Mycobacterium avium subsp. paratuberculosis (MAP) is the causal bacteria for Johne’s Disease, a chronic granulomatous enteritis affecting both wild and domestic ruminants. During the subclinical stage of infection, infected animals may excrete MAP in feces, allowing disease to spread undetected throughout the herd. Epidemiological studies have used PCR-based techniques to examine loci found throughout the genome known as MIRU-VNTR. Additional studies have used DNA fragment analysis performed on specific short sequence repeats (SSRs), which also discriminate strains. An important consideration is the occurrence of mixed strain infections (MSIs), which may exhibit different phenotypes or antigens, complicating the immune response. Instances of MSIs are typically considered as rare events, with few studies successfully identifying MSIs within MAP host animals. This study examines strains of MAP isolated from 14 cows and evaluates molecular methods for rapid MSI identification, notably using MIRU-VNTR and SSR-based fragment analysis. Cows were selected from three farms and were categorized based on blood ELISA and fecal ISMAP02 qPCR results. Strains of MAP (10 per cow) were selected on solid cultures. For each strain, an axenic liquid culture was prepared, totalling 139 isolates. DNA extracted from each strain was examined using 8 MIRU-VNTR, 2 SSR loci, and whole genome-sequencing. The MIRU-VNTR analysis results were identical across all isolates. However, the results from the SSR fragment analysis showed up to 9 unique patterns within each animal suggesting that MSIs may be present. As the rate of change of SSR could be independent of the rate of chromosomal evolution, further work will include more JD cases, which provides the greatest resolution for differentiation between strains. Results of this analysis show that SSR can discriminate strains with greater resolving ability than MIRU-VNTR. Our study suggests that MSI events may be overlooked within herds and should be considered in a phylogenetic context for affirming epidemiological connections.