Tebbs and Christopher S. McMahan explain how, by pooling specimens, testing capacity for SARS-CoV-2 can be increased.

Analytic Sensitivity of an ELISA Test on Pooled Sera Samples for Detection of Bovine Brucellosis in Eradication Stages in Uruguay

Bovine brucellosis has been under eradication in Uruguay since 1998. The eradication program includes, among other interventions, individual sera sampling of beef animals at slaughter, and annual serum testing of all dairy cows—accounting for two million samples annually. At a herd prevalence of 0.8%, a pooled-sera sample approach could reduce the economic burden of the surveillance system by reducing the testing and operational costs. Our objective was to evaluate the analytic sensitivity of an indirect ELISA test for Brucella abortus in serum pools. Sixty-two Brucella abortus-positive bovine sera samples (based upon rose bengal and fluorescent polarization assay) were used as the positive control samples. Rose bengal-negative sera from negative farms were used to dilute the positive samples to the desired concentrations. Positive samples were diluted by using 1 ml of positive sera and 1 ml of negative sera (1/2 dilution) up to 1/1,024. Data were analyzed using generalized linear mixed models with a binary outcome (positive or negative), dilution number as a fixed effect, and a random effect for sample ID. Analytic sensitivity was 99.0% [95% confidence interval (CI): 96.3–99.7], 98.3% (95% CI: 93.1–99.6), 97.3% (95% CI: 87.4–99.4) for dilutions 1/2, 1/4, and 1/8, respectively. The analytical sensitivity, however, decreased when diluted to greater proportions. Given the current herd prevalence in Uruguay, it seems plausible that the use of a pooled sample approach could be adopted by policymakers to reduce the cost of the surveillance program and increase the number of samples being tested.

Flock sensitivity and specificity of pooled fecal qPCR and pooled serum ELISA for screening ovine paratuberculosis

The aim of our study was to evaluate the flock sensitivity and specificity of fecal qPCR and serum ELISA using pooled samples for screening paratuberculosis in French sheep.

Using individual feces with low or high qPCR Ct values from ewes sampled in 14 infected flocks, a total of 555 pools of size 5, 10 and 20 were created by diluting individual materials in negative feces and analysed using a commercial IS900 qPCR kit. The relative performances of pooled serum ELISA analysis were evaluated based on the analysis of 181 different pools of size 5 and 10, composed of individual serum samples of various individual S/P values. Results showed that for pools of size 5, 10 or 20, individual fecal samples with low Ct values were invariably detected. Conversely fecal samples with high Ct values were associated with a lower detection rate in both pools of size 5 (87.0% to 90.0%), 10 (63.0% to 70.7%) and 20 (46.7% to 60.0%). After lowering the decision threshold to 25% and 15% for serum pools of size 5 and 10 respectively, the pooled serum ELISA relative sensitivity ranged between 62.2% and 100.0% depending on the composition of the pools.

Finally, a simulation study was carried out to evaluate the performances of 16 screening strategies at flock level, with varying pool size (5 to 20) and number (5 to 60). The use of pooled serum ELISA led to very false positive detection rate ranging between 37.6% and 91.8% in paratuberculosis free flocks and prevents its further use in that context. For infection prevalence ≤ 5%, the flock sensitivity based on pooled fecal qPCR ranged between 39.0% (5 pools of size 10) and 99.9% (300 sampled individuals, with pools of size 5,10 or20), and was always above 93% when the infection prevalence was greater or equal to 15%. We conclude that pooled-fecal qPCR but not pooled-serum ELISA could be a useful tool to detect sheep flocks infected with paratuberculosis.

The objective function controversy for group testing: Much ado about nothing?

Group testing is an indispensable tool for laboratories when testing high volumes of clinical specimens for infectious diseases. An important decision that needs to be made prior to implementation is determining what group sizes to use. In best practice, an objective function is chosen and then minimized to determine an optimal set of these group sizes, known as the optimal testing configuration (OTC). There are a few options for objective functions, and they differ based on how the expected number of tests, assay characteristics, and testing constraints are taken into account. These varied options have led to a recent controversy in the literature regarding which of two different objective functions is better. In our paper, we examine these objective functions over a number of realistic situations for infectious disease testing. We show that this controversy may be much ado about nothing because the OTCs and corresponding results (eg, number of tests and accuracy) are largely the same for standard testing algorithms in a wide variety of situations.

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article available online.