Nisin is a commonly used bacteriocin for controlling spoilage and pathogenic bacteria in food products. Strains possessing high natural nisin resistance that reduce or increase the potency of this bacteriocin against
Listeria monocytogenes
have been described. Our study sought to gather more insights into nisin resistance mechanisms in natural
L. monocytogenes
populations by examining a collection of 356 field strains that were isolated from different foods, food production environments, animals and human infections. A growth curve analysis-based approach was used to access nisin inhibition levels and assign the
L. monocytogenes
strains into three nisin response phenotypic categories; resistant (66%), intermediate (26%), and sensitive (8%). Using this categorization isolation source, serotype, genetic lineage, clonal complex (CC) and strain-dependent natural variation in nisin phenotypic resistance among
L. monocytogenes
field strains was revealed. Whole genome sequence analysis and comparison of high nisin resistant and sensitive strains led to the identification of new naturally occurring mutations in nisin response genes associated with increased nisin resistance and sensitivity in this bacterium. Increased nisin resistance was detected in strains harboring RsbU
G77S
and PBPB3
V240F
amino acid substitution mutations, which also showed increased detergent stress resistance as well as increased virulence in a zebra fish infection model. On the other hand, increased natural nisin sensitivity was detected among strains with mutations in
sigB
,
vir
, and
dlt
operons that also showed increased lysozyme sensitivity and lower virulence. Overall, our study identified naturally selected mutations involving
pbpB3
(
lm0441
) as well as
sigB
,
vir
, and
dlt
operon genes that are associated with intrinsic nisin resistance in
L. monocytogenes
field strains recovered from various food and human associated sources. Finally, we show that combining growth parameter-based phenotypic analysis and genome sequencing is an effective approach that can be useful for the identification of novel nisin response associated genetic variants among
L. monocytogenes
field strains.