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Citation: Flach, M.G.; Dogan, O.B.;
Kreikemeier, W.M.; Nightingale, K.K.;
Brashears, M.M. Reduction of
Pathogens in Feces and Lymph
Nodes Collected from Beef Cattle Fed
Lactobacillus salivarius (L28),
Lactobacillus acidophilus (NP51) and
Propionibacterium freudenreichii
(NP28), Commercially Available
Direct-Fed Microbials. Foods 2022,11,
3834. https://doi.org/10.3390/
foods11233834
Academic Editor: Chunlei Shi
Received: 23 September 2022
Accepted: 23 November 2022
Published: 28 November 2022
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foods
Article
Reduction of Pathogens in Feces and Lymph Nodes
Collected from Beef Cattle Fed Lactobacillus salivarius (L28),
Lactobacillus acidophilus (NP51) and Propionibacterium
freudenreichii (NP28), Commercially Available
Direct-Fed Microbials
Makenzie G. Flach 1, Onay B. Dogan 1, Wanda M. Kreikemeier 2, Kendra K. Nightingale 1
and Mindy M. Brashears 1, *
1International Center for Food Industry Excellence, Department of Animal and Food Sciences,
Texas Tech University, Lubbock, TX 79409, USA
2Livestock Logic, LLC, 79521 Rd 417, Callaway, NE 68825, USA
*Correspondence: mindy.brashears@ttu.edu; Tel.: +1-(806)834-4274
Abstract:
The purpose of the study was to evaluate the prevalence and concentration of foodborne
pathogens in the feces and peripheral lymph nodes (PLNs) of beef cattle when supplemented
with direct-fed microbials (DFMs) in feedlots. Fecal samples were collected from the pen floors
over a 5-month period at three different feedlots in a similar geographical location in Nebraska,
where each feed yard represented a treatment group: (i.) control: no supplement, (ii.) Bovamine
Defend: supplemented with NP51 and NP24 at a target dose of 9 log
10
CFU/g/head/day, and (iii.)
Probicon: supplemented with L28 at a target dose of 6 log
10
CFU/g/head/day. Each fecal sample
was tested for the prevalence of E. coli O157:H7 and Salmonella, and concentration of E. coli O157:H7,
Enterobacteriaceae and Clostridium perfringens. Cattle were harvested and PLNs were collected on the
harvest floor. Real-time Salmonella PCR assays were performed for each PLN sample to determine
Salmonella presence. The cattle supplemented with both DFMs had reduced foodborne pathogens
in fecal samples, but feces collected from the pens housing the cattle supplemented with Probicon
consistently had significantly less E. coli O157:H7 and Salmonella prevalence as well as a lower
C. perfringens
concentration. While DFMs do not eliminate foodborne pathogens in fecal shedding
and PLNs, the use of DFMs as a pre-harvest intervention allows for an effective way to target multiple
pathogens reducing the public health risks and environmental dissemination from cattle.
Keywords:
E. coli O157:H7; Salmonella;Clostridium perfringens; enterobacteriaceae; peripheral lymph
node; direct-fed microbials; pre-harvest food safety
1. Introduction
Food safety is a prominent concern for meat products in the United States. It is
estimated that each year in the U.S., nine million people become ill, 56,000 are hospitalized,
and 1300 die of foodborne diseases caused by known pathogens [
1
]. Of the 31 known
pathogens, seven of the leading ones contribute to 90% of domestically acquired foodborne
illnesses, hospitalizations, and deaths, causing about 112,000 disability adjusted life years
(DALYs) annually in the U.S. [
2
]. “Healthy people” goals for 2030 include being free of
preventable diseases, including foodborne diseases that originate from livestock [
3
]. While
this 10-year goal may seem far reaching, these goals have driven research in identifying
problem areas within the meat industry and in controlling and mitigating pre- and post-
harvest contamination of products.
Naturally, livestock harbor a wide variety of microorganisms, some of which are
identified as foodborne pathogens and have the potential to enter the food supply chain.
Foods 2022,11, 3834. https://doi.org/10.3390/foods11233834 https://www.mdpi.com/journal/foods
Foods 2022,11, 3834 2 of 16
Recent studies have identified Escherichia coli O157:H7, Salmonella spp., Enterobacteriaceae,
and Clostridium perfringens all as common pathogens found in cattle feces [
4
–
11
]. In addition
to causing foodborne illnesses, C. perfringens can result in animal health issues in cattle [
12
].
These pathogens from the live cattle can contaminate the carcass on the harvesting floor if
proper dressing procedures are not sustained, which can lead to contamination in the final
product, causing risk to the consumer. According to The Interagency Food Safety Analytics
Collaboration (IFSAC), in 2019 beef contributed to an estimated 24.3% of foodborne E. coli
O157:H7 infections and 6.2% of Salmonella infections [
1
]. While efforts should continue to
focus on reducing these percentages, it is important to note that over the last seven years a
declining trend in the percentage of illness contributed by beef, has been observed. In 2013,
it was reported by IFSAC that beef contributed to 37.9% of E. coli O157:H7 illnesses and
9.1% of Salmonella illnesses [
13
]. This decline is greatly attributed to the significant efforts
from the beef industry in terms of their advancement in pathogen reduction with the use of
antimicrobials and emphasis on proper dressing procedures to prevent the contamination
of carcasses [
5
]. While post-harvest interventions have been a main research focus over
the years, these issues also warrant management strategies geared towards controlling the
incoming pathogen loads entering commercial abattoirs on harvest-ready feedlot cattle.
Recent pre-harvest strategies have focused on the use of interventions, such as an-
timicrobials, bacteriophages, direct-fed microbials (DFMs), sodium chlorate, and vac-
cines
[14–16].
The majority of the research on pre-harvest interventions in cattle is targeted
to reduce the prevalence of E. coli O157:H7, mainly due to the recognition of cattle as
the principal reservoir of E. coli O157:H7 [
5
,
14
,
16
–
19
]. However, cattle have a very com-
plex natural gut microflora that colonizes multiple types of pathogenic bacteria; therefore,
supplementing their diet with DFMs provides the ability to target multiple foodborne
pathogens, including E. coli O157:H7, all within one intervention. Per the U.S. Food and
Drug Administration, DFMs are defined as “products that contain live microorganisms
like bacteria and/or yeast“ [
20
]. The use of DFM supplementation is an approach that
may confer health benefits on the host while simultaneously reducing the colonization of
pathogenic bacteria in the gastrointestinal tract [
21
]. The overall goal of feeding DFMs is to
promote the growth of microorganisms that are competitive or hostile to pathogenic bacte-
ria [
5
]. Recent studies have noted the efficacy of a DFM containing Lactobacillus acidophilus
(NP51) and Propionibacterium freudenreichii (NP24), also commercially known as Bovamine
®
Defend (CHR-Hansen; Hoersholm, Denmark) [
17
,
22
,
23
]. A systematic review from Sargent
et al. reported that four of the five treatment comparisons evaluating a DFM combination
of NP51 and NP24 achieved a significantly lower prevalence of E. coli O157:H7 in treated
cattle, regardless of the dosage [16].
The bovine lymphatic system, which includes the peripheral lymph nodes (PLNs),
has been identified as another potential source of pathogenic bacteria, more specifically
Salmonella, contamination in ground beef [
24
–
26
]. Pathogen contamination of ground beef
can occur when lymph nodes are incorporated in the manufacturing of beef trimmings.
According to the Centers for Disease Control (CDC), Salmonella causes about 1.35 million
infections, 26,500 hospitalizations, and 420 deaths in the United States every year [
27
].
Ground beef is an important vehicle for human exposure to Salmonella, and in recent years
an increasing trend in outbreaks, due to this foodborne pathogen, has been seen [
26
].
Since 2017, three large Salmonella outbreaks have totaled nearly as many illnesses and
more hospitalizations than all the Salmonella outbreaks linked to ground beef during the
previous 36 years [
28
,
29
]. For this reason, in October 2019, the United States Department of
Agriculture—Food Safety and Inspection Service (USDA-FSIS) announced the proposed
standards for Salmonella in raw ground beef, allowing for a maximum of two positive
samples in a 52-week period for a plant to be in “good standings” [30].
Significant efforts have been dedicated to surface area antimicrobial treatments in
beef production and processing; however, harborage of Salmonella within the PLNs pro-
vides protection against these surface-oriented mitigation approaches [
27
]. This source
of contamination would explain the greater prevalence of Salmonella observed in ground
Foods 2022,11, 3834 3 of 16
beef, relative to beef trim destined for ground beef. The effect of DFMs on Salmonella
prevalence has not been widely studied; however, results from Vipham et al., 2014 illustrate
that supplementing NP51 and NP24 in the diet of cattle may aid in reducing Salmonella
prevalence and concentration in the subiliac lymph nodes [
31
]. Overall, the proposed
Salmonella performance standards for ground beef will drive changes in the beef processing
industry to utilize more effective Salmonella controls throughout the production line, such
as the removal of lymph nodes from carcasses, and through pre-harvest interventions,
such as DFMs, in the hope of reducing pathogen prevalence corresponding to the public
health burden.
Lactobacillus salivarius is often isolated from animal and human samples and is known
to produce bacteriocins and has been used as a probiotic supplement for animal and human
health [
32
]. Lactobacillus salivarius L28 (Probicon) is a novel DFM isolated from ground
beef samples. When compared to a variety of lactic acid bacteria strains in a screening
study, L28 was shown to be more effective in inhibiting the growth of important foodborne
pathogens, Salmonella, E. coli O157:H7 and Listeria monocytogenes [
33
]. Being a novel strain,
its effectiveness in reducing foodborne pathogens in bovine feces in commercial conditions
have not been extensively reported; however, preliminary data indicates that the use of
L28 reduced and inhibited the growth of E. coli and Salmonella in artificially challenged
cattle manure and had similar effects as a sub-therapeutic antibiotic in terms of gain
performance and carcass traits in beef cattle (our unpublished data), indicating that it can
be an alternative to reduce the dependence on antibiotics in the cattle industry.
The objectives of this study were to (i) evaluate the effect of supplementing DFMs in
cattle’s diet compared to those who were fed a standard diet on the prevalence and/or con-
centration of E. coli O157:H7, Salmonella, Enterobacteriaceae, and Clostridium perfringens in
the feces of beef cattle; (ii) evaluate whether the administration of Probicon (L28) [
34
] would
have greater or similar effects to Bovamine Defend (NP51 and NP24); and
(iii) evaluate
the
impact the supplementation of DFMs has on Salmonella prevalence in the peripheral lymph
nodes of beef cattle.
2. Materials and Methods
2.1. Treatment Groups—Cattle Feed Yards
Three different cattle feed yards, all part of a Wagyu branded natural beef program,
located in Eastern Nebraska and Western Iowa, were utilized in this study. The size of these
three feed yards ranged from approximately 1000 to 9000 cattle on feed, with a range in
pen sizes from approximately 75 to 300 head/pen. From each feed yard three pens were
selected in which the same pens were sampled during every sampling event. The total
number of cattle housed between the three pens sampled for each treatment group were
approximately 300 head in the BD supplemented pens, approximately 600 head in the PC
supplemented pens, and approximately 500 head in the control group pens. The cattle were
on feed yard rations for a minimum of 200 days, when their diets consisted of high moisture
corn, course roughage, corn silage, corn by-products, and supplements (no monensin or
tylosin added). The study consisted of three treatment groups: (i.) Control: standard diet
with no supplemented DFM; (ii.) Bovamine Defend (BD): standard diet supplemented with
Lactobacillus acidophilus (NP51) and Propionibacterium freudenreichii (NP24) at a target dose of
9 log
10
CFU/head/day, which is a commercially available DFM (CHR-Hansen; Hoersholm,
Denmark); and (iii.) Probicon (PC): standard diet supplemented with Lactobacillus salivarius
(L28) at a target dose of 6 log
10
CFU/head/day, which is a commercially available DFM
(NexGen Innovations LLC, Lubbock, TX, USA). DFMs were directly mixed with the daily
feed using a commercial feed yard micro machine and distributed to the pens during the
study period. The control yard had never been supplemented with any DFM or probiotic,
the BD yard had been using BD for at least a year, and the PC yard had been on BD for at
least five years but started using PC in March 2021.
Foods 2022,11, 3834 4 of 16
2.2. Sample Collection
Fresh fecal samples from the pen floor were collected from a total of nine pens
(
n= 3 pens/feed yard
) every 28 days over a five-month period, from May to September
2021. All three feed yards were sampled on the same day for each sampling event as
outlined in Table 1. Fresh fecal material from the pen floors was collected using a teaspoon,
one spoon per fecal pat, and placed into a sterile fecal specimen container. Approximately
5 to 10 samples were collected from each pen, depending on how many head were in the
pen (<100 head = 5 samples; >200 head = 10 samples) to capture approximately 5% of the
total animal population in the pens. A total of 300 fecal samples were collected among
all treatments (Control: n= 110, BD: n= 75, PC: n= 115). Specimen containers contain-
ing fecal samples, were immediately chilled and shipped overnight to an independent,
third-party laboratory.
Table 1. Overview of the fecal sampling design with corresponding sample sizes.
Date Treatment
Number of Samples
Pen 1 Pen 2 Pen 3
26-May-2021 Control 10 10 2
28-Jun-2021 Control 10 10 2
27-Jul-2021 Control 10 10 2
23-Aug-2021 Control 10 10 2
21-Sep-2021 Control 10 10 2
26-May-2021 BD 5 5 5
28-Jun-2021 BD 5 5 5
27-Jul-2021 BD 5 5 5
23-Aug-2021 BD 5 5 5
21-Sep-2021 BD 5 5 5
26-May-2021 PC 10 10 3
28-Jun-2021 PC 10 10 3
27-Jul-2021 PC 10 10 3
23-Aug-2021 PC 10 10 3
21-Sep-2021 PC 10 10 3
Bovine subiliac PLNs were collected, over a two-month period, from the carcasses
of the same cattle used in the fecal sampling portion of this study. Lymph nodes were
immediately chilled and shipped overnight to the ICFIE Food Microbiology Laboratory
at Texas Tech University for microbiological analysis. A total of 215 PLNs (control:
n= 74
,
BD: n= 72, PC: n= 69) were collected between all treatment groups. All samples were
collected from the carcasses of animals after post-mortem inspection at a large commercial
USDA-FSIS inspected beef processing facility in Eastern Nebraska.
2.3. Fecal Sample Analysis
Fecal samples were blindly sent to a third-party laboratory (Food Safety Net Services,
San Antonio, TX, USA) for analysis. Each fecal sample was homogenized manually in the
original sample bag and 10 g sub-samples were transferred to a new, sterile, filtered sample
bag for further processing for each analysis.
For the detection of E. coli O157:H7, the sub-samples were homogenized in 90 mL BAX
MP Media (Hygiena, Camarillo, CA, USA) for 2 min and incubated at 42
◦
C for
18–24 h
.
After incubation, a 20
µ
L aliquot was placed into a BAX Cluster Tube filled with 200
µ
L
of prepared BAX Lysis Reagent (150
µ
L protease + 12 mL lysis buffer). The tubes were
heated at 37
◦
C for 20 min and at 95
◦
C for 10 min and then cooled to 2–8
◦
C for at least
5 min
. After cooling, a 30
µ
L aliquot of lysate was placed into a BAX System Real-Time
PCR Assay for the E. coli O157:H7 PCR tube and processed in a BAX Q7 Instrument for the
BAX System Real-Time PCR Assay for E. coli O157:H7 Exact.
Only the positive E. coli O157:H7 samples were subjected to quantification by a modi-
fied three-tube most probable number method combined with molecular detection. Briefly,
Foods 2022,11, 3834 5 of 16
three replications of 10
−1
to 10
−4
dilutions of the retained original sample were placed in
96-well deep well plates and incubated at 42
◦
C for 18–24 h for enrichment. After incuba-
tion, 10
µ
L of enriched samples were added to 500
µ
L of pre-warmed (37
◦
C) Brain Heart
Infusion (BHI) broth and incubated at 37
◦
C for 3 h and processed following the same steps
for detection of E. coli O157:H7 using the BAX System Real-Time PCR Assay.
For Salmonella detection, 90 mL of buffered peptone water (BPW) was added to the
bags, stomached for 2 min, and incubated at 35
◦
C for 18–24 h. After incubation, 5
µ
L
aliquots were transferred to BAX Cluster Tubes filled with 200
µ
L prepared BAX Lysis
Reagent (150
µ
L protease + 12 mL lysis buffer). The tubes were heated at 37
◦
C for 20 min,
at 95
◦
C for 10 min, and cooled to 2–8
◦
C for at least 5 min. After cooling, 30
µ
L aliquots
of lysate were transferred to BAX System PCR tubes and allowed to sit for 10–30 min in a
cooling block to allow full hydration of the PCR pellets. After hydration, all tubes were
placed in the BAX Q7 Instrument and the full process for BAX System Real-Time PCR
Assay for Salmonella was run [35]. Salmonella in positive samples was not enumerated.
Enterobacteriaceae enumeration was conducted by serially diluting the sub-sample
used for Salmonella detection in Butterfield’s Phosphate-Buffered Dilution Water (BPD)
blanks and plating 1 mL on Petrifilm
™
Enterobacteriaceae Count Plates (3M, St. Paul, MN,
USA) [
36
]. The plates were incubated at 35
◦
C for 24 h and all red colonies with yellow
zones and/or red colonies with gas bubbles with or without yellow zones were counted
as Enterobacteriaceae.
For C. perfringens enumeration, the sub-sample used for Salmonella detection was
serially diluted in BPD and 100
µ
L was spread plated on Tryptose Sulfite Cycloserine
Agar and incubated anaerobically at 35
◦
C for 24 h. All black colonies were counted as
C. perfringens.
2.4. Lymph Node Sample Processing and Salmonella Detection
Upon arrival, the surrounding fat and fascia were trimmed from the lymph node.
Each PLN was weighed, submerged into boiling water for 3 to 5 s for surface sterilization,
placed in a filtered Whirl-Pak bag (Nasco, St. Petersburg, FL, USA), and pulverized with a
rubber mallet. Depending on the weight of the lymph node, either 20 mL (if
PLN < 10 g
) or
80 mL (if PLN 10–50 g) of BAX MP (Hygiena, LLC, Camarillo, CA, USA), a non-selective
enrichment media, was aseptically added. The lymph node homogenate (LNH) was
then stomached (Model 400 circulator, Seward, West Sussex, UK) at 230 RPM for 1 min.
Following homogenization, the samples were incubated at 42 ◦C for 24 h.
After the desired incubation time was reached, a Real-Time (RT) Salmonella assay was
performed on the pre-enriched samples for Salmonella prevalence using the Hygiena BAX
®
Q7 system (Hygiena, LLC, Camarillo, CA, USA) according to the Association of Official
Agriculture Chemists (AOAC) approved BAX
®
System Q7 test protocol for RT Salmonella
PCR assays following the procedure given in Section 2.3 [37].
2.5. Statistical Analysis
Longitudinal fecal contamination data was analyzed using the generalized estimating
equations (GEE) approach using the “geepack” package available for R (Version 4.1.1.) [
38
].
The generalized estimating equation method is an extension to generalized linear mod-
els (GLM) that would allow the analysis of correlated data, such as repeated measures,
longitudinal analysis, or nested designs, and continuous or discrete dependent variables.
In this study, it was expected that the longitudinal design would require adjustments for
the correlation within the sampled pens and both dichotomous and continuous outcomes
were observed; therefore, GEE was selected as the method of statistical analysis [
39
,
40
].
Prevalence data were modeled using binomial distribution with logit link and concentra-
tion data were modeled using Gaussian distribution with identity link. The treatment
type and the date of sampling were included in the models as categorical variables and
the measurements were assumed to be nested within the different pens over repeated
measures. The interaction terms were removed from the model if no significant interaction
Foods 2022,11, 3834 6 of 16
was detected by a preliminary analysis. All significant differences were evaluated using a
p-value lower than 0.05. The results of the analysis were provided as a natural logarithm of
the odds ratio (lnOR) for prevalence and the mean difference for concentration.
The PLN data was analyzed using R (Version 4.1.1) statistical software to evaluate
the prevalence of Salmonella between the different treatment groups (control, BD, and PC).
Contingency tables were produced for the prevalence of Salmonella (+/
−
). Within table
differences were determined using Fisher’s exact test to determine the significance
(p< 0.05)
between treatment groups. Exact binomial confidence intervals for the prevalence estimates
were calculated using the ‘propCI’ base function in R based on Clopper and Pearson [41].
3. Results
The results indicate that both DFMs used in the study are effective in reducing the
prevalence and/or concentration of foodborne pathogens in cattle feces throughout the
beef production chain. Overall, the feces samples collected from the pens housing cattle
supplemented with Probicon had significantly less E. coli O157:H7 and Salmonella as well
as C. perfringens concentration. Salmonella prevalence in PLNs collected from the cattle
supplemented with DFM was lower compared to the presence of Salmonella in the control
group. Although DFMs tested in this study and other similar studies do not eliminate the
presence of pathogens [
22
,
31
,
42
–
44
], DFM supplements can reduce the public health risks
and environmental dissemination from cattle.
3.1. Fecal Samples
3.1.1. E. coli O157:H7 Prevalence and Concentration
The average E. coli O157:H7 prevalence was 20% (22/110), 10% (12/115), and 11%
(8/75) for the control, PC, and BD groups, respectively, averaging over the sampling
period. A comparison of E. coli O157:H7 prevalence at each sampling date for the two
treatment groups and the control group is represented in Figure 1. At the beginning of
the study period (May 2021), prior to any DFM supplementation, the prevalence in the
fecal samples was 0.00 (95% CI: 0, 15) for the control group, 17% (95% CI: 5, 39) for the
PC group, and 7% (95% CI: 0, 32) for the BD group. In order to account for prevalence
differences in pens, the GEE analysis was nested within the different pens. At the end
of the sampling period (September 2021), E. coli O157:H7 prevalence was higher than
the initial prevalence (May 2021) for both the treatment and control groups, which could
have occurred because prevalence typically increases in the summer months. Prevalence
in the control group reached up to 50% (95% CI: 28, 72), while the PC and BD groups
had a lower and more comparable prevalence of 22% (95% CI: 7, 44) and 20% (95% CI: 4,
48), respectively, and the difference was marginally significant (p< 0.10) when compared
pairwise, possibly due to the limited sample size. Seasonal differences in prevalence were
observed during the sampling period. Although the initial prevalence (May 2021) of the
pens treated with PC was higher than the others, it was lower than the control and BD
groups during sampling in June 2021. In July and August 2021, overall prevalence was low
for all three groups combined. No E. coli O157:H7 was detected in the samples from the PC
and BD supplemented pens on these sampling dates, while the control treatment yielded
some positive results.
Foods 2022,11, 3834 7 of 16
Foods 2022, 11, x FOR PEER REVIEW 7 of 16
during sampling in June 2021. In July and August 2021, overall prevalence was low for all
three groups combined. No E. coli O157:H7 was detected in the samples from the PC and
BD supplemented pens on these sampling dates, while the control treatment yielded some
positive results.
Figure 1. E. coli O157: H7 prevalence (%) of fecal samples collected from the pen floors over the
course of a 5-month sampling period at three different feed yards (n = 3 pens/feed yard). Control
(May: 0/22, June: 8/22, July: 1/22, August: 2/22, September: 11/22); BD (May: 1/15, June: 4/15, July:
0/15, August: 0/15, September: 3/15); PC (May: 4/23, June: 3/23, July: 0/23, August: 0/23, September:
5/23). Error bars represent 95% confidence intervals (CI).
The results of the statistical analysis indicated that the effect of PC was significantly
different from the control treatment (OR = 0.42, p = 0.039), while the effect of BD was not
(OR = 0.43, p = 0.099) when analyzed using the GEE approach given in Table 2. However,
the effect of BD was meaningful and comparable to PC. When compared to the measures
used in May 2021 (beginning of the sampling period), the prevalence in June 2021 and
September 2021 (end of the sampling period), were significantly higher throughout the
different treatment groups (p = 0.04, p = 0.01, respectively).
Table 2. Results of the GEE analysis for E. coli O157:H7 prevalence.
Term Estimate (lnOR) Standard Error p-Value
Intercept −1.92 0.60 0.001
Probicon −0.88 0.43 0.039
Bovamine Defend −0.85 0.52 0.099
June 2021 1.33 0.64 0.039
July 2021 −1.69 1.01 0.093
August 2021 −0.98 1.02 0.338
September 2021 1.67 0.66 0.012
Since very few samples were positive for E. coli O157:H7 throughout the study, no
statistical analysis was performed for the concentration measured by the modified MPN
method. Enumeration was not performed in May and July 2021. However, in June 2021,
Figure 1.
E. coli O157: H7 prevalence (%) of fecal samples collected from the pen floors over the
course of a 5-month sampling period at three different feed yards (n= 3 pens/feed yard). Control
(May: 0/22, June: 8/22, July: 1/22, August: 2/22, September: 11/22); BD (May: 1/15, June: 4/15,
July: 0/15, August: 0/15, September: 3/15); PC (May: 4/23, June: 3/23, July: 0/23, August: 0/23,
September: 5/23). Error bars represent 95% confidence intervals (CI).
The results of the statistical analysis indicated that the effect of PC was significantly
different from the control treatment (OR = 0.42, p= 0.039), while the effect of BD was not
(OR = 0.43, p= 0.099) when analyzed using the GEE approach given in Table 2. However,
the effect of BD was meaningful and comparable to PC. When compared to the measures
used in May 2021 (beginning of the sampling period), the prevalence in June 2021 and
September 2021 (end of the sampling period), were significantly higher throughout the
different treatment groups (p= 0.04, p= 0.01, respectively).
Table 2. Results of the GEE analysis for E. coli O157:H7 prevalence.
Term Estimate (lnOR) Standard Error p-Value
Intercept −1.92 0.60 0.001
Probicon −0.88 0.43 0.039
Bovamine Defend −0.85 0.52 0.099
June 2021 1.33 0.64 0.039
July 2021 −1.69 1.01 0.093
August 2021 −0.98 1.02 0.338
September 2021 1.67 0.66 0.012
Since very few samples were positive for E. coli O157:H7 throughout the study, no
statistical analysis was performed for the concentration measured by the modified MPN
method. Enumeration was not performed in May and July 2021. However, in June 2021,
the geometric means for the E. coli O157:H7 counts were 138.0 (n= 8), 790.0 (n= 4), and
3.6 (n= 2) MPN/g for the control, BD and PC groups, respectively. In August 2021, two
control samples that tested positive had a geometric mean of 39.3 MPN/g. In September
2021, the E. coli O157:H7 geometric mean of counts was 4.6 (n= 11), 11.8 (n= 3), and 3.4
(n= 5) MPN/g for the control, BD, and PC groups, respectively.
Foods 2022,11, 3834 8 of 16
3.1.2. Salmonella Prevalence
The average Salmonella prevalence in feces was 24% (26/110), 2% (2/115), and 3%
(2/75) for the control, PC, and BD supplemented cattle, respectively. Salmonella prevalence
for the two treatments and a control group over the experimental period is represented in
Figure 2. Initially in May 2021, none of the fecal samples were positive for feces collected
from pens housing cattle supplemented with PC and BD, while the control group had a
prevalence of 18% (95% CI: 5, 40). During sampling in June 2021, the prevalence in all
three groups increased, and during the consecutive two months a prevalence similar to
the initial sampling dates was observed. At the end of the five-month sampling period
(September 2021), the prevalence of Salmonella was 9% (95% CI: 1, 29), 4% (95% CI: 0, 22),
and 7%
(95% CI: 0, 32)
for the control, PC, and BD feces samples, respectively. There was
no significant difference at the end of the sampling period (p> 0.05), thus both DFMs were
effective in keeping the Salmonella prevalence low when averaged over time.
Foods 2022, 11, x FOR PEER REVIEW 8 of 16
the geometric means for the E. coli O157:H7 counts were 138.0 (n = 8), 790.0 (n = 4), and 3.6
(n = 2) MPN/g for the control, BD and PC groups, respectively. In August 2021, two control
samples that tested positive had a geometric mean of 39.3 MPN/g. In September 2021, the
E. coli O157:H7 geometric mean of counts was 4.6 (n = 11), 11.8 (n = 3), and 3.4 (n = 5)
MPN/g for the control, BD, and PC groups, respectively.
3.1.2. Salmonella Prevalence
The average Salmonella prevalence in feces was 24% (26/110), 2% (2/115), and 3%
(2/75) for the control, PC, and BD supplemented cattle, respectively. Salmonella prevalence
for the two treatments and a control group over the experimental period is represented in
Figure 2. Initially in May 2021, none of the fecal samples were positive for feces collected
from pens housing cattle supplemented with PC and BD, while the control group had a
prevalence of 18% (95% CI: 5, 40). During sampling in June 2021, the prevalence in all
three groups increased, and during the consecutive two months a prevalence similar to
the initial sampling dates was observed. At the end of the five-month sampling period
(September 2021), the prevalence of Salmonella was 9% (95% CI: 1, 29), 4% (95% CI: 0, 22),
and 7% (95% CI: 0, 32) for the control, PC, and BD feces samples, respectively. There was
no significant difference at the end of the sampling period (p > 0.05), thus both DFMs were
effective in keeping the Salmonella prevalence low when averaged over time.
Figure 2. Salmonella prevalence (%) in fecal samples collected from the pen floors over the course of
a 5-month sampling period at three different feed yards (n = 3 pens/feed yard). Control (May: 4/22,
June: 12/22, July: 4/22, August: 4/22, September: 2/22); BD (May: 0/15, June: 1/15, July: 0/15, August:
0/15, September: 1/15); PC (May: 0/23, June: 1/23, July: 0/23, August: 0/23, September: 1/23). Error
bars represent 95% confidence intervals (CI).
The prevalence at the end of the sampling period was not significantly different for
the control or treatment groups, when compared pairwise. However, a longitudinal anal-
ysis showed that the effect of PC (OR = 0.05, p < 0.001) and BD (OR = 0.07, p < 0.001) were
both statistically significant over time (Table 3). Overall, the prevalence in June 2021 was
significantly higher (p < 0.001) than the other sampling dates.
Figure 2.
Salmonella prevalence (%) in fecal samples collected from the pen floors over the course of a
5-month
sampling period at three different feed yards (n= 3 pens/feed yard). Control (
May: 4/22
,
June: 12/22, July: 4/22, August: 4/22, September: 2/22); BD (
May: 0/15
, June: 1/15, July: 0/15, Au-
gust: 0/15, September: 1/15); PC (May: 0/23, June: 1/23, July: 0/23, August: 0/23,
September: 1/23
).
Error bars represent 95% confidence intervals (CI).
The prevalence at the end of the sampling period was not significantly different for the
control or treatment groups, when compared pairwise. However, a longitudinal analysis
showed that the effect of PC (OR = 0.05, p< 0.001) and BD (OR = 0.07, p< 0.001) were
both statistically significant over time (Table 3). Overall, the prevalence in June 2021 was
significantly higher (p< 0.001) than the other sampling dates.
Foods 2022,11, 3834 9 of 16
Table 3. Results of the GEE analysis for Salmonella prevalence.
Term Estimate (lnOR) Standard Error p-Value
Intercept −1.64 0.31 <0.001
Probicon −3.05 0.68 <0.001
Bovamine Defend −2.61 0.73 <0.001
June 2021 1.76 0.43 <0.001
July 2021 0.00 0.90 1.000
August 2021 0.00 0.90 1.000
September 2021 0.00 0.70 1.000
3.1.3. Clostridium Perfringens Concentration
The enumeration of C. perfringens in the fecal samples was conducted monthly between
June and September 2021 and the data is illustrated in Figure 3. During the initial sampling
in June 2021, the mean concentrations in feces were 1.77 log
10
CFU/g (95% CI: 0.95, 2.58),
0.97 log
10
CFU/g (95% CI: 0.24, 1.70), and 2.03 log
10
CFU/g (95% CI: 0.91, 3.16) for the
control, PC, and BD groups, respectively. In September 2021, the concentrations for the
control (3.92 log
10
CFU/g; 95% CI: 3.69, 4.15) and BD (3.93 log
10
CFU/g; 95% CI: 3.68,
4.18) treated pens were similar, but it was significantly lower in the pens treated with PC
(2.27 log
10
CFU/g; 95% CI: 1.53, 3.03; p< 0.001). Overall, it was observed that the cattle
supplemented with PC had a mean of 1.07 log
10
CFU/g reduction in fecal shedding of
C. perfringens
. The statistical analysis showed that only PC provided a significantly reduced
number of C. perfringens throughout and at the end of the sampling period (p< 0.001), while
BD was not significantly different from the control group (p> 0.05) as shown in Table 4. The
effect of time was also significant during sampling in July and September 2021, indicating
seasonal changes in concentrations.
Foods 2022, 11, x FOR PEER REVIEW 9 of 16
Table 3. Results of the GEE analysis for Salmonella prevalence.
Term Estimate (lnOR) Standard Error p-Value
Intercept −1.64 0.31 <0.001
Probicon −3.05 0.68 <0.001
Bovamine Defend −2.61 0.73 <0.001
June 2021 1.76 0.43 <0.001
July 2021 0.00 0.90 1.000
August 2021 0.00 0.90 1.000
September 2021 0.00 0.70 1.000
3.1.3. Clostridium Perfringens Concentration
The enumeration of C. perfringens in the fecal samples was conducted monthly be-
tween June and September 2021 and the data is illustrated in Figure 3. During the initial
sampling in June 2021, the mean concentrations in feces were 1.77 log
10
CFU/g (95% CI:
0.95, 2.58), 0.97 log
10
CFU/g (95% CI: 0.24, 1.70), and 2.03 log
10
CFU/g (95% CI: 0.91, 3.16) for
the control, PC, and BD groups, respectively. In September 2021, the concentrations for
the control (3.92 log
10
CFU/g; 95% CI: 3.69, 4.15) and BD (3.93 log
10
CFU/g; 95% CI: 3.68,
4.18) treated pens were similar, but it was significantly lower in the pens treated with PC
(2.27 log
10
CFU/g; 95% CI: 1.53, 3.03; p < 0.001). Overall, it was observed that the cattle sup-
plemented with PC had a mean of 1.07 log
10
CFU/g reduction in fecal shedding of C.
perfringens. The statistical analysis showed that only PC provided a significantly reduced
number of C. perfringens throughout and at the end of the sampling period (p < 0.001),
while BD was not significantly different from the control group (p > 0.05) as shown in
Table 4. The effect of time was also significant during sampling in July and September
2021, indicating seasonal changes in concentrations.
Figure 3. C. perfringens average concentration (log
10
CFU/g) in fecal samples collected from the pen
floors over the course of a 4-month sampling period at three different feed yards (n = 3 pens/feed
yard). Error bars represent 95% confidence intervals (CI).
Figure 3.
C. perfringens average concentration (log
10
CFU/g) in fecal samples collected from the pen
floors over the course of a 4-month sampling period at three different feed yards (n= 3 pens/feed
yard). Error bars represent 95% confidence intervals (CI).
Foods 2022,11, 3834 10 of 16
Table 4. Results of the GEE analysis for C. perfringens concentration.
Term Estimate Standard Error p-Value
Intercept 1.97 0.29 <0.001
Probicon −1.08 0.28 <0.001
Bovamine Defend 0.06 0.26 0.822
July 2021 3.23 0.35 <0.001
August 2021 0.66 0.37 0.071
September 2021 1.77 0.32 <0.001
The frequency of obtaining high (>4 log
10
CFU/g), medium (>2 log
10
CFU/g and
≤
4 log
10
CFU/g), or low (
≤
2 log
10
CFU/g) counts was also considered for C. perfringens
concentrations at four distinct sampling dates as shown in Figure 4. It was observed that
the frequency of medium or low concentrations in fecal samples from the pens treated
with PC was constantly higher than for the control and BD groups for all sampling dates
(June through September 2021). Overall, the data highlights the performance of Probicon
on controlling C. perfringens contamination in pen surface fecal samples by lowering the
concentration in the feces, which was comparable to and often better than BD.
Foods 2022, 11, x FOR PEER REVIEW 10 of 16
Table 4. Results of the GEE analysis for C. perfringens concentration.
Term Estimate Standard Error p-Value
Intercept 1.97 0.29 <0.001
Probicon −1.08 0.28 <0.001
Bovamine Defend 0.06 0.26 0.822
July 2021 3.23 0.35 <0.001
August 2021 0.66 0.37 0.071
September 2021 1.77 0.32 <0.001
The frequency of obtaining high (>4 log
10
CFU/g), medium (>2 log
10
CFU/g and ≤4
log
10
CFU/g), or low (≤2 log
10
CFU/g) counts was also considered for C. perfringens concen-
trations at four distinct sampling dates as shown in Figure 4. It was observed that the
frequency of medium or low concentrations in fecal samples from the pens treated with
PC was constantly higher than for the control and BD groups for all sampling dates (June
through September 2021). Overall, the data highlights the performance of Probicon on
controlling C. perfringens contamination in pen surface fecal samples by lowering the con-
centration in the feces, which was comparable to and often better than BD.
Figure 4. Frequency (number of samples) of C. perfringens contamination levels in fecal samples
collected from the pen floors over a 4-month period sampling three different treatment groups. The
contamination level is represented on a scale of low, medium, and high. High being > 4 log
10
CFU/g,
medium being > 2 log
10
CFU/g, and low being ≤ 2 log
10
CFU/g. Each bar represents the number of
samples for that treatment that fall into each contamination level category for each of the four dis-
tinct sampling dates.
Figure 4.
Frequency (number of samples) of C. perfringens contamination levels in fecal samples
collected from the pen floors over a 4-month period sampling three different treatment groups. The
contamination level is represented on a scale of low, medium, and high. High being > 4 log
10
CFU/g,
medium being > 2 log
10
CFU/g, and low being
≤
2 log
10
CFU/g. Each bar represents the number of
samples for that treatment that fall into each contamination level category for each of the four distinct
sampling dates.
Foods 2022,11, 3834 11 of 16
3.1.4. Enterobacteriaceae Concentration
The enumeration of Enterobacteriaceae bacteria in fecal samples was conducted over
a 4-month period between May to September 2021 as an indicator, excluding the month
of August 2021. The mean counts of Enterobacteriaceae were above 4 log
10
CFU/g for all
treatments throughout the entire sampling period, and achieved a minimum 1 log
10
CFU/g
reduction, naturally, as shown in Figure 5. The effect of both DFM treatments were not
statistically significant (p> 0.05) throughout the experimental period, as shown in Table 5.
During the sampling period a mean reduction of 1.32
±
0.17 log
10
CFU/g was observed for
all the treatment groups. However, the counts were statistically significant during July and
September 2021 (p< 0.01) with a decreasing trend over time (Table 5).
Foods 2022, 11, x FOR PEER REVIEW 11 of 16
3.1.4. Enterobacteriaceae Concentration
The enumeration of Enterobacteriaceae bacteria in fecal samples was conducted over
a 4-month period between May to September 2021 as an indicator, excluding the month
of August 2021. The mean counts of Enterobacteriaceae were above 4 log
10
CFU/g for all
treatments throughout the entire sampling period, and achieved a minimum 1 log
10
CFU/g
reduction, naturally, as shown in Figure 5. The effect of both DFM treatments were not
statistically significant (p > 0.05) throughout the experimental period, as shown in Table
5. During the sampling period a mean reduction of 1.32 ± 0.17 log
10
CFU/g was observed
for all the treatment groups. However, the counts were statistically significant during July
and September 2021 (p < 0.01) with a decreasing trend over time (Table 5).
Figure 5. Enterobacteriaceae concentration in fecal samples collected from the pen floors over the
course of 4-month sampling period at three different feed yards (n = 3 pens/feed yard). Error bars
represent 95% confidence intervals (CI).
Table 5. Results of the GEE analysis for Enterobacteriaceae concentration.
Term Estimate Standard Error p-Value
Intercept 6.16 0.26 <0.001
Probicon 0.12 0.27 0.65
Bovamine Defend 0.45 0.28 0.11
May 2021 −0.42 0.28 0.13
July 2021 −1.30 0.49 0.007
September 2021 −1.07 0.27 <0.001
3.2. Peripheral Lymph Node Samples
Salmonella Prevalence
The lymph nodes collected from the control group cattle and from the cattle housed
in pens treated with Probicon and Bovamine Defend were compared using Fisher’s exact
test. The prevalence of Salmonella was 8.11% (6/74) in the control group, 1.45% (1/69) in
Figure 5.
Enterobacteriaceae concentration in fecal samples collected from the pen floors over the
course of 4-month sampling period at three different feed yards (n= 3 pens/feed yard). Error bars
represent 95% confidence intervals (CI).
Table 5. Results of the GEE analysis for Enterobacteriaceae concentration.
Term Estimate Standard Error p-Value
Intercept 6.16 0.26 <0.001
Probicon 0.12 0.27 0.65
Bovamine Defend 0.45 0.28 0.11
May 2021 −0.42 0.28 0.13
July 2021 −1.30 0.49 0.007
September 2021 −1.07 0.27 <0.001
3.2. Peripheral Lymph Node Samples
Salmonella Prevalence
The lymph nodes collected from the control group cattle and from the cattle housed
in pens treated with Probicon and Bovamine Defend were compared using Fisher’s exact
test. The prevalence of Salmonella was 8.11% (6/74) in the control group, 1.45% (1/69) in
the PC group, and 0% (0/72) in the BD group, as shown in Figure 6. The difference among
Foods 2022,11, 3834 12 of 16
three treatment groups were significant according to the Fisher’s test (p= 0.015) indicating
that at least one treatment group was different from another and the prevalence for BD
was significantly different from the control group (p= 0.028). However, the prevalence
for PC was not statistically different from either the BD or the control group (p> 0.05). It
should be noted that although Fisher’s exact test is suitable for small samples and low cell
counts, the statistical power of the test was impacted by the low prevalence and limited
sample size. The OR was 0.17 (95% CI: 0.02, 1.42) and the risk ratio (RR) was 0.18 (95%
CI: 0.02, 1.45) when comparing the odds of detecting positive PLNs in cattle treated with
PC compared to the control group, and a 39.63% (95% CI: 11.37, 50.00) prevented fraction
in the population and an 82% relative risk reduction (RRR) were estimated. For BD, OR
was 0.08 (95% CI: 0.00, 1.44), RR was 0.09 (95% CI: 0.00, 1.50), prevented fraction in the
population was 49.32% (95% CI: 39.66, 50.00) and RR was 91%.
Foods 2022, 11, x FOR PEER REVIEW 12 of 16
the PC group, and 0% (0/72) in the BD group, as shown in Figure 6. The difference among
three treatment groups were significant according to the Fisher’s test (p = 0.015) indicating
that at least one treatment group was different from another and the prevalence for BD
was significantly different from the control group (p = 0.028). However, the prevalence for
PC was not statistically different from either the BD or the control group (p > 0.05). It
should be noted that although Fisher’s exact test is suitable for small samples and low cell
counts, the statistical power of the test was impacted by the low prevalence and limited
sample size. The OR was 0.17 (95% CI: 0.02, 1.42) and the risk ratio (RR) was 0.18 (95% CI:
0.02, 1.45) when comparing the odds of detecting positive PLNs in cattle treated with PC
compared to the control group, and a 39.63% (95% CI: 11.37, 50.00) prevented fraction in
the population and an 82% relative risk reduction (RRR) were estimated. For BD, OR was
0.08 (95% CI: 0.00, 1.44), RR was 0.09 (95% CI: 0.00, 1.50), prevented fraction in the popu-
lation was 49.32% (95% CI: 39.66, 50.00) and RR was 91%.
Figure 6. Salmonella prevalence (%) in bovine, subiliac, peripheral lymph node samples collected
from the carcasses of the same cattle that were studied in the fecal portion of this study. The total
number of positives for each treatment group, from all PLNs collected was Control: 6/74, BD: 0/72
and PC: 1/69. Error bars represent 95% confidence intervals (CI).
4. Discussion
In this study, the average E. coli O157:H7 prevalence was 20%, 10%, and 11% for con-
trol, PC, and BD groups, respectively. The cattle supplemented with Probicon had a sig-
nificantly reduced prevalence (p < 0.05) of E. coli O157:H7 in pen surface fecal samples
compared to the control group, although the initial prevalence was higher than the other
two groups, 17.4% compared to 0% for the control group and 6.67% for the BD group.
However, initial prevalence was low compared to similar previous reports within a range
from 12% to 42% [42–45] and most studies sampled fecal grabs rather than pen surface
material. According to a systematic review and meta-analysis by Weisener et al., a pooled
OR of 0.55 (95% CI: 0.45, 0.68) with moderate heterogeneity was estimated, indicating a
reduction in prevalence comparable to the results obtained in this study [44].
The average Salmonella prevalence in this study was 24%, 2%, and 3% for the control,
PC, and BD groups, respectively. The data indicated that both DFM treatments were sim-
ilarly effective in reducing prevalence, when averaged overtime, compared to no DFM
supplementation, corresponding to a lower risk of environmental dissemination. Previous
Figure 6.
Salmonella prevalence (%) in bovine, subiliac, peripheral lymph node samples collected
from the carcasses of the same cattle that were studied in the fecal portion of this study. The total
number of positives for each treatment group, from all PLNs collected was Control: 6/74, BD: 0/72
and PC: 1/69. Error bars represent 95% confidence intervals (CI).
4. Discussion
In this study, the average E. coli O157:H7 prevalence was 20%, 10%, and 11% for
control, PC, and BD groups, respectively. The cattle supplemented with Probicon had a
significantly reduced prevalence (p< 0.05) of E. coli O157:H7 in pen surface fecal samples
compared to the control group, although the initial prevalence was higher than the other
two groups, 17.4% compared to 0% for the control group and 6.67% for the BD group.
However, initial prevalence was low compared to similar previous reports within a range
from 12% to 42% [
42
–
45
] and most studies sampled fecal grabs rather than pen surface
material. According to a systematic review and meta-analysis by Weisener et al., a pooled
OR of 0.55 (95% CI: 0.45, 0.68) with moderate heterogeneity was estimated, indicating a
reduction in prevalence comparable to the results obtained in this study [44].
The average Salmonella prevalence in this study was 24%, 2%, and 3% for the control,
PC, and BD groups, respectively. The data indicated that both DFM treatments were
similarly effective in reducing prevalence, when averaged overtime, compared to no DFM
supplementation, corresponding to a lower risk of environmental dissemination. Previous
studies on the reduction of Salmonella prevalence in cattle treated with DFMs are scarce. In
a similar study, Tabe et al. reported no significant difference between the fecal prevalence
Foods 2022,11, 3834 13 of 16
of naturally infected cattle treated with L. acidophilus (LA51) and p. freudenreichii (PF24)
and control groups followed up for nine weeks [
42
]. However, they noted that DFM
supplements were effective in preventing new Salmonella infections among the studied
cohorts. Stephens et al. reported 48%, 38%, and 10% reductions in the likeliness of
detecting high, medium, and low concentrations, respectively in the feces of cattle treated
with BD compared to a control group [
22
]. Although Salmonella was not enumerated
from pen surface fecal samples during this study, reductions in the overall prevalence are
in accordance.
Although C. perfringens is a clinically important human and livestock pathogen [
46
]
the effect of DFM supplements in cattle has not been widely studied. Schoster et al.
and Goli´c et al. reported successful
in vitro
inhibition of C. perfringens by L. helveticus,
L. fermentum,Streptococcus thermophilus, and a variety of commercial strains of Lactobacillus
and Bifidobacterium as potential DFMs [
47
,
48
]. Goli´c et al. also reported undetectable levels
of C. perfringens in goats after probiotic treatment and another trial in commercial broilers
with a commercial DFM significantly reduced the C. perfringens concentration in broiler
chickens [
48
,
49
]. Our results show that the novel DFM strain, Lactobacillus salivarius L28,
can be effective in reducing the C. perfringens concentration in cattle feces, which would
reduce the dependency on antibiotics during cattle production.
The Salmonella prevalence in this study was 8.11%, 1.45%, and 0% for the control,
PC, and BD groups, respectively. Bovamine Defend was statistically significant from the
control group (p< 0.05), but it should be noted that the low prevalence and small sample
size impacts the statistical power of the test. In a previous study, Vipham et al. reported
a RRR of 50% (RR:0.50) and 31% (0.69) for detecting positive subiliac lymph nodes in
commercial feedlot cattle treated with NP51 and NP24 [
31
]. Furthermore, they estimated
an 82% RRR (RR:0.18) in research feedlot cattle within the same study settings.
Brown et al.
conducted an artificial challenge test to address PLN contamination in cattle quantita-
tively and qualitatively using three DFM formulations containing various Lactobacilli and
Pediococcus acidilactici [50]
. Although the number of Salmonella positive PLNs from the
treated cattle were numerically lower in the treatment groups (63% and 68.8% vs. 80.0%),
no statistical significance was detected. However, the quantitative results indicated a
significant reduction in Salmonella concentrations in PLNs. Therefore, the results of this
study, when compared to previous studies, indicate that Probicon might offer significant
reductions in Salmonella prevalence to mitigate ground beef contamination through PLNs.
5. Conclusions
The direct-fed microbials used in this study were effective in reducing the fecal shed-
ding of E. coli O157:H7, Salmonella, and C. perfringens and the prevalence of Salmonella
in PLNs, which means it may be an effective pre-harvest intervention. Furthermore,
while both DFMs were effective, feces collected from the cattle housed in pens treated
with Probicon had significantly less prevalence of E. coli O157:H7 and Salmonella and
Clostridium perfringens
concentration, thus it gave a better food safety outcome. The reduc-
tion of C. perfringens can be beneficial not only for food safety, but also for animal health
in feedlot settings. While supplementing cattle with Probicon does not eliminate the fecal
shedding of human and animal pathogens, it provides an effective solution to targeting
multiple foodborne pathogens within a single intervention in the hope of controlling the
incoming pathogen loads on harvest-ready feedlot cattle, thus lowering the risk to the
consumer. Probicon also served as an effective intervention in reducing Salmonella preva-
lence in bovine PLNs, which may aid in less ground beef contamination and help respond
to the public health burden. Overall, these results support the use of DFMs in a feedlot
setting, but further research should be conducted on a larger scale in commercial feedlots to
determine the efficacy of DFMs, specifically Probicon (L28), on the reduction of foodborne
pathogens in fecal shedding and the prevalence of Salmonella within bovine PLNs.
Foods 2022,11, 3834 14 of 16
Author Contributions:
Conceptualization, M.M.B., K.K.N.; methodology, M.M.B., W.M.K.; software,
O.B.D., M.G.F.; validation, M.M.B.; formal analysis, O.B.D., M.G.F.; investigation, W.M.K., M.G.F.,
M.M.B.; resources, M.M.B., W.M.K.; data curation, O.B.D., M.G.F., W.M.K.; writing—original draft
preparation, M.G.F., O.B.D.; writing—review and editing, M.G.F., O.B.D., M.M.B., K.K.N., W.M.K.;
visualization, O.B.D., M.G.F.; supervision, M.M.B., K.K.N.; project administration, M.M.B.; funding
acquisition, M.M.B. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by the Beef Checkoff and NexGen Innovations, LLC.
Data Availability Statement:
The data used to support the findings of this study can be made
available by the corresponding author upon request.
Acknowledgments:
We would like to acknowledge the help of all the ICFIE Food Microbiology
personnel that helped with the lymph node processing.
Conflicts of Interest:
Drs. Brashears and Nightingale are co-founders and own shares of NexGen
Innovations, LLC and their participation is governed by a management plan in place at Texas Tech to
mitigate the risks from conflicts of interest. Dr. Brashears receives royalty income from the sales of
Bovamine Defend.
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