High Occurrence of Multiresistant Salmonella Infantis in Retail Meat in Ecuador

Abstract

Salmonella enterica is among the most important foodborne pathogens. In Ecuador, there is limited information about non-typhoidal S. enterica occurrence in raw meats, its serotype distribution, and antimicrobial resistance. In this study, we addressed this issue in 1095 retail fresh meats (chicken, pork, veal, lamb, beef, and turkey) in Quito by performing a traditional culture methodology and molecular detection. We found that S. enterica was present in 38.1% of the samples, and Salmonella Infantis was the most common serotype showing a high antibiotic resistance and a wide host range. Some host-adapted serotypes were found in uncommon sources of meat, suggesting cross-contamination and the need to implement good manufacturing practices in meat processing. High levels of multidrug resistance were found in all serotypes. There is an urgent need to identify Salmonella serotypes in food to compare with clinical data and to carry out epidemiological studies to control and prevent outbreaks and infections.

Introduction

Non-typhoidal Salmonella enterica (NTS) is one of the four global causes of diarrhea, which is the most frequent foodborne disease (Mahmoud, 2012; WHO, 2018; CDC, 2020). The NTS is among the most common foodborne pathogens that cause the majority of hospitalizations worldwide (78 million Salmonella infections, which result in more than 59,000 deaths annually) (WHO, 2018). These estimates are underrepresented since there are about 30 Salmonella infection cases that are not confirmed for each confirmed one (CDC, 2020). Besides, this bacterial foodborne pathogen is one of the most frequently associated with animal products and vegetables, especially when eaten raw or with minimal processing (Strawn et al., 2013). Some of the foods involved in different Salmonella outbreaks are eggs (contamination of shells and white/yolk), chicken and other products of animal origin, as well as vegetables (Mahmoud, 2012; WHO, 2018).

Salmonella can survive (even multiply from low initial numbers to levels that are capable of causing human disease) on work surfaces, equipment, and in some foods, during improper storage, insufficient cooking, or cross-contamination events (Doyle and Beuchat, 2007; Carrasco et al., 2012; Finn et al., 2013). There are reports of high survival rate during frozen storage of beef (Dykes and Moorhead, 2001), chicken meat (Dominguez and Schaffner, 2009), and low-moisture environments (Finn et al., 2013). The infectious dose of Salmonella spp. varies depending on the serotype, the immune system of the individual, and the type of food ingested (Pegues and Miller, 2010). An infectious dose of the order of 10–100 colony-forming units in contaminated low-water activity products is enough to cause salmonellosis, whereas >10⁵ is needed in other contaminated foods (Finn et al., 2013). These survival capacities and their wide genetic diversity allow Salmonella to become an important public health pathogen.

According to the Health Ministry in Ecuador, 2647 NTS infection cases were registered in 2018 (MSP, 2020). These weekly reports do not differentiate among Salmonella serotypes, which is epidemiologically important, to establish prevalence, define endemic disease patterns, investigate salmonellosis transmission, audit control programs, and avoid outbreaks (CDC, 2020). In general, data collection on the prevalence of Salmonella serotypes in different kinds of food products in Latin America is limited (Donado-Godoy et al., 2012; Pulido-Landínez et al., 2013; Vinueza-Burgos et al., 2016).

S. enterica is important not only due to its implication on the high number of human infections worldwide but also due to its diversity (+2600 serotypes) and its frequent resistance to several different antibiotics. Common administration of antimicrobials in animal feed production systems is among the most important activities that have led to the emergence of antibiotic-resistant bacteria that can be easily transmitted to humans through food of animal origin (Barrow et al., 2012). These resistance patterns vary greatly between serotypes (Su et al., 2004). Surveillance of resistance and adequate serotype determination is necessary to help control foodborne infection caused by Salmonella. To identify the overall occurrence of S. enterica in fresh meats, we evaluated its presence and determined the most common clinical serotypes and antimicrobial susceptibility patterns during 2015 and 2016.

Materials and Methods

Sample collection and bacterial strains

During the second semester of 2015 and the first semester of 2016, retail fresh meats from chicken, pork, veal, lamb, beef, and turkey were collected from markets and supermarkets in Quito (Ecuador) and taken to the Instituto de Microbiología in Universidad San Francisco de Quito to be analyzed with 3M Molecular Detection System for Salmonella (MDS) (3M, St. Paul, Minnesota). Briefly, 25 g of food products was enriched with 225 mL Buffered Peptone Water ISO for 18–26 h at 37°C. To release DNA, 20 μL of enrichment broth with lysis solution was incubated for 15 min at 100°C ± 1°C. These lysates were amplified in a 3M Molecular Detection Instrument following the manufacturer's instructions. The detection of Salmonella nucleic acid amplification was performed automatically by the software.

All samples that were detected as positive for Salmonella by 3M MDS were chosen for further analyses. We obtained two different types of samples from these products: bacterial isolates and lysates. The isolates came from additional conventional bacterial cultures (following the Bacteriological Analytical Manual Method for isolation of Salmonella) of positive samples. The lysates came directly from the 3M MDS lysis. This differentiation of samples was performed, because isolates allowed us to perform antimicrobial susceptibility evaluation, whereas lysates allowed us to analyze the presence of more than one serotype in the enrichment product. Two different molecular typing techniques were applied as explained later. A total of 190 Salmonella isolates were obtained and biochemically identified, and a total of 163 lysates were selected for co-infection analysis. From a group of samples (n = 64), we decided to analyze the lysate and the culture isolates to confirm the results of serotypes from both techniques.

Antimicrobial susceptibility

Antimicrobial susceptibility in culture isolates was evaluated by Kirby-Bauer antibiotic testing with 13 antibiotics (BD BBL, Franklin Lakes): ampicillin (AM-10), amoxicillin-clavulanic acid (AMC-30), azithromycin (AZM-15), cefotaxime (CTX-30), nalidixic acid (NA-30), ciprofloxacin (CIP-5), ceftriaxone (CRO-30), gentamicin (GM-10), kanamycin (K-30), streptomycin (S-10), trimethoprim-sulfamethoxazole (SXT 23.75/1.25), tetracycline (TE-30), and chloramphenicol (C-5), following the CLSI recommendations (CLSI, 2020). Multidrug resistance was defined as resistance to at least four antimicrobials as previously defined for Salmonella (Parry and Threlfall, 2008).

DNA extraction

Salmonella isolates were cultured in nutrient agar for 24 h at 37°C. A pool with three to five colonies in 300 μL of sterile distilled water was boiled for 10 min to release DNA. The resulting supernatant was kept at −20°C until the polymerase chain reaction (PCR) test. The MDS lysates were used directly as DNA for PCR analysis.

For all DNA samples, the amplification of a 1500 bp segment of 16S rRNA gene was used as the internal control. This amplification was carried out in a final volume of 10 μL containing 1 × colorless reaction buffer, 1.75 mM MgCl₂, 0.12 mM dNTPs, 0.8 μM of each primer (27F-1492R), 0.25 U of GoTaq polymerase (PROMEGA Corporation, Madison), and 2 μL of DNA. The amplification conditions started with an initial denaturation at 94°C for 4 min, followed by 30 cycles of 1 min at 94°C, 30 s at 50°C, and 2 min at 72°C. The final extension step was done at 72°C for 10 min. Amplification products were analyzed on 1.5% agarose gels and visualized with ethidium bromide staining under UV light exposure.

Salmonella molecular detection

For confirmation of salmonella DNA presence in all samples, we performed invA gene amplification (Akiba et al., 2011). DNA from ATCC 14028 Salmonella Typhimurium strain was used as a positive control, and PCR water was used as a negative control. A final volume of 10 μL amplification reaction containing 1 × buffer, 2.5 mM MgCl₂, 0.2 mM of dNTPs, and 0.3 μM of each primer (invA F and invA R); 0.25 U of GoTaq polymerase was prepared. The amplification program started with an initial denaturation at 94°C for 2 min, followed by 35 cycles of 10 s at 98°C, 30 s at 60°C, and 30 s at 72°C, with a final extension of 5 min at 72°C. Gel electrophoresis with 1.5% agarose was carried out for 1 h at 80 V with 0.5 μg/mL ethidium bromide staining.

Salmonella serotype identification

DNA from culture isolates were subjected to a modified version of the multiplex PCR programs described elsewhere (Kim et al., 2006) to genotype 30 Salmonella serotypes commonly associated with salmonellosis. Two separate reactions were carried out based on genomic regions from Salmonella Typhimurium LT2 (STM) and Salmonella Typhi CT18 (STY) that are common to NTS, and different band patterns are obtained for each serotype. For STM amplification, 0.3 μM of each primer (STM1, STM2, STM3, STM4, and STM5), 0.75 U of GoTaq polymerase (PROMEGA Corporation) and 1 μL of DNA were used. For STY reaction, 0.08 μM of primers STY1, STY2, and STM6; 0.3 μM of STY3; 0.1 μM of primers STY4; 0.75 U of GoTaq polymerase; and 1 μL de DNA were used. The amplification program for both multiplex reactions started with denaturation at 94°C for 5 min, 40 cycles of 30 s at 94°C, 30 s at 62°C, 1 min at 72°C, and a final denaturation at 72°C for 5 min. Electrophoresis was done with 2.5% agarose gel with 0.5 μg/mL ethidium bromide staining for 2 h at 80 V. The use of a 50 bp ladder is recommended.

For DNA from lysates, an amplification of six serotype-specific genes (Salmonella Typhimurium 303 pb, Salmonella Cholerasuis 305 pb, Salmonella Infantis 198 pb, Salmonella Enteritidis 299 pb, Salmonella Gallinarum 97 pb, and Salmonella Dublin 203 pb) was done as previously described (Akiba et al., 2011). The reagent concentrations and the amplification program are the same as for invA gene amplification as previously described.

Statistical analyses

p-Values were calculated to compare percentages of Salmonella occurrence among years for each animal species, percentages of serovar presence among years for each type of sample, percentages of serovar presence for each year by type of samples, and percentages of antibiotic resistance for both years. For a proportion comparison among two populations, the two-sided test was applied with a confidence level of 95%. A p-value <0.05 was considered statistically significant.

Results

A total of 1095 samples from chicken, pork, veal, lamb, beef, and turkey were collected during 2015 (n = 298) and 2016 (n = 797) from retail meat (Table 1). A different Salmonella occurrence regarding the animal species was observed. The higher percentage was found in chickens (64.9%), followed by pork (30%) and veal (26.1%) during the 2015 sampling. For 2016, the three most contaminated types of meat were chicken (69.1%), turkey (22.2%), and pork (20.8%). We detected S. enterica in 417 (38.1%) samples, having contamination in 46.3% of samples during the first year and 35% during the second year. Occurrences for pork, beef, veal and turkey were statistically different when 2015 results were compared with 2016 results (Table 1).

Table 1.

Salmonella enterica Occurrence by Type of Meat by Year

Type of meat	2015 (n = 298)				2016 (n = 797)
Type of meat	Total samples	Positives	Occurrence (%)	Serovars	Total samples	Positives	Occurrence (%)	Serovars
Poultry	185	120	64.9	Infantis (100%) Gallinarum (16.7%)	298	206	69.1	Infantis (92.7%) Dublin (2.9%)
Pork	10	3	30.0	Infantis (100%)	130	27	20.8	Infantis (81.5%) Dublin—Typhimurium (7.4%)
Beef	50	6	12.0	Infantis (83.3%) Javiana (16.7)	130	10	7.7	Infantis (80%) Gallinarum—Dublin (10%)
Veal	23	6	26.1	Typhimurium (50%) Infantis (33.3%)	145	22	15.2	Dublin (36.4%) Infantis—Typhimurium—Enteritidis (18.2%)
Lamb	25	3	12.0	Infantis (66.7%) Cholerasuis (33.3%)	85	12	14.1	Infantis (91.7%) Heidelberg (8.3%)
Turkey	5	0	0.0	N/A	9	2	22.2	Infantis (100%)
Total	298	138	46.3		797	279	35.0

The two most frequent serovars are shown. Percentages do not always sum up to 100%, because serovar co-infections in lysates are considered. Bold percentages indicate p-values <0.05 when comparing 2015 with 2016 occurrences.

Depending on the origin of the sample, different serovars were isolated (in Table 1, the two most frequent serovars are shown). Salmonella Infantis was recovered in all types of samples (chicken, pork, beef, veal, lamb, and turkey). We isolated Salmonella Gallinarum in poultry, beef, and veal. Salmonella Dublin and Salmonella Cholerasuis were found in four and three different sources, respectively. Chicken products harbored the majority of the serotypes. Salmonella Stanley was only isolated in chickens, whereas beef was the only source of Salmonella Javiana strains (16.7%). Salmonella Typhimurium was found in pork and veal, whereas turkey samples only harbored Salmonella Infantis isolates.

From all positive meats, we obtained two different types of samples: 163 MDS lysates for analyzing Salmonella co-infections and serotype identification; and 190 culture isolates for identifying serotype and antibiotic resistance patterns. We also analyzed both lysates and culture isolates for 64 positive samples.

The most common serotype was Salmonella Infantis, which was prevalent in more than 80% of the samples during the 2 years (Tables 1 and 2). Serotype identification for lysates and isolates is also shown in Table 2. Eight lysates were not typeable with our technique. In MDS lysates, Salmonella Infantis was present in similar percentages for 2015 and 2016 (80.8% and 81.2%, respectively); whereas in culture isolates, a higher difference between the 2 years was observed.

Table 2.

Salmonella enterica Serovars Percentage in Molecular Detection System Lysates and Culture Isolates from Samples Collected During 2015 and 2016

Salmonella serovars	Lysates (%)		Culture isolates (%)
Salmonella serovars	2015	2016	2015	2016
Infantis	80.8	81.2	94.3	87.5
Typhimurium	0.8	4.9	4.3	1.5
Dublin	1.5	4.9	0	6
Gallinarum	16.2	3	NI	NI
Choleraesuis	2.3	2	0	0
Enteritidis	1.5	4.9	0	0
Javiana	NI	NI	1.4	0
Heidelberg	NI	NI	0	2.5
Branderburg	NI	NI	0	1
Stanley	NI	NI	0	0.5
Derby	NI	NI	0	0.5
Co-infection	13.8	8.9	NI	NI

Bold and italic percentages show statistical differences (p-values <0.05) for serovar presence when comparing both years in the same type of sample. Bold percentages indicate statistical differences (p-values <0.05) of serovar presence when comparing the same year by each type of sample.

NI, not included in the molecular technique for that type of sample.

In both types of samples, apart from Salmonella Infantis, Salmonella Typhimurium and Salmonella Dublin serotypes were found in different percentages (0–6%). In lysates, Salmonella Cholerasuis occurrence was similar in 2015 (2.3%) and 2016 (2%). Salmonella Enteritidis presented a higher percentage in 2016 (4.9%) than in 2015 (1.5%). In culture isolates, Salmonella Dublin, Salmonella Heidelberg, Salmonella Branderburg, Salmonella Stanley, and Salmonella Derby were absent in samples from 2015 and were found between 0.5% and 6% in 2016. Because of the methodology applied, detection of Salmonella Gallinarum was carried out only in lysates where it was present in 16.2% of the samples in 2015 compared with 3% in 2016, mostly in co-infections. Statistical differences among percentages for the 2 years were observed only for Salmonella Gallinarum in lysates; and Salmonella Dublin and Salmonella Heidelberg in culture isolates, with p-values <0.05 (shown in bold and italic in Table 2). When comparing serovar percentages of the same year between different types of samples, statistical differences were found only for Salmonella Infantis in 2015 and for Salmonella Enteritidis in 2016 (shown in bold in Table 2).

Samples co-infected (analysis only applied for lysates) with two different serotypes are accounted but not specified in Table 1. That is why some of the percentages of the serovars per type of meat do not add up to 100%. As seen in Table 2, we found 13.8% of co-infection in 2015, and 8.9% in 2016 (a statistical difference was not found). During 2015, 15 samples had co-infection with Salmonella Infantis-Salmonella Gallinarum, two samples presented Salmonella Infantis-Salmonella Dublin, and only one sample had Salmonella Infantis-Salmonella Choleraesuis. During 2016, four samples had Salmonella Infantis-Salmonella Dublin; co-infections of Salmonella Infantis-Salmonella Choleraesuis, Salmonella Gallinarum-Salmonella Typhimurium, Salmonella Enteritidis-Salmonella Typhimurium, and Salmonella Infantis-Salmonella Typhimurium were found in only one sample for each combination (data not shown).

All Salmonella isolates were tested against 13 antibiotics according to CLSI recommendations. Antibiotic resistance patterns are shown in Table 3 for 2015 isolates and in Table 4 for 2016 samples. During the first year, 15 different patterns were identified (n = 67), and for 2016, we found 44 different patterns. Four patterns (bold in Tables 3 and 4) were found in both years. Patterns that showed resistance to more than six antibiotic groups were evident in most of the isolates (60/67 in 2015 and 174/187 in 2016). The pattern most frequent in 2015 (only Salmonella Infantis) was also the most common among isolates in 2016 (Salmonella Infantis, Salmonella Heidelberg, Salmonella Dublin, and Salmonella Typhimurium). During 2015, each pattern was exclusive to a unique serovar. Nevertheless, during 2016, we found highly resistant isolates from Salmonella Heidelberg, Salmonella Dublin, Salmonella Typhimurium, Salmonella Branderburg, and Salmonella Stanley sharing the same pattern with Salmonella Infantis. There were 11 culture isolates, Salmonella Infantis (9), Salmonella Branderburg (1), and Salmonella Dublin (1) strains that showed phenotypic resistance to all antibiotics tested (Table 4).

Table 3.

Antibiotic Resistance Patterns in Salmonella enterica Isolates from 2015

No. of antibiotics to which resistance was shown	Salmonella isolated from 2015 (n = 67)
No. of antibiotics to which resistance was shown	Antibiotic resistant pattern observed	No. of resistant isolates	Serovar
11	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM,K	30	Infantis
10	S,SXT,CTX,CRO,CIP,NA,TE,C,AM,K	12	Infantis
7	S,CTX,CRO,CIP,NA,TE,AM	10	Infantis
10	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM	2	Infantis
9	S,CTX,CRO,CIP,NA,TE,C,AM,K	2	Infantis
8	S,CTX,CRO,CIP,NA,TE,AM,K	2	Infantis
9	S,SXT,CTX,CRO,CIP,NA,TE,AM,K	1	Infantis
9	S,SXT,CTX,CRO,NA,TE,C,AM,K	1	Infantis
6	S,SXT,NA,TE,AZM,K	1	Infantis
6	S,SXT,CIP,NA,TE,C	1	Infantis
6	CTX,CRO,CIP,NA,TE,AM	1	Infantis
4	S,NA,TE,C	1	Typhimurium
1	TE	1	Javiana
1	S	1	Typhimurium
1	CIP	1	Typhimurium
	Total	67

Patterns in bold are also present in isolates from 2016 in Table 4.

S, Streptomycin; SXT, Trimethoprim-Sulfamethoxazole; CTX, Cefotaxime; AMC, Amoxicillin-Clavulanic acid; CRO, Ceftriaxone; CIP, Ciprofloxacin; NA, Nalidixic acid; TE, Tetracycline; C, Chloramphenicol; GM, Gentamicin; AM, Ampicillin; AZM, Azithromycin; K, Kanamycin.

Table 4.

Antibiotic Resistance Patterns in Salmonella enterica Isolates from 2016

No. of antibiotics to which resistance was shown	Salmonella isolated from 2016 (n = 187)
No. of antibiotics to which resistance was shown	Antibiotic resistant pattern observed	No. of resistant isolates	Serovars
11	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM,K	60	Infantis (56), Heidelberg (2), Dublin (1), Typhimurium (1)
7	S,CTX,CRO,CIP,NA,TE,AM	17	Infantis
12	S,SXT,CTX,AMC,CRO,CIP,NA,TE,C,GM,AM,K	14	Infantis (12), Dublin (1), Heidelberg (1)
13	S,SXT,CTX,AMC,CRO,CIP,NA,TE,C,GM,AM,AZM,K	11	Infantis (9), Branderburg (1), Dublin (1) ^a
10	S,SXT,CTX,CRO,NA,TE,C,GM,AM,K	11	Infantis (10), Heidelberg (1)
12	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM,AZM,K	10	Infantis (8), Dublin (1), Stanley (1)
10	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM	9	Infantis (8), Branderburg (1)
9	S,CTX,CRO,CIP,NA,TE,C,GM,AM	5	Infantis
10	S,SXT,CTX,CRO,CIP,NA,TE,GM,AM,K	4	Infantis
10	S,CTX,CRO,CIP,NA,TE,C,GM,AM,K	4	Infantis
9	S,SXT,CTX,CRO,NA,TE,C,GM,AM	4	Infantis
11	S,SXT,CTX,AMC,CRO,NA,TE,C,GM,AM,K	2	Infantis
9	S,CTX,CRO,NA,TE,C,GM,AM,K	2	Infantis, Dublin
8	S,SXT,CIP,NA,TE,C,GM,K	2	Infantis
4	S,CIP,NA,TE	2	Infantis, Typhimurium
3	S,TE,K	2	Dublin
11	S,SXT,CTX,AMC,CRO,CIP,NA,TE,C,GM,AM	1	Infantis
11	S,SXT,CTX,CRO,CIP,NA,TE,C,GM,AM,AZM	1	Infantis
11	S,SXT,CTX,AMC,CRO,CIP,NA,TE,C,AM,K	1	Infantis
10	S,CTX,CRO,CIP,NA,TE,C,GM,AM,AZM	1	Infantis
10	S,CTX,AMC,CRO,CIP,NA,TE,C,GM,AM	1	Infantis
10	S,CTX,CRO,CIP,NA,TE,C,AM,AZM,K	1	Heidelberg
9	S,SXT,CTX,CRO,CIP,NA,TE,GM,AM	1	Dublin
9	SXT,CTX,CRO,CIP,NA,TE,C,GM,AM	1	Infantis
9	SXT,CTX,CRO,CIP,NA,TE,C,AM,K	1	Infantis
8	S,AMC,CRO,CIP,NA,TE,GM,AZM	1	Derby
8	S,CTX,AMC,CRO,CIP,NA,TE,AM	1	Infantis
8	S,CTX,CRO,CIP,NA,TE,AM,AZM	1	Infantis
8	S,CTX,CRO,CIP,NA,TE,AM,K	1	Infantis
8	S,CTX,CRO,CIP,NA,TE,GM,AM	1	Infantis
8	S,CTX,CRO,NA,TE,C,GM,AM	1	Infantis
8	S,SXT,CTX,CRO,CIP,NA,TE,AM	1	Infantis
8	S,SXT,CTX,CRO,NA,TE,GM,AM	1	Infantis
7	S,SXT,CIP,NA,TE,C,GM	1	Infantis
7	S,SXT,CIP,NA,TE,GM,K	1	Infantis
6	S,CRO,CIP,NA,AM,K	1	Dublin
6	S,SXT,CIP,NA,TE,K	1	Infantis
6	S,SXT,NA,TE,C,GM	1	Infantis
5	CTX,CRO,CIP,NA,AM	1	Infantis
5	CTX,CRO,NA,TE,AM	1	Infantis
5	S,SXT,CIP,TE,K	1	Dublin
4	CRO,CIP,NA,TE	1	Infantis
4	S,AMC,CIP,NA	1	Dublin
3	NA,TE,C	1	Dublin
	Total	187

Serovars are specified per pattern. Patterns in bold are also present in isolates from 2015 in Table 3.

Pattern in italics corresponds to isolates resistant to all antibiotics tested in the study.

Results for all isolates from 2015 to 2016 are presented in Table 5. In almost every antibiotic tested, a percentage increase was observed from 2015 to 2016, especially for AMC, AZM, and GM (p-values <0.05 were found for these antibiotics). For 10 antibiotics, more than 70% of the isolates presented resistance but the differences between both years were not statistically significant.

Table 5.

Percentage of Antibiotic Resistance in Culture Isolates Between 2015 and 2016

Symbol	Antibiotic	2015 (n = 67)	2016 (n = 187)
AMC	Amoxicillin-Clavulanate^a	0	35.4
AZM	Azithromycin^a	1.4	26.15
GM	Gentamicin^a	50	78.5
K	Kanamycin	71.4	81.5
SXT	Trimethoprim-Sulfamethoxazole	72.8	83.1
C	Chloramphenicol	74.3	83.1
CRO	Ceftriaxone	88.6	93.5
CTX	Cefotaxime	90	92.3
AM	Ampicillin	91.4	90.8
CIP	Ciprofloxacin	92.8	98.5
S	Streptomycin	95.7	98.5
NA	Nalidixic acid	95.7	98.5
TE	Tetracycline	97.1	96.9

Antibiotics with p-values <0.05 between both years.

Discussion

We report an NTS occurrence of 38.1% in retail meat and Salmonella Infantis as the most frequent serotype (80–94%) for both years. This occurrence is higher than others reported by South American countries such as Colombia (27% in chicken meat) (Donado-Godoy et al., 2012), Brazil (2.7% in chicken carcasses (Medeiros et al., 2011), 6.7% in beef meat (Bier et al., 2018)), and Argentina (20% in chicken carcasses) (Jimenez et al., 2002). In Ecuador, the occurrence of NTS is underestimated and little is known about the serotypes circulating in raw meats. There are only a few reports on Salmonella prevalence in farms where lower prevalence is registered. Vinueza and colleagues reported a prevalence of 16% in Ecuadorian broilers at slaughter age in Pichincha (Vinueza-Burgos et al., 2016). Another research showed an 11% Salmonella detection in 145 poultry farms in 23 out of the 24 provinces (Casart et al., 2018). It is important to notice that most of the publications refer to chicken meat only but we also included other animal species. Salmonella frequency also varies according to animal species. In New Zealand, lower prevalences were observed (3% in chicken, 1.3% in lamb, 0.5% in veal, 0.4% in beef, and 0% in pork) (Wong et al., 2007), whereas a national surveillance plan in Belgium found that 25% of pork carcasses, 43.1% of chicken carcasses, 2.5% of beef, and 0.8% of veal were contaminated with Salmonella (Ghafir et al., 2005). Differences in Salmonella prevalence among years and animal species may be the result of different factors, such as slaughterhouse sanitation, vaccines and antimicrobials that use possible cross-contamination at the retail level, and variation in the isolation protocols (Su et al., 2004; WHO, 2018).

Notably, Salmonella Infantis was the most common serotype in all samples for 2015 and 2016. This is surprising since Salmonella Enteritidis and Salmonella Typhimurium are usually present with a higher frequency in poultry, pigs, and cattle products (Antunes et al., 2016) and are responsible for more than half of reported invasive NTS infections (Mughini-Gras et al., 2019). Hence, they are considered a public health concern. In the European Union, Salmonella Infantis was the most prevalent serotype in broiler meat during 2011 and 2013 (Antunes et al., 2016), and worldwide, it was among the top 13 serovars isolated from human, animal, environmental, and/or food sources in Africa (8th), Asia (13th), Europe (5th), North America (11th), Oceania (5th), and Latin America (7th) (Hendriksen et al., 2011). In other parts of the world, Salmonella Infantis is also responsible for outbreaks and infections (Najjar et al., 2012; CDC, 2013, 2016, 2017; Chironna et al., 2014). In Ecuador, Salmonella Infantis was found in 83.9% broiler batches at slaughterhouses in Pichincha (Vinueza-Burgos et al., 2016), and in 34.6% industrialized poultry farms in 23 provinces (Casart et al., 2018). Besides, non-published data from INSPI (National Reference Laboratory for antimicrobial resistance) show that Salmonella Infantis has also been isolated in clinical samples. Also, there is a report of a small outbreak of travelers' diarrhea caused by Salmonella Infantis harboring CTX-M-65 in Ecuador (Cartelle Gestal et al., 2016). All these data show evidence that Salmonella Infantis is causing disease in the country and presents usually multiresistant profiles. The role of this serovar in human infections in Ecuador needs further attention. Differences in specific serotype prevalences in different parts of the world may be the result of the introduction of strains due to international travel, food, and animal feed trading (Hendriksen et al., 2011; Carrasco et al., 2012).

Regarding the poultry industry, there are vaccines available for the control of Salmonella infection (live attenuated strains, inactivated and subunit vaccines) that have successfully reduced the contamination rate in poultry farms and products, especially for the most common serotypes Salmonella Enteritidis and Salmonella Typhimurium (Eeckhaut et al., 2018). There are also several Salmonella Cholerasuis vaccines available in different parts of the world but, only in Germany, vaccination in pigs is a requirement (Chiu et al., 2004). More than one vaccine against Salmonella Enteritidis is used in chicken intended for egg production and breeders in Ecuador, which may explain the low incidence of this serotype in our samples. The reduction in the prevalence of the serovars that were frequently associated with salmonellosis (Salmonella Enteritidis and Salmonella Typhimurium) due to vaccine control and other measures may have caused the emergence of other non-host-adapted serovars, such as Salmonella Infantis in the animal production industry.

Regarding the type of meat, Salmonella Infantis was found in all types of analyzed samples. These results are interesting, because they suggest a wide host range for this serotype. Among others, serotypes such as Salmonella Cholerasuis, which are considered swine-adapted serotypes, were isolated in chicken and lamb, which may suggest cross-contamination during meat processing. Salmonella Dublin is another host-adapted serotype (Silva et al., 2014), predominantly found in cattle, yet it was found in chicken and pork. Salmonella Stanley was unexpectedly found in chicken, whereas non-clinical and non-human Salmonella Stanley strains have been usually found in reptiles and are absent in bovine, chicken, equine, porcine, and turkey (CDC, 2013). From the broad-host-range serotypes: Salmonella Javiana was only found in beef, which is surprising since it has been isolated from bovine (10.2%), chicken (20.2%), equine (8.4%), porcine (1.2%), and turkey samples (38.3%) (CDC, 2013). Salmonella Derby was found only in veal samples, whereas it has been found mostly in porcine (66.9%) and only in a small percentage in bovine samples (2.6%) (CDC, 2013). Salmonella Typhimurium is usually found in many types of meat and was isolated in this study from chicken, veal, and pork. The presence of many serotypes in chicken (Salmonella Infantis, Salmonella Typhimurium, Salmonella Cholerasuis, Salmonella Enteritidis, Salmonella Heidelberg, Salmonella Branderburg, Salmonella Stanley, Salmonella Gallinarum, and Salmonella Dublin) and the association of serotypes with uncommon sources may suggest cross-contamination in slaughterhouses, during transportation or handling of the meat products.

On the other hand, there are no published data available corresponding to the antibiotic resistance patterns of Salmonella in Ecuadorian fresh meats. In this study, we found a great variety of antibiotic resistance patterns among Salmonella isolates. However, there are a great number of isolates that share the same patterns with resistance to seven and more antibiotics. And they do not belong to one serovar, which highlights the importance of horizontal gene transfer. Ninety isolates share the phenotypic resistance to 11 antibiotics. This result shows the urgent need to investigate the genetic basis of antibiotic resistance, and also a genomic approach to identify their phylogenetic relation. The fact that 11 isolates are resistant to all antibiotics tested suggests the necessity to improve control measures in Ecuador to generate better control of this foodborne pathogen in the food chain.

Our results also showed a dramatic increase in antibiotic resistance from strains isolated in 2015 to the ones isolated after 6 months, particularly for AMC, AZM, and GM and the statistical analyses confirm these differences (Table 5). In two cases the percentage of resistant strains was lower in 2016 than in 2015 (TE and AM), but the differences were not significant. Resistance to ciprofloxacin was found in 92.8–98.5% of isolates, which is one of the “critically important antibiotics for human health” and its resistance has led to increased severity, morbidity, and mortality of invasive disease due to Salmonella (WHO, 2017). Salmonella Infantis showed more resistant strains than any other serotype. During 2015 and 2016, we found 11 strains that were resistant to all antibiotics tested, and 9 of them were Salmonella Infantis. These low levels of susceptibility to antimicrobials may be related to the intensive misuse of antibiotics in the poultry industry not only as therapeutics but also as prophylactics and growth promoters (Van Boeckel et al., 2015).

Inadequate hygiene practices and storage, contamination of equipment, and staff hands are common causes of cross-contamination incidents, which are associated with 25% of foodborne outbreaks (WHO, 2018). Salmonella can be easily disseminated in kitchens from fresh and frozen chicken to surfaces, utensils, hands, and foods, implying a cross-contamination or recontamination risk (Carrasco et al., 2012). This is one of the reasons why not only animal products are sources for Salmonella outbreaks, but also plant products (Silva et al., 2014). One health perspective should be applied to reduce Salmonella transmission between humans, animals, and plants.

Conclusions

Our results show a high occurrence of Salmonella in meat products in Quito, with a different contamination frequency depending on the animal species tested. Salmonella Infantis was the most common serotype among these samples, which, together with other investigations carried out in poultry farms and clinical samples, suggests that it is an important Salmonella serotype in our country. The most important trait of clinical importance of the isolates, mainly not only from Salmonella Infantis but also from other serovars, is the high resistance to antimicrobials found in all types of samples. Our data could be used for implementing national control and surveillance programs to limit the risk of contamination of Salmonella in food products and to identify the source of dissemination of Salmonella strains through the food chain to humans.

Footnotes

Acknowledgment

The authors are very grateful to Ana Ulloa for her lab work during her short internship in their lab.

Author Disclosure

No competing financial interests exist.

Funding Information

This work was supported by the Universidad San Francisco de Quito.

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