Many multidrug-resistant bacteria form biofilms to survive in unfavorable conditions and use them as a defense mechanism. Biofilms are sessile microbial colonies surrounded by extracellular matrix and attached to non-living or living subjects. They are associated with antibiotic tolerance and the production of virulence factors (Young et al. 2002). Methicillin-resistant
The present study was part of a surveillance project on “Enteric Fever” carried out among people of a rural cohort established under the model rural health research unit (MRHRU) in Odisha, India. In the current paper, we present our findings on the antimicrobial resistance patterns and biofilm-forming ability of
Under the study, 718 consented eligible participants (febrile patients suspected of enteric fever) visiting four public healthcare facilities in the study area were enrolled from December 2020 to December 2021. Patients over six months presenting with fever were included, and those who did not give written consent and were severely sick without fever were excluded. While the sample size was calculated to determine the prevalence of enteric fever, the primary objective of the present article focused on understanding the antimicrobial resistance pattern and the biofilm-forming characteristics of the isolates among the
Before the data and sample collection, the purpose of the study was explained to all participants, and their written informed consent was obtained. Socio-demographic data and clinical history were recorded using a standardized questionnaire developed by the National Surveillance System for Enteric Fever in India, with the help of the Android-based open data kit tool. Blood samples from the study participants were collected aseptically (3 ml from children and 5 ml from adults) by a trained phlebotomist, inoculated into BACTEC culture bottles, and immediately transported to the MRHRU laboratory for further processing. Blood cultures of
All the samples were incubated in BD BACTEC™ FX 40 Automated Blood Culture System (BD, USA). After incubation at 37°C, when the culture was positive, the colonies were streaked onto MacConkey agar and blood agar plates (Hi Media Laboratories, India). The inoculated plates were incubated for 48 h at 37°C, followed by Gram staining. The pure cultures were examined for colony morphology and biochemical characteristics (catalase and coagulase tests) to identify the bacteria.
Antibiotic susceptibility profiles of the isolates were determined by the Kirby-Bauer disk diffusion technique using Hi-media antibiotic disks following the criteria set by CLSI (CLSI 2018). Antibiotics, including penicillin (10 μg), erythromycin (15 μg/ml), ampicillin (10 μg), azithromycin (15 μg), cefoxitin (30 μg), co-trimoxazole (25 μg), clindamycin (30 μg), teicoplanin (30 μg), ciprofloxacin (5 μg), vancomycin (30 μg), chloramphenicol (30 μg), levofloxacin (5 μg), tetracycline (30 μg), gentamicin (10 μg), and linezolid (30 μg) were used to determine the antibiogram.
MRSA identification test was performed in accordance with the criteria of Clinical Laboratory Standard Institute (CLSI) 2020 using cefoxitin (30 μg) disk diffusion assay (Weinstein and Lewis 2020). The isolates showing the zone of inhibition of ≥ 22 mm, 21–22 mm, and ≤ 21 mm, respectively, were considered sensitive, intermediate, and resistant.
Biofilm formation assay for all isolates was carried out using the microplate method described by Aslantaş and Demir (2016). Individual isolates were grown in tryptic soy broth (TSB) overnight at 37°C. When the culture’s optical density (OD) reached 0.5, the suspension was diluted with 1:10 in TSB with 1% dextrose, and 200 μl was put in each 96-well polystyrene microtiter plate in triplicate. Wells with TSB served as a negative control. The plate was incubated at 37°C for 48 h without shaking. After incubation, the planktonic cells were carefully removed by micropipette aspiration and gently washed two times with sterile phosphate-buffered saline (PBS) to remove nonadherent cells. Methanol in the volume of 200 μl was added to each well for 10 min, and then, the biofilms were stained with 0.1% (w/v) crystal violet for 10 min. The plates were washed with water thrice and air-dried for 2 h. The stained biomass was dissolved with 200 μl 30% (v/v) acetic acid for 10 mins, and then, 150 μl from each well was transferred to new flat-bottomed microtiter plate to measure the OD at 570 nm using a microplate reader (Erba Mannheim, Germany). The result was analyzed as described by Stepanović et al. (2007). The biofilm formation ability was determined by comparing the OD of the isolates to that of the control and the cut-off value (ODc). The isolates were categorized into four groups: no biofilm producers (OD ≤ ODc), weak biofilm producers (ODc<OD≤2×ODc), moderate biofilm producers (2×ODc<OD≤4×ODc), and strong biofilm producers (OD>4×ODc) (Stepanović et al. 2007).
The univariate descriptive statistical analysis was carried out to determine the socio-demographic and clinical parameters’ distribution of the patients included in this study and those found positive for
Detailed information on patients is provided in Table SI. The age of 718 study participants ranged between 11 months to 95 years, with a median age of 35. Among the participants, 397 (55.29%) were male. The median duration of fever was three days (Table SII A). Out of 718 blood samples, 73 (10.2%) showed the presence of
The workflow for sample collection and their investigation is presented in Fig. 1A. Out of 718 blood samples initially incubated in the BD BACTEC™ FX 40 Automated Blood Culture System, 84 (11.7%) were found positive for bacterial growth. Based on the colony characteristics, Gram stain, and biochemical properties
All
Antibiotic susceptibility pattern of
Name of antibiotics | S | I | R |
---|---|---|---|
Penicillin | 8 (11%) | 0 (0%) | 65 (89%) |
Ampicillin | 9 (12%) | 0 (0%) | 64 (88%) |
Erythromycin | 9 (12%) | 7 (10%) | 57 (78%) |
Azithromycin | 18 (25%) | 3 (4%) | 52 (71%) |
Cefoxitin | 33 (45%) | 0 (0%) | 40 (55%) |
Co-trimoxazole | 35 (48%) | 2 (3%) | 36 (49%) |
Clindamycin | 52 (71%) | 11 (15%) | 10 (14%) |
Teicoplanin | 54 (74%) | 8 (11%) | 11 (15%) |
Ciprofloxacin | 59 (81%) | 2 (3%) | 12 (16%) |
Vancomycin | 58 (81%) | 10 (12%) | 5 (7%) |
Chloramphenicol | 62 (85%) | 5 (7%) | 6 (8%) |
Levofloxacin | 62 (85%) | 5 (7%) | 6 (8%) |
Tetracycline | 67 (92%) | 0 (0%) | 6 (8%) |
Gentamicin | 71 (97%) | 0 (0%) | 2 (3%) |
Linezolid | 73 (100%) | 0 (0%) | 0 (0%) |
S – susceptible, I – intermediate, R – resistant
All
Details of antibiotic susceptibility pattern of strong biofilm-forming
Sample ID | Antibiotic |
---|---|
38 | COT, VA, C, TEI, LZ, CD, TE |
116 | GEN, COT, CIP, C, LZ, TE, LE |
143 | GEN, COT, CIP, VA, C, LZ, TE, LE |
153 | GEN, COT, CIP, VA, C, CX, LZ, CD, TE, LE |
156 | GEN, COT, CIP, VA, C, TEI, CX, LZ, CD, TE, LE |
161 | GEN, COT, AMP, CIP, AZM, VA, C, TEI, P, CX, E, LZ, CD, TE, LE |
221 | GEN, CIP, C, TEI, LZ, CD, TE, LE |
229 | GEN, CIP, VA, C, TEI, LZ, CD, TE, LE |
231 | GEN, CIP, VA, C, TEI, CX, LZ, CD, TE, LE |
236 | GEN, CIP, VA, C, TEI, LZ, CD, TE, LE |
241 | GEN, COT, AMP, CIP, AZM, VA, C, TEI, LZ, TE, LE |
242 | GEN, CIP, VA, C, TEI, CX, LZ, CD, TE, LE |
271 | GEN, CIP, AZM, VA, C, TEI, LZ, CD, LE |
277 | GEN, CIP, C, LZ, CD, TE, LE |
350 | GEN, COT, CIP, VA, LZ, TE, LE |
352 | GEN, VA, TEI, LZ, TE |
354 | GEN, COT, CIP, AZM, VA, TEI, E, LZ, CD, TE, LE |
382 | GEN, CIP, VA, C, TEI, CX, LZ, CD, TE, LE |
498 | GEN, COT, CIP, VA, C, TEI, CX, LZ, CD, TE, LE |
515 | GEN, AMP, CIP, VA, C, TEI, P, CX, LZ, CD, TE, LE |
Most of the strong biofilm-producing S.
Access to high-quality medical services is a great challenge in low-income and middle-income countries and often leads to lower rate of disease screening, diagnosis, and treatment (Wilson et al. 2018). To the best of our knowledge, this is the first study carried out in a rural cohort of eastern India to understand the antibiotic resistance and biofilm-forming characteristics of
The antimicrobial stewardship program has been restricted owing to the challenges concerning data collection, access, awareness, and lack of accurate diagnosis tools, thereby limiting information on Anti-Microbial Resistance (AMR) burden. A higher resistance of
Biofilm formation in clinical isolates of
We found