cELISAs sold by VMRD are licensed for use in defined species. For instance, the test for antibody to Anaplasma is approved for use with bovine serum samples. The cELISA will detect antibody to Anaplasma in serum from other animals including sheep and goats (1). Further, the test should detect antibody to Anaplasma in serum from any animal species because sufficient quantities of antibody of the appropriate specificity will inhibit the binding of labeled mouse monoclonal antibody in the test and cause a positive result. The reason that the Anaplasma cELISA is not approved for use with sera from sheep and goats and other animals such as wild ruminants is that the available data is insufficient to determine the appropriate cutoff value in order to resolve positives and negatives. The cutoff for the bovine serum cELISA is 30% inhibition (i.e. samples inhibiting the binding of the labeled monoclonal antibody greater than or equal to 30% are positive; samples with less than 30% inhibition are negative). A group of bovine samples defined as Anaplasma positive or negative by nested PCR followed by hybridization (2) were used to define a 30% inhibition cut-off which resulted in a sensitivity of 95% and a specificity of 98% (see data at www.vmrd.com). Why not use the 30% inhibition cutoff for the other animal species? It is not used because it might not be correct. Sera from defined negative cattle inhibit the binding of labeled monoclonal antibody used in the Anaplasma cELISA to some extent (from 0% to <30%). Whether sera from other animals with no antibody to Anaplasma (negative sera) always inhibit <30% is not known; they may or may not, but it is an empirical question that has not been examined in sufficient detail. Further, a determination of the ability of each infected animal species to make sufficient amounts of antibody with the appropriate specificity needs to be made in order to evaluate the sensitivity of the cELISA for that species. The cELISA to detect serum antibody to caprine arthritis-encephalitis virus (CAEV) is licensed for use only for goats. However, in research to see if the CAEV cELISA could detect cross-reacting antibodies in sheep infected with a related virus, ovine progressive pneumonia virus (OPPV), it seemed clear that sera from CAEV negative goats inhibited binding of the labeled CAEV monoclonal antibody more than did than serum from OPPV negative sheep (3,4). The % inhibition cutoff for the VMRD CAEV cELISA for goats is 35% to obtain high sensitivity and specificity, whereas in a research study a cutoff of 20.9% inhibition could be used in the CAEV cELISA with sheep sera to detect cross-reacting antibodies to OPPV (4). However, more data is needed to further evaluate the sensitivity for the CAEV cELISA for use in detecting antibody to OPPV in sheep from various geographic regions. Therefore, cutoff data needs to be obtained with serum from each animal species before using a particular cELISA. On the surface, it appears that obtaining data for determining a cutoff is easy. In fact, it requires considerable effort because a "gold standard" is needed to determine true negative and true positive status for a relatively large number of sera from different locations for use in obtaining a cutoff which results in high specificity and sensitivity. References 1. Ndung'u LW, et al. Detection of Anaplasma ovis infection in goats by major surface protein 5 competitive inhibition enzyme-linked immunosorbent assay. J Clin Microbiol. 33 (3):675-679 1995. 2. Torioni de Echaide S., et al. Detection of cattle naturally infected with Anaplasma marginale in a region of endemicity by nested PCR and a competitive enzyme-linked immunosorbent assay using recombinant major surface protein 5. J Clin Microbiol. 36:777-782, 1998. 3. Herrmann LM, et al. Competitive-inhibition enzyme-linked immunosorbent assay for detection of serum antibodies to caprine arthritis-encephalitis virus: diagnostic tool for successful eradication. Clin Diagn Lab Immunol. 10:267-271, 2003. 4. Herrmann LM, et al. Detection of serum antibodies to ovine progressive pneumonia virus in sheep by using a caprine arthritis-encephalitis virus competitive-inhibition enzyme-linked immunosorbent assay. Clin Diagn Lab Immunol. 10:862-865, 2003.

Malignant Catarrhal Fever Virus Infection of Domestic Cattle and Other Susceptible Ruminants The often fatal lymphoproliferative and inflammatory disease syndrome malignant catarrhal fever (MCF) is caused by closely related members of the family Gammaherpesvirinae. Two epidemiologic entities of the disease exist: wildebeest-associated MCF (WA-MCF), an endemic subclinical infection in antelope of the Alcelaphine subfamily, and sheep-associated MCF (SA-MCF), an inapparent MCF virus (MCFV) infection of sheep.  The MCFV of WA-MCF has been isolated, well characterized and named alcelaphine herpesvirus (AHV-1).  The MCFV assumed to infect sheep has never to our knowledge been isolated.  However, exposure to sheep has frequently been associated with outbreaks of MCF in cattle worldwide.  Furthermore, MCFV DNA sequences have been demonstrated in sheep tissues and MCFV antibodies have been shown in sheep by CI-ELISA.  Thus, it is virtually certain that sheep are important carriers of MCFV. Competitive Inhibition Enzyme-Linked Immunosorbent Assay for Antibody in Sheep and Other Ruminants to a Conserved Epitope of Malignant Catarrhal Fever Virus Neither the pathogenesis nor the epidemiology of SA-MCF is well understood because the etiologic agent has not been isolated from sheep and because an MCFV-specific antibody test has not heretofore been available.  A monoclonal antibody, 15-A, has been identified, characterized and adapted to a CI-ELISA. Monoclonal antibody 15-A has been shown to react with four different isolates of MCFV.  Rabbit, sheep, calf, deer and wildebeest antibodies to various MCFV strains including both wildebeest- and sheep-associated strains all strongly inhibited binding of 15-A to its epitope in the CI-ELISA.  Furthermore, 15-A did not react with 13 common sheep, goat, and cattle viruses nor did antisera to these viruses inhibit in the CI-ELISA. Among 149 samples from sheep associated with outbreaks of MCF in seven states, the sensitivity of the CI-ELISA was comparable to immunofluorescence (83% concordance).  It is assumed that most, if not all, of the immunofluorescence positive/CI-ELISA negative samples were due to cross-reacting antibodies to other ruminant herpesviruses.  There were no samples positive by CI-ELISA and negative by immunofluorescence (100% specificity). Reference: Li, H., et al., J. Clin. Microbiol., 32:1674-1679, 1994.

Ehrlichia canis – Question: Why is the IFA positive using VMRD E. canis substrate slides while with the same sample I get a negative reaction with an E. canis lateral flow device? Answer: IFA has broader reactivity than the lateral flow assay. The lateral flow assay detects antibody to E. canis only. The IFA will detect antibody to E. ewingii and E. chaffeensis as well and perhaps to other Ehrlichia spp. yet to be identified. Clostridium novyi species reclassification – Question: Does VMRD’s C. novyi Direct FA conjugate (Catalog Nos. 210-16-CN & 210-17-CN) react with C. haemolyticum? Answer: We have recently learned that Clostridium novyi and Clostridium haemolyticum have been reclassified as very similar, if not the same organism. Thus, our C. novyi (B) direct FA conjugate will react with both C. novyi and C. haemolyticum organisms. Anaplasma marginale-Anaplasma phagocytophilum cross-reactivity – Question: A recent paper out of Switzerland [Dreher et al.] documents serologic cross-reactivity between A. marginale and A. phagocytophilum using VMRD’s cELISA and IFA for the aforementioned agents, respectively. What is VMRD’s position with respect to the meaning of data derived from either assay? Answer: From the time that VMRD began marketing the cELISA for detection of antibody to Anaplasma in cattle it was known and we readily acknowledged in our literature and product insert that it was designed to detect antibody to Anaplasma spp. not A. marginale only. This was based on work previously published about MSP-5, major surface protein-5 of Anaplasma spp. by Visser et al. The species specifically mentioned at the time were A. marginale, A. centrale and A. ovis. Furthermore, the cELISA has been shown to detect antibody to A. ovis in goat sera [Ndung'u et al.]. Thus it is not surprising to find that another species, A. phagocytophilum, which has recently been reclassified from an Ehrlichia to an Anaplasma spp., would also induce antibody capable of inhibiting binding of the monoclonal antibody used in the cELISA, thus giving a positive result. Therefore, as indicated from the beginning, VMRD’s cELISA is a genus specific test for Anaplasma . Bovine Herpesvirus 1-Bovine Herpesvirus 5 cross- reactivity – Question: Do any of VMRD’s BHV-1 monoclonal antibodies react with BHV-5? Answer: Yes. The table below shows the results of IFA tests against our isolates of BHV-1 and BHV-5. Only F2 does not react with BHV-5. L6G reacts only with BHV-5 and not BHV-1.

HOW ELISAWARE™ CAME TO BE For many years VMRD customers have been requesting a software program that would support our ELISA assays.  The development of such software always seemed to be a monumental, if not impossible, effort for a small, private company.  At a certain point, however, I realized that we were wasting a lot of time, and creating a lot of error potential, by entering optical density (OD) values by hand.  Not only did our customers need software, we needed software!  This epiphany resulted in several weeks of furious code-writing on my part, the product of which was my first Microsoft®Windows® program. This creation designated “E-Z Reader,” only supported one model of reader and did nothing other than to retrieve and display ODs and export them into Microsoft® Excel®.  Nevertheless, it gained something of a following in VMRD’s laboratories that persists to this day. The experience whetted my appetite for programming and I have devoured numerous books and produced several programs in the five intervening years since E-Z Reader’s debut in our labs. With E-Z Reader’s modest success, an ELISA program no longer seemed completely out of reach.  Nevertheless the constraints of my responsibilities at VMRD did not permit sufficient time to develop the software myself.  My predecessor as marketing manager began the project using outsourced software engineers and I served in an advisory capacity.  Development was severely hampered by language barriers and lack of continuity as programmer after programmer tackled the project.  When I became marketing manager, I found that in addition to these problems, we had an identity crisis.  Up to that point we had been calling the program “MyLab”—some customers may recall seeing that name in our 2003 catalog—a name that was already in use by several other companies.  After much brainstorming and trademark searching I arrived, for better or for worse, at the name “ELISAWare.”  The identity crisis was solved, but my new duties as marketing manager allowed me less time for programming than ever.  Outsourced development had proved so chaotic that I abandoned it and the ELISAWare™ project ground to a standstill. Public release of ELISAWare™ appeared indefinitely postponed until I met an excellent programmer named Eric Foryan.  Instead of being half a world of iffy Internet connections away, Eric lived about four minutes from VMRD, and he was enthusiastic to work on the project.  It was a new and refreshing experience to sit down face to face with a programmer, explain what needed to happen, and see evidence of cognition manifest in head nods instead of in instant messages in broken English. Currently working on a computer science degree at Washington State University, Eric shares my user-centric philosophy of software development.  We believe that software should be self-explanatory, easy to use, and bug free.  We believe that stability takes precedence over an abundance of features.  We believe that the computer should work for the user, not the reverse. As Eric became increasingly familiar with the program he became more and more concerned about the existing code.  I had been pushing for rapid development, so he prefaced his request to rewrite with a number of apologies.  He did not realize that he was preaching to the choir; I too had serious misgivings.  After careful consideration we made a strategic decision to take the time to rewrite.  It took some doing and it took some time, but the resulting program is so much better.  I am sure that ELISAWare™ users will appreciate the stable and robust program that Eric’s rewrite produced.  Very little of the outsourced code remains, so I am proud to say that this program is made in the USA.  I thank Eric for his hard work, conscientiousness, and all the overtime he put in to meet deadlines. What ELISAWare™ Does The essential function of ELISAWare™ is to retrieve data from a microplate absorbance reader, display them to the user, validate the assay, calculate qualitative results from the data, display these to the user, store sample identifications and results, and report these to the user. Data acquisition is supported for a number of readers from four different manufacturers as noted in the center bar on page two.  We are not sure just how many different readers will work with the reader drivers in ELISAWare™, but based on customer input we believe that most readers used by our customers will be supported.  If your reader is not supported we encourage you to let us know as we are fully capable of adding additional reader drivers and will do so based on demand. Please give us a call at 800-222-8673 or e-mail your reader brand and model to vmrd@vmrd.com. ELISAWare™ presently supports all of VMRD’s ELISA test kits.  As we bring new test kits to market, we will offer ELISAWare™ upgrades to accommodate them.  For reasons having to do with stability, complexity, and liability, we chose to build the test validation and calculation into the program rather than to provide some means for the user to enter validation and calculation formulas.  This of course means that other manufacturer’s assays are not supported for validation and calculation.  The software will retrieve ODs from any supported plate reader for any assay, but it will only perform validation and calculation on VMRD’s assays.  Users may retrieve ODs for any assay by choosing the “Generic” test protocol. In ELISAWare™, Sample IDs are entered directly on a 96-position grid representing the microplate.  To prevent confusion of results, calculated results will not be displayed until sample IDs have been entered.  In most cases, sample IDs can be copied from a spreadsheet and pasted into the ELISAWare™ sample ID grid. Samples can be separated into groups such as by farm, vet or client.  These groups can be used to report results from a single plate, a single run or any result in any run within a specified date range.  Because reporting over a date range requires that the group name used be identical in each run, ELISAWare™ keeps a registry of group names and automatically suggests matching group names as the user enters data. Once ELISAWare™ retrieves ODs it performs validation on the results, verifying that the controls are performing within the ranges specified by the kit insert.  If test verification fails, ELISAWare™ reports the reason and displays the ODs but does not calculate results.  If the validation failure was caused by something such as mislabeling a well as a control when it was actually a sample, the user can re-designate the well as a sample and ELISAWare™ will automatically re-verify and calculate results if validation passes—without the necessity of re-reading the plate.  In fact, the position of all the controls, blanks, and samples on the plate, or even the assay, can be changed and ELISAWare™ will re-verify and re-calculate with each change without the necessity of re-reading the plate.  Another of ELISAWare’s™ handy features is the tooltip that displays the OD and calculated result when a user hovers the cursor over a sample ID, and displays the sample ID and calculated result when a user hovers the cursor over the OD. Storing, aggregating, and displaying data is the ultimate purpose of ELISAWare™. These functions necessitate some sort of database.  We chose a Microsoft® Access®database for its speed, prevalence, and reliability.  Advanced users may find that they can re-locate this database, or even use multiple databases—and that the database is password protected to preserve data integrity.  Ordinary users will be content with storing their runs in the database and using ELISAWare’s™ built-in reporting features.  These features include the ability to generate separate reports for each group on a plate, each group in a run, or for a group across multiple runs and multiple tests.  There are both client reports, which merely list sample, test date, and results, and analytical reports intended largely for internal laboratory use.  These latter additionally show ODs, %I or S/P, test used, read date, etc.  While we based these report layouts on customer input and our own experience, we expect that, asELISAWare™ is used in the field, customers will help us fine tune them for maximum usefulness.  We look forward to your input. rom the perspective of displaying report data, we wanted ELISAWare™ to be as flexible as possible.  It is frustrating when reports are only useful for printing; we thought it would be great if one could copy results out of a report and paste them into Microsoft® Word® or Excel®.  It is annoying when you cannot get back into the software to check something because a report is open.  We thought it would be convenient to have reports open in a separate window.  A one-size-fits-all approach to report screen resolutions and font sizes always leaves some users squinting or leaning back for a more distant view.  We thought it would be nice if ELISAWare’s™ reporting engine had the flexibility to adapt to different screen resolutions and font-size preferences.  Sometime during all this thinking we realized that an Internet browser satisfied all of these requirements.  We gave it a try and the more we used it, the better we liked it.  We were careful to make the reports as adaptable to different browsers as possible, so whether you prefer Internet Explorer®, Firefox™, Opera™, or Netscape®, ELISAWare™ will display a readable and printable report in your default browser.  Furthermore, since the reports are composed of simple HTML, the standard markup language of the Internet, they have great potential for importation and manipulation in many different text-editing, word-processing, and spreadsheet programs. That concludes our tour of ELISAWare™.  We think that the hard work that we have invested has resulted in a good piece of software.  However, the opportunity to make it great software lies in your hands.  There is no way that we as programmers and assay developers can think of every desirable feature or catch every bug.  We encourage you to give us your input on this software—not only by reporting bugs, but by telling us how you wish the software worked.  We developed it; we can change it; and we are eager to make it useful to you!

It is often useful to know the titer of antibody in a serum for comparison with sera taken earlier or later from the same animal or for other purposes. The cELISAs made by VMRD recommend using undiluted sera and the results are scored as positive or negative.  These assays are adjusted to detect low as well as high amounts of antibody.  Therefore, moderate amounts of specific antibody will cause maximal % inhibition preventing using the % inhibition to differentiate sera with moderate and high antibody.  Of course, sera with low amounts of antibody that cause % inhibitions near the cutoff have less antibody than sera with higher % inhibitions.  However, sera with similar % inhibitions near maximal for a particular cELISA can have very different amounts of antibody.  These cELISAs can easily be turned into very quantitative tests by evaluating serial dilutions of a serum.  The endpoint can be determined for each dilution by scoring each dilution tested as positive or negative based on the % inhibition cutoff recommended for the kit being used. For instance, using the CAEV cELISA to test dilutions of 1:10, 1:100, 1:1000 and 1:10,000 of an infected goat’s serum results in a >60% inhibition at 1:10, 1:100 and 1:1000 dilutions with the 1:10,000 dilution causing <35% inhibition.  Since the recommended cutoff for a negative test in the CAEV cELISA is 35% or less, then the titer of the serum is 1:1000 in this example.  A similar procedure can be used to obtain antibody titers using the Anaplasma, Neospora, Babesia equi, Babesia caballi and Bluetongue virus cELISAs. One issue to keep in mind when determining antibody titers using these cELISAs is that antibody is being measured to a single epitope present on a single protein.  This is because a positive assay for antibody in all these tests depends on the antibody in the serum of interest inhibiting the binding of a monoclonal antibody.  The monoclonal antibodies are directed to an epitope on a protein or glycoprotein of the organisms for which antibody is being used.  Detecting antibody to a single epitope is not a problem since the monoclonal antibodies in each test were selected because sera from infected animals inhibited their binding.  This is the basis of the usefulness of these cELISA’s to detect specific antibody in infected animals.

Equine piroplasmosis is a tick-borne hemoparasitic disease of horses caused by Theileria equi, B. caballi or both. Piroplasmosis is known to be endemic in every country except the USA, Canada, England, Ireland, Japan and Australia. Thus, in these countries movement of horses serologically positive to either organism is restricted. For many years the complement fixation (CF) test was the Office International des Epizooties (OIE) prescribed test for piroplasmosis serology. However, as indicated in another article in this newsletter, the CF test has well-documented shortcomings that produce false negative results. It is for this reason that a plethora of horses carrying piroplasmosis have been imported into the USA in spite of statutory requirements for negative serology for T. equi and B. caballi on entry. In 1959 piroplasmosis was introduced into Florida and was not eliminated from the native horse population until 1982. Cases from new introductions of CF test negative carriers continue to occur in Florida. Several other states have also found seropositive carriers that were initially CF negative on entry to the USA. There are tick populations known to be capable of transmitting T. equi and B. caballi in large geographic areas of the USA outside of Florida. For these reasons in the late 1980s and early 1990s USDA Agricultural Research Service (ARS) scientists at Washington State University (WSU) began work based on recombinant antigens and monoclonal antibodies aimed at development of better diagnostic tests for equine piroplasmosis. The cELISAs developed by them have been adopted by OIE as the prescribed tests for international trade. VMRD, Inc. has acquired intellectual property licenses for these technologies and further developed them into uniform commercial diagnostic kits: Theileria equi Antibody Test Kit, cELISA and Babesia caballi Antibody Test Kit, cELISA. Each has undergone rigorous testing to insure high levels of sensitivity and specificity so that carriers of equine piroplasmosis can be detected prior to importation into the USA. Specificity of these kits was established by testing 2395 and 1924 samples of USA origin by the T. equi and the B. caballi cELISAs, respectively (Figures 1 and 2). All samples were negative for antibody to T. equi and only one sample (0.05%) was found positive by the B. caballi cELISA. Specificity for each assay with these large sample sets was 100% and 99.95%, respectively. It is reasonable to assume that the single B. caballi positive sample was in fact a true positive, perhaps an imported horse. Both kits were tested with check sets from NVSL and compared to results from the APHIS-OIE cELISA protocol (Figures 3 and 4). Results with the two kits correlated 100% with results from the APHIS-OIE protocol. The B. equi kit was further tested against a panel of 78 samples supplied by the USDA ARS Animal Disease Research Unit (ADRU) at WSU. Results compared to the APHIS-OIE cELISA protocol were identical. The B. caballi kit was tested against a panel of 106 samples supplied by ADRU at WSU. Four more positives were detected by the kit than by the APHIS-OIE cELISA protocol. However, these four samples were all very high negatives in the APHIS-OIE cELISA protocol, just below the cut-off, and thus quite possibly false negatives by the APHIS-OIE cELISA protocol. A panel of 158 samples from Thailand (a T. equi endemic country) were tested with the T. equi kit and by the CF test. Eighty-four samples were negative with both assays. However, only 17 of 74 (23%) cELISA positive samples were positive with the CF test. Twenty-three percent is remarkably similar to published findings in which the CF test detected only about 20% of Anaplasma cELISA / PCR positives.3 Clearly, we need to detect horses carrying T. equi and B. caballi PRIOR to their entry into the United States. The CF test is grossly inadequate for the task. Now that cELISA kits with high specificity and sensitivity far in excess of the CF test are available, importation of equids infected with B. equi and B. caballi is inexcusable. *Article updated 06/2024 to reflect modern nomenclature of "T. equi" and "Theileria equi". References 1. McGuire, T.C., et al. Functional properties of bovine IgG1 and IgG2: Interaction with complement, macrophages, neutrophils and skin. Immunology 38:249-256, 1979. 2. McGuire, T.C., et al. The complement-fixation reaction in equine infectious anemia: Demonstration of inhibition by IgG (T). J. Immunol. 107:1738-1744, 1971. 3. Bradway, D.S., et al. Sensitivity and specificity of the complement fixation test for detection of cattle persistently infected with Anaplasma marginale. J. Vet. Diagn. Invest. 13:79-81, 2001. 4. Torioni de Echaide, S., et al. Detection of cattle naturally infected with Anaplasma marginale in a region of endemicity by nested PCR and a competitive enzyme-linked immunosorbent assay using recombinant major surface protein 5. J. Clin. Microbiol. 36:777-782, 1998.

The complement fixation (CF) test is sometimes used for detection of antibody to infectious agents in domestic animals. There is a major problem with the use of this test to detect antibodies in serum for cattle, sheep, goats and horses. The problem is false negative reactions. These are caused by failure of antibody of certain isotypes to fix guinea pig complement which is the complement source used in standard CF tests. The presence of antibody of a non-complement-fixing isotype will result in a negative CF reaction even though antibody is present.(1) The problem is further compounded because non-complement-fixing antibody competes with the complement-fixing antibody for antigen. This also results in a negative reaction when, in fact, antibody is present.(2) It is bovine, sheep and goat IgG2 isotype antibody that does not bind guinea pig complement and this isotype is present in large quantities in the sera of these animals. That bovine IgG2 antibody fails to bind complement was first described in 1966 and verified in at least four other manuscripts (reviewed in reference 1). The same observations have been made with sheep and goat IgG2 antibodies. In horses, IgG(T), which is a major immunoglobulin isotype in serum, does not bind guinea pig complement (reviewed in reference 2). The severity of the problem of using CF for detection of cattle serum antibodies is clearly illustrated in a publication on detection of antibodies to Anaplasma marginale. Sera from 232 cattle were defined as A. marginale positive or negative by nested polymerase chain reaction methods and hybridization and evaluated for antibody using the CF test.3 The best estimate of the CF test sensitivity was 20%; this means that 80% of the A. marginale positive cattle were not detected. A cELISA detected 98% of the A. marginale positive cattle from the same cohort of cattle.(4) The cELISA detects antibodies of all isotypes. It was concluded from these studies that the CF test was ineffective for identifying cattle persistently infected with A. marginale.(3) A problem of similar magnitude has been documented in horses. Horses infected with equine infectious anemia virus (EIAV) are infected for life and have detectable antibody for life. However, the CF test is positive early after infection, but then becomes negative.(2) Purified IgG isotype antibody from the CF negative sera of infected horses was positive in the CF test. Purified IgG(T) isotype antibody from the same CF negative sera from infected horses was negative in the CF test. Mixing the purified IgG(T) and IgG isotype antibodies resulted in a negative CF test.(2) These observations provide an explanation for why the CF test with whole serum obtained later in EIAV infection is negative even though antibody to EIAV antigen is present and detectable by agar gel immunodiffusion which detects antibody of both isotypes. Based on these documented problems, the CF test should be avoided when the aim is to detect antibodies to infectious agents in cattle, sheep, goats and horses. Further, if the CF test is used, there will be very little correlation with the sensitivity obtained using other tests including ELISA, cELISA, immunofluorescence, and western blot that are not negatively affected by certain isotypes of the antibody. References 1. McGuire, T.C., et al.  Functional properties of bovine IgG1 and IgG2: Interaction with complement, macrophages, neutrophils and skin.  Immunology 38:249-256, 1979. 2. McGuire, T.C., et al.  The complement-fixation reaction in equine infectious anemia: Demonstration of inhibition by IgG (T). J. Immunol. 107:1738-1744, 1971. 3. Bradway, D.S., et.al.  Sensitivity and specificity of the complement fixation test for detection of cattle persistently infected with Anaplasma marginale.  J. Vet. Diagn. Invest. 13:17-81, 2001. 4. Torioni de Echaide, S., et al. Detection of cattle naturally infected with Anaplasma marginale in a region of endemicity by nested PCR and a competitive enzyme-linked immunosorbent assay using recombinant major surface protein 5.  J. Clin. Microbiol. 36:777-782, 1998.

In the last issue (VMRD Newsletter, April 2004) we saw how to use Microsoft Excel to calculate positive / negative values from optical density (OD) results of ELISA assays. This can be helpful in reducing faulty results caused by human error and human bias. However, it bears mentioning that blindly trusting a computer is a good way to produce nonsensical data. It is always a good idea to double-check the computer’s work. One thing that facilitates such an evaluation—as well as being useful for reporting purposes—is color coding of the data sheet. In this article, I will show you how to persuade Excel to automatically highlight cells or rows based on the data contained in them. You might use this functionality to highlight all positive samples, for instance. We will use the same data set used in the April article. It might be helpful to create a similar spread sheet in Excel so that you can follow along. To begin, we will select a row of cells and choose Conditional Formatting from the Format menu (Figure 1). In the ensuing Conditional Formatting dialog (Figure 2), choose “Cell Value Is” from the first pull-down menu, “equal to” from the second pull-down menu, and enter “Pos.” in the text box. This tells Excel what cells we want to format—in this case cells containing the text, “Pos.” Next, push the “Format . . .” button. In the ensuing dialog, we can specify the font, style, size and color of text; the style, color, and width of border; and the background color and pattern of cells that match the criteria that we previously chose. Right now we just want to highlight cells containing “Pos.” in yellow, so we go to the Patterns tab, click on the swatch that is our desired color of yellow, click OK, and OK again to close out of the Conditional Formatting dialog. If you’re following along with this tutorial, you may be surprised to find that, in spite of my earlier promises, only one cell on your worksheet is yellow. This is because we have yet to copy the formatting from that one yellow cell to the others. This process is facilitated by the Format Painter, a handy little tool that copies the format of whatever area is highlighted when the tool is selected and then “pastes” that formatting on to whatever area is highlighted immediately after it is selected. Make sure that your cursor is on the cell to which you applied conditional formatting and double click the Format Painter icon in the toolbar. Use the resulting Format Painter cursor to click on each cell to which you wish to apply conditional formatting. You can also click and drag over contiguous cells in order to apply formatting to them. When you are finished applying your conditional formatting to all the cells you desire, click on the Format Painter icon in the toolbar once again in or to put it away. Incidentally, it is possible to single click the Format Painter when getting it out of the tool box. In this case it behaves somewhat differently in that it puts itself away immediately after you have finished highlighting one cell or range of cells with it. Using it this way will work just fine, but I find it more convenient to use it as many times as I want and then put it away. At this point you will find that your spreadsheet looks like Figure 4 with only cells that actually contain “Pos.” highlighted in yellow. My preference is to have not only the result, but also the OD and the sample identification highlighted. To do this, highlight cells A3:C3, choose Conditional Formatting from the Format menu, change the first pull-down menu to “Formula Is”, type “=$C3=“Pos.”” in the text box to its right, and use the Format button to specify a yellow background (Figure 5). Then use the format painter as previously described to copy the format from cells A3:C3 to cells A4:C8. The resulting formatted spread sheet is shown in Figure 6. The “$” preceding the cell address is important in this formula; without it only the cells in column C would be highlighted in yellow because Excel will change the “C3” to “B3” when it copies the formatting formula to column B. Of course, the value in B3 does not equal “Pos.” so the cell will not be highlighted. Having highlighted all of our positives, we may want a count of how many positives or negatives exist in our data set. This is easily accomplished using Excel’s COUNTIF worksheet function. The syntax of this function is as follows: COUNTIF(range_of_cells_to_be_examined, criteria_for_counting). If we add the formula, “=COUNTIF(C3:C8, “Pos.”)” to Cell C9 on the tutorial spreadsheet, Excel will count the total number of positives and place the number in well C9. Likewise, placing the formula, “=COUNTIF(C3:C8, “Neg.”)” in cell C10 of the tutorial spreadsheet will cause Excel to count the total number of negatives and place the number in cell C10. The complete spreadsheet, along with the formula for counting positives, is shown in Figure 7. In this article I have hopefully elucidated several techniques that can significantly reduce human error associated with interpreting OD data, but I must reiterate that it is always a good practice to check and double check. Excel almost never makes a mistake, but it is fairly easy to make mistakes with Excel, either through error or misunderstanding.

A survey of 93 dairy and five beef herds from five regions of the United States revealed that at least one cow in 90% of the herds was seropositive for antibody to Neospora caninum (1). The prevalence of seropositive cattle in these herds was 2 to 65%. With Neospora caninum, seropositive cattle are infected because the organism is persistent and not cleared. There are several problems that result from having seropositive cows in a herd. The major problem is production losses from decreased milk production and abortion. Independent studies in the United States demonstrated that seropositive cows had decreased milk production of 2.5 lbs./day/cow in one study (2) and 2.8 lbs./day/cow in another study (3) when compared with seronegative cows. In the later study, decreased milk production caused a $128 loss per lactation period/seropositive cow. Another major problem with having seropositive cows in a herd is that vertical transmission occurs. The frequency of vertical transmission varies considerably, but can reach 100% (4). A recent evaluation of economic considerations for diagnostic and control options for Neospora caninum-induced abortion in beef cattle used a 5-year economic simulation model (5). A seroprevalence of 10% in cow-calf herds decreased mean return to fixed assets by 22.2%. The control strategy with the best economic return involved testing the entire herd for antibodies to Neospora caninum and excluding heifers from seropositive cows as replacements (5). References 1. Rodriguez I, L Choromanski, SJ Rodgers, and D Weinstock. Survey of Neospora caninum antibodies in dairy and beef cattle from five regions of the United States. Vet. Ther. 3:396-401, 2002. 2. Thurmond MC, and SK Hietala. Effect of Neospora caninum infection on milk production in first-lactation dairy cows. J. Am. Vet. Med. Assoc. 210:672-674, 1997. 3. Hernandez J, C Risco, and A Donovan. Association between exposure to Neospora caninum and milk production in dairy cows. J. Am. Vet. Med. Assoc. 219:632-635, 2001. 4. Campero CM, DP Moore, H Lagomarsino, AC Odeon, M Castro, and H Visca. Serological status and abortion rate in progeny obtained by natural service or embryo transfer from Neospora caninum-seropositive cows. J. Vet. Med. B Infect. Dis. Vet. Public Health 50:458-460, 2003. 5. Larson RL, DK Hardin, and VL Pierce. Economic considerations for diagnostic and control options for Neospora caninum-induced abortions in endemically infected herds of beef cattle. J. Am. Vet. Med. Assoc. 224:1597-1604, 2004.

According to the third edition of Veterinary Virology (1999), “Canine distemper is the most important viral disease of dogs, producing high morbidity and mortality in unvaccinated populations worldwide.” However, for many years, perhaps 20 or 30, canine distemper (CD) has not been the significant clinical problem it once was in the United States presumably because of our high rate of vaccination. That is, until recently. Popular literature and even professional veterinary publications are replete with the idea that we are vaccinating dogs too much. Now it appears that CD may be making a comeback. Do we have too many unvaccinated dogs and/or is a new strain able to overcome protection of current vaccines? Nikki Proutsos, Executive Director of Chicago Animal Care and Control, has recently stated that there have been over eighty confirmed cases of CD in the Chicago area since May of this year against no confirmed cases in 2003. The situation has prompted Chicago Animal Care and Control to suspend their dog adoption program. This apparent outbreak is not limited to Chicago, but seems to be occurring in multiple states east of the Mississippi river especially in kennels, pet stores and animal shelters. Diagnosis of CD can be a clinical challenge but laboratory confirmation is not difficult with good reagents. In late August of this year blood samples and organs of five dogs were submitted to American BioResearch by Dr. Page for conformation of CD. Tissues were cultured for the presence of virus and impression smears of brain and lung tissues were examined by direct immunofluorescence (DFA). Sera were titered for CD virus (CDV) specific IgG and IgM by IFA as previously described.(1) Samples were sent to VMRD, Inc. for DFA of blood and cryostat sections of lung and brain tissues. Reagents used: CDV FA substrate slide (VMRD 210-88-12-CDV), CDV IgG positive control (VMRD 211-P-CDV-G), CDV IgM positive control (211-P-CDV-M), anti-canine IgG FITC conjugate (VMRD 035-10), serum diluting buffer (VMRD 210-93-SB), rinse buffer (VMRD 210-90-RB), mounting fluid (210-92-MF), CDV direct FA conjugate/polyclonal (VMRD 210-02-CDV), and CDV control slide (VMRD 210-88-2-CDV). Table 1, Clinical Data, provides details about the clinical presentation including ages and breeds of the dogs. Table 2, Diagnostic findings, details the results of the diagnostic work performed by ABR and VMRD. Figures 1-5 are digital photomicrographs of DFA results on cryostat sections. Clinical Data Diagnostic Findings References 1. Black, John W., “Single Serum-Sample Diagnosis of Canine Viral Diseases,” VMRD, Inc. Newsletter, Volume 1, No. 2, October 1994.

“What’s in a name? That which we call a rose by any other name would smell as sweet.”  It might smell as sweet, yes, but it would be much harder to remember.  In our lab we have experienced some confusion resulting from recent nomenclature changes.  Hopefully the following digest of some recent name changes relevant to veterinary diagnostics will reduce confusion for other labs as well as for our own. Perhaps the most baffling changes in nomenclature have been in the order Rickettsiales.  The taxa designations in this order were previously based on morphological, ecological, epidemiological and clinical characteristics. A 2001 publication by Dumler et al.(5) proposed re-classification based on genetic analysis of 16S rRNA, groESL, and surface protein genes.  A number of species formerly classified in the genera Anaplasma, Ehrlichia, Cowdria, Neorickettsia andWolbachia have been re-arranged into the genera Anaplasma, Ehrlichia, Wolbachia, and Neorickettsia.  Ehrlichia equi has been determined to be insufficiently distinct from either Ehrlichia phagocytophila or the human granulocytic ehrlichiosis (HGE) agent to justify separate species designations for any of these pathogens.  Moreover these three agents have been—or rather, this agent has been—determined to belong in theAnaplasma genus.  Thus Ehrlichia equi, Ehrlichia phagocytophila, and HGE are all now designated Anaplasma phagocytophila.  Another former Ehrlichia, Ehrlichia risticii, now belongs to the Neorickettsia genera; it is now known as Neorickettsia risticii.  Other Rickettsiales changes include:  Ehrlichia bovis is now Anaplasma bovis;Cowdria ruminatum is now Ehrlichia ruminatum; Ehrlichia platys is now Anaplasma platys; and Ehrlichia sennetsu is now Neorickettsia sennetsu.  Further changes have been made higher up the taxonomic tree that I will not treat here; they are detailed extensively in the Dumler publication. In a 1998 publication by Mehlhorn and Schein(6) it was argued that Babesia equi should be re-designated Theileria equi.  Among other reasons cited for the reclassification was the fact that equi, in common with Theileria spp. first infects lymphocytes wherein it inititates a schizogonic phase resulting in the production of motile merozoites.  By contrast, other Babesia species first enter erythrocytes.  Also in common with Theileria spp. is equi’s development in the salivary glands of its vector ticks.  Typical ofTheileria spp., equi is not present in tick organs other than salivary glands and is not transmitted transstadially from egg to larva (though it can be transmitted transstadially from nymph to adult stages).  Babesia spp. generally infect other tick organs in addition to the saliva glands and transstadial transmission from egg to larva is typical. The morphology of sexual stages of equi differs from that of typical Babesia spp. Moreover, equi shares a surface protein common to Theileria spp.  Furthermore, drug susceptibility of equi is similar to Theileria spp. and differs from Babesia spp.  The membership of equi in the genus Theileria is also supported by ssRNA analysis. Thus there is compelling developmental, morphologic, biochemical, and genetic evidence supporting equi’s classification as a Theileria spp. and Theileria equi is beginning to be the accepted designation, though Babesia equi is still widely used. Oh, you were hoping for interesting reading?  May I suggest Romeo and Juliet by William Shakespeare?

Cattle persistently infected with Anaplasma marginale are a major reservoir for transmission of anaplasmosis.  This is because a main mode of transmission is by ticks, yet the ticks involved in transmission do not transmit the organism to their progeny through the eggs.  This lack of transovarial transmission means that new generations of ticks must acquire infection by feeding on an A. marginale-infected host.  Once an immature tick stage acquires infection, it is transmitted to subsequent developmental stages, including the adult stage.  Any infected stage that feeds on cattle can transmit the infection during feeding. Uninfected ticks can acquire A. marginale infection by feeding on cattle which have very low numbers of infected erythrocytes.  In fact, the number of infected erythrocytes can be 10 to 10,000 times less than can be detected by microscopic examination of stained blood smears. Once the tick is infected from small amounts of organisms obtained by feeding on persistently infected cattle, organisms replicate to high levels in the tick’s salivary gland and can be transmitted to uninfected cattle during feeding. Based on this information, ticks cannot be a long-term reservoir for A. marginale. However, cattle are infected with A. marginale for life and can serve as a continual source of infection for tick populations which can then transmit to uninfected cattle.  The information that cattle are a major reservoir of A. marginale provides a rationale for testing herds in regions where anaplasmosis occurs and removing infected cattle from these herds.  Since antibody is continuously present in A. marginale-infected cattle, testing for antibody is the easiest and most economical way to identify persistently-infected cattle for treatment with long-acting oxytetracycline or culling. References: Stich RW, Kocan KM, Palmer GH, Ewing SA, Hair JA, Barron SJ. Transstadial and attempted transovarial transmission of Anaplasma marginale by Dermacentor variabilis. Am J Vet Res. 50:1377-1380, 1989. Eriks IS, Stiller D, Palmer GH. Impact of persistent Anaplasma marginale rickettsemia on tick infection and transmission. J Clin Microbiol. 31:2091-206, 1993.