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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

by
Makenzie G. Flach
1,
Onay B. Dogan
1,
Wanda M. Kreikemeier
2,
Kendra K. Nightingale
1 and
Mindy M. Brashears
1,*
1
International Center for Food Industry Excellence, Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA
2
Livestock Logic, LLC, 79521 Rd 417, Callaway, NE 68825, USA
*
Author to whom correspondence should be addressed.
Foods 2022, 11(23), 3834; https://doi.org/10.3390/foods11233834
Submission received: 23 September 2022 / Revised: 13 November 2022 / Accepted: 23 November 2022 / Published: 28 November 2022
(This article belongs to the Section Food Microbiology)
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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 log10CFU/g/head/day, and (iii.) Probicon: supplemented with L28 at a target dose of 6 log10CFU/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.

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. Recent studies have identified Escherichia coli O157:H7, Salmonella spp., Enterobacteriaceae, and Clostridium perfringens all as common pathogens found in cattle feces [4,5,6,7,8,9,10,11]. 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 antimicrobials, bacteriophages, direct-fed microbials (DFMs), sodium chlorate, and vaccines [14,15,16]. 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 [5,14,16,17,18,19]. However, cattle have a very complex 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 bacteria [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 [24,25,26]. 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 provides protection against these surface-oriented mitigation approaches [27]. This source of contamination would explain the greater prevalence of Salmonella observed in ground 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 concentration 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 log10CFU/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 log10CFU/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.

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 containing fecal samples, were immediately chilled and shipped overnight to an independent, third-party laboratory.
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 μL aliquot was placed into a BAX Cluster Tube filled with 200 μL of prepared BAX Lysis Reagent (150 μL 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 μL 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 modified three-tube most probable number method combined with molecular detection. Briefly, 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 incubation, 10 μL of enriched samples were added to 500 μL 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 μL aliquots were transferred to BAX Cluster Tubes filled with 200 μL prepared BAX Lysis Reagent (150 μL 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 μL 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 μL 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 models (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 concentration 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 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 [22,31,42,43,44], 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.
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).
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.

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.
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.

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 log10CFU/g (95% CI: 0.95, 2.58), 0.97 log10CFU/g (95% CI: 0.24, 1.70), and 2.03 log10CFU/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 log10CFU/g; 95% CI: 3.69, 4.15) and BD (3.93 log10CFU/g; 95% CI: 3.68, 4.18) treated pens were similar, but it was significantly lower in the pens treated with PC (2.27 log10CFU/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 log10CFU/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.
The frequency of obtaining high (>4 log10CFU/g), medium (>2 log10CFU/g and ≤4 log10CFU/g), or low (≤2 log10CFU/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.

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 log10CFU/g for all treatments throughout the entire sampling period, and achieved a minimum 1 log10CFU/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 log10CFU/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).

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 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%.

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% [42,43,44,45] 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 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 Golić 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]. Golić 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 quantitatively 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 shedding 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 reduction 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 prevalence 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.

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.

References

  1. Interagency Food Safety Analytics Collaboration [IFSAC]. Foodborne Illness Source Attribution Estimates for 2019 for Salmonella, Escherichia coli O157, Listeria monocytogenes, and Campylobacter Using Multi-Year Outbreak Surveillance Data, United States; GA and D.C: U.S. Department of Health and Human Services’ Centers for Disease Control and Prevention and U.S. Food and Drug Administration, U.S. Department of Agriculture’s Food Safety and Inspection Service 2021. Available online: https://www.cdc.gov/foodsafety/ifsac/pdf/P19-2019-report-TriAgency-508.pdf (accessed on 2 September 2022).
  2. Scallan, E.; Hoekstra, R.M.; Mahon, B.E.; Jones, T.F.; Griffin, P.M. An assessment of the human health impact of seven leading foodborne pathogens in the United States using disability adjusted life years. Epidemiol. Infect. 2015, 143, 2795–2804. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Office of Disease Prevention and Health Promotion. Healthy People 2030 Framework. Available online: https://health.gov/healthypeople/about/healthy-people-2030-framework (accessed on 15 July 2022).
  4. Donkersgoed, J.V.; Bohaychuk, V.; Besser, T.; Song, X.M.; Wagner, B.; Hancock, D.; Renter, D.; Dargatz, D. Occurrence of foodborne bacteria in Alberta feedlots. Can. Vet. J. 2009, 50, 166–172. [Google Scholar] [PubMed]
  5. Brashears, M.M.; Chaves, B.D. The diversity of beef safety: A global reason to strengthen our current systems. Meat Sci. 2017, 132, 59–71. [Google Scholar] [CrossRef]
  6. Stephens, T.P.; Loneragan, G.H.; Thompson, T.W.; Sridhara, A.; Branham, L.A.; Pitchiah, S.; Brashears, M.M. Distribution of Escherichia coli O157 and Salmonella on hide surfaces, the oral cavity, and in feces of feedlot cattle. J. Food Prot. 2007, 70, 1346–1349. [Google Scholar] [CrossRef] [PubMed]
  7. Arthur, T.M.; Keen, J.E.; Bosilevac, J.M.; Brichta-Harhay, D.M.; Kalchayanand, N.; Shackelford, S.D.; Wheeler, T.L.; Nou, X.; Koohmaraie, M. Longitudinal study of Escherichia coli O157:H7 in a beef cattle feedlot and role of high-level shedders in hide contamination. Appl. Environ. Microbiol. 2009, 75, 6515–6523. [Google Scholar] [CrossRef] [Green Version]
  8. Berry, E.D.; Wells, J.E. Chapter 4—Escherichia coli O157:H7: Recent advances in research on occurrence, transmission, and control in cattle and the production environment. Adv. Food Nutr. Res. 2010, 60, 67–117. [Google Scholar] [CrossRef] [PubMed]
  9. Callaway, T.R.; Edrington, T.S.; Brabban, A.D.; Keen, J.E.; Anderson, R.C.; Rossman, M.L.; Engler, M.J.; Genovese, K.J.; Gwartney, B.L.; Reagan, J.O.; et al. Fecal prevalence of Escherichia coli O157, Salmonella, Listeria, and bacteriophage infecting E. coli O157:H7 in feedlot cattle in the southern plains region of the United States. Foodborne Pathog. Dis. 2006, 3, 234–244. [Google Scholar] [CrossRef] [PubMed]
  10. Tschirdewahn, B.; Notermans, S.; Wernars, K.; Untermann, F. The presence of enterotoxigenic Clostridium perfringens strains in faeces of various animals. Int. J. Food Microbiol. 1991, 14, 175–178. [Google Scholar] [CrossRef] [PubMed]
  11. Hamza, D.; Dorgham, S.M.; Elhariri, M.; Elhelw, R.; Ismael, E. New insight of apparently healthy animals as a potential reservoir for Clostridium perfringens: A public health implication. J. Vet. Res. 2018, 62, 457–462. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Uzal, F.A.; McClane, B.A.; Cheung, J.K.; Theoret, J.; Garcia, J.P.; Moore, R.J.; Rood, J.I. Animal models to study the pathogenesis of human and animal Clostridium perfringens infections. Vet. Microbiol. 2015, 179, 23–33. [Google Scholar] [CrossRef] [PubMed]
  13. Interagency Food Safety Analytics Collaboration [IFSAC]. Foodborne Illness Source Attribution Estimates for 2013 for Salmonella, Escherichia coli O157, Listeria monocytogenes, and Campylobacter Using Multi-Year Outbreak Surveillance Data, United States; GA and D.C.: U.S. Department of Health and Human Services, CDC, FDA, USDA-FSIS, 2017. Available online: https://www.cdc.gov/foodsafety/pdfs/IFSAC-2013FoodborneillnessSourceEstimates-508.pdf (accessed on 2 September 2022).
  14. Wheeler, T.L.; Kalchayan, N.; Bosilevac, J.M. Pre- and post-harvest interventions to reduce pathogen contamination in the U.S. beef industry. Meat Sci. 2014, 98, 372–382. [Google Scholar] [CrossRef] [Green Version]
  15. Loneragan, G.H.; Brashears, M.M. Pre-harvest interventions to reduce carriage of E. coli O157 by harvest-ready feedlot cattle. Meat Sci. 2005, 71, 72–78. [Google Scholar] [CrossRef] [PubMed]
  16. Sargeant, J.M.; Amezcua, M.R.; Rajic, A.; Waddell, L. Pre-harvest interventions to reduce the shedding of E. coli O157 in the faeces of weaned domestic ruminants: A systematic review. Zooneses Public Health 2007, 54, 260–277. [Google Scholar] [CrossRef]
  17. Stephens, T.P.; Loneragan, G.H.; Chichester, L.M.; Brashears, M.M. Prevalence and enumeration of Escherichia coli O157 in steers receiving various strains of Lactobacillus-based direct-fed microbials. J. Food Prot. 2007, 70, 1252–1255. [Google Scholar] [CrossRef]
  18. Cull, C.A.; Paddocka, Z.D.; Nagarajaa, T.G.; Bello, N.M.; Babcockc, A.H.; Renter, D.G. Efficacy of a vaccine and a direct-fed microbial against fecal shedding of Escherichia coli O157:H7 in a randomized pen-level field trial of commercial feedlot cattle. Vaccine 2012, 30, 6210–6215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Brashears, M.M.; Amezquita, A.; Jaroni, D. Lactic acid bacteria and their uses in animal feeding to improve food safety. Adv. Food Nutr. Res. 2005, 50, 2–25. [Google Scholar] [CrossRef]
  20. U.S. Food and Drug Administration. Compliance Policy Guideline Sec. 689.100 Direct-Fed Microbial Products. Available online: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/cpg-sec-689100-direct-fed-microbial-products (accessed on 15 July 2022).
  21. Opheim, T.L. The Effects of a Novel Direct-Fed Microbial on Animal Performance and Carcass Characteristics of Feedlot Cattle. Ph.D. Thesis, Texas Tech University, Lubbock, TX, USA, May 2020. Available online: https://hdl.handle.net/2346/85832 (accessed on 24 February 2022).
  22. Stephens, T.P.; Loneragan, G.H.; Karunasena, E.; Brashears, M.M. Reduction of Escherichia coli O157 and Salmonella in feces and on hides of feedlot cattle using various doses of a direct-fed microbial. J. Food Prot. 2007, 70, 2386–2391. [Google Scholar] [CrossRef]
  23. Younts-Dahl, S.M.; Galyean, M.L.; Loneragan, G.H.; Elam, N.A.; Brashears, M.M. Dietary supplementation with Lactobacillus- and Propionibacterium-based direct-fed microbials and prevalence of Escherichia coli O157 in beef feedlot cattle and on hides at harvest. J. Food Prot. 2004, 67, 889–893. [Google Scholar] [CrossRef] [PubMed]
  24. Gragg, S.E.; Loneragan, G.H.; Brashears, M.M.; Arthur, T.M.; Bosilevac, J.M.; Kalchayanand, N.; Wang, R.; Schmidt, J.W.; Brooks, J.C.; Shackelford, S.D.; et al. Cross-sectional study examining Salmonella enterica carriage in subiliac lymph nodes of cull and feedlot cattle at harvest. Foodborne Pathog. Dis. 2013, 10, 368–374. [Google Scholar] [CrossRef] [Green Version]
  25. Arthur, T.M.; Brichta-Harhay, D.M.; Bosilevac, J.M.; Guerini, M.N.; Kalchayanand, N.; Wells, J.E.; Shackelford, S.D.; Wheeler, T.L.; Koohmaraie, M. Prevalence and characterization of Salmonella in bovine lymph nodes potentially destined for use in ground beef. J. Food Prot. 2008, 71, 1685–1688. [Google Scholar] [CrossRef] [PubMed]
  26. Webb, H.E.; Brichta-Harhay, D.M.; Brashears, M.M.; Nightingale, K.K.; Arthur, T.M.; Bosilevac, J.M.; Kalchayanand, N.; Schmidt, J.W.; Wang, R.; Granier, S.A.; et al. Salmonella in peripheral lymph nodes of healthy cattle at slaughter. Front. Microbiol. 2017, 8, 2214. [Google Scholar] [CrossRef] [Green Version]
  27. Centers for Disease Control and Prevention (CDC). Salmonella. Available online: https://www.cdc.gov/salmonella/index.html (accessed on 16 July 2022).
  28. Laufer, A.S.; Grass, J.; Holt, K.; Whichard, J.M.; Griffin, P.M.; Gould, L.H. Outbreaks of Salmonella infections attributed to beef—United States, 1973–2011. Epidemiol. Infect. 2015, 143, 2003–2013. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. National Center for Emerging and Zoonotic Infections. Salmonella and Ground Beef. Available online: https://www.cdc.gov/ncezid/dfwed/prevention-priorities/salmonella-and-ground-beef.html (accessed on 24 February 2022).
  30. Food Safety Inspection Service—U.S. Department of Agriculture. Public Health Effects of Performance Standards for Ground Beef and Beef Manufacturing Trimmings. 2019. Available online: https://www.fsis.usda.gov/sites/default/files/media_file/2020-08/beef-ps-aug-2019.pdf (accessed on 12 July 2022).
  31. Vipham, J.L.; Loneragan, G.H.; Guillen, L.M.; Brooks, J.C.; Johnson, B.J.; Pond, A.; Pond, N.; Brashears, M.M. Reduced burden on Salmonella enterica in bovine subiliac lymph nodes associated with administration of direct-fed microbial. Zoonoses Public Health 2015, 62, 599–608. [Google Scholar] [CrossRef] [PubMed]
  32. Chavez, B.D.; Brashears, M.M. Applications and safety considerations of Lactobacillus salivarius as a probiotic in animal and human health. J. Appl. Microbiol. 2017, 123, 18–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Ayala, D.I.; Cook, P.W.; Franco, J.G.; Bugarel, M.; Kottapalli, K.R.; Loneragan, G.H.; Brashears, M.M.; Nightingale, K.K. A systematic approach to identify and characterize the effectiveness and safety of novel probiotic strains to control foodborne pathogens. Front. Microbiol. 2019, 10, 1108. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Brashears, M.M.; Nightingale, K.K.; Campos, D. Reduction of Pathogens and Other Bacteria in Food and Feed Products Utilizing a Multiple Inhibition System with Lactic Acid Bacteria. U.S. Patent WO 2019/113217 A1, 13 June 2019. Available online: https://patentimages.storage.googleapis.com/1a/72/ae/c4386992ded080/WO2019113217A1.pdf (accessed on 23 July 2022).
  35. Bordonaro, R.; McDonough, P.L.; Chang, Y.; Mohammed, H.O. Molecular detection of Salmonella species in bovine fecal samples. J. Vet. Diagn. 2013, 25, 756–758. [Google Scholar] [CrossRef] [Green Version]
  36. U.S. Food and Drug Administration. BAM R11: Butterfield’s Phosphate-Buffered Dilution Water. Available online: https://www.fda.gov/food/laboratory-methods-food/bam-r11-butterfields-phosphate-buffered-dilution-water (accessed on 9 November 2022).
  37. Hygiena. BAX® System Real-Time PCR Assay: Salmonella. Available online: https://www.hygiena.com/wp-content/uploads/2020/09/BAX-Q7-Assay-Kit-Insert-Salmonella-RT-English.pdf (accessed on 17 July 2022).
  38. Liang, K.Y.; Zeger, S.L. Longitudinal data analysis using generalized linear models. Biomet. 1986, 73, 13–22. [Google Scholar] [CrossRef]
  39. Hanley, J.A.; Negassa, A.; Edwardes, M.D.B.; Forrester, J.E. Statistical analysis of correlated data using generalized estimating equations: An orientation. Am. J. Epidemiol. 2003, 157, 364–375. [Google Scholar] [CrossRef]
  40. Ballinger, G.A. Using generalized estimating equations for longitudinal data analysis. Organ. Res. Methods 2004, 7, 127–150. [Google Scholar] [CrossRef]
  41. Clopper, C.J.; Pearson, E.S. The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 1934, 26, 404–413. [Google Scholar] [CrossRef]
  42. Tabe, E.S.; Oloya, J.; Doetkott, D.K.; Uer, M.L.; Gib, P.S.; Khaitsa, M.L. Comparative effect of direct-fed microbials on fecal shedding of Escherichia coli O157:H7 and Salmonella in naturally infected feedlot cattle. J. Food Prot. 2008, 71, 539–544. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Younts-Dahl, S.M.; Osbo, G.D.; Galyean, M.L.; Rivera, J.D.; Loneragan, G.H.; Brashears, M.M. Reduction of Escherichia coli O157 in finishing beef cattle by various doses of Lactobacillus acidophilus in direct-fed microbials. J. Food Prot. 2016, 68, 6–10. [Google Scholar] [CrossRef] [PubMed]
  44. Wisener, L.V.; Sargeant, J.M.; O’Connor, A.M.; Faires, M.C.; Glass-Kaastra, S.K. The use of direct-fed microbials to reduce shedding of Escherichia coli O157 in beef cattle: A systematic review and meta-analysis. Zoonoses Public Health 2015, 62, 75–89. [Google Scholar] [CrossRef] [PubMed]
  45. Brashears, M.M.; Galyean, M.L.; Loneragan, G.H.; Mann, J.E.; Killinger-Mann, K. Prevalence of Escherichia coli O157:H7 and performance by beef feedlot cattle given Lactobacillus direct-fed microbials. J. Food Prot. 2016, 66, 748–754. [Google Scholar] [CrossRef] [PubMed]
  46. Uzal, F.A.; Freedman, J.C.; Shrestha, A.; Theoret, J.R.; Garcia, J.; Awad, M.M.; Adams, V.; Moore, R.J.; Rood, J.I.; McClane, B.A. Towards an understanding of the role of Clostridium perfringens toxins in human and animal disease. Future Microbiol. 2014, 9, 361–377. [Google Scholar] [CrossRef] [Green Version]
  47. Schoster, T.P.; Loneragan, G.H.; Karunuasena, E.; Brashears, M.M. In vitro inhibition of Clostridium difficile and Clostridium perfringens by commercial probiotic strains. Anaerobe 2013, 20, 36–41. [Google Scholar] [CrossRef]
  48. Golić, N.; Veljović, K.; Popović, N.; Djokić, J.; Strahinić, I.; Mrvaljević, I.; Terzić-Vidojević, A. In vitro and in vivo antagonistic activity of new probiotic culture against Clostridium difficile and Clostridium perfringens. BMC Microbiol. 2017, 17, 108. [Google Scholar] [CrossRef] [Green Version]
  49. McReynolds, J.; Waneck, C.; Byrd, J.; Genovese, K.; Duke, S.; Nisbet, D. Efficacy of multistrain direct-fed microbial and phytogenetic products in reducing necrotic enteritis in commercial broilers. Poultry Sci. 2009, 88, 2075–2080. [Google Scholar] [CrossRef] [PubMed]
  50. Brown, T.R.; Edrington, T.S.; Genovese, K.J.; He, H.L.; Anderson, R.C.; Nisbet, D.J. Evaluation of the efficacy of three direct fed microbial cocktails to reduce fecal shedding of Escherichia coli O157:H7 in naturally colonized cattle and fecal shedding and peripheral lymph node carriage of Salmonella in experimentally infected cattle. J. Food Prot. 2019, 83, 28–36. [Google Scholar] [CrossRef] [PubMed]
Foods 11 03834 g001 550
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).
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).
Foods 11 03834 g001
Foods 11 03834 g002 550
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).
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).
Foods 11 03834 g002
Foods 11 03834 g003 550
Figure 3. C. perfringens average concentration (log10CFU/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 (log10CFU/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).
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Foods 11 03834 g004 550
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 log10CFU/g, medium being > 2 log10CFU/g, and low being ≤ 2 log10CFU/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.
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 log10CFU/g, medium being > 2 log10CFU/g, and low being ≤ 2 log10CFU/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.
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Foods 11 03834 g005 550
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).
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).
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Foods 11 03834 g006 550
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).
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).
Foods 11 03834 g006
Table
Table 1. Overview of the fecal sampling design with corresponding sample sizes.
Table 1. Overview of the fecal sampling design with corresponding sample sizes.
DateTreatmentNumber of Samples
Pen 1Pen 2Pen 3
26-May-2021Control10102
28-Jun-2021Control10102
27-Jul-2021Control10102
23-Aug-2021Control10102
21-Sep-2021Control10102
26-May-2021BD555
28-Jun-2021BD555
27-Jul-2021BD555
23-Aug-2021BD555
21-Sep-2021BD555
26-May-2021PC10103
28-Jun-2021PC10103
27-Jul-2021PC10103
23-Aug-2021PC10103
21-Sep-2021PC10103
Table
Table 2. Results of the GEE analysis for E. coli O157:H7 prevalence.
Table 2. Results of the GEE analysis for E. coli O157:H7 prevalence.
TermEstimate (lnOR)Standard Errorp-Value
Intercept−1.920.600.001
Probicon−0.880.430.039
Bovamine Defend−0.850.520.099
June 20211.330.640.039
July 2021−1.691.010.093
August 2021−0.981.020.338
September 20211.670.660.012
Table
Table 3. Results of the GEE analysis for Salmonella prevalence.
Table 3. Results of the GEE analysis for Salmonella prevalence.
Term Estimate (lnOR)Standard Errorp-Value
Intercept−1.640.31<0.001
Probicon−3.050.68<0.001
Bovamine Defend−2.610.73<0.001
June 20211.760.43<0.001
July 20210.000.901.000
August 20210.000.901.000
September 20210.000.701.000
Table
Table 4. Results of the GEE analysis for C. perfringens concentration.
Table 4. Results of the GEE analysis for C. perfringens concentration.
Term EstimateStandard Errorp-Value
Intercept1.970.29<0.001
Probicon−1.080.28<0.001
Bovamine Defend0.060.260.822
July 20213.230.35<0.001
August 20210.660.370.071
September 20211.770.32<0.001
Table
Table 5. Results of the GEE analysis for Enterobacteriaceae concentration.
Table 5. Results of the GEE analysis for Enterobacteriaceae concentration.
Term EstimateStandard Errorp-Value
Intercept6.160.26<0.001
Probicon0.120.270.65
Bovamine Defend0.450.280.11
May 2021−0.420.280.13
July 2021−1.300.490.007
September 2021−1.070.27<0.001
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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

AMA Style

Flach MG, Dogan OB, Kreikemeier WM, Nightingale KK, Brashears MM. 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(23):3834. https://doi.org/10.3390/foods11233834

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Flach, Makenzie G., Onay B. Dogan, Wanda M. Kreikemeier, Kendra K. Nightingale, and Mindy M. Brashears. 2022. "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 11, no. 23: 3834. https://doi.org/10.3390/foods11233834

APA Style

Flach, M. G., Dogan, O. B., Kreikemeier, W. M., Nightingale, K. K., & Brashears, M. M. (2022). 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, 11(23), 3834. https://doi.org/10.3390/foods11233834

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