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Scientists Find New Weapon Against Superbug Behind Infant Deaths

Superbugs are resistant to the majority of antibiotics commonly used today.

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Indian scientists have found a new weapon in the battle against Acinetobacter strains, the superbugs of the modern hospital environment, notorious for infection outbreaks in hospitals and responsible for the maximum numbers of newborn deaths in India.

Strains belonging to the Acinetobacter baumannii group have been identified as pathogens in hospital-borne pneumonia (particularly ventilator-associated pneumonia), bloodstream infections, urinary tract infections, surgical site infections, and other types of wound infections.

A measure of the gravity of the situation can be garnered from the fact that A. baumannii (carbapenem-resistant strain) is included in the WHO’s list of antibiotic-resistant "priority pathogens" – a catalogue of 12 families of bacteria that pose the greatest threat to human health.

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Studies say that in the context of the worldwide threat of antimicrobial resistance (AMR), India’s condition is considered “more stark” than any other place, and neonatal infections form an important piece in the equation.

The Situation in India

Superbugs are resistant to the majority of antibiotics commonly used today.
Estimates show that 58,000 neonatal deaths are attributable to sepsis caused by drug-resistance to first-line antibiotics, each year.
(Photo: iStockphoto)

In India, as elsewhere in South East Asia, many interlinked factors—including overuse of antibiotics, limited clinical diagnostic and laboratory capacity, and poor infection control, hygiene, and sanitation—have contributed to the emergence and spread of AMR.

Estimates show that 58,000 neonatal deaths are attributable to sepsis caused by drug-resistance to first-line antibiotics, each year.

Although the attributable mortality of multidrug-resistant Acinetobacter infections is debatable, these infections are clearly associated with increased time on mechanical ventilation, in the ICU, and in the hospitals. This bacterium is responsible for maximum amount of neo-natal deaths in India. The choice of antibiotics depends on the kind of strains you encounter, including last resort antibiotics such as colistin.
Dr* Ranjana Pathania, Department of Biotechnology, IIT Roorkee

Clinical strains of A. baumannii can resist the action of all the prevalent antibiotics and such infections are often fatal. The introduction of new drugs has rather slowed down and on top of that, the bacterium’s ability to develop resistance rapidly, defeats the overall purpose of having new drugs. “Therefore, it is pertinent to identify novel drug targets to increase our arsenal against this pathogen,” Professor Pathania said.

This bacterium is rather clever. It can survive in dry and dehydrated conditions for long durations of time that help in its spread. But what makes it deadly is the multi-drug resistant form.
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Acinetobacter spp., especially those belonging in the A. baumannii group, are intrinsically resistant to many antimicrobial agents due to their selective ability to exclude various molecules from penetrating their outer membrane, according to the World Health Organization (WHO).

But exposure to broad-spectrum antimicrobial agents, especially third-generation cephalosporins, fluoroquinolones, and carbapenems triggers the bacterium to develop strategies to counter the assault of drugs. The emerging resistance to colistin (mostly among carbapenem-resistant A. baumannii strains) makes the choice of antibiotics for treatment extremely difficult.

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Is There a Way Around?

Superbugs are resistant to the majority of antibiotics commonly used today.
To find a way around rapid generation of resistance to drugs, scientists are targeting virulence factors.
(Photo: iStockphoto)

To find a way around rapid generation of resistance to drugs, scientists are targeting virulence factors, which are microbial components that can damage a susceptible host and help in establishment of disease or infection.

Professor Pathania’s group has identified Hfq, an RNA chaperone protein, as an important virulence factor in A. baumannii. Hfq is also linked to metabolism, drug resistance and stress tolerance in the species.

The study is published last month in the Journal of Biological Chemistry.

We found that this protein, unlike its homologs in other bacteria, is particularly long. This is because the end of the protein (it’s C-terminus) is unusual inthe sense that it is long. We conducted experiments by truncating this region and observed that this region is very important for functions of A. baumannii.
Dr Ranjana Pathania, Department of Biotechnology, IIT Roorkee

Professor Pathania and her team knocked out the protein in A. baumannii and found that the cells were not able to grow properly and were not able to establish infections in mice in the absence of the protein.

So it looks like the protein is a global regulator of lot of important processes for A. baumannii, including virulence, the pathogen’s or microbe’s ability to infect or damage a host. Since this protein controls a lot of pathways so it will be difficult for the bacteria to develop resistance against antibiotics,if molecules are developed against this protein.
Dr. Ranjana Pathania, Department of Biotechnology, IIT Roorkee

Her lab is now working towards developing molecules against the Hfq protein.

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Artificial Intelligence and Antimicrobial Resistance

Superbugs are resistant to the majority of antibiotics commonly used today.
It is important to address the challenge of AMR given its urgency and formidability.
(Photo: iStockphoto)

Commending Professor Pathania’s work, on the other end of the spectrum, clinician data-scientist Tavpritesh Sethi advocates Big-data, Artificial Intelligence and Machine Learning based solutions to address the challenge of AMR given its urgency and formidability.

“This can be envisioned at multiple levels including molecular, individual and community models,” said Sethi currently working with the Stanford University School of Medicine as a Visiting Assistant Professor.

Commending Professor Pathania’s work, on the other end of the spectrum, Tavpritesh Sethi, a clinician data-scientist, advocates Big-data, Artificial Intelligence and Machine Learning-based solutions to address the challenge of AMR given its urgency and formidability.

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While Big-data analytics and simulations have been a part of the standard toolkit of molecular experiments, the ongoing digitisation of healthcare now presents a unique opportunity to expand the scope of Big-data, machine learning and artificial intelligence to decision making in clinical and public health settings.

Sethi, is a faculty member at Indraprastha Institute of Information Technology Delhi and currently working with the Stanford University's School of Medicine as a Visiting Assistant Professor.

“For example, in our Artificial Intelligence based analysis of antimicrobial resistance in the pediatric ICU at All India Institute of Medical Sciences, New Delhi, we identify the drug-bug decision-network for guiding antimicrobial stewardship,” observed Sethi who leads a Big-data project supported by the Wellcome Trust/DBT India Alliance along with Professor Rakesh Lodha at the Department of Pediatrics at AIIMS.

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What is Antibiotic Stewardship?

Superbugs are resistant to the majority of antibiotics commonly used today.
It can be foreseen that in the near future antibiotic prescriptions will be assisted by algorithms operating in the context of molecular, patient, hospital and community level data.
(Photo: iStockphoto)

Antibiotic stewardship refers to a set of coordinated strategies to promote the judicious use of antimicrobial medications to enhance patient health outcomes, reducing resistance to antibiotics, and decreasing unnecessary costs.

Acinetobacter baumanii is a growing menace in the ICUs and indeed we find it is an important indicator of overall resistance in the ICU, said Sethi. They collaborated with Professor Arti Kapil from Department of Microbiology for obtaining patient-level antimicrobial susceptibility data.

Sethi and colleagues arrived at this conclusion because they enabled the Pediatric ICU with Big-data and Artificial Intelligence pipelines (set of actions that extract, collect, warehouse and draw insights) from patient data, that gets generated each second in the Pediatric ICU, for prediction of killer diseases such as sepsis and shock.

“It can be foreseen that in the near future antibiotic prescriptions will be assisted by algorithms operating in the context of molecular, patient, hospital and community level data. This could have far-reaching consequences by improving antimicrobial stewardship as the world is facing a real threat of entering the post-antibiotic era,” Sethi said.

(Sahana Ghosh is a microbiologist-turned-journalist. She writes on science and environment and is interested in science in remote areas.)

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