Antibiotic Design Strategy Overcomes Efflux-Mediated Resistance in Preclinical Study

Researchers headed by a team at King’s College London have developed a new way of designing antibiotics that could support the discovery of new treatments for drug-resistant infections.

Designed to overcome one of the ways bacteria escape antibiotic treatment, the Efflux Resistance Breaker (ERB) approach allows researcher to chemically redesign antibiotics so that they are less easily removed from the cells by bacterial efflux pumps. The technology could also help revive antibiotics that have lost effectiveness due to the evolution of efflux-mediated resistance.

Study lead Professor Khondaker Miraz Rahman, PhD, a professor of medicinal chemistry at King’s College London, said: “Antimicrobial resistance is rising, but the number of truly new antibiotics in development remains worryingly low. Our work shows that we can redesign antibiotics so they stay inside bacterial cells at higher concentrations and overcome resistance mechanisms that would normally make them ineffective. This approach could help us design better new antibiotics, but it could also help revive existing antibiotic classes that bacteria have learned to defeat.”

Rahman is senior author of the team’s published paper in Journal of Medicinal Chemistry, titled “Designing Antibiotics with Inherent Resistance to Efflux as a Strategy to Revive Discovery against Multidrug-Resistant Pathogens.”

Worldwide increase in antimicrobial resistance (AMR) is threatening new developments in antibiotics, the authors noted. “The development and approval of new antibiotics are currently being outpaced by the emergence of resistance to existing drugs, a trend that must be reversed to ensure the long-term effectiveness of antibiotics.”

Many bacteria use molecular pumps, known as efflux pumps, to push antibiotics out of the cell before the drugs can reach levels high enough to kill them. This reduces the amount of antibiotic inside the bacteria and allows resistant infections to survive. Previous strategies have tried to combine antibiotics with separate efflux pump inhibitors (EPIs), the team continued. “Efflux pump inhibitors (EPIs) have been pursued as adjunct therapies to safeguard approved antibiotics prone to efflux-based resistance.” However, no EPI has yet been approved. “As well as a lack of mechanistic insight and biochemical information regarding efflux pumps, we opine that this failure is rooted in a fundamental flaw in the EPI-antibiotic combination approach: that the antibiotics remain unmodified substrates and can be effluxed by different pumps despite the presence of EPIs,” the authors noted.

The study by Rahman and colleagues has now shown that antibiotics can be chemically redesigned so they are less easily removed by these pumps. Their approach builds resistance-breaking properties directly into the antibiotic molecule, meaning that the antibiotic is designed to protect itself from being pumped out, allowing it to remain inside the bacterial cell at higher concentrations, and so restoring its ability to kill bacteria even when resistance mechanisms are present.

Importantly, the work shows that the ERB approach could support a new way of developing antibiotics by building resistance-breaking properties directly into their design. In their reported study the team developed ERB-modified fluoroquinolones and demonstrated their effectiveness against multiple bacterial pathogens, and in mouse infection models. The study provides an important proof of concept for antibiotic discovery, showing that maintaining high intracellular antibiotic concentration can help overcome resistance, including in bacteria that already show reduced susceptibility to existing antibiotics. “This study demonstrates that ERB modification enhances intracellular accumulation, reduces efflux susceptibility, and preserves antibacterial potency, as supported by complementary mechanistic, biochemical, and in vivo evidence,” the scientists concluded.

Added J. Mark Sutton, PhD, at the UK Health Security Agency, a key collaborator on this project, “Efflux pumps are a major cause of antibiotic resistance because they reduce the concentration of drug inside the bacterial cell. This study shows that rational chemical design can be used to overcome that problem. By building efflux resistance directly into the antibiotic, we may be able to restore activity against bacteria that are no longer controlled by current drugs.”

The researchers believe the ERB platform could be used as a general strategy to design antibiotics with built-in resilience to efflux-mediated resistance. Their team describes the ERB technology as a framework for developing next-generation antibiotics and for revitalizing existing drugs. “Beyond revitalizing existing drugs, ERB technology provides a general framework for designing next-generation antibiotics with built-in resilience to efflux-mediated resistance at the earliest stages of discovery,” they stated.

The team says it will work towards commercializing the ERB technology and advancing antibiotics developed using this strategy towards clinical development, with the aim of translating this discovery into new treatment options for drug-resistant infections.

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Wearable- and Mobile App–Based Activity Pacing and Fatigue Management in Post–COVID-19 Condition: Exploratory Observational Study

<strong>Background:</strong> Post–COVID-19 fatigue affects millions worldwide; yet, evidence-based management strategies remain limited. Activity pacing, regulating activity to match available energy and minimize symptom exacerbation, may support symptom management, although optimal pacing approaches remain unclear. <strong>Objective:</strong> This study aimed to explore associations between activity pacing strategies delivered through a mobile app and daily fatigue levels in individuals with post–COVID-19 fatigue. <strong>Methods:</strong> In this exploratory observational study, 19 adults with post–COVID-19 fatigue used wearable devices (Fitbit Inspire 3) for objective activity monitoring and a mobile app (FatigueSense) to self-report daily symptoms (fatigue and energy levels) and optionally select activity pacing goals (light, balanced, or active) over a period of 3 months. We examined associations between pacing strategies and symptom outcomes by using mixed-effects linear models with random intercepts. Same-day outcomes (fatigue and energy reported on the day of goal selection) were analyzed controlling for age and sex. Next-day outcomes (fatigue and energy reported the day following goal selection) were analyzed controlling for age, sex, and prior-day symptoms. <strong>Results:</strong> Across 2182 observation days, participants self-selected pacing goals on 816 (37.4%) days, demonstrating symptom-responsive behavior with higher baseline fatigue on pacing days (mean score 1.74, SD 0.59 vs 1.58, SD 0.54 on nonpacing days on a 0-3 scale where 0=“none” and 3=“severe”; <i>P</i>=.004). On pacing days (584/816, 71.6% with complete data from 18 participants), active pacing was associated with reduced same-day fatigue (β=−0.34, 95% CI −0.49 to −0.19; <i>P</i>&lt;.001) and increased same-day energy (β=8.8, 95% CI 4.7-12.9; <i>P</i>&lt;.001) compared to light pacing. Balanced pacing also showed significant reductions in fatigue (β=−0.15; <i>P</i>=.008) and increases in energy (β=5.8; <i>P</i>&lt;.001) compared to light pacing. Next-day effects were attenuated and nonsignificant (fatigue: β=−0.05, <i>P</i>=.53; energy: β=1.1, <i>P</i>=.61). Individual heterogeneity was substantial, with an intraclass correlation coefficient of 0.32, indicating that 32% of the variance was attributable to between-person differences. Among participants trying multiple strategies, 58.3% (7/12) showed meaningful responses (≥0.3-point fatigue reduction) to structured pacing strategies. <strong>Conclusions:</strong> Structured activity pacing strategies (active and balanced) were associated with improved same-day symptom management in individuals with post–COVID-19 fatigue. However, substantial confounding by indication (self-selection of pacing based on symptom state) and individual heterogeneity limit causal interpretation. These exploratory findings warrant testing in randomized controlled trials to establish efficacy and identify responder characteristics. <strong>Trial Registration:</strong>

Illumina Announces MRD Kit Ahead of ASCO Meeting

Ahead of the American Society of Clinical Oncology (ASCO) Annual Meeting in Chicago, kicking off this weekend, Illumina has announced a new molecular residual disease (MRD) product. The distributed kit enables solid tumor MRD and blood cancer genomic profiling and, the company says, will enable more labs to adopt MRD detection for clinical research.

It is the first in a new portfolio of WGS oncology research offerings, with additional solutions in development leveraging the latest advancements of the NovaSeq X. Illumina’s MRD research solution is available today for early access to select partners and will launch for global customers next year.

“In precision healthcare, early and accurate detection of molecular residual disease is critical to monitoring patients during and after cancer treatment,” said Todd Christian, senior vice president of Services, Arrays, and Genomic Access at Illumina. “Illumina’s MRD solution for clinical research leverages the advanced sensitivity of whole-genome sequencing, coupled with unparalleled analysis, to enable our customers to more easily deliver the most precise information to advance MRD research. We aim to make WGS in oncology more accessible and scalable to support the integration of precision solutions into the standard of care.”

The MRD solution supports fingerprinting through solid tumor samples, and MRD detection using blood samples, all compatible on NovaSeq Systems. The end-to-end research workflow can be completed in as fast as five days and is optimized for analytical sensitivity as low as 10 ppm, particularly important for early-stage and low-shedding tumors, including breast, ovarian, and renal.

Illumina’s DRAGEN MRD analysis connects each fingerprint to serial circulating tumor DNA (ctDNA). The new MRD solution has been optimized across thousands of samples to develop and demonstrate a ctDNA detection algorithm with 99.5% analytical specificity to distinguish true tumor signals from background noise.

Mayo Clinic evaluated the solution on a small sample cohort and found high concordance among previously characterized paired samples. The results were also highly correlated with clinical and imaging results over time. The team is planning to expand the cohort for additional research with Mayo Clinic and other academic partners.

“We are looking forward to participating in early access and evidence generation for a tumor-informed, non-bespoke whole-genome sequencing approach to MRD,” said Gang Zheng, MD, PhD and professor of Laboratory Medicine and Pathology at Mayo Clinic. “We have seen early pilot results across several solid tumor clinical samples that demonstrated the potential utility of highly sensitive solid tumor MRD detection, and we continue to pilot technologies that help us efficiently progress in our ability to analyze and translate complex genomic arrays.”

Built on recently announced NovaSeq X advancements, including 35B output and Q70 quality scores, a complementary research workflow that will deliver ultra-sensitive MRD detection in the single-digit ppm range leveraging duplex reads is currently in development.

Illumina’s new oncology portfolio builds upon the integrated ecosystem of workflows, data and community across genomic, multiomic, and clinical research applications—anchored on the NovaSeq X.

Illumina and Bristol Myers Squibb will jointly present a poster at the 2026 American Society of Clinical Oncology (ASCO) Annual Meeting on Sunday, May 31, from 9:00 a.m. to 12:00 p.m. (abstract ID 8591, poster board #381, Lung Cancer: Non–Small Cell Metastatic track).

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Machine Learning–Based Prediction Model for 30-Day Emergency Department Revisits in a Medically Underserved Tertiary Hospital: Formative Retrospective Cohort Study

Background: Emergency department (ED) revisits are critical quality indicators, particularly in medically underserved areas, where traditional prediction tools show limited performance. Machine learning (ML) approaches may offer improved predictive performance for identifying high-risk patients. Objective: This formative study aimed to develop and validate an ML-based model for predicting 30-day ED revisits using electronic health records from a tertiary hospital serving a medically underserved area in South Korea and to evaluate its clinical utility through interpretability analysis and risk stratification. Methods: This retrospective cohort study analyzed 36,230 adult patients visiting the Gangneung Asan Hospital ED in 2023. We developed and compared 3 ML models (extreme gradient boosting [XGBoost], random forest, and ElasticNet) using electronic health records. Model interpretability was ensured through Shapley additive explanations (SHAP) analysis, and clinical utility was evaluated through 5-tier risk stratification. Results: Among 36,230 patients, 798 (2.2%) revisited within 30 days. XGBoost achieved superior performance with an area under the receiver operating characteristic curve of 0.90 (95% CI 0.88‐0.92), a sensitivity of 0.94, and a specificity of 0.69. The SHAP analysis identified ED length of stay, oxygen saturation, systolic blood pressure, computed tomography performance, antibiotic use, and liver disease as key predictors. Risk stratification demonstrated a 25-fold difference in the actual revisit rates between the lowest (152/8450, 1.8%) and the highest (686/1500, 45.7%) risk groups. Conclusions: The XGBoost model demonstrated excellent predictive performance with high interpretability for 30-day ED revisit predictions. The implementation of this model could enable risk-stratified interventions and more efficient resource allocation in medically underserved settings, potentially reducing unnecessary revisits and improving patient outcomes. This formative study establishes feasibility and provides a foundation for future multicenter validation studies in similar medically underserved settings.
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Neuronal Protein Tracing Reveals How the Brain Routes Its Waste

The brain is one of the busiest organs in the body, constantly processing and reshaping itself. That activity produces an equally constant stream of molecular byproducts—proteins that need to be moved out before they accumulate. When those clearance routes slow or break down, waste lingers, and the consequences can be profound. In Alzheimer’s disease, for example, toxic proteins build up in vulnerable regions. Yet despite decades of research, scientists have lacked a clear view of how waste normally leaves the brain.

A new study from the Gladstone Institutes offers the clearest picture yet of how the brain normally takes out its trash—and what happens when those routes fail. Published in Cell as “Physiological brain clearance architecture revealed by neuronal protein tracing,” the work introduces a method that traces waste proteins from the moment they are produced inside neurons to the moment they leave the brain.

For decades, researchers have relied on injecting tracers into the cerebrospinal fluid (CSF) to visualize drainage. But this approach, while illuminating, shows all possible routes, instead of pinpointing the most-used exit. “These injected tracers disturb the very system we’re attempting to measure,” said lead author Andrew Yang, PhD, a Gladstone investigator. “We wanted to find a better way.”

Yang’s team engineered neurons in mice to produce a fluorescent protein, ZsGreen, that could be followed as it exited the brain through its natural routes. This allowed the researchers to track waste as it moved into the dura, skull, nasal cavity, and lymph nodes—regions populated by specialized immune cells that interact with brain‑derived proteins.

The resulting map diverged sharply from the field’s long‑held assumptions. Traditional CSF tracers had pointed to the cervical lymph nodes as a major drainage site. But the new method revealed that very little neuronal waste actually reaches those nodes. “We were surprised to find that very little ZsGreen drained to the cervical lymph nodes,” Yang said. “Instead, waste drained through the dura, skull, and nasal cavity. Our findings underscore why tracking waste proteins themselves, rather than movement of the cerebrospinal fluid, provides a more accurate understanding of waste clearance dynamics.”

The team also uncovered a striking organizational principle: where a protein is made determines where it drains. Proteins produced in upper forebrain regions exited through upper routes, while those from deeper structures, such as the striatum, used lower pathways. The researchers call this the brain’s “nearest‑exit” model. “It’s like each brain region has a biological ZIP code system to ensure waste will be sent to the correct drainage site,” said Nalini Rao, PhD, a postdoctoral fellow. She noted that in aging or disease, these ZIP codes may become scrambled, potentially explaining why certain regions are more vulnerable to disorders like Alzheimer’s.

Disease models reinforced the system’s fragility. In mice with acute inflammation, ZsGreen leaked directly into the bloodstream, bypassing normal routes. In an Alzheimer’s model, waste became trapped inside the brain, unable to drain effectively. “Understanding how diseases disrupt brain clearance could help us design therapeutics to target the brain border compartments and enhance waste removal,” Rao said.

With their new tracing method, Yang’s group plans to probe how clearance changes across aging, sleep, and disease—and whether brain tumors exploit these pathways to evade immune detection. The architecture of brain waste disposal, once opaque, is now open for exploration.

The post Neuronal Protein Tracing Reveals How the Brain Routes Its Waste appeared first on GEN – Genetic Engineering and Biotechnology News.

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Kenya court suspends U.S. plan for Ebola quarantine facility for Americans

NAIROBI, Kenya — A court in Kenya on Friday suspended a U.S. plan to establish a quarantine facility for Americans exposed to a rare type of Ebola virus spreading in northeastern Congo, following a backlash by medical workers and activists.

A U.S. administration official said on Wednesday that the U.S. was planning to send Americans who are exposed to Ebola while abroad to a new facility in Kenya instead of flying them home. The official spoke on condition of anonymity to share the administration’s plans. It was unclear where in Kenya the new facility will be built or whether the Kenyan government has signed off on the plan.

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