Urinary tract infections are among the most common bacterial infections worldwide, but the drugs used to treat them are steadily losing their power. A new cross-sectional study from Chennai, India, has found that multidrug-resistant Escherichia coli was present in more than two-thirds of the urine isolates examined, highlighting the growing difficulty of treating infections that were once considered routine. The researchers analysed 1,356 E. coli isolates collected over six months, from October 2023 through March 2024, and identified extensive resistance to several major antibiotic classes. Their findings add to mounting evidence that antimicrobial resistance is transforming everyday infections into increasingly complex clinical problems.
E. coli normally lives harmlessly in the intestinal tract, yet it is also the leading cause of many urinary tract infections. When the bacterium enters the urinary system, it can multiply in the bladder and, in some cases, travel to the kidneys or enter the bloodstream. Treatment traditionally relies on antibiotics selected according to local resistance patterns. However, repeated exposure to antibiotics creates evolutionary pressure: susceptible bacteria are eliminated, while variants carrying resistance mechanisms survive and reproduce. The Chennai study provides a detailed snapshot of how far that process has progressed in a population of urinary E. coli isolates examined in a diagnostic laboratory setting.
The investigators used the VITEK2 automated identification and antimicrobial susceptibility testing system, a platform widely used in clinical microbiology laboratories. The system determines whether bacterial growth is inhibited by specific antimicrobial agents and helps classify an isolate as susceptible, intermediate, or resistant according to laboratory standards. In this study, the antibiotic susceptibility card used was the GN-specific AST N-235 panel. The researchers then examined the results statistically and applied computational methods to reveal patterns that may be difficult to see when antibiotics are considered one at a time. This combination of routine laboratory testing, statistical analysis, and network science allowed the team to map resistance as an interconnected biological phenomenon.
The central result was striking: 70.5 percent of the isolates met the study’s definition of multidrug resistance. MDR generally refers to resistance to multiple antimicrobial categories, meaning that the bacterium is no longer vulnerable to several standard treatment options. The most prominent resistance was reported against nalidixic acid, ampicillin, and ticarcillin. Nalidixic acid is an older quinolone, while ampicillin and ticarcillin belong to the β-lactam family, a broad group that includes many drugs used against urinary and other bacterial infections. Resistance to these agents can reflect both long-standing antibiotic selection and the spread of bacterial lineages carrying multiple resistance genes.
The study also detected extended-spectrum β-lactamase production in 35.3 percent of the isolates. ESBLs are enzymes that break down a wide range of β-lactam antibiotics, including many penicillin and cephalosporin drugs. Their presence is clinically important because ESBL-producing bacteria can remain resistant even when a physician selects an antibiotic that would ordinarily be effective against E. coli. The genes encoding these enzymes are often carried on plasmids, small DNA molecules that can move between bacteria. This mobility enables resistance traits to spread not only through bacterial reproduction but also through horizontal gene transfer, allowing unrelated organisms to acquire similar defences.
To explore these relationships, the researchers constructed a co-resistance network. In this model, each node represented an antibiotic, while the connections between nodes reflected the number of isolates simultaneously resistant to both drugs. A stronger connection indicated that resistance to two antibiotics frequently appeared in the same bacterial isolates. The resulting network was concentrated around nalidixic acid, ampicillin, and ticarcillin, suggesting that resistance to these drugs was not occurring independently. Instead, it may have been linked by shared genetic elements, common exposure to antibiotic classes, or the expansion of bacterial clones carrying several resistance determinants.
Network analysis offers a different perspective from a conventional resistance table. A table can show that a bacterium is resistant to one drug at a particular frequency, but it does not necessarily reveal which resistances travel together. When several antibiotic resistances are tightly connected, prescribing one drug may indirectly select for bacteria resistant to others if the same genetic package or bacterial lineage carries multiple traits. These patterns can help microbiologists and public-health teams identify priority combinations for surveillance. They may also support antibiotic stewardship by showing where unnecessary or poorly targeted prescribing could reinforce a broader resistance network.
The researchers further investigated whether age was associated with antimicrobial resistance using logistic regression, a statistical method that estimates how a potential factor changes the odds of an outcome. Their analysis indicated a positive relationship between patient age and resistance to fluoroquinolone antibiotics. Older patients may have greater cumulative exposure to antibiotics, more frequent healthcare contact, recurrent urinary infections, or medical conditions that increase the likelihood of colonisation by resistant organisms. The study also reported that females accounted for a higher proportion of cases, with 75.5 percent reported in the analysis. This is consistent with the well-established observation that women experience UTIs more often, partly because of anatomical factors that facilitate the movement of intestinal bacteria into the urinary tract.
The findings carry implications beyond a single laboratory or city. They reinforce the need for urine cultures and susceptibility testing when infections are recurrent, severe, or unlikely to respond to first-line treatment. They also underline the importance of antimicrobial stewardship programmes, which aim to ensure that antibiotics are prescribed only when necessary, at the correct dose, for the appropriate duration, and with the narrowest effective spectrum. Surveillance systems can track changing resistance patterns, while infection-control measures can reduce the spread of resistant strains in healthcare environments. The authors argue that addressing MDR urinary infections will require coordinated action involving clinicians, laboratories, public-health authorities, and international monitoring networks.
Because the investigation was conducted at one diagnostic laboratory and covered a six-month period, its results may not represent every patient or healthcare setting in India. Nevertheless, the large number of isolates and the integration of laboratory data with co-resistance network analysis provide a valuable warning. E. coli is adapting to the antibiotic environment created by modern medicine, and the appearance of resistance to several drugs within the same isolates narrows the margin for safe and effective treatment. The study’s message is clear: urinary infections cannot be managed sustainably through prescribing habits alone. Continued resistance surveillance, better diagnostic testing, responsible antibiotic use, and collaboration across regions will be essential to prevent common bacterial infections from becoming increasingly difficult to control.
Subject of Research: Multidrug-resistant Escherichia coli isolates causing urinary tract infections, antimicrobial resistance patterns, ESBL production, co-resistance networks, and age-associated resistance.
Article Title: Prevalence and co-resistance network analysis of multidrug-resistant Escherichia coli isolates from urinary tract infections, a cross-sectional study
Article References: Srijith, L., Sivakumar, V., Parameswaran, R. et al. “Prevalence and co-resistance network analysis of multidrug-resistant Escherichia coli isolates from urinary tract infections, a cross-sectional study.” BMC Infectious Diseases (2026).
Image Credits: AI Generated
DOI: 10.1186/s12879-026-14213-6
Keywords: Multidrug-resistant Escherichia coli, urinary tract infections, antimicrobial resistance, extended-spectrum β-lactamase, ESBL, co-resistance network, fluoroquinolone resistance, antibiotic stewardship, logistic regression.
