S1 Fig. Conventional PCR for the detection ofMycobacterium bovis. PCR targeting RD1,
RD4 and RD9 as previously described. PCR products of +- 268bp (RD4 absent), +- 196bp
(RD1 absent) and +- 108bp (RD9 absent) indicate M. bovis BCG. Animals 18, 21 and 31 belong
to group 1 (live M. bovis BCG), animals 2, 6, 7, 16 and 29 belong to group 2 (formalin-inactivated
M. bovis BCG), animals 8, 9, 10, 11 and 26 belong to group 3 (heat-killed M. bovis) and
animals 12 and 15 belong to group 4 (control). R = right prescapular lymph node.
S1 Dataset. Tables containing the raw data of the immunological assays. (A) BOVIGAM
assay. OD-values for all stimulations and controls. (B) IDEXX TB ELISA. OD-values for the
samples and controls as well as S/P-ratio. (C) Skin test. Skin fold thickness measurements at
0hrs, 72hrs and the difference (Δmm) in mm. Avian = PPD-A; Bovine = PPD-B; PC1 = protein
cocktail 1; PC2 = protein cocktail 2. (D) Culture. Weights (g) and bacterial counts (CFU/g of
PLN) of left and right PLNs.
S2 Dataset. Tables describing the statistical models and their outcomes. (A) Linear mixed
effects models describing PPD-B and the ratios of PPD-B/PPD-A and PPD-B/PPD-F. Outcome
= a + b1 time + b2 group + b3 (time group). Data were log transformed in order
to meet the model assumptions of normality and homoscedasticity. Back-transformed estimates
and 95% confidence intervals are given. Significant results are in bold. (B) Linear mixed
effects models describing ESAT-6 and CFP-10. Outcome = a + b1 time + b2 group + b3
(time group). Data were log transformed in order to meet the model assumptions of normality
and homoscedasticity. Back-transformed estimates and 95% confidence are given. Significant
results are in bold. (C) Linear mixed effects model describing the S/P ratio. Outcome = a
+ b1 time + b2 group + b3 (time group). Data were log transformed in order to meet the
model assumptions of normality and homoscedasticity. Back-transformed estimates and 95%
confidence intervals are given. Significant results are in bold. (D) Double generalized linear
model describing ΔPPDBÐΔPPDA in the skin test. Outcome = a + b1 group. Estimates and
95% confidence intervals are given. Significant results are in bold. (E) A simple general linear
model describing ΔPC1 and ΔPC2. Outcome = a + b1 group. Estimates and 95% confidence
intervals are given. Significant results are in bold. (F) Linear mixed effects model describing
the PLN weights. Outcome = a + b1 LN side + b2 group + b3 (LN side group) + b4 gender.
Data (PLN weights) were log transformed in order to meet the model assumptions of normality
and homoscedasticity. Estimates and 95% confidence intervals are given. Significant
results are in bold. (G) Negative binomial generalized linear model describing the bacterial
counts. Outcome = a + b1 group. Back-transformed estimates and 95% confidence intervals
are given. Significant results are in bold.