Each of these pathotypes represents a group of clones that share similar virulence characteristics. It should be mentioned, too, that because of the genome's flexibility, many E. coli isolates have been challenging to categorise as a pathotype. This is due to the fact that some isolates, which may be more virulent hybrid pathogenic strains, combine the most pathogenic features of many pathotypes. Further epidemiological studies are necessary to officially designate DAEC as a unique DEC pathotype, despite the fact that they are classified as a group apart from the other pathotypes. These studies have been impeded by the challenges associated with identifying and classifying DAEC. Material and Methods This is a prospective, observational, Random and cross-sectional study conducted in the Department of Microbiology at Index Medical College, located in Indore, Madhya Pradesh. Submission of a stool sample that reveals an excess of five white blood cells per high-power field (HPF). A total of 180 fecal samples was collected by using disposable container. Each container was inverted and sealed immediately after collection. Results A total of 111 (61.7%) isolates were found to be ESBL producers in Table 1, whereas 68 (37.8%) isolates were shown to be MBL producers using both approaches (combined disk diffusion test and Modified Hodge test). By using both the zone indentation and the boronic acid disk test technique, AmpC was found in 48 (26.7%) diarrheagenic E. Coli isolates, while the disk approximation test yielded positive results in 44 (24.4%) isolates. The production of ESBL, MBL, and AmpC in the healthy group was comparable to those of the other study groups. It was shown that the boronic acid disk test method for AmpC detection was more user-friendly and reproducible. Conclusion: In this investigation, the isolates' primary resistance patterns that were assessed were AmpC, ESBL, and MBL. The widespread usage of third-generation cephalosporins was the cause of the high frequency of ESBL and plasmid-mediated AmpC. The aim of phenotypic approaches for beta-lactamase detection was to determine the drug resistance profile of E. coli gut flora prior to medication delivery.
Each of these pathotypes represents a group of clones that share similar virulence characteristics. It should be mentioned, too, that because of the genome's flexibility, many E. coli isolates have been challenging to categorise as a pathotype. [1] This is due to the fact that some isolates, which may be more virulent hybrid pathogenic strains, combine the most pathogenic features of many pathotypes. [2]
Further epidemiological studies are necessary to officially designate DAEC as a unique DEC pathotype, despite the fact that they are classified as a group apart from the other pathotypes. These studies have been impeded by the challenges associated with identifying and classifying DAEC. [3]
The resistance genes found inside gene cassettes are expressed and transmitted by integrons, which are genetic structures. Numerous integron types may be identified using the sequence of certain recombinases called integrases; class 1 integrons are the most therapeutically relevant. [4] Typically, the 3′-CS has two genes: sul1, which confers sulfonamide resistance, and qacEΔ1, which is a faulty quaternary ammonium compound resistance gene. [5]
Because diarrheal episodes caused by DEC infections are linked to morbidity and death in children under five, they significant public health concern for adults and children in underdeveloped countries. With a focus on research carried out in India, this study aimed to compile data on the most recent definitions, serotypes and diagnostics of main DEC pathotypes.
This is a prospective, observational, Random and cross-sectional study conducted in the Department of Microbiology at Index Medical College, located in Indore, Madhya Pradesh.
Duration: 3 years, from 2021 to 2023
Data collected from January 2022 to December 2023
Inclusion criteria:
Submission of a stool sample that reveals an excess of five white blood cells per high-power field (HPF).
Exclusion criteria:
Fecal Samples
A total of 180 fecal samples was collected by using disposable container. Each container was inverted and sealed immediately after collection.
We have done Pilot study from March 2021 to May 2021 at Index medical college.
Fecal Samples
A total of 180 fecal samples were collected by using disposable container. Each container was inverted and sealed immediately after collection.
To isolate and characterize E. coli phenotypically from feces of children (OPD and IPD) as well as from normal healthy children existing as commensal.
Phenotypic methods
Samples All of the children's fresh feces samples were obtained and sent straight to the lab in clean, sterile, labeled, wide-mouthed plastic containers with tight lids (for tiny children, rectal swabs or stools from diapers were collected).
The protocols for laboratory diagnosis of enteric pathogens were followed in the processing of all the specimens. After being inoculated, specimens were incubated aerobically for 24 hours at 37 °C on MacConkey agar plates. To identify the E. Coli isolates, microscopy, colony morphology, and several sugar fermentation assays were used. On MacConkey agar plates, discrete colonies of lactose fermenters—a typical pink hue associated with Escherichia coli—were seen. Organisms once identified was stocked in 1ml capacity vials containing stock media (Himedia, Mumbai, India), and stored at room temperature. Every isolate that was first suspected to be E. coli based on its growth characteristics on MacConkey agar was subsequently confirmed phenotypically using standard biochemical tests.
Statistical analysis
The Statistical Package for the Social Sciences (version 29.0) was used to do the statistical analysis. The chi-square test and Fisher's exact test were used to evaluate the statistical significance of the data. It was considered statistically significant when P < 0.05.
Table 1: Comparison of ESBL, MBL and AmpC production by different phenotypic methods in three study groups.
Groups |
ESBL N (%) Double Disk Synergy Test (DDST) |
MBL N (%) Double disk potentiation test |
MBL N (%) (Modified Hodge test) |
AmpC N (%) |
||
(ZONE INDENTATION TEST) |
(BORONIC ACID DISK TEST METHOD) |
(DISK APPROXIMATION TEST) |
||||
1(n=60) |
39(65) |
30(50) |
30(50) |
24(40) |
24(40) |
21(35) |
2(n=60) |
39(65) |
20(33.3) |
20(33.3) |
9(15) |
9(15) |
8(13.3) |
3(n=60) |
33(55) |
18(30) |
18(30) |
15(25) |
15(25) |
15(25) |
Total (n=180) |
111(61.7) |
68 (37.8) |
68 (37.8) |
48 (26.7) |
48 (26.7) |
44 (24.4) |
P value |
0.407 |
0.024* |
0.024* |
0.611 |
0.595 |
0.708 |
A total of 111 (61.7%) isolates were found to be ESBL producers in Table 1, whereas 68 (37.8%) isolates were shown to be MBL producers using both approaches (combined disk diffusion test and Modified Hodge test). By using both the zone indentation and the boronic acid disk test technique, AmpC was found in 48 (26.7%) diarrheagenic E. Coli isolates, while the disk approximation test yielded positive results in 44 (24.4%) isolates. The production of ESBL, MBL, and AmpC in the healthy group was comparable to those of the other study groups. It was shown that the boronic acid disk test method for AmpC detection was more user-friendly and reproducible.
Table 2: Comparison of prevalence of ESBL production by phenotypic and genotypic methods.
Groups |
Average age (years) |
Phenotypic |
Genotypic |
|
ESBL positive by screening |
ESBL confirmation by DDST |
ESBL by PCR |
||
Group1(n=60) |
2.17 |
42(70) |
39(65) |
39(65) |
Group 2(n=60) |
1.74 |
44((73.3) |
39(65) |
39(65) |
Group3(n=60) |
3.88 |
35(58.3) |
33(55) |
33(55) |
Total (n=180) |
2.59 |
39(65) |
39(65) |
39(65) |
P value |
0.209 |
0.407 |
0.407 |
Table 2 shows a comparative distribution of ESBL generation by genotypic and phenotypic techniques. Both the multiplex PCR (65%) and the double disk synergy test revealed comparable levels of ESBL production. Although, ESBL production was not found to be significant by any of the methods.
Table 3: Multiplex PCR of the TEM, SHV, CTX-M, and OXA genes in E. coli isolates
Genes |
Group1 (n=60) |
Group2 (n=60) |
Group3(n=60) |
Total (n=180) |
|
P value |
OR 95% CI (lower-upper) |
TEM |
28 (46.7) |
21(35) |
24(40) |
73(40.6) |
131(72.8) |
<0.001* |
4.394 (2.554 - 7.668) |
SHV |
21 (35) |
21(35) |
16(26.7) |
58(32.2) |
|||
CTX-M |
11(18.3) |
12(20) |
12(20) |
35(19.4) |
72 (40) |
||
OXA |
15 (25) |
11(18.3) |
11 (18.3) |
37 (20.6) |
In Table 3, the chances of presence of TEM and SHV genes in combination was 4.394 times higher as compare to CTX-M and OXA genes together, which was highly significant too (P value 0.01).
Table 4: Presence of TEM, SHV, CTX-M and OXA genes in E. coli isolates by Multiplex PCR.
Groups |
Multiplex PCR result |
||||||||||
|
ESBL |
TEM |
SHV |
CTX |
OXA |
TEM+ SHV |
TEM+ CTX |
TEM+ OXA |
SHV+ CTX |
SHV+ OXA |
CTX+ OXA |
1 (n=60) |
positive (n=35) |
1 (1.7) |
3 (5) |
1 (1.7) |
4 (6.7) |
8 (20) |
6 (10) |
6 (10) |
3 (5) |
3 (5) |
0 |
2 (n=60) |
positive (n=39) |
1 (1.7) |
4 (6.7) |
1 (1.7) |
1 (1.7) |
7 (11.7) |
6 (10) |
6 (10) |
6 (10) |
3 (5) |
0 |
3 (n=60) |
positive (n=33) |
3 (5) |
6 (10) |
9 (15) |
0 |
7 (11.7) |
0 |
7 (11.7) |
0 |
1 (1.7) |
0 |
Total |
107 |
5 (2.8) |
13 (7.2) |
11 (6.1) |
5 (2.8) |
22 (12.2) |
12 (6.7) |
19 (10.6) |
9 (5) |
7 (3.9) |
0 |
P value |
0.778 |
0.697 |
0.035* |
0.163 |
0.555 |
0.117 |
0.917 |
0.121 |
1.000 |
0.355 |
Table 4 illustrates that of the 180 E. coli isolates that yielded 76 ESBL producers (35, 39, and 33 from groups 1, 2, and 3 respectively), 5 (2.8%) had TEM alone, 13 (7.2%) had SHV alone, 11 (6.1%) had CTX-M alone, and 5 (2.8%) samples had OXA alone. None of the isolates had all of the ESBL genes present at once. TEM and SHV genes only were found in isolates that tested negative for ESBL using the combined disk test. 18 isolates showed co-production of TEM and SHV, 13 isolates showed TEM and OXA, 8 isolates showed TEM and CTX-M, 6 isolates showed SHV with CTX, 6 isolates showed SHV with OXA, and 4 isolates showed CTX with OXA. Eight E. Coli isolates were negative for combined disc testing but positive (6.5%) for ESBL production by PCR.
Table 5: Various predictors of ESBL infection.
Predictors of ESBL production |
n=180 |
P value |
Adjusted Odds ratio |
95% CI (Lower) |
95% CI (Upper) |
Extended spectrum beta lactamases |
|||||
Yes |
108 |
0.01* |
2.969 |
1.76 |
5.05 |
No |
72 |
1 |
|||
TEM |
|
|
|||
yes |
54 |
0.004* |
0.477 |
0.284 |
0.798 |
No |
126 |
1 |
|||
SHV |
|
||||
yes |
36 |
0.01* |
0.227 |
0.131 |
0.389 |
No |
144 |
1 |
Various predictors of ESBL production have been shown in Table 5, it was found that the factors like ESBL genes (TEM, SHV, CTX and OXA) and age were found to be the possible cause of ESBL infection (P value=0.00), while gender does not play any significant role in causing the infection. This may be due to the fact that in typical circumstances ESBL derive from TEM, SHV, CTX-M and OXA genes and their various variants and in these age group of children (upto 3 years).
Table 6: Comparison of prevalence of MBL by phenotypic and genotypic methods.
Group |
Phenotypic |
Genotypic |
|
|
MBL positive by screening |
MBL confirmation by DDST |
MBL by PCR |
Group 1(n=60) |
31(51.7) |
30(50) |
30(50) |
Group 2(n=60) |
21(35) |
18(30) |
18(30) |
Group 3(n=60) |
21(35) |
18(30) |
15(25) |
Total (n=180) |
73 (40.6) |
66 (36.7) |
63(35) |
P value |
0.228 |
0.131 |
0.057 |
A comparison of MBL production distributions using genotypic and phenotypic approaches is shown in Table 6. It was seen that the MBL production was found to be 66 (36.7%) by phenotypic method and 63 (35%) by the genotypic method. Although, MBL production was not found to be significant by any of the methods. Confirmatory phenotypic testing, as opposed to genotypic analysis, may provide false-positive findings, which, if dispersed unevenly over time, may cause erroneous trends in β-lactamase rates. More significantly, improper diagnosis might lead to poor patient treatment. The influence of environmental factors and the phenotypic technique's reduced sensitivity on the occurrence of resistance may account for the observed discrepancy in the identification of positive isolates by the two distinct methods. Erroneous diagnosis of antibiotic resistance may result in the prescription of the wrong medication, which can then exert selection pressure on bacteria to generate new resistance genes.
The dynamics, development, and evolution of resistance in E. coli populations are contingent upon the hosts, resistance mechanisms, and used antimicrobial classes. The predominant defenses of E. coli against various antimicrobials consist of efflux pumps and mobile resistance mechanisms associated with plasmids and/or other transferable elements. The emergence of hybrid plasmids, including both resistance and pathogenicity, in E. coli generates increased apprehension.
Consequently, due to the dynamic nature of resistance, the surveillance of antimicrobial characteristics (phenotypes and genotypes) of commensal intestinal E. coli (and Enterococcus) from food animals is an essential measure for evaluating ongoing trends and ensuring that national and community services remain informed about current advancements in antimicrobial resistance and its determinants. The integration of phenotypic and genotypic characterizations, coupled with relevant gene expression and metagenomic analyses, would elucidate the significance of commensal E. coli in food animals as an overlooked and undervalued reservoir of various antibiotic resistance mechanisms.
The existence and dissemination of these "deleterious genes" inside this extensive and versatile in vivo environment may provide a growing public health issue in the future. The significance of multidrug-resistant (MDR) commensal E. coli is most apparent in the food animal industry, where they act as a reservoir for intra- and interspecific gene exchange and a source of MDR determinants transmitted to humans via contaminated food. Consequently, the public health implications of multidrug-resistant commensal E. coli in food animals need enhanced monitoring and molecular research moving forward.
We propose three notable changes in chromosomal composition between these two temporal markers: 1) Stabilization of mcr-1 via the loss of ISApl1 and the transition from fitness-cost plasmids to less burdensome plasmids, such as IncI2; 2) association with hitchhiker genes that confer resistance to other clinically significant antibiotics, potentially leading to co-selection; and 3) an increase in the prevalence of mcr-1-positive ExPEC strains capable of occupying broader ecological niches and occasionally causing gastroenteritis.
All MCRPEC strains will be obtained from healthy individuals without observable intestinal or other diseases; hence, the exact pathogenicity and risk to human health require additional investigation. Ultimately, our comparative analysis indicates that human fecal MCRPEC strain populations have experienced a genetic alteration; however, it remains ambiguous whether the ExPECs acquired the mcr-1-positive plasmids via stochastic mechanisms or alternative processes, as well as what molecular modifications or unidentified factors may have facilitated this shift.
patterns that were assessed were AmpC, ESBL, and MBL. The widespread usage of third-generation cephalosporins was the cause of the high frequency of ESBL and plasmid-mediated AmpC. The aim of phenotypic approaches for beta-lactamase detection was to determine the drug resistance profile of E. coli gut flora prior to medication delivery. More than ever, microbiological expertise is required, and quick and precise detection of ESBLs, AmpC beta-lactamases, and carbapenemases is essential. E. Coli isolates with multiple antimicrobial drug resistances make treating infections therapeutically more difficult.
In regular laboratory settings, early detection of beta lactamase generation is critical for establishing antibiotic treatment and achieving successful therapeutic results. We were able to stop the spread of different beta-lactamase harboring E. coli in both sick and healthy children by using basic phenotypic testing in the lab. New tactics to counter this phenomena may be developed with an understanding of the molecular basis of resistance acquisition and transfer.