Nghiên cứu đặc điểm kháng kháng sinh và gen liên quan ở các chủng salmonella đa kháng tt tiếng anh

MINISTRY OF EDUCATION

VIETNAM ACADEMY OF

AND TRAINING

SCIENCE AND TECHNOLOGY

GRADUATE UNIVERSITY SCIENCE AND TECHNOLOGY

……..….***…………

NGUYEN THANH VIET

ANTIMICROBIAL RESISTANCE CHARACTERISTICS AND
RELATED GENES OF MULTIDRUG-RESISTANT Salmonella

Major: Microbiology
Code: 9420107

SUMMARY OF BIOLOGY DOCTORAL THESIS

Hanoi – 2020


INTRODUCTION
1. The urgency of the thesis
The burden of foodborne diseases is substantial. Each year,
foodborne diseases cause almost 1 in 10 people fall ill and 33 million
of healthy life years are lost. Foodborne diseases can be severe,
especially for young children. Diarrhoeal diseases are the most

common illnesses resulting from unsafe food, 550 million people
falling ill each year, including 220 million children under the age of 5
years. Salmonella is 1 of the 4 key global causes of diarrhoeal diseases.
The increasing rate of antibiotic resistance in Salmonella spp.
poses a significant global concern and is a major threat to global
health. Therefore, it is necessary to isolate and identify antibiotic
resistance characteristics of Salmonella from food. Studying the
antibiotic resistance characteristics of Salmonella will provide
important information for the prevention, control of diseases as well
as food contamination control and regulations on the use of antibiotics
in treatment and animal husbandry in order to limit antibiotic
resistance of bacteria.
In Vietnam, there has been no research on identifying related
gene categories of multidrug-resistant Salmonella isolated from food
using Next-generation sequencing. Studying the expression genome
of Salmonella, especially antibiotic resistance genes in multi‐
antibiotic resistant Salmonella isolates, provides insight into the
molecular epidemiology of antibiotic resistance genes. More
importantly, it is possible to detect new mutations in antibiotic
resistance genes that cause antibiotic resistance in Salmonella. In
addition, studying the expression genome could help to identify new
gene groups that can cause antibiotic resistance in this bacterium.
1


According to the Food and Agriculture Organization of the
United Nations, Vietnam is a country where consumption of beef,
pork, and poultry has increased rapidly since 1993 and is expected to
increase significantly in the next years. Therefore, this thesis has been
implemented with the following objectives and content:

2. The objectives of the thesis
•

Identify Salmonella isolated from pork, beef, and chicken meat at
the retail markets in Hanoi.

•

Determining antibiotic resistance characteristics of isolated
Salmonella.

•

Analysis of related gene categories in multi-antibiotic resistant
Salmonella.

3. The main contents of the thesis
•

Microbial culture, isolation and identification of Salmonella from
retail meats.

•

Conducting antibiotic testing, then selecting multidrug resistant
Salmonella.

•

Using next-generation sequencing to analyze the related gene

categories in some of multi-antibiotic resistant Salmonella.
Confirm some of the new finding results by Sanger sequencing
Chapter 1. OVERVIEW

1.1. Biological characteristics of Salmonella
Salmonella is a nonspore-forming rod-shaped, Gram-negative
bacterium, most Salmonella strains are motile with peritrichous
flagella, facultatively anaerobic bacilli. Salmonella can grow on some
selective growth medium, such as XLD agar. On XLD agar,
Salmonella species have red colonies, some with black centers. They
are sensitive to heat and usually killed at temperatures over 70°C.
2


Salmonella possesses three major antigens: H (flagellar), O (somatic),
and Vi antigens.
The genus Salmonella is part of the Enterobacteriaceae. The
genus comprises two species, S. bongori, and S. enterica, the latter of
which is divided into six subspecies: I (enterica), II (salamae), IIIa
(arizonae), IIIb (diarizonae), IV (houtenae) và VI (indica).
1.2. Genetic characteristics of Salmonella
1.2.1.

Salmonella genome structure
The genome size of Salmonella varies from 3.39 to 5.59 Mb.

The number of genes average is 4,742. Salmonella contains from 1 to
2 plasmids, which vary in size from 2-200 kb. S. enterica needs about
3,499 genes and S. bongori needs about 3,368 genes for normal
growth. Salmonella's genome is homologous from 65% to 99%.

Salmonella strain has a large stable core, whilst there is an abundance
of accessory genes, including the Salmonella pathogenicity islands
(SPIs), transposable elements, phages, and plasmid DNA. The core
and pan-genome of Salmonella were estimated to be around 2,800 and
10,000 gene families, respectively
1.2.2.

Mechanisms of Antibiotic resistance in Salmonella
The most common antimicrobials that Salmonella has

developed resistance at the present are namely; aminoglycosides, βlactams, chloramphenicol, quinolones, tetracyclines, sulfonamides,
and trimethoprim.
Aminoglycosides. The Salmonella uses mechanisms such as
expression of plasmid-mediated aminoglycoside modifying enzymes
against aminoglycoside. These enzymes are categorized into three
groups and are named based on reactions they perform, including
acetyltransferases, phosphotransferases, and nucleotidyltransferases.
3


Beta-lactams. In Salmonella, the secretion of a beta-lactamase
is the common mechanism of resistance to beta-lactams. These
enzyme acts by hydrolyzing the structural rings of the B-lactam, by
producing beta amino acids with no antimicrobial activity To date,
there is well comprehended about more than 340 beta-lactamases
resistance genes.
Chloromphenicol (C). Chloramphenicol is specific and potent
inhibitor of protein by binding to the peptidyltransferase center of the
50s ribosomal unit, thus preventing formation of peptide bonds. There
are

two

mechanisms

in

which

Salmonella

resistance

to

chloramphenicol is conferred: (i) by the plasmid-located enzymes
called

chloramphenicol

acetyltransferases

or

nonenzymatic

chloramphenicol resistance gene cm1A and (ii) Efflux pump in which
the antibiotic is removed.
Quinolones. Salmonella resistance to quinolone has been
classified into two mechanisms. The first is the two gyrA and gyrB,

genes which encode for the subunits of DNA gyrase, and in the parC
subunit of topisomerase IV. Also, the second mode of action involves
changes in the AcrAB-TolC efflux system expression. However, it is
an accumulation of multi-mutations that provides resistance, rather
than one mutation.
Tetracycline (TE). Tetracycline resistance in Salmonella can
be attributed to the production of an energy dependent efflux pump to
remove the antibiotic from within the cell. To date, 46 TE-resistance
genes have been found.
Sulfonamide and trimethoprime (SXT). These classes of
antibiotics are bacteriostatic and it mode of action is by competitively
inhibiting enzymes involved in the synthesis of tetrahydrofolic acid.
4


Sulfonamide inhibit dihyrdropteroate synthetase, while trimethoprim
inhibits dihydrofolate reductase. The resistance of Salmonella to
sulfonamide has been attributed to the presence of an extra sul gene.
Beside, attributed to dhfr and dfr gene.
1.2.3.

Relationship between drug resistance and gene mutations
Although many mutations contributing to antibiotic resistance

have been identified, the relationship between the mutations and the
related phenotypic changes responsible for the resistance has yet to be
fully elucidated. The relationship between a mutation and drug
resistance is not always a simple one-to-one correspondence. Multiple
mutations are often required to acquire high levels of resistance to a
specific drug. Overall, the complex relationship between drug

resistance acquisition, genetic alternations and global phenotypic
changes remains unclear.
1.2.4.

Bacterial efflux pumps
Efflux pumps not only can expel a broad range of antibiotics

owing to their poly-substrate specificity, but also drive the acquisition
of additional resistance mechanisms by lowering intracellular
antibiotic concentration and promoting mutation accumulation. Overexpression of multidrug efflux pumps have been increasingly found to
be associated with clinically relevant drug resistance.
1.3. Contamination and antibiotic resistance of Salmonella in food
1.3.1.

In the world
There have been many different studies on Salmonella

contamination rate in food which have been published. In general, the
research results show that Salmonella strains are distributed
differently depending on the geographical region and the food source.

5


The common serotypes vary by geographic region and their rates of
antibiotic resistance in Salmonella are increasing each year.
1.3.2.

In Vietnam
Recent reports show that Vietnam food is contaminated

Salmonella at different rates, including multiple antibiotic-resistant
species. The prevalence of Salmonella in food and the rate of multiantibiotic resistance in Salmonella isolates are increasing every year.
Therefore, it is necessary to isolate and determine the antibiotic
resistance characteristics of Salmonella in each food type in a
particular geographical region at different time periods.
1.4.

Methods are commonly used in gene expression research
Currently, there are four methods are used: Reverse

transcription PCR (RT-PCR), Real-time PCR (qPCR), Microarray,
and next generation sequencing (NGS) to study gene expression.
Among the above techniques, the next generation sequencing has the
most advantage, this technique can overcome the disadvantages of the
remaining three techniques and is the only one capable of detecting
new genes.
Next generation sequencing
NGS is a direct measurement of nucleic acid sequences
present in the sample. There is the linear relationship between the
number of sequences and the concentration of nucleic acid sequences
present in the sample. Moreover, NGS is not dependent on the
information of nucleic acid sequences and highly homologous genes
that can be expressed in the sample. Thus new genes can be detected.
Among the next generation sequencing technologies, the Illumina
technology produces the most accurate data, the procedure is simple,
and is widely applied in many different research fields. Currently,
6

more than 90% of the sequence data in the world is generated by
Illumina technology.
Chapter 2. MATERIAL AND METHODS
2.1. MATERIAL
2.1.1. Samples
A total of 90 meat samples, including 30 porks (from TL-1 to
TL-30), 30 chicken meats (from TG-1 to TG-30), and 30 beef samples
(from TL-1 to TL-30). symbols from TB-1 to TB-30), randomly
collected at 10 markets in Hanoi.
2.1.2. Culture media, chemicals, antibiotics, and kits
Culture media, antibiotics, and kits are purchased from
reputable companies globally.
2.1.3. Research equipment
The equipments are used at prestigious lab in Vietnam, such
as Vietnam Academy of Science and Technology, National Institute
of Burn, Vietnam Medical Military University.
2.2. METHODS
2.2.1. Sampling
Samples were collected according to TCVN 4833-2002, from
7-8 am in the winter season, from October to December 2016.
2.2.2. Identification of Salmonella
Salmonella was detected according to ISO 6579: 2002.
2.2.3. Antibiotics susceptibility
Salmonella’s antibiotics susceptibility was testing using
Kirby-Bauer diffuse method.
2.2.4. Nex generation sequencing
We choosed some of multidrug resistant Salmonella to
transcriptome sequence using Illumina's technology.
7

2.2.5. Bioinformatics methods
The sequence quality is checked by FastQC software. The
adapter sequences and noise sequences were removed by
Trimmomatic 0.32 software. The sequence at Q20 quality score was
de novo assembled using Geneious R11 software. The de novo
sequence was annotated by different databases such as RAST,
PATRIC 3.5.2, BASys, and Geneious R11 software. Identification of
antibiotic resistance genes using: ResFinder, ARG-ANNOT, CARD,
and PATRIC 3.5.2. Identify the gene mutation resistance to quinolone,
by ResFinder tool.
2.2.6. Confirm antimicrobial resistant gene mutations using Sanger
sequencing
To confirm the predicted results of antibiotic resistance gene
mutations obtained from the next generation sequencing method, the
new gene mutations related to quinolone resistance will be confirmed
using Sanger sequencing from cDNA of the samples.
2.2.7. Statistical analyzed
Using SPSS 16.0 software to calculate the χ2, Fisher exact
test, p values.
Chapter 3. RESULTS AND DISCUSSION
3.1. Isolate and identify the Salmonella serotype
3.1.1. Identify Salmonella results
After non-selective enrichment, selective enrichment and
biochemical confirmation, we have obtained Salmonella spp. from the
research samples. The results are presented in Table 3.1

8

Table 3.1. Results of identify Salmonella in the research samples
Positive
Negative
Total
Sample
(number) number rate (%) number rate (%)
Chicken
30
11
36,7
19
63,3
Pork
30
9
30,0
21
70,0
Beef
30
5
16,7
25
83,3
Total
90
25
27,8
65
72,2

χ2 = 3,102; df = 2; p = 0,212
The list of Salmonella positive isolated sources is presented in
Table 3.2
Table 3.2. List of samples positive for Salmonella
1
2
3

Sample sources
Chicken (11 samples)
Pork (9 samples )
Beef (5 samples )

Sample ID
TG-1, 2, 3, 4, 5, 6, 14, 25, 28, 29, 30
TL-1, 2, 3, 4, 5, 15, 26, 29, 30
TB-1, 2, 3, 15, 29

The prevalence of Salmonella in this study was 27.8%, this
result is in line to that of Do Ngoc Thuy et. al. (30%). However, this
rate is lower than other studies such as Ta et. al. (48.7%), Nguyen et.
al. (69.7%), Boomar et. al. (80%). This lower result may be due to
collecting samples in the morning, when meat was fresh, limiting
bacterial infection. Moreover, the time of sample collection is in the
winter season, the low temperature and humidity, combined with the
dry air, these factors pose inhibited to the growth of bacteria.
Among Salmonella positive samples, chicken samples were
the most prevalence (36.7%), followed by pork samples (30%), and
beef samples were the lowest rate (16.7%). This result is in line with
the research results of Do Ngoc Thuy et. al., Zhao et. al., Miranda et.

al. However, this result is different from other studies such as Phan et.
al. (pork, beef, chicken) and Nguyen et. al. (pork, chicken, beef). The
Salmonella positive rate in chicken is often higher than pork, which
9


can be due to chickens are plucked, slaughter and bleeding directly on
the cement floor, there is no separation between these areas, so
bacteria from feces, environment easily contaminate into meat. From
the above research results it can be seen that the prevalence of
Salmonella in retail meats is very different, depending on the
geographic area of sample collection.
3.1.2. Salmonella serotype results
Identify serotype from the Salmonella spp. we obtained, we
obtained 9 different serovars. The most common was S. Typhimurium
(11/25 strains). Following by S. Derby (4/25 strains), S. Warragul, S.
Indiana, S. Rissen (2/25 strains), S. London, S. Meleagridis, S. Give,
S. Assine (1/25 strains). We found that in different studies the common
serovar was also different. For example, Moe et. al. (S. Albany),
Patchanee et. al. (S. Rissen). From the above research results, it is
shown that the common serovars in the studies are different,
depending on the geographical area and time of sample collection.
3.2. Antibiotic resistance characteristics of Salmonella isolated
3.2.1. The level of antibiotic resistance of Salmonella isolated
Base on the antibiotic susceptibility results, we obtained 52%
(13/25) strains resistant to at least one antibiotic, of which the multiple
resistance rate was 36%. The rate of resistance to Streptomycin (STR)
and tetracycline (TE) was highest (44%). This is understandable
because these two antibiotics are widely used in Vietnam, both in
treatment and animal husbandry. All Salmonella are susceptible to

ceftazidime (CAZ), thus this is a good antibiotic that can be used to
treat Salmonella infection. It is needed to monitor the use of CAZ.
Antibiotic-resistant Salmonella is a source of transmission of
resistance genes to other organisms, more dangerous is to humans
10


through the consumption of food. The rate of antibiotic resistance in
this study (52%) is lower than the results of some studies in Vietnam
(62.2%) and Japan (89.9%). The rate of multi-resistance (36%) is
lower than some other research results such as Nguyen et. al. (41.1%)
and Katoh et. al. (90.2%). This difference may be due to the overuse
of antibiotics in animal husbandry and treatment between nations,
which increases selective pressures, resulting in emergence different
rates of antimicrobial resistance Salmonella. The number of samples
in this study is small (25 samples). Therefore, further research on
resistance rates and multiple antibiotic resistance should be conducted
with a larger number of samples.
3.2.2. The number of each Salmonella resistant to antibiotics
according to the isolation source
Determining the rate of antibiotic resistance of Salmonella
according to isolated sources helps to evaluate in detail their antibiotic
resistance characteristics by food source. The results showed that
Salmonella isolates from pork were most resistant to antibiotics, with
66.7% (6/9 strains), of which 44.4% (4/9 strains) were multi-antibiotic
resistant. Following by the isolated from chicken with the rate of
36.4% (4/11 strains) of which 27.3% (3/11 strains) are resistant. There
is only one S. Typhimurium from beef that is antibiotic resistant and
is multi-resistant. S. Typhimurium accounts for a large proportion of
all three isolates (11 strains), but only 3 strains of antibiotic resistance

are also multi-resistant.
3.2.3. Number of Salmonella resistant to each antibiotic according
to the isolation source
The determination of Salmonella antibiotic resistance
according to isolated sources helps to evaluate in detail their antibiotic
11


resistance characteristics by food source. Accordingly, all Salmonella
isolated from chicken were antibiotic resistant (except CAZ). No
strains were isolated from pork and beef resistant to CIP. Salmonella
isolated from three meat sources that are resistant to AM, STR, C, TE
and SXT, among which isolates from pork have the highest rate of
antibiotic resistance. All Salmonella isolates from beef are sensitive to
CAZ, GN and CIP. Salmonella was isolated from pork resistant to
AM, STR, and TE with the largest percentage. Salmonella from
chicken is the most C resistant, especially the CIP resistant strains
were found only in chicken. Beef is the least contaminated Salmonella
and these strains are most susceptible to antibiotics.
3.2.4. Antibiotic resistance phenotypic
Base upon antibiotic susceptibility results, we have identified
the antibiotic resistance pattern of Salmonella studied. Two common
phenotypes of antibiotic resistance are TE, STR, AM (2/9), and C, TE,
SXT, STR, AM (3/9). TE, STR, AM phenotypes are only found in
Salmonella isolated from pork. The two common antibiotic resistant
phenotypes in this study differ from the antibiotic resistance
phenotypes published in the Miranda et. al., Kim et. al. studies. From
the above results it can be said that the common patterns of antibiotic
resistance are different between the studies.
Identifying the antibiotic resistance phenotype in the research

samples is important. This phenotypic result combined with genomic
analysis results will show antibiotic resistance genes, mutations
related to antibiotic resistance phenotypes. From the phenotypic
results, we have obtained 9 multi-resistant Salmonella, of which S.
Typhimurium is the most common. Pork is the most isolated source of

12


multi-resistant Salmonella (5 serovars), followed by chicken (3
serovars), beef (1 serovar).
Antibiotic resistance rates, multidrug resistance rates, and
antibiotic resistance patterns are different among published studies.
This difference, according to some researchers, may be due to the
overuse of antibiotics in treatment and animal husbandry, increasing
the selection pressure on bacteria leading to the emergence of different
strains of multi-antibiotic resistant Salmonella by region. geography.
3.3. Results of analyzing gene categories in some multidrug
resistance Salmonella
Transcriptome sequencing is rarely used to identify antibiotic
resistance genes. Instead, researchers often use the entire whole
genome sequencing. Transcriptome sequencing allows us to study the
function of genes better than DNA sequencing. In this study, we want
to focus on the functional genome of bacteria. This is important
because the unnecessary genes will not be expressed and tend to be
lost or degraded. Moreover, the whole genome sequencing technique
could not distinguish the genes that were inactivated in the genome
and other related functions of that gene. In addition, in our opinion,
the expression gene will be related to the phenotype, particular
resistant or sensitive phenotypes, higher than the non-expression gene.

We have sequenced transcriptome of multidrug resistant
Salmonella using method which was published by Marcelino et. al.
(the author also sequenced the transcriptome of bacteria in bird gut in
Australia to identify of antibiotic resistance genes). It is very important
that antibiotic resistance genes are also expressed in antibiotic
sensitive bacteria under normal culture conditions. Therefore, in this
study we did not use antibiotic sensitive strains for comparison.
13


Instead, we use the same phenotype that is sensitive and resistant to
each antibiotic in the strains to compare. From that, we predict which
genes, or mutations, might be related to antibiotic resistance in this
bacterium.
In order to analyze the gene groups in multidrug-resistant
Salmonella, several resistant serovars should be selected to sequence
transcriptome. However, in the framework of this thesis, we selected
only 6 strains according to the criteria of high infection rate, resistance
to as many antibiotics as possible and by isolated sources, including S.
Derby, S. Give, S. Indiana, S. Typhimurium S384, S. Typhimurium
S360, and S. Typhimurium S181.
After extracted RNA from 6 research samples, we conducted
quality control by concentration measurement at OD260/280, and
electrophoresis. Results showed that these RNA samples were of good
quality. This sample was then synthesized cDNA and tested for
integrity. The results showed that the RIN (RNA Integrity Number)
was above 8.0, qualified for sequencing. The results are as follows:
3.3.1. Number of read
From the raw sequence results, we conducted trimming
sequence by Trimmomatic software: this yield total of 160,043,486

read, total number of read at Q20 score is 146,080,642. The number
of read is highest in Sal 4 and at least in Sal 6. The read sequences at
Q20 will be used for de novo assembly and used for further analysis.
3.3.2. De novo assembly
Results of de novo assembly showed that the transcriptome
size ranged from 4.69 Mb (Sal 4) to 5.1 Mb (Sal 11), GC values around
52%, N50 values are high and L50 values are low. This result is similar
to the sequencing result of S. Derby 07CR553 published by
14


Kérouanton et. al. From that, it can be concluded that the sequence of
6 research samples is of good quality, eligible for subsequent analysis.
3.3.3. Genes annotation
To avoid the missing annotation genes, gene analysis tools
have been used as many as possible. The number of genes detected in
these tools is different. The findings of these tools' genes differ
because of their different methods of analysis, and there is currently
no standard method for annotating genes accepted among researchers
around the world. The number of coding sequences found by different
databases is shown in Table 3.3.
Table 3.3. Coding sequences in 6 research samples
Number of coding sequences

Gene
analysis tool

Sal 4

RAST

4.807 4.917

5.154

5.097

5.357

5.000

PATRIC

4.807 4.917

5.154

5.049

5.357

5.000

BASys

4.973 5.100

5.336

5.253

5.566

5.209

Genious R11

4.400 4.513

5.022

5.207

5.304

5.309

Sal 6 Sal 7

Sal 8 Sal 11 Sal 12

In 2017, Baek et. al. announced that many genes that encode
proteins less than 100 amino acids undetectable when annotating the
bacterial genome. Therefore, further studies of the above genes are
needed in the research samples.
3.3.4. Gene categories analysis in multidrug resistant Salmonella
In addition to housekeeping genes...We have identified
important gene categories expressed in multi-resistant Salmonella:
3.3.4.1. Antibiotic resistance genes
Results of antibiotic resistance genes and antibiotic resistance

phenotype are presented in Table 3.4. Accordingly, a total of 107
15


antibiotic resistance genes (list of genes not shown in this summary).
Including 22 β-lactam resistance genes, 46 aminoglycoside resistance
genes, 8 quinolone resistance genes, 7 phenicol resistance genes, 6
cycline resistance genes, 3 sulfonamide resistance genes, 3
trimethoprim resistance genes. Furthermore, we have found 12
antibiotic resistance genes which resistant to macrolides, rifamycin,
fosfomycin, lincosamide, polymyxin, and peptides. The number and
diversity of antibiotic resistance genes in this study are similar to the
results of the study by Saskia et. al. (2018).
A total of 42 phenotypes were identified from antibiotic
susceptibility results. There are 29 antibiotic resistant phenotypes have
expression of antibiotic resistance genes. There are 12 antibioticsensitive phenotypes have expression of antibiotic resistance gene.
The only sensitive phenotype is that there is no expression of the
antibiotic resistance gene, Sal 6 is susceptible to SXT and there is no
expression of SXT resistance gene. Thus, the genotype and phenotype
accordant is (29 + 1) / 42 = 71.4%. And the genotype and antibiotic
resistance phenotype not accordant is 12/42 = 28.6%. The correlation
between genotype and phenotype is similar to the study results of
Owen et al., 2017 (72.7%). Our research results are lower than those
of some other authors like McDermott et. al, 2016 (99%), Zankari et.
al., 2013 (99.74%). The genotypes and phenotypes not accordant in
this study can be explained by the inadequate expression of antibiotic
resistance genes, due to the multiple antibiotic resistance mechanisms
involved in resistance to one antibiotic, and the other mechanisms of
antibiotic resistance have not been found.

16


Table 3.4. Summarize results of antibiotic resistance genes and antibiotic resistance phenotype in the research samples
KS

Mẫu nghiên cứu (Kiểu hình kháng kháng sinh/gen kháng kháng sinh)
Sal 4
(R)
blaOXA-1
blaTEM family, PBPE**
(R)
aac family*
aph family*
ant family*, kdpE

Sal 6
(R)
blaTEM
family
(S)
aac(6')-Iy
kdpE

Sal 7
(R)
blaTEM family
PBPE**
(S)
aac (6')-Iy, aac6-Iy,

aadA8, aadA17;
kdpE

Sal 8
(R)
blaTEM family

(R)
aac family*
aph family*
ant family*, kdpE
(R)
aac(6')Ib-cr,
gyrA,
gyrB, parC

(R)
aac(6')-Iy
kdpE

(R)
aac (6')-Iaa, aac3-IIa
aadA17, aadA8b
aph3-IIa, kdpE
(S)
qnrS1, qnr-S3, qnr-S5,
gyrB, parC

(R)
aac family*

aph family*
kdpE
(S)
gyrA, gyrB, parC

(S)
floR, cmlA1

(S)
cmlA1

(R)
sul1, sul2, dfrA12

(R)
tet(A),
tet(B),
tet(C), tet(R)
(R)
sul2, dfrA14, dfrA5

(R)
tet(A)

SXT

(R)
floR, cmlA1, cmlA5,
cat2
(R)

tet(A), tet(B), tet(C),
tet(M), tet(R), tet(S)
(R)
sul2, sul3, dfrA12

(R)
floR, cmlA1

TE

(R)
floR, cmlA1,
catB4, catB8
(R)
tet(A), tet(R)

(R)
aac (6')-Iy, aac6-Iy
aadA8, aadA17
kdpE
(S)
qnr-S1,
qnr-S3,
gyrA, gyrB, parC,
parE
(R)
floR, cmlA1, cmlA5,
cat2
(R)
tet(A),

tet(M),
tet(R), tet(S)
(R)
sul2, sul3, dfrA12

Sal 12
(R)
blaTEM family
PBPE**
(S)
aac(6')-Iaa,
aac6Iaa,
aph(6)-Id,
aph(3'')-Ib
strA, strB, kdpE
(R)
aac(6')-Iaa, aac6-Iaa
aph(6)-Id, aph(3'')-Ib
strA, strB, kdpE
(S)
gyrA, gyrB, parC

AM

GN

STR

CIP
C

catB3,

(S)
gyrA, gyrB,
parC

(R)
tet(A),
et(M), tet(S)
(S)

(S)
aac (6')-Iaa, aac3-IIa,
aadA17, aadA8b
aph3-IIa, kdpE

Sal 11
(R)
blaTEM family
PBPE**
(R)
aac family*
aph family*
kdpE

(S)
sul2

Abbreviation: *Aac (Acetylation) family; Aph (Phosphorylation) family; Ant (Adenylylation) family; ** Penicillin

Binding Protein E. coli. KS (kháng sinh), AM (ampicillin), GN (gentamycin), STR (streptomycin), CIP (ciprofloxacin),
C (chloramphenicol), TE (tetracyclin), SXT (sulfamethoxazol/trimetoprim).
17


3.3.4.2. Quinolone resistance gene mutations
Quinolone is commonly used in the treatment of Salmonella
infections in humans. For food-borne Salmonella, quinolone
resistance is the most concerned and has been mentioned in the list of
the most important antibiotics in the field of medicine in 2016 by
WHO. One of the quinolone resistance mechanisms in Salmonella is
caused by mutations of the gyrA, gyrB and parC genes. Thus, we
found mutations of these genes, the results are presented in Table 3.5.
Table 3.5. Results of the quinolone resistance gene mutations
Gene mutations
Samples

SR
gyrA

parC

Sal 4

R

Sal 6

S

Sal 7

S

Sal 8

S

T255S; N395S; S469A; A620T

Sal 11

S

T255S; N395S; S469A; A620T

Sal 12

S

T255S; N395S; S469A; A620T

parE

S83F;D87G T57S; S80R; T255S; A628S
T57S; T255S; N395S
S83Y

T57S; T255S; A352V

S592N

Abbreviation: A (Alanine), N (Asparagine), R (Arginine), S (Serine),
T (Threonine), V (Valine), SR (susceptibility results), R (resistant), S
(sensitive).
The results of Table 3.5 show that the list of mutations was
identified: S83F, S83Y, D87G, S80R, T57S, T255S, N395S, S469A,
A620T, A628S, S592N. To date, there are no reports of mutations
A628S, T255S, N395S, S469A, and A620T have been published.
However, the mutations T255S, N395S, S469A, A620T were
identified in CIP-sensitive strains Sal 6, Sal 7, Sal 8, Sal 11, and Sal
18


12 proving that these mutations have no role in CIP resistance in
research samples. The parC mutation (A628S) may have a role in CIP
resistance because it appears only in Sal 4, the only CIP resistant
strain. This result is not only new but also has high scientific
significance, paving the way for further research on antibiotic
resistance in Salmonella.
3.3.4.3. The gene categories involved in the efflux pumps
We identified the expression of 41 efflux pumps-related
genes, including 37 genes in S. Typhimurium S181, 25 genes in S.
Typhimurium S384, 27 genes in S. Typhimurium S360, 27 genes in S.
Give, 23 genes in S. Derby, 26 genes in S. Indiana. Efflux pumps were
detected in research samples belonging to 3 families: MFS (MefB,
EmrAB, tetA, tetB, MdtD), SMR (QacE), and RND (AcrAB-TolC,
AcrAD-TolC,

AcrEF-TolC,

MdtABC-TolC,

MexPQ-OpmE).

Understanding of efflux pumps is essential for the development of
interventions to limit antibiotic resistance in Salmonella.
Some strains of Salmonella are susceptible to antibiotics but
still have expression of efflux pumps, like AcrAB-TolC, AcrEF-TolC,
and MdfA in C-sensitive strains. AcrD in GN-sensitive strains.
MexPQ-OpmE in CIP-sensitive and C-sensitive strains. Therefore
these channels do not play a role in resistant to these antibiotics.
Some antibiotic resistant strains have the expression of efflux
pumps, like AcrD in AM, STR-resistant strains, MexPQ-OpmE in TEresistance strains, EmrAB in TE, STR and AM-resistant strains.
Therefore, we predicted that these channels may be related to
resistance to the respective antibiotics. Further studies on the drug
dispensing canal system in Salmonella need to be conducted in the
future.
19


New finding the role of the above efflux pumps on antibiotic
resistance is the novelty of the thesis.
3.3.4.4. Analysis results of some other gene categories
In addition to the antibiotic resistance gene category and the
genes related to efflux pumps, we identified many other gene groups
related to antibiotic resistance and bacterial toxins. The number of
genes in each of these functional categories is shown in Table 3.6.
Table 3.6. Expression of related gene groups.
Gene category

Number of genes
Sal 4 Sal 6 Sal 7 Sal 8

Sal 11

Sal 12

Toxin genes

118

124

125

130

131

133

flagellar

38

38

38

38

38

38

Cell wall and LPS

52

39

48

52

51

51

Response to Selenium

2

2

2

2

2

2

Response to Tellurite

3

3

3

3

3

3

2

2

2

2

2

2

12

24

22

27

26

26

21

21

21

21

21

21

Response to
Formaldehyde
Mobile elements, phage
and prophage
ABC transporter

Abbreviation: Sal 4 (S. Indiana), Sal 6 (S. Derby), Sal 7 (S. Give), Sal
8 (S. Typhimurium S360), Sal 11 (S. Typhimurium S384), Sal 12 (S.
Typhimurium S181).
Toxic gene categories
To date, about 200 toxin-related genes in Salmonella have
been discovered, however, the function and action mechanism of most
of these genes have not been fully elucidated. In this study, a total of
134 toxin genes were identified. The number and diversity of these
20


genes are similar to those of other publications, for example, by
Figueiredo et. al. (114 genes), Card et. al. (105 genes). The presence
of the toxic gene indicates that all six multidrug resistant Salmonella
strains are virulent. These genes play a role in the pathogenesis and
may have a role in antibiotic resistance in Salmonella. This is the first
study to determine the expression of all virulence genes in multidrug
resistant Salmonlla strains in Vietnam.
The gene categories involved in flagellar synthesis
Flagellar plays an important role in producing the toxin of
bacteria, which is often mixed in the outer membrane protein when an
antigen is isolated to make a Salmonella vaccine. Understanding the
expression genes associated with flagellar will be very helpful for
purifying this component. For example, inactivating these genes will
create pure outer membrane vesicles, as antigens to make the vaccine.
This is also one of the new contributions of the thesis.
The gene categories involved in the synthesis of LPS and cell walls
Apart from S. Typhi, LPS of other Salmonella has not been
fully studied. The lipidA synthesis genes, an important component of
the LPS, involved in resistance to polymixin antibiotics were also

expressed in all six study samples. LPS and the outer membrane
protein form the outer vesicles, which are immune stimulating and are
considered important components for making vaccines. The results of
this study contribute in part to the knowledge of LPS-encoded genes,
which is a reference source for further studies.
Genetic group responds to toxic substances
In addition to selenium, tellurite is a highly toxic element, and
formaldehyde is also found in six Salmonella samples, which is an
alarming fact. The results of this study show that extensive research is
21


needed to shed more light on the original sources of these substances
and the extent of contamination of this compound in foodstuffs in
Hanoi. Therefore, controlling the origin and food processing process
is necessary.
Mobile elemetnts group, phage and prophage
Phage usually carries toxic genes, forming toxins of
Salmonella. A number of bacteriophages that exist in Salmonella can
be used as a marker for rapid diagnostic. We have identified the Gifsy2 phage in all samples, so this could be a marker for quick diagnosis
of Salmonella. However, the number of research samples is small (6
samples), so it is necessary to conduct research on a larger number of
samples to confirm the above problem.
The gene group involved in the ABC transport channel
The ABC transport channel produces toxins in many bacteria.
Their ability to transport is related to therapeutic antibiotic resistance.
However, in most Salmonella species, the function of some
components of this transport channel such as sapABCDF has not been
fully elucidated. In S. Typhimurium, sapABCDF produces a toxin that
helps bacteria resist peptide antibiotics.

3.4. Confirm antimicrobial resistant gene mutations using Sanger
sequencing
Base on the predicted results by the next generation
sequencing method on the new mutation in parC gene (A628S)
possibly related to quinolone resistance, we conducted a Sanger
sequencing of parC gene containing the above mutation to confirm the
results.
The Sanger gene sequencing results showed that only the Sal
4 sample at position 1882 of the parC gene showed a mutation that
22


changed nucleotide G→T, this mutation altered amino acid A628S,
this result was consistent with the results of the analysis by the next
generation sequencing method. The A628S mutation may be a factor
that changes the function of the parC gene, making the gene resistant
to antibiotics in Sal 4. We have not seen any announcement of this
mutation yet. However, to confirm whether the parC gene mutation
(A628S) is related to quinolone antibiotic resistance, further studies
are needed.
CONCLUSIONS
To conclude
1. Isolated and identified Salmonella strains from pork, beef, and
chicken at retail markets in Hanoi. Samples contaminated with
Salmonella were 27.8%, 9 different serovars have been found, the
most common serovar was S. Typhimurium.
2. Identified antibiotic resistance characteristics of Salmonella
isolated. The antibiotic resistance rate of Salmonella was 52%, the
rate of multidrug resistant Salmonella was 36%. The highly
resistant antibiotics are STR and TE (44%). In contrast, 100% of

strains are sensitive to CAZ. The common of antibiotic resistance
phenotype are TE, STR, AM, and C, TE, SXT, STR, AM.
3. Analyzed the gene categories of multidrug resistant Salmonella.
These include the groups of genes related to antibiotic resistance
and the groups of genes related to bacterial toxins. Base these
results we have identified:
•

A new mutation in the parC gene (A628S) is possibly
associated with quinolone resistance in Salmonella.

•

Identified genes related to efflux pumps that may play a role
in resistance to antibiotics in Salmonella such as: AcrD in
23


AM, STR and GN resistance, EmrAB in TE and STR and AM
resistance, and MexPQ-OpmE in TE resistance.
Recommendation
1. Studies on the role of the parC gene mutation (A628S) in response
to quinolone resistance.
2. Studies on the role and function of the some efflux pumps in
Salmonella, especially the role of AcrD in AM, STR and GN
resistance, EmrAB in TE, STR and AM resistance, MexPQ-OpmE
in TE resistance.
3. Studies to evaluate the role of small-sized genes, coding for
proteins less than 100 amino acids undetectable in the study
samples.

NEW FINDINGS OF THE THESIS
1. Identify a new mutation point in the parC gene (A628S) possibly
related to quinolone antibiotic resistance in Salmonella.
2. Proposing the role of the efflux pumps in resistance to some
antibiotics in Salmonella such as AcrD in AM, STR and GN
resistance, EmrAB channel in TE, STR and AM resistance,
MexPQ-OpmE in TE resistance.

24