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Effects of strain, sex and age on immunophenotyping parameters in the rat and mouse

Effects of strain, sex and age on immunophenotyping parameters in the rat and mouse Immunophenotyping of lymphocyte subsets can be a useful addition to toxicological or investigatory studies where there is the potential for effects on the immune system. We have validated assays for rat or mouse lymphocytes using a FACSVerse flow cytometer and FACSuite software, with commercially available antibodies. Whole blood was stained using the following markers: Rat—CD3, CD45RA, CD161a, CD4 and CD8; mouse—CD3e, CD19, NK1.1, CD4 and CD8. This allows detection and quantitation of T cells, B cells, NK cells, T helper cells and T cytotoxic cells. The stopping criteria for analysis were set at 30,000 lymphocytes, although data were considered acceptable if a minimum of 5000 lymphocytes were counted. To maintain the same analysis protocol throughout and across studies, an assay was created for each species in the FACSuite software. Assay functionality uses CS&T beads for performance quality control and assay setup to ensure that laser settings remain consistent and compensation settings are such that any drift in machine performance does not affect results. Blood samples from both sexes and the following ages and strains were analysed: Rats—2, 4 and 7 months, Crl:WI(Han) and 2 months Crl:CD(SD); mice—2–3, 4–6 and 7–8 months, Crl:CD1(ICR). In general, there was a low level of variation within the results for each sex or age group. However, there are strain, sex and age differences that should be considered when evaluating results from immunophenotyping analysis or when planning studies where there may be an immunological effect. . . . . Keywords Immunophenotyping Flow cytometry Rat Mouse Strain effects Introduction population can be generated to complement and enhance the data collected in routine haematology analysis. It can also Immunophenotyping uses specific antibodies for each cell of contribute to the translation of the effects in animals to humans interest to identify specific leukocyte subsets. Although it can as the ICH S8 guideline on immunotoxicity studies for human be conducted using immunohistochemistry, it is increasingly pharmaceuticals state, BData obtained from peripheral blood being performed by flow cytometry in order to obtain quanti- can be useful as a bridge for clinical studies in which periph- tative data. While immunohistochemistry offers its own ad- eral blood leukocytes are also evaluated.^ (ICH 2005). vantages, an assay using commercially available, specific, Immunophenotyping is recommended in pre-clinical studies fluorescently tagged antibodies allows for the direct interro- when there is the potential for adverse effects on the immune gation of a blood sample by multicolour flow cytometry. system by pharmaceuticals and is generally used within the Multiple cell types can be identified and quantified in a single context of a wider immunotoxicity investigation. For reference, blood sample, helping to limit sample volume, which is par- immunotoxicity is the unintended enhancement or suppression ticularly useful in the rodent species routinely used for pre- of theimmunesystem(ICH 2005) and the conduct of this in- clinical toxicology. By immunophenotyping peripheral blood, vestigation is based on the weight of evidence for the compound data on specific components of the white blood cell (WBC) which will also influence the species and strain used for testing. The assays used in this paper were setup on the FACSVerse flow cytometer using FACSuite software. The functionality of this software allows for assay-based function and uses CS&T beads * Brenda Finney for performance quality control and assay setup to ensure that brenda.finney@sequani.com laser settings remain within a specific range and compensation Sequani Limited, Bromyard Road, Ledbury, Hereford HR8 1LH, UK settings are correct for each fluorophore used. These 42 Comp Clin Pathol (2019) 28:41–51 compensation settings are such that any drift in machine perfor- differences when planning a study or evaluating the data pro- mance does not affect results over time, ensuring that the same duced from an investigation. analysis protocol is performed throughout all studies, which is an important aspect of validation within a GLP-compliant facili- ty and aids in the evaluation of data for regulatory purposes. The Materials and methods assay validation was based on recommendations in partner publications by Green et al. (2011)and O’Hara et al. (2011)in All samples were analysed on a FACSVerse flow cytometer the Journal of Immunological Methods. using FACSuite software (BD Biosciences, UK). After initial For the detection and quantitation of T cells, B cells, NK setup, an assay was created with specific tube settings and cells, T helper cells and T cytotoxic cells, whole blood was gates relevant to each assay. This ensured that all sample anal- stained using markers relevant for each species. In the rat, ysis was done to the same specifications. Tube and assay set- CD3, CD45RA, CD161a, CD4 and CD8a were used. In the tings were set using Research FC beads (BD Biosciences, mouse, CD3e, CD19, NK1.1, CD4 and CD8 were used. UK). Cytometer setup and quality control were performed on Blood samples from both sexes and the following ages and each day of cytometer use according to the manufacturer’s strains were analysed: Rats 2 months Crl:CD(SD), 2, 4 and instructions using CS&T beads. Due to the ability to use 7 months Crl:WI(Han); mice 2–3, 4–6and7–8months, CS&T and Research FC beads for the setup and maintenance Crl:CD-1(ICR). The objective of this study was to compare of the compensation settings needed for each assay, isotype and contrast data across strains, sexes and ages, in order to controls were not used. However, depending upon the analyser understand the variation of these factors when choosing ex- used, isotype controls may be required when establishing this perimental subjects. The data contained in this paper are also assay in other laboratories. Additionally, Comp beads, with used as historical control data, for comparison to data collect- positive and negative populations, can be used to determine ed during regulatory toxicological investigations. It is hoped parameters for the specific antibodies used in each assay. that the protocols and data presented in this paper will be of Specific consumables purchased from BD Biosciences, UK, use to other laboratories that are performing or looking to have specific information provided in Table 1. perform this type of assay on these species and strains. Difference in gating strategies between analysts, analysers Methods and laboratories is a primary reason why flow cytometry data sets are difficult to compare. To control for this in our labora- Use of animals tory, we have used the assay functionality of the FACSuite software in conjunction with the FACSVerse flow cytometer. All institutional and national guidelines for the care and use of This function ensures that when gates are set and saved as part laboratory animals were followed and all animal work was of the assay, the gates are in the same position for each sample conducted under authority of a Project Licence in compliance each time the assay is opened. In terms of GLP compliance, it with the Animals (Scientific Procedures) Act 1986 (as also ensures that the initial settings of the assay can be com- amended). Euthanasia and blood collection were done accord- pared with any data used for reporting, and changes can be ing to routine standard operating procedures. detected or annotated between samples or days of analysis. As a part of the assay function, compensation settings are routine- Blood sampling and sample processing ly checked and updated using quality control beads. These beads are either fluorophore-specific, Research FC beads or Blood was collected from either the sublingual vein (rats on- wide-spectrum CS&T beads. There have been initial steps ly), abdominal vena cava (both species) or orbital sinus (mice taken to standardise or automate gating strategies across insti- only) into tubes containing K EDTA depending upon the tutions and platforms, but as of yet, these are not widely used. study type from which the animals were taken. The tubes were Due to the use of mice in immunology research, there ap- then mixed on a roller at room temperature for 5–10 min. pears to be a greater amount of published material on the After mixing, they were kept on ice or at 2–8 °C until proc- immunophenotype found in mouse strains than in rat strains. essed. Processing was performed on the day of collection. Cell However, data on the Crl:CD1(ICR) mouse strain were not counts were performed on an ADVIA 120 (Siemens, UK) found, nor were there data comparing different ages. Although haematology analyser and samples were normalised to 1 × published data on rat strains were limited, information was 10 lymphocytes/mL with phosphate buffered saline (PBS). found on immunophenotyping in RccHan:Wist (Yamatoya After normalisation, antibodies were added to the sample at et al. 2012) and Sprague Dawley (Morris and Komocsar, the concentrations listed in Table 1. The samples were incu- 1997). This paper expands the available strain data and pro- bated in the dark at room temperature. The incubation was vides a direct comparison of results between two rat strains ended by the addition of 20× volume of FACSLyse and and shows that it is worth considering age, sex and strain vortexed. Samples were then centrifuged at 500g for 5 min, Comp Clin Pathol (2019) 28:41–51 43 Table 1 Reagents and consumables used for immunophenotyping assays Reagent Catalogue Assay Cell types and fluorophore Amount used per test (if applicable) number species CS&T beads 650621 N/A N/A N/A FACSLyse 349202 N/A N/A 20× sample volume T, B, NK cell cocktail 558495 Rat T cell: CD3, APC 10/100 μL sample at 1 × 10 lymphocytes/mL B cell: CD45RA, FITC NK cell: CD161a, PE CD45 antibody 561586 Rat Lymphocytes, APC-Cy7 2/100 μL (rat) 200 μL (mouse) sample at 1 × 10 (Used during initial assay setup, information 557659 Mouse lymphocytes/mL included for reference) T lymphocyte cell cocktail 558493 Rat T cell: CD3, APC 10/200 μL sample at 1 × 10 lymphocytes/mL T helper cell: CD4, PE T cytotoxic cell: CD8a, FITC T lymphocyte cell cocktail 558431 Mouse T cell: CD3e, PE-Cy7 10/200 μL sample at 1 × 10 lymphocytes/mL T helper cell: CD4, PE T cytotoxic cell: CD8, APC CD19 antibody 557398 Mouse B cell: FITC 2/200 μL sample at 1 × 10 lymphocytes/mL NK1.1 antibody 560618 Mouse NK cell: APC-Cy7 2/200 μL sample at 1 × 10 lymphocytes/mL most of the supernatant removed and 2 mL PBS added. The characteristics; when labelled with CD45, the constituents of 4 5 cells were resuspended by tapping the tube and then centri- this gate showed fluorescence in the 10 –10 region on a log fuged at 500g for 5 min. The supernatant was then removed scale. The lymphocyte population gate in the FSC vs. SSC dot and the cells resuspended in 300 μL PBS for analysis. plot was used as the gate for the stopping criteria of 30,000 lymphocytes. As FSC and SSC characteristics should not change greatly between animals, the use of the CD45 marker Rat immunophenotyping was discontinued after several samples confirmed the location of the gate on the FSC vs. SSC plot. Sub-population gates Data were collected from animals of both sexes in the were also confirmed by plots comparing the different CD Crl:WI(Han) and Crl:CD(SD) strains (Charles River, UK). markers used to each other to check for overlap. The age of the animals varied by strain. Crl:CD(SD) data were collected at 2 months of age while Crl:WI(Han) data were obtained at 2, 4 and 7 months of age. Comparisons between Mouse immunophenotyping strains were made on animals of the same sex and similar ages. This assay was performed as a two-tube assay which was Data were collected from both sexes in the Crl:CD1(ICR) strain (Charles River, UK) at 2–3, 4–6and 7–8months of age. dictated by the fluorophores available in the staining cocktails. One tube was the lymphocyte assay which counted T, B and This was a single-tube assay for all cell types. Samples were analysed until 30,000 cells in the lymphocyte gate were NK cells; the second tube counted T cells, CD4 + T helper cells and CD8 + T cytotoxic cells using the staining cocktails counted. Samples were accepted if at least 5000 lymphocytes were counted. Stability was tested during the validation; how- in Table 1. In the T, B and NK cell assay, samples were analysed until 30,000 cells in the lymphocyte gate were count- ever, changes in cell populations in the conditions tested on subsequent days required that samples be analysed on the ed. Samples were accepted if at least 5000 lymphocytes were counted. In the T cell subset, tube samples were analysed until same day. The gating strategy for this assay is shown in Fig. 3. 5000 T cells were counted and accepted if at least 2500 T cells were counted. Samples were checked for stability with both of Data and statistics the staining cocktails. Sample results were acceptable only on the day following collection where samples had been stained, The data collected included both the absolute cell counts and lysed and washed prior to storage at 2–8°C. the percentage of the cell subtypes present in the parent pop- The gating strategies for these assays are shown in Figs. 1 ulations, either lymphocytes or T cells depending on the cell and 2. The initial assay setup utilised the pan-lymphocyte types. Data were correlated in a Microsoft Excel spreadsheet marker CD45 labelled with APC-Cy7 to confirm the estab- before transfer to GraphPad Prism (GraphPad Software, CA, lishment of the lymphocyte population gate. The lymphocyte USA), which was used for graph production and statistical cluster was initially identified based on FSC and SSC analysis. T helper:T cytotoxic ratio for 2-month rat samples 44 Comp Clin Pathol (2019) 28:41–51 Fig. 1 Gating strategy in rat T, B and NK cell assay. a FSC vs. SSC expression of CD3. d Blue gate indicating B cell population based on graph, orange circle highlights the lymphocyte population. b Gating CD45RA expression. e Green gate indicating NK cell population based hierarchy for assay. c Purple gate indicating T cell population based on on CD161a expression Fig. 2 Gating strategy in rat Tcell subset assay. a Gating hierarchy for assay. b Purple T cell gate based on CD3 expression. c Green circle gate for T helper cell population based on CD4 expression. d Red circle gate for T cytotoxic cells based on CD8 expression Comp Clin Pathol (2019) 28:41–51 45 Fig. 3 Gating strategy for mouse immunophenotyping assay.a FSC vs. indicating NK cell population based on NK1.1 expression. e Green gate SSC graph, orange circle highlights the lymphocyte population. b Purple indicating T cytotoxic cell population based on CD8 expression. f Blue gate indicating Tcell population based on expression of CD3e. c Red gate circle gate indicating T helper cell population based on CD4 expression indicating B cell population based on CD19 expression. d Teal circle gate was calculated by dividing the absolute T helper cell number absolute numbers and percentages as well as in data sets (CD4+) by the absolute T cytotoxic cell number (CD8+); this compared. Therefore, different numbers of animals would is also called the CD4:CD8 ratio. Statistical analysis was per- be required to increase the power depending upon the cell formed on cell percentages as initial analyses showed that type of interest. As this is not practical, we recommend that absolute counts and percentages gave the same results. The each laboratory have an understanding of the power statistical test performed was a non-parametric, two-tailed t achieved by their study design and potential effects on data test with Mann-Whitney. Statistical significance was consid- interpretation. In general, where statistical significance was ered to have been reached when p ≤ 0.05. achieved, the power was as follows: * = 0.5–.65, ** = Post hoc power analysis was conducted on the results pre- 0.79–.93and***=0.72–1. As this data is intended for sented in Tables 2 and 3, both absolute numbers and percent- use as background data, the power will change as data is ages, using G*Power 3.1 (Dusseldorf, Germany). The settings continually added from control animals on our routine were as follows: test family = t tests; statistical test = means studies. Wilcoxon-Mann-Whitney test (two groups); type of power analysis = post hoc compute achieved power given α,sample size and effect size. Input parameters were two-tailed, normal Rat immunophenotyping parent distribution, α err prob = 0.05. The effect size was calculated based on the observed means and SDs, and the Strain differences sample sizes were as listed in the data. Results of this analysis varied by cell type and data sets compared. The data for this analysis is presented in Table 2. At 2 months of age, there are significant differences in the percentage of cells which make up the lymphocyte and T cell sub- Results populations in Crl:WI(Han) vs. Crl:CD(SD) rats. These dif- ferences occur in both sexes for B cells, T helper and T cyto- toxic cells, while there is a statistically significant change in Power analysis the T cell population for males only. The NK cell population is the only population where there is no apparent significant Assessment of the statistical power of these data sets re- difference between the strains. vealed variation in the power achieved between cell types, 46 Comp Clin Pathol (2019) 28:41–51 Table 2 Rat immunophenotyping results by sex and strain, at 2 months of age, mean ± SD. Statistical test was a non-parametric, two-tailed t test with Mann-Whitney comparing results between sexes. Statistical significance was considered to have been reached when p ≤ 0.05, asterisks indicate level of significance. Number in parentheses below results = n Sex T cell number % T cells B cell %B cells NKcell % NK cells T helper %Thelper T cytotoxic %T number number cell cells number cytotoxic number cells Crl:WI(Han) Male 12,411 ± 1790 41.39 ± 5.99 7662 ± 1655 25.55 ± 5.51 1940 ± 833 6.47 ± 2.78 3635 ± 168 72.72 ± 3.35 1362 ± 173 27.25 ± 3.46 (28) (28) (28) (28) (28) (28) (19) (19) (19) (19) Female 13,871 ± 2692 46.24 ± 8.97 6614 ± 1824 22.04 ± 6.08 2708 ± 281 9.03 ± 0.93 3731 ± 236 74.64 ± 4.72 1191 ± 150 23.83 ± 3.01 (12) (12) (12) (12) (12) (12) (13) (13) (13) (13) Sex difference p = 0.13 0.15 0.008** 0.08 0.009** T helper:T cytotoxic ratio Male Female (CD4:CD8) 2.7 ± 0.5 3.2 ± 0.5* Crl:CD(SD) Male 11,244 ± 1308 37.48 ± 4.36 9138 ± 1196 30.46 ± 3.99 2554 ± 685 8.87 ± 2.35 3396 ± 174 67.99 ± 3.48 1614 ± 171 32.31 ± 3.42 (14) (14) (14) (14) (14) (14) (16) (16) (16) (16) Female 12,718 ± 1703 42.39 ± 5.68 8148 ± 1503 27.16 ± 5.01 3233 ± 766 10.78 ± 2.55 3316 ± 118 66.35 ± 2.39 1686 ± 128 33.74 ± 2.56 (12) (12) (12) (12) (12) (12) (16) (16) (16) (16) Sex difference p = 0.017* 0.046* 0.085 0.61 0.54 T helper:T cytotoxic ratio Male Female (CD4:CD8) 2.1 ± 0.4 2.2 ± 0.3 Male strain difference p = 0.035* 0.002** 0.11 0.0002*** 0.0002*** Female strain difference p 0.19 0.04* 0.55 0.0001*** < 0.0001*** = Comp Clin Pathol (2019) 28:41–51 47 Table 3 Mouse immunophenotyping results by sex and age, mean ± SD. Statistical test was a non-parametric, two-tailed t test with Mann-Whitney comparing results between sexes at each age. Statistical significance was considered to have been reached when p ≤ 0.05, asterisks indicate level of significance. Number in parentheses below results = n Sex T cell number % T cells B cell number % B cells NK cell % NK cells T helper cell %Thelper T cytotoxic %T number number cells number cytotoxic cells 2–3 months Male 12,117 ± 2011 40.39 ± 6.70 13,059 ± 2523 43.53 ± 8.41 2432 ± 976 8.11 ± 3.25 8126 ± 1472 67.04 ± 4.37 3019 ± 782 24.86 ± 4.23 (24) (24) (24) (24) (24) (24) (24) (24) (24) (24) Female 13,680 ± 2342 45.60 ± 7.81 10,720 ± 2815 35.73 ± 9.38 3277 ± 1182 10.92 ± 3.94 8937 ± 1259 65.85 ± 5.47 3400 ± 872 24.78 ± 4.49 (23) (23) (23) (23) (23) (23) (23) (23) (23) (23) Sex difference 0.022* 0.0047** 0.003** 0.44 0.86 p = 4–6 months Male 13,772 ± 2410 45.91 ± 8.03 8996 ± 2874 29.99 ± 9.41 2855 ± 898 9.52 ± 2.99 8975 ± 1670 65.33 ± 6.66 3667 ± 890 26.63 ± 4.50 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Female 13,672 ± 2566 45.57 ± 8.55 7350 ± 1840 24.50 ± 6.13 3597 ± 1182 11.99 ± 3.94 9453 ± 1435 69.86 ± 5.89 3132 ± 1237 22.21 ± 6.27 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Sex difference 0.99 0.017* 0.069 0.054 0.024* p = 7–8 months Male 12,333 ± 2582 41.11 ± 8.61 11,666 ± 3653 38.89 ± 12.18 2111 ± 1037 7.04 ± 3.46 8154 ± 1784 66.28 ± 7.80 3272 ± 1029 26.55 ± 7.11 (19) (19) (19) (19) (19) (19) (19) (19) (19) (19) Female 13,837 ± 3773 46.12 ± 12.58 9917 ± 2256 33.06 ± 8.52 2388 ± 811 7.96 ± 2.70 8040 ± 2705 57.25 ± 7.69 4051 ± 1061 29.88 ± 5.73 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Sex difference 0.075 0.13 0.33 0.0013** 0.25 p = 48 Comp Clin Pathol (2019) 28:41–51 Sex differences T and NK cells only at 2–3 months and in T cytotoxic cells at 4–6months. At 2 months of age, Crl:WI(Han) animals have statistically significant differences in amounts of NK and T cytotoxic cells Age differences in their lymphocyte pool depending upon their sex (Table 2). Females show an increased number of NK cells and decreased Data are presented in Table 3 and statistical information is number of T cytotoxic cells in comparison to males. There is contained in Fig. 5. As mice age from 2 to 3 months to 4– also a statistically significant difference in the T helper/T cy- 6 months, regardless of sex, there is a decrease in the B cell totoxic (CD4:CD8) ratio between the sexes in this strain. number and increases in the NK cell numbers. Statistical sig- At 4 and 7 months of age (Fig. 4), there are statistically nificance is reached for B cells when comparing 2–3and 4– significant differences in the percentage of B cells in the lym- 6 months. In NK cells, statistical significance is reached when phocyte pool with females having fewer B cells than males. comparing 2–3and4–6 months in males but not females. This The only other significant difference is seen in the T cell pop- trend appears reversed at 7–8 months where there is an in- ulation at 7 months of age where females have higher numbers crease in the B cell number and decrease in the NK cell num- of T cells. All other populations show no difference between ber. The changes in B cell numbers for both sexes are statis- the sexes at these ages. tically significant when comparing 4–6and7–8 months, while At 2 months of age, Crl:CD(SD) animals have statistically in NK cells, statistical significance is reached when comparing significant differences in amounts of T and B cells in their 4–6and 7–8months in males and 2–3or4–6and7–8months lymphocyte pool depending upon their sex (Table 2). in females. The T cell populations appear to be more stable in Females show an increased number of T cells and decreased mice and the only point of statistical significance was an in- number of B cells in comparison to males. crease in male T cell numbers when comparing 2–3and4– 6 month data. Interestingly, there are changes in the T cell sub- populations in females which appear to be age related and do Age differences not appear to affect the overall T cell numbers. T helper cell numbers are initially higher at 4–6 months and then fall at 7– In the Crl:WI(Han) strain, there were age-related differences 8 months. Statistical significance is reached when comparing in the percentages of cells which make up the lymphocyte data from 2 to 3 or 4–6and7–8 months. These changes are pool (Fig. 4). As rats age, there are increases in the number accompanied by the opposite pattern in the T cytotoxic cell of B cells with decreases in the NK cell numbers. These population with the same pattern of statistical significance. changes are statistically significant between 2 and 4 or 7 months, but not between 4 and 7 months. T cell populations show a different pattern of change with a decrease in T cell Discussion numbers that is significant between 2 and 7 months or 4 and 7 months in males, but only between 2 and 7 months in fe- An important component of any assay used within a GLP- males. Interestingly, there are changes in the T cell sub-popu- compliant laboratory is the ability to perform the assay rou- lations, which do not appear to affect the overall T cell num- tinely, with the same parameters over days, weeks, months or bers. Higher numbers of T helper cells with age reached sta- even years. It is this reproducibility that allows for the pro- tistical significance between 2 and 4 or 7 months in males, and gressive steps of toxicology investigations to show the safety between 2 and 7 or 4 and 7 months in females. These changes margins of a new treatment or chemical over different dose were accompanied by decreases in the T cytotoxic cell popu- levels, time periods, sexes and ages. Flow cytometric analysis lation that were statistically significant at all points tested in of peripheral blood cell populations can be an important part the males, and between 2 and 4 or 7 months in females. of this investigation, particularly where prior knowledge indi- cates that the immune system may be affected by a test item. Mouse immunophenotyping The FACSVerse flow cytometer and its associated software, FACSuite, is a useful system for ensuring that analysis is re- Sex differences producible when the Quality Control functions, tube and assay settings are used in conjunction with Assay Programming. Data are presented in Table 3 for each age and sex. In This system is geared towards the standardisation of collection Crl:CD1(ICR) mice, it appears that sex differences diminish parameters and protocols between users, instruments and lab- with age; as by 7–8 months, the only significant difference is oratories. Assay settings with gating protocols can be exported in the number of T helper cells making up the T cell pool. At and shared between laboratories. CS&T and Research FC younger ages of either 2–3or 4–6 months, sex differences are beads are used for instrument and assay setup, ensuring that seen in B cells. Statistically significant differences are seen in compensation settings are such that collection parameters are Comp Clin Pathol (2019) 28:41–51 49 Fig. 4 Immunophenotyping of Crl:WI(Han) rats at 2, 4 and 7 months cytotoxic cells). Each point is an individual animal. Error bars show the of age. a B cells. b NK cells. c Tcells. d T helper cells. e Tcytotoxic cells. mean ± SD. Asterisks indicate statistically significant differences between All results are presented as the percentage of cells making up their parent the ages in the same sex, *p ≤ 0.05; **0.005; ***0.0005; ****0.0001 population (lymphocytes for B, NK and T cells, T cells for T helper and T the same across time, instruments, laboratories and users. This studies so that if there are any changes induced by different system also has functions which allow for the electronic ap- batches of antibodies, these can be annotated as such. As an proval, annotation and electronic signature of data which con- additional control measure, the procedure of performing this tributes to GLP adherence and data security. analysis has been detailed in a method document which can- Regardless of the instrument and software used, an assay not be changed without review and signature of multiple sci- needs to be validated to ensure that it is functioning to an entists and changes to the assay itself cannot be performed acceptable standard. Validation also ensures that when an as- without administrator-level access rights to the FACSuite soft- say component is changed, antibody batches, for example, this ware. A copy of this method, electronic copies of the assay does not change the function or results of the assay. Validation setup prior to analysis, as well as all FCS, CSV and PDF files parameters tested for this assay included intra-assay (within- are kept with each study so that they may be reviewed as part run) precision, inter-assay (between-run) precision, sample of Quality Assurance assessments. fixation and stability and staining profile. In this case, samples The data sets presented in this paper have been collected were not stable enough to make a positive statement on inter- over multiple analysis days and offer insight with larger num- assay precision. However, intra-assay precision where sam- bers of samples compared to other published studies (Morris ples were stained and analysed in triplicate had coefficients and Komocsar 1997, Petkova et al. 2008, Pinchuk and Filipov of variation of less than ± 20%. This showed that the staining 2008, Yamatoya et al. 2012) which have indicated that sex and and analysis procedure did not introduce variability into sam- strain differences are present in lymphocyte sub-populations. ples. The staining profile of each cell type was plotted against But the effects of age have not been robustly assessed. While it the other markers used in the assay to show that there was is difficult to compare absolute cell numbers between pub- minimal number of cells which expressed multiple markers lished studies due to strain, collection and gating differences, and the expression profile of cells was as expected and listed it can be noted that the CD4:CD8 ratio obtained in this study in Table 1. The data from this study is compared against data for 2-month-old Crl:CD(SD) rats is similar to that published by Morris and Komocsar (1997) where they used Sprague from control (untreated) animals of a similar age in routine 50 Comp Clin Pathol (2019) 28:41–51 Fig. 5 Immunophenotyping of Crl:CD1(ICR) mice at 2–3, 4–6and T helper and T cytotoxic cells). Each point is an individual animal. Error 7–8months of age.a Bcells. b NK cells. c T cells. d T helper cells. e T bars show the mean ± SD. Asterisks indicate statistically significant cytotoxic cells. All results are presented as the percentage of cells making differences between the ages in the same sex, *p ≤ 0.05; **0.005; up their parent population (lymphocytes for B, NK and T cells, T cells for ***0.0005; ****0.0001 Dawley rats obtained from Charles River in the USA, as are detected in these data sets. However, as this data is intended the percentages of B cells and CD3+ T cells. Although as for use as background data, the power will change as data is shown here, strain differences can be marked and could exist continually added from control animals on our routine studies, between different suppliers of Sprague Dawley rats. and so may improve. Also, where statistical significance was Therefore, it is important that when published, there is specific achieved, the higher the significance the higher the power strain information so that comparability between studies can indicated, so while there may be some differences which are be assured. not yet distinguishable, the differences currently seen are The data collected here demonstrate that there is potential robust. for standard total lymphocyte counts to be overly simplistic In terms of toxicology investigations, generally, both abso- where there is potential for effects on the immune system. For lute cell numbers and percentages are used to evaluate any example, in the Crl:CD1(ICR) mouse data set, T cell numbers effects which may be induced by test articles. But, where do not vary widely across either sex or age; however, when the numbers are limited by stopping criteria, critical thought on sub-populations of T helper and T cytotoxic cells are investi- the scale and direction of any changes or differences is needed. gated, females show highly significant differences in the ratios It should be considered if an increase in one cell type results in of cells that make up their T cell population as they age. a decrease in another cell type or vice versa, it should be kept Similarly, in the same cell types in rats, although the changes in mind that this change may not be wholly reflective of the appear small (differences of 5–10%), they are highly statisti- cell number in the circulation. There is also the possibility that cally significant, particularly between the strains. Therefore, the cell types interrogated may miss a cell type, and therefore, discrimination of the counts or relative percentages of each decreases in the lymphocyte subsets counted may be due to an sub-population could indicate an aspect of toxicity or potential increase in a cell type which does not have a specific lympho- mechanisms of action not highlighted by the total lymphocyte cyte sub-gate in the protocol. As an example, there is a subset or even T cell count, which may not change. It is also possible of T cells, natural killer T cells, which may not express either that due under powering indicated in some parameters, partic- CD4 or CD8, but increase in some inflammatory situations (RnD systems accessed 2018). If such a response was assayed ularly T cells, there may be differences which have not been Comp Clin Pathol (2019) 28:41–51 51 by the methods in this paper, T cell number may be as expect- gathered, and we would encourage all those working in this ed, but CD4 and CD8 populations could be decreased. area to share data, to either confirm the changes we have seen It is critical that immunophenotyping data be considered in as true age- and sex-related variances, or alternatively, to clar- conjunction with routine haematology data. In the assays pre- ify expected ranges for laboratory animals. sented in this paper, lymphocyte numbers are normalised for staining purposes, but the initial absolute count of lympho- Compliance with ethical standards cytes needs to be considered in relation to the WBC count. It Ethical approval All applicable international, national and institutional is possible that 30,000 lymphocytes can still be counted even guidelines for the care and use of animals were followed. All procedures when there are reductions to this population in the performed in studies involving animals were in accordance with the eth- haematology analysis. As an alternative, assays could be setup ical standards of the institution at which the studies were conducted. to count cells for a fixed amount of time, so that any changes in the absolute lymphocyte number may be detected and Conflict of interest The authors declare that they have no conflict of interest. accounted for in the assay. Whichever method is used needs to be clearly stated with the results so that accurate interpreta- Open Access This article is distributed under the terms of the Creative tion can be applied, as it is possible to get a statistical differ- Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, ence in either absolute numbers or percentages and not both distribution, and reproduction in any medium, provided you give appro- which would change the way that the data is interpreted. priate credit to the original author(s) and the source, provide a link to the Additionally, power analysis can be conducted to ensure that Creative Commons license, and indicate if changes were made. the data set is of a size sufficient to accurately assess the differences in study groups. Although it should be noted that the number of animals needed may vary by cell type of interest due to the different variability in the individual cell types, or References dictated by guidelines associated with the study type. The use of both sexes in investigations, which may affect Green CL, Brown L, Stewart JJ, Xu Y, Litwin V, McCloskey TW (2011) lymphocyte subsets, is an important part of study design. Recommendations for the validation of flow cytometric testing dur- ing drug development: I instrumentation. J Immunol Methods 363: Depending upon the guidelines relevant for the study, 104–119 OECD, EPA, FDA, etc., it may be possible to use the more International conference on harmonisation of technical requirements for sensitive sex, where this is known. Therefore, when designing registration of pharmaceuticals for human use (2005) ICH a study, it is important to consider the utility of using both harmonised tripartite guideline immunotoxicity studies for human pharmaceuticals, S8. http://www.ich.org/fileadmin/Public_Web_ sexes considering any previously established data. As shown Site/ICH_Products/Guidelines/Safety/S8/Step4/S8_Guideline.pdf in this study, while the significant differences are not universal Morris DL, Komocsar WJ (1997) Immunophenotyping analysis of pe- to a single cell type, there are sex differences in at least one ripheral blood, splenic, and thymic lymphocytes in male and female cell type of each species, strain and age examined. However, it rats. J Pharmacol Toxicol Methods 37:37–46 O’Hara DM, Xu Y, Liang Z, Reddy MP, Wu DY, Litwin V (2011) should be noted that in mice at least, the sexes are the most Recommendations for the validation of flow cytometric testing dur- similar in animals of 7–8 months of age. Therefore, if a back- ing drug development: II assays. J Immunol Methods 363:120–134 ground database for T, B and NK cell data is produced using a Petkova SB, Yuan R, Tsaih SW, Schott W, Roopenian DC, Paigen B single sex at this age, it could contribute to the principles of the (2008) Genetic influence on immune phenotype revealed strain- specific variations in peripheral blood lineages. Physiol Genomics 3Rs and be used as a baseline for comparison against both 34:304–314 sexes. Pinchuk LM, Filipov NM (2008) Differential effects of age on circulating As with any investigation of this nature, the robustness of and splenic leukocyte populations in C57BL/6 and BALB/c male the results is hampered by the relatively small sample size. mice. Immunol Aging 5:1. https://doi.org/10.1186/1742-4933-5-1 RnD Systems, https://www.rndsystems.com/research-area/natural-killer- Although the number of samples investigated here is substan- t–nkt–cells, Accessed March 2018 tially greater than has been reported elsewhere, it is as yet Yamatoya H, Kawaguchi H, Fukuda T, Kadokura H, Yamashita R, unclear whether some of the differences highlighted represent Yoshikawa T, Shiraishi M, Miyamoto A, Miyoshi N (2012) Data a true difference, or whether there is quite substantial varia- on Wistar Hannover rats from an immunotoxicity study. Exp Anim tion. This will only become clear as a greater volume of data is 61:171–175 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Comparative Clinical Pathology Springer Journals

Effects of strain, sex and age on immunophenotyping parameters in the rat and mouse

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Springer Journals
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Copyright © 2018 by The Author(s)
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Medicine & Public Health; Pathology; Hematology; Oncology
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10.1007/s00580-018-2713-6
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Abstract

Immunophenotyping of lymphocyte subsets can be a useful addition to toxicological or investigatory studies where there is the potential for effects on the immune system. We have validated assays for rat or mouse lymphocytes using a FACSVerse flow cytometer and FACSuite software, with commercially available antibodies. Whole blood was stained using the following markers: Rat—CD3, CD45RA, CD161a, CD4 and CD8; mouse—CD3e, CD19, NK1.1, CD4 and CD8. This allows detection and quantitation of T cells, B cells, NK cells, T helper cells and T cytotoxic cells. The stopping criteria for analysis were set at 30,000 lymphocytes, although data were considered acceptable if a minimum of 5000 lymphocytes were counted. To maintain the same analysis protocol throughout and across studies, an assay was created for each species in the FACSuite software. Assay functionality uses CS&T beads for performance quality control and assay setup to ensure that laser settings remain consistent and compensation settings are such that any drift in machine performance does not affect results. Blood samples from both sexes and the following ages and strains were analysed: Rats—2, 4 and 7 months, Crl:WI(Han) and 2 months Crl:CD(SD); mice—2–3, 4–6 and 7–8 months, Crl:CD1(ICR). In general, there was a low level of variation within the results for each sex or age group. However, there are strain, sex and age differences that should be considered when evaluating results from immunophenotyping analysis or when planning studies where there may be an immunological effect. . . . . Keywords Immunophenotyping Flow cytometry Rat Mouse Strain effects Introduction population can be generated to complement and enhance the data collected in routine haematology analysis. It can also Immunophenotyping uses specific antibodies for each cell of contribute to the translation of the effects in animals to humans interest to identify specific leukocyte subsets. Although it can as the ICH S8 guideline on immunotoxicity studies for human be conducted using immunohistochemistry, it is increasingly pharmaceuticals state, BData obtained from peripheral blood being performed by flow cytometry in order to obtain quanti- can be useful as a bridge for clinical studies in which periph- tative data. While immunohistochemistry offers its own ad- eral blood leukocytes are also evaluated.^ (ICH 2005). vantages, an assay using commercially available, specific, Immunophenotyping is recommended in pre-clinical studies fluorescently tagged antibodies allows for the direct interro- when there is the potential for adverse effects on the immune gation of a blood sample by multicolour flow cytometry. system by pharmaceuticals and is generally used within the Multiple cell types can be identified and quantified in a single context of a wider immunotoxicity investigation. For reference, blood sample, helping to limit sample volume, which is par- immunotoxicity is the unintended enhancement or suppression ticularly useful in the rodent species routinely used for pre- of theimmunesystem(ICH 2005) and the conduct of this in- clinical toxicology. By immunophenotyping peripheral blood, vestigation is based on the weight of evidence for the compound data on specific components of the white blood cell (WBC) which will also influence the species and strain used for testing. The assays used in this paper were setup on the FACSVerse flow cytometer using FACSuite software. The functionality of this software allows for assay-based function and uses CS&T beads * Brenda Finney for performance quality control and assay setup to ensure that brenda.finney@sequani.com laser settings remain within a specific range and compensation Sequani Limited, Bromyard Road, Ledbury, Hereford HR8 1LH, UK settings are correct for each fluorophore used. These 42 Comp Clin Pathol (2019) 28:41–51 compensation settings are such that any drift in machine perfor- differences when planning a study or evaluating the data pro- mance does not affect results over time, ensuring that the same duced from an investigation. analysis protocol is performed throughout all studies, which is an important aspect of validation within a GLP-compliant facili- ty and aids in the evaluation of data for regulatory purposes. The Materials and methods assay validation was based on recommendations in partner publications by Green et al. (2011)and O’Hara et al. (2011)in All samples were analysed on a FACSVerse flow cytometer the Journal of Immunological Methods. using FACSuite software (BD Biosciences, UK). After initial For the detection and quantitation of T cells, B cells, NK setup, an assay was created with specific tube settings and cells, T helper cells and T cytotoxic cells, whole blood was gates relevant to each assay. This ensured that all sample anal- stained using markers relevant for each species. In the rat, ysis was done to the same specifications. Tube and assay set- CD3, CD45RA, CD161a, CD4 and CD8a were used. In the tings were set using Research FC beads (BD Biosciences, mouse, CD3e, CD19, NK1.1, CD4 and CD8 were used. UK). Cytometer setup and quality control were performed on Blood samples from both sexes and the following ages and each day of cytometer use according to the manufacturer’s strains were analysed: Rats 2 months Crl:CD(SD), 2, 4 and instructions using CS&T beads. Due to the ability to use 7 months Crl:WI(Han); mice 2–3, 4–6and7–8months, CS&T and Research FC beads for the setup and maintenance Crl:CD-1(ICR). The objective of this study was to compare of the compensation settings needed for each assay, isotype and contrast data across strains, sexes and ages, in order to controls were not used. However, depending upon the analyser understand the variation of these factors when choosing ex- used, isotype controls may be required when establishing this perimental subjects. The data contained in this paper are also assay in other laboratories. Additionally, Comp beads, with used as historical control data, for comparison to data collect- positive and negative populations, can be used to determine ed during regulatory toxicological investigations. It is hoped parameters for the specific antibodies used in each assay. that the protocols and data presented in this paper will be of Specific consumables purchased from BD Biosciences, UK, use to other laboratories that are performing or looking to have specific information provided in Table 1. perform this type of assay on these species and strains. Difference in gating strategies between analysts, analysers Methods and laboratories is a primary reason why flow cytometry data sets are difficult to compare. To control for this in our labora- Use of animals tory, we have used the assay functionality of the FACSuite software in conjunction with the FACSVerse flow cytometer. All institutional and national guidelines for the care and use of This function ensures that when gates are set and saved as part laboratory animals were followed and all animal work was of the assay, the gates are in the same position for each sample conducted under authority of a Project Licence in compliance each time the assay is opened. In terms of GLP compliance, it with the Animals (Scientific Procedures) Act 1986 (as also ensures that the initial settings of the assay can be com- amended). Euthanasia and blood collection were done accord- pared with any data used for reporting, and changes can be ing to routine standard operating procedures. detected or annotated between samples or days of analysis. As a part of the assay function, compensation settings are routine- Blood sampling and sample processing ly checked and updated using quality control beads. These beads are either fluorophore-specific, Research FC beads or Blood was collected from either the sublingual vein (rats on- wide-spectrum CS&T beads. There have been initial steps ly), abdominal vena cava (both species) or orbital sinus (mice taken to standardise or automate gating strategies across insti- only) into tubes containing K EDTA depending upon the tutions and platforms, but as of yet, these are not widely used. study type from which the animals were taken. The tubes were Due to the use of mice in immunology research, there ap- then mixed on a roller at room temperature for 5–10 min. pears to be a greater amount of published material on the After mixing, they were kept on ice or at 2–8 °C until proc- immunophenotype found in mouse strains than in rat strains. essed. Processing was performed on the day of collection. Cell However, data on the Crl:CD1(ICR) mouse strain were not counts were performed on an ADVIA 120 (Siemens, UK) found, nor were there data comparing different ages. Although haematology analyser and samples were normalised to 1 × published data on rat strains were limited, information was 10 lymphocytes/mL with phosphate buffered saline (PBS). found on immunophenotyping in RccHan:Wist (Yamatoya After normalisation, antibodies were added to the sample at et al. 2012) and Sprague Dawley (Morris and Komocsar, the concentrations listed in Table 1. The samples were incu- 1997). This paper expands the available strain data and pro- bated in the dark at room temperature. The incubation was vides a direct comparison of results between two rat strains ended by the addition of 20× volume of FACSLyse and and shows that it is worth considering age, sex and strain vortexed. Samples were then centrifuged at 500g for 5 min, Comp Clin Pathol (2019) 28:41–51 43 Table 1 Reagents and consumables used for immunophenotyping assays Reagent Catalogue Assay Cell types and fluorophore Amount used per test (if applicable) number species CS&T beads 650621 N/A N/A N/A FACSLyse 349202 N/A N/A 20× sample volume T, B, NK cell cocktail 558495 Rat T cell: CD3, APC 10/100 μL sample at 1 × 10 lymphocytes/mL B cell: CD45RA, FITC NK cell: CD161a, PE CD45 antibody 561586 Rat Lymphocytes, APC-Cy7 2/100 μL (rat) 200 μL (mouse) sample at 1 × 10 (Used during initial assay setup, information 557659 Mouse lymphocytes/mL included for reference) T lymphocyte cell cocktail 558493 Rat T cell: CD3, APC 10/200 μL sample at 1 × 10 lymphocytes/mL T helper cell: CD4, PE T cytotoxic cell: CD8a, FITC T lymphocyte cell cocktail 558431 Mouse T cell: CD3e, PE-Cy7 10/200 μL sample at 1 × 10 lymphocytes/mL T helper cell: CD4, PE T cytotoxic cell: CD8, APC CD19 antibody 557398 Mouse B cell: FITC 2/200 μL sample at 1 × 10 lymphocytes/mL NK1.1 antibody 560618 Mouse NK cell: APC-Cy7 2/200 μL sample at 1 × 10 lymphocytes/mL most of the supernatant removed and 2 mL PBS added. The characteristics; when labelled with CD45, the constituents of 4 5 cells were resuspended by tapping the tube and then centri- this gate showed fluorescence in the 10 –10 region on a log fuged at 500g for 5 min. The supernatant was then removed scale. The lymphocyte population gate in the FSC vs. SSC dot and the cells resuspended in 300 μL PBS for analysis. plot was used as the gate for the stopping criteria of 30,000 lymphocytes. As FSC and SSC characteristics should not change greatly between animals, the use of the CD45 marker Rat immunophenotyping was discontinued after several samples confirmed the location of the gate on the FSC vs. SSC plot. Sub-population gates Data were collected from animals of both sexes in the were also confirmed by plots comparing the different CD Crl:WI(Han) and Crl:CD(SD) strains (Charles River, UK). markers used to each other to check for overlap. The age of the animals varied by strain. Crl:CD(SD) data were collected at 2 months of age while Crl:WI(Han) data were obtained at 2, 4 and 7 months of age. Comparisons between Mouse immunophenotyping strains were made on animals of the same sex and similar ages. This assay was performed as a two-tube assay which was Data were collected from both sexes in the Crl:CD1(ICR) strain (Charles River, UK) at 2–3, 4–6and 7–8months of age. dictated by the fluorophores available in the staining cocktails. One tube was the lymphocyte assay which counted T, B and This was a single-tube assay for all cell types. Samples were analysed until 30,000 cells in the lymphocyte gate were NK cells; the second tube counted T cells, CD4 + T helper cells and CD8 + T cytotoxic cells using the staining cocktails counted. Samples were accepted if at least 5000 lymphocytes were counted. Stability was tested during the validation; how- in Table 1. In the T, B and NK cell assay, samples were analysed until 30,000 cells in the lymphocyte gate were count- ever, changes in cell populations in the conditions tested on subsequent days required that samples be analysed on the ed. Samples were accepted if at least 5000 lymphocytes were counted. In the T cell subset, tube samples were analysed until same day. The gating strategy for this assay is shown in Fig. 3. 5000 T cells were counted and accepted if at least 2500 T cells were counted. Samples were checked for stability with both of Data and statistics the staining cocktails. Sample results were acceptable only on the day following collection where samples had been stained, The data collected included both the absolute cell counts and lysed and washed prior to storage at 2–8°C. the percentage of the cell subtypes present in the parent pop- The gating strategies for these assays are shown in Figs. 1 ulations, either lymphocytes or T cells depending on the cell and 2. The initial assay setup utilised the pan-lymphocyte types. Data were correlated in a Microsoft Excel spreadsheet marker CD45 labelled with APC-Cy7 to confirm the estab- before transfer to GraphPad Prism (GraphPad Software, CA, lishment of the lymphocyte population gate. The lymphocyte USA), which was used for graph production and statistical cluster was initially identified based on FSC and SSC analysis. T helper:T cytotoxic ratio for 2-month rat samples 44 Comp Clin Pathol (2019) 28:41–51 Fig. 1 Gating strategy in rat T, B and NK cell assay. a FSC vs. SSC expression of CD3. d Blue gate indicating B cell population based on graph, orange circle highlights the lymphocyte population. b Gating CD45RA expression. e Green gate indicating NK cell population based hierarchy for assay. c Purple gate indicating T cell population based on on CD161a expression Fig. 2 Gating strategy in rat Tcell subset assay. a Gating hierarchy for assay. b Purple T cell gate based on CD3 expression. c Green circle gate for T helper cell population based on CD4 expression. d Red circle gate for T cytotoxic cells based on CD8 expression Comp Clin Pathol (2019) 28:41–51 45 Fig. 3 Gating strategy for mouse immunophenotyping assay.a FSC vs. indicating NK cell population based on NK1.1 expression. e Green gate SSC graph, orange circle highlights the lymphocyte population. b Purple indicating T cytotoxic cell population based on CD8 expression. f Blue gate indicating Tcell population based on expression of CD3e. c Red gate circle gate indicating T helper cell population based on CD4 expression indicating B cell population based on CD19 expression. d Teal circle gate was calculated by dividing the absolute T helper cell number absolute numbers and percentages as well as in data sets (CD4+) by the absolute T cytotoxic cell number (CD8+); this compared. Therefore, different numbers of animals would is also called the CD4:CD8 ratio. Statistical analysis was per- be required to increase the power depending upon the cell formed on cell percentages as initial analyses showed that type of interest. As this is not practical, we recommend that absolute counts and percentages gave the same results. The each laboratory have an understanding of the power statistical test performed was a non-parametric, two-tailed t achieved by their study design and potential effects on data test with Mann-Whitney. Statistical significance was consid- interpretation. In general, where statistical significance was ered to have been reached when p ≤ 0.05. achieved, the power was as follows: * = 0.5–.65, ** = Post hoc power analysis was conducted on the results pre- 0.79–.93and***=0.72–1. As this data is intended for sented in Tables 2 and 3, both absolute numbers and percent- use as background data, the power will change as data is ages, using G*Power 3.1 (Dusseldorf, Germany). The settings continually added from control animals on our routine were as follows: test family = t tests; statistical test = means studies. Wilcoxon-Mann-Whitney test (two groups); type of power analysis = post hoc compute achieved power given α,sample size and effect size. Input parameters were two-tailed, normal Rat immunophenotyping parent distribution, α err prob = 0.05. The effect size was calculated based on the observed means and SDs, and the Strain differences sample sizes were as listed in the data. Results of this analysis varied by cell type and data sets compared. The data for this analysis is presented in Table 2. At 2 months of age, there are significant differences in the percentage of cells which make up the lymphocyte and T cell sub- Results populations in Crl:WI(Han) vs. Crl:CD(SD) rats. These dif- ferences occur in both sexes for B cells, T helper and T cyto- toxic cells, while there is a statistically significant change in Power analysis the T cell population for males only. The NK cell population is the only population where there is no apparent significant Assessment of the statistical power of these data sets re- difference between the strains. vealed variation in the power achieved between cell types, 46 Comp Clin Pathol (2019) 28:41–51 Table 2 Rat immunophenotyping results by sex and strain, at 2 months of age, mean ± SD. Statistical test was a non-parametric, two-tailed t test with Mann-Whitney comparing results between sexes. Statistical significance was considered to have been reached when p ≤ 0.05, asterisks indicate level of significance. Number in parentheses below results = n Sex T cell number % T cells B cell %B cells NKcell % NK cells T helper %Thelper T cytotoxic %T number number cell cells number cytotoxic number cells Crl:WI(Han) Male 12,411 ± 1790 41.39 ± 5.99 7662 ± 1655 25.55 ± 5.51 1940 ± 833 6.47 ± 2.78 3635 ± 168 72.72 ± 3.35 1362 ± 173 27.25 ± 3.46 (28) (28) (28) (28) (28) (28) (19) (19) (19) (19) Female 13,871 ± 2692 46.24 ± 8.97 6614 ± 1824 22.04 ± 6.08 2708 ± 281 9.03 ± 0.93 3731 ± 236 74.64 ± 4.72 1191 ± 150 23.83 ± 3.01 (12) (12) (12) (12) (12) (12) (13) (13) (13) (13) Sex difference p = 0.13 0.15 0.008** 0.08 0.009** T helper:T cytotoxic ratio Male Female (CD4:CD8) 2.7 ± 0.5 3.2 ± 0.5* Crl:CD(SD) Male 11,244 ± 1308 37.48 ± 4.36 9138 ± 1196 30.46 ± 3.99 2554 ± 685 8.87 ± 2.35 3396 ± 174 67.99 ± 3.48 1614 ± 171 32.31 ± 3.42 (14) (14) (14) (14) (14) (14) (16) (16) (16) (16) Female 12,718 ± 1703 42.39 ± 5.68 8148 ± 1503 27.16 ± 5.01 3233 ± 766 10.78 ± 2.55 3316 ± 118 66.35 ± 2.39 1686 ± 128 33.74 ± 2.56 (12) (12) (12) (12) (12) (12) (16) (16) (16) (16) Sex difference p = 0.017* 0.046* 0.085 0.61 0.54 T helper:T cytotoxic ratio Male Female (CD4:CD8) 2.1 ± 0.4 2.2 ± 0.3 Male strain difference p = 0.035* 0.002** 0.11 0.0002*** 0.0002*** Female strain difference p 0.19 0.04* 0.55 0.0001*** < 0.0001*** = Comp Clin Pathol (2019) 28:41–51 47 Table 3 Mouse immunophenotyping results by sex and age, mean ± SD. Statistical test was a non-parametric, two-tailed t test with Mann-Whitney comparing results between sexes at each age. Statistical significance was considered to have been reached when p ≤ 0.05, asterisks indicate level of significance. Number in parentheses below results = n Sex T cell number % T cells B cell number % B cells NK cell % NK cells T helper cell %Thelper T cytotoxic %T number number cells number cytotoxic cells 2–3 months Male 12,117 ± 2011 40.39 ± 6.70 13,059 ± 2523 43.53 ± 8.41 2432 ± 976 8.11 ± 3.25 8126 ± 1472 67.04 ± 4.37 3019 ± 782 24.86 ± 4.23 (24) (24) (24) (24) (24) (24) (24) (24) (24) (24) Female 13,680 ± 2342 45.60 ± 7.81 10,720 ± 2815 35.73 ± 9.38 3277 ± 1182 10.92 ± 3.94 8937 ± 1259 65.85 ± 5.47 3400 ± 872 24.78 ± 4.49 (23) (23) (23) (23) (23) (23) (23) (23) (23) (23) Sex difference 0.022* 0.0047** 0.003** 0.44 0.86 p = 4–6 months Male 13,772 ± 2410 45.91 ± 8.03 8996 ± 2874 29.99 ± 9.41 2855 ± 898 9.52 ± 2.99 8975 ± 1670 65.33 ± 6.66 3667 ± 890 26.63 ± 4.50 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Female 13,672 ± 2566 45.57 ± 8.55 7350 ± 1840 24.50 ± 6.13 3597 ± 1182 11.99 ± 3.94 9453 ± 1435 69.86 ± 5.89 3132 ± 1237 22.21 ± 6.27 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Sex difference 0.99 0.017* 0.069 0.054 0.024* p = 7–8 months Male 12,333 ± 2582 41.11 ± 8.61 11,666 ± 3653 38.89 ± 12.18 2111 ± 1037 7.04 ± 3.46 8154 ± 1784 66.28 ± 7.80 3272 ± 1029 26.55 ± 7.11 (19) (19) (19) (19) (19) (19) (19) (19) (19) (19) Female 13,837 ± 3773 46.12 ± 12.58 9917 ± 2256 33.06 ± 8.52 2388 ± 811 7.96 ± 2.70 8040 ± 2705 57.25 ± 7.69 4051 ± 1061 29.88 ± 5.73 (18) (18) (18) (18) (18) (18) (18) (18) (18) (18) Sex difference 0.075 0.13 0.33 0.0013** 0.25 p = 48 Comp Clin Pathol (2019) 28:41–51 Sex differences T and NK cells only at 2–3 months and in T cytotoxic cells at 4–6months. At 2 months of age, Crl:WI(Han) animals have statistically significant differences in amounts of NK and T cytotoxic cells Age differences in their lymphocyte pool depending upon their sex (Table 2). Females show an increased number of NK cells and decreased Data are presented in Table 3 and statistical information is number of T cytotoxic cells in comparison to males. There is contained in Fig. 5. As mice age from 2 to 3 months to 4– also a statistically significant difference in the T helper/T cy- 6 months, regardless of sex, there is a decrease in the B cell totoxic (CD4:CD8) ratio between the sexes in this strain. number and increases in the NK cell numbers. Statistical sig- At 4 and 7 months of age (Fig. 4), there are statistically nificance is reached for B cells when comparing 2–3and 4– significant differences in the percentage of B cells in the lym- 6 months. In NK cells, statistical significance is reached when phocyte pool with females having fewer B cells than males. comparing 2–3and4–6 months in males but not females. This The only other significant difference is seen in the T cell pop- trend appears reversed at 7–8 months where there is an in- ulation at 7 months of age where females have higher numbers crease in the B cell number and decrease in the NK cell num- of T cells. All other populations show no difference between ber. The changes in B cell numbers for both sexes are statis- the sexes at these ages. tically significant when comparing 4–6and7–8 months, while At 2 months of age, Crl:CD(SD) animals have statistically in NK cells, statistical significance is reached when comparing significant differences in amounts of T and B cells in their 4–6and 7–8months in males and 2–3or4–6and7–8months lymphocyte pool depending upon their sex (Table 2). in females. The T cell populations appear to be more stable in Females show an increased number of T cells and decreased mice and the only point of statistical significance was an in- number of B cells in comparison to males. crease in male T cell numbers when comparing 2–3and4– 6 month data. Interestingly, there are changes in the T cell sub- populations in females which appear to be age related and do Age differences not appear to affect the overall T cell numbers. T helper cell numbers are initially higher at 4–6 months and then fall at 7– In the Crl:WI(Han) strain, there were age-related differences 8 months. Statistical significance is reached when comparing in the percentages of cells which make up the lymphocyte data from 2 to 3 or 4–6and7–8 months. These changes are pool (Fig. 4). As rats age, there are increases in the number accompanied by the opposite pattern in the T cytotoxic cell of B cells with decreases in the NK cell numbers. These population with the same pattern of statistical significance. changes are statistically significant between 2 and 4 or 7 months, but not between 4 and 7 months. T cell populations show a different pattern of change with a decrease in T cell Discussion numbers that is significant between 2 and 7 months or 4 and 7 months in males, but only between 2 and 7 months in fe- An important component of any assay used within a GLP- males. Interestingly, there are changes in the T cell sub-popu- compliant laboratory is the ability to perform the assay rou- lations, which do not appear to affect the overall T cell num- tinely, with the same parameters over days, weeks, months or bers. Higher numbers of T helper cells with age reached sta- even years. It is this reproducibility that allows for the pro- tistical significance between 2 and 4 or 7 months in males, and gressive steps of toxicology investigations to show the safety between 2 and 7 or 4 and 7 months in females. These changes margins of a new treatment or chemical over different dose were accompanied by decreases in the T cytotoxic cell popu- levels, time periods, sexes and ages. Flow cytometric analysis lation that were statistically significant at all points tested in of peripheral blood cell populations can be an important part the males, and between 2 and 4 or 7 months in females. of this investigation, particularly where prior knowledge indi- cates that the immune system may be affected by a test item. Mouse immunophenotyping The FACSVerse flow cytometer and its associated software, FACSuite, is a useful system for ensuring that analysis is re- Sex differences producible when the Quality Control functions, tube and assay settings are used in conjunction with Assay Programming. Data are presented in Table 3 for each age and sex. In This system is geared towards the standardisation of collection Crl:CD1(ICR) mice, it appears that sex differences diminish parameters and protocols between users, instruments and lab- with age; as by 7–8 months, the only significant difference is oratories. Assay settings with gating protocols can be exported in the number of T helper cells making up the T cell pool. At and shared between laboratories. CS&T and Research FC younger ages of either 2–3or 4–6 months, sex differences are beads are used for instrument and assay setup, ensuring that seen in B cells. Statistically significant differences are seen in compensation settings are such that collection parameters are Comp Clin Pathol (2019) 28:41–51 49 Fig. 4 Immunophenotyping of Crl:WI(Han) rats at 2, 4 and 7 months cytotoxic cells). Each point is an individual animal. Error bars show the of age. a B cells. b NK cells. c Tcells. d T helper cells. e Tcytotoxic cells. mean ± SD. Asterisks indicate statistically significant differences between All results are presented as the percentage of cells making up their parent the ages in the same sex, *p ≤ 0.05; **0.005; ***0.0005; ****0.0001 population (lymphocytes for B, NK and T cells, T cells for T helper and T the same across time, instruments, laboratories and users. This studies so that if there are any changes induced by different system also has functions which allow for the electronic ap- batches of antibodies, these can be annotated as such. As an proval, annotation and electronic signature of data which con- additional control measure, the procedure of performing this tributes to GLP adherence and data security. analysis has been detailed in a method document which can- Regardless of the instrument and software used, an assay not be changed without review and signature of multiple sci- needs to be validated to ensure that it is functioning to an entists and changes to the assay itself cannot be performed acceptable standard. Validation also ensures that when an as- without administrator-level access rights to the FACSuite soft- say component is changed, antibody batches, for example, this ware. A copy of this method, electronic copies of the assay does not change the function or results of the assay. Validation setup prior to analysis, as well as all FCS, CSV and PDF files parameters tested for this assay included intra-assay (within- are kept with each study so that they may be reviewed as part run) precision, inter-assay (between-run) precision, sample of Quality Assurance assessments. fixation and stability and staining profile. In this case, samples The data sets presented in this paper have been collected were not stable enough to make a positive statement on inter- over multiple analysis days and offer insight with larger num- assay precision. However, intra-assay precision where sam- bers of samples compared to other published studies (Morris ples were stained and analysed in triplicate had coefficients and Komocsar 1997, Petkova et al. 2008, Pinchuk and Filipov of variation of less than ± 20%. This showed that the staining 2008, Yamatoya et al. 2012) which have indicated that sex and and analysis procedure did not introduce variability into sam- strain differences are present in lymphocyte sub-populations. ples. The staining profile of each cell type was plotted against But the effects of age have not been robustly assessed. While it the other markers used in the assay to show that there was is difficult to compare absolute cell numbers between pub- minimal number of cells which expressed multiple markers lished studies due to strain, collection and gating differences, and the expression profile of cells was as expected and listed it can be noted that the CD4:CD8 ratio obtained in this study in Table 1. The data from this study is compared against data for 2-month-old Crl:CD(SD) rats is similar to that published by Morris and Komocsar (1997) where they used Sprague from control (untreated) animals of a similar age in routine 50 Comp Clin Pathol (2019) 28:41–51 Fig. 5 Immunophenotyping of Crl:CD1(ICR) mice at 2–3, 4–6and T helper and T cytotoxic cells). Each point is an individual animal. Error 7–8months of age.a Bcells. b NK cells. c T cells. d T helper cells. e T bars show the mean ± SD. Asterisks indicate statistically significant cytotoxic cells. All results are presented as the percentage of cells making differences between the ages in the same sex, *p ≤ 0.05; **0.005; up their parent population (lymphocytes for B, NK and T cells, T cells for ***0.0005; ****0.0001 Dawley rats obtained from Charles River in the USA, as are detected in these data sets. However, as this data is intended the percentages of B cells and CD3+ T cells. Although as for use as background data, the power will change as data is shown here, strain differences can be marked and could exist continually added from control animals on our routine studies, between different suppliers of Sprague Dawley rats. and so may improve. Also, where statistical significance was Therefore, it is important that when published, there is specific achieved, the higher the significance the higher the power strain information so that comparability between studies can indicated, so while there may be some differences which are be assured. not yet distinguishable, the differences currently seen are The data collected here demonstrate that there is potential robust. for standard total lymphocyte counts to be overly simplistic In terms of toxicology investigations, generally, both abso- where there is potential for effects on the immune system. For lute cell numbers and percentages are used to evaluate any example, in the Crl:CD1(ICR) mouse data set, T cell numbers effects which may be induced by test articles. But, where do not vary widely across either sex or age; however, when the numbers are limited by stopping criteria, critical thought on sub-populations of T helper and T cytotoxic cells are investi- the scale and direction of any changes or differences is needed. gated, females show highly significant differences in the ratios It should be considered if an increase in one cell type results in of cells that make up their T cell population as they age. a decrease in another cell type or vice versa, it should be kept Similarly, in the same cell types in rats, although the changes in mind that this change may not be wholly reflective of the appear small (differences of 5–10%), they are highly statisti- cell number in the circulation. There is also the possibility that cally significant, particularly between the strains. Therefore, the cell types interrogated may miss a cell type, and therefore, discrimination of the counts or relative percentages of each decreases in the lymphocyte subsets counted may be due to an sub-population could indicate an aspect of toxicity or potential increase in a cell type which does not have a specific lympho- mechanisms of action not highlighted by the total lymphocyte cyte sub-gate in the protocol. As an example, there is a subset or even T cell count, which may not change. It is also possible of T cells, natural killer T cells, which may not express either that due under powering indicated in some parameters, partic- CD4 or CD8, but increase in some inflammatory situations (RnD systems accessed 2018). If such a response was assayed ularly T cells, there may be differences which have not been Comp Clin Pathol (2019) 28:41–51 51 by the methods in this paper, T cell number may be as expect- gathered, and we would encourage all those working in this ed, but CD4 and CD8 populations could be decreased. area to share data, to either confirm the changes we have seen It is critical that immunophenotyping data be considered in as true age- and sex-related variances, or alternatively, to clar- conjunction with routine haematology data. In the assays pre- ify expected ranges for laboratory animals. sented in this paper, lymphocyte numbers are normalised for staining purposes, but the initial absolute count of lympho- Compliance with ethical standards cytes needs to be considered in relation to the WBC count. It Ethical approval All applicable international, national and institutional is possible that 30,000 lymphocytes can still be counted even guidelines for the care and use of animals were followed. All procedures when there are reductions to this population in the performed in studies involving animals were in accordance with the eth- haematology analysis. As an alternative, assays could be setup ical standards of the institution at which the studies were conducted. to count cells for a fixed amount of time, so that any changes in the absolute lymphocyte number may be detected and Conflict of interest The authors declare that they have no conflict of interest. accounted for in the assay. Whichever method is used needs to be clearly stated with the results so that accurate interpreta- Open Access This article is distributed under the terms of the Creative tion can be applied, as it is possible to get a statistical differ- Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, ence in either absolute numbers or percentages and not both distribution, and reproduction in any medium, provided you give appro- which would change the way that the data is interpreted. priate credit to the original author(s) and the source, provide a link to the Additionally, power analysis can be conducted to ensure that Creative Commons license, and indicate if changes were made. the data set is of a size sufficient to accurately assess the differences in study groups. Although it should be noted that the number of animals needed may vary by cell type of interest due to the different variability in the individual cell types, or References dictated by guidelines associated with the study type. The use of both sexes in investigations, which may affect Green CL, Brown L, Stewart JJ, Xu Y, Litwin V, McCloskey TW (2011) lymphocyte subsets, is an important part of study design. Recommendations for the validation of flow cytometric testing dur- ing drug development: I instrumentation. J Immunol Methods 363: Depending upon the guidelines relevant for the study, 104–119 OECD, EPA, FDA, etc., it may be possible to use the more International conference on harmonisation of technical requirements for sensitive sex, where this is known. Therefore, when designing registration of pharmaceuticals for human use (2005) ICH a study, it is important to consider the utility of using both harmonised tripartite guideline immunotoxicity studies for human pharmaceuticals, S8. http://www.ich.org/fileadmin/Public_Web_ sexes considering any previously established data. As shown Site/ICH_Products/Guidelines/Safety/S8/Step4/S8_Guideline.pdf in this study, while the significant differences are not universal Morris DL, Komocsar WJ (1997) Immunophenotyping analysis of pe- to a single cell type, there are sex differences in at least one ripheral blood, splenic, and thymic lymphocytes in male and female cell type of each species, strain and age examined. However, it rats. J Pharmacol Toxicol Methods 37:37–46 O’Hara DM, Xu Y, Liang Z, Reddy MP, Wu DY, Litwin V (2011) should be noted that in mice at least, the sexes are the most Recommendations for the validation of flow cytometric testing dur- similar in animals of 7–8 months of age. Therefore, if a back- ing drug development: II assays. J Immunol Methods 363:120–134 ground database for T, B and NK cell data is produced using a Petkova SB, Yuan R, Tsaih SW, Schott W, Roopenian DC, Paigen B single sex at this age, it could contribute to the principles of the (2008) Genetic influence on immune phenotype revealed strain- specific variations in peripheral blood lineages. Physiol Genomics 3Rs and be used as a baseline for comparison against both 34:304–314 sexes. Pinchuk LM, Filipov NM (2008) Differential effects of age on circulating As with any investigation of this nature, the robustness of and splenic leukocyte populations in C57BL/6 and BALB/c male the results is hampered by the relatively small sample size. mice. Immunol Aging 5:1. https://doi.org/10.1186/1742-4933-5-1 RnD Systems, https://www.rndsystems.com/research-area/natural-killer- Although the number of samples investigated here is substan- t–nkt–cells, Accessed March 2018 tially greater than has been reported elsewhere, it is as yet Yamatoya H, Kawaguchi H, Fukuda T, Kadokura H, Yamashita R, unclear whether some of the differences highlighted represent Yoshikawa T, Shiraishi M, Miyamoto A, Miyoshi N (2012) Data a true difference, or whether there is quite substantial varia- on Wistar Hannover rats from an immunotoxicity study. Exp Anim tion. This will only become clear as a greater volume of data is 61:171–175

Journal

Comparative Clinical Pathology – Springer Journals

Published: Apr 13, 2018

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