The immediate trigger for the correspondence is a randomized, single-blind trial by Millot and colleagues, published in the same journal, that evaluated a strategy using multiplex PCR for targeted antibiotic therapy in patients with suspected ventilator-associated pneumonia or hospital-acquired pneumonia requiring mechanical ventilation. The trial is one of the most direct tests to date of whether syndromic molecular panels can change what clinicians actually prescribe. Its findings, alongside earlier randomized data, form the backdrop against which the Reims team frames its argument about the gap between diagnostic speed and therapeutic action.

The technical logic behind multiplex PCR panels is straightforward. Platforms such as the FilmArray Pneumonia Panel extract nucleic acids from endotracheal aspirates or bronchoalveolar lavage fluid and amplify targets for a broad battery of bacterial and viral pathogens, together with key resistance determinants. Compared with conventional culture, which requires 24 to 72 hours before organisms can be identified and susceptibility tested, the molecular route delivers a pathogen profile within about an hour of sample processing. In principle, this should allow intensivists to narrow empirically broad regimens earlier, escalate when unexpected pathogens appear, or stop antibiotics altogether when no bacterial target is detected.

Randomized evidence, however, has painted a more nuanced picture. The Poole and colleagues trial published in the Journal of Infection in 2022 showed that molecular point-of-care testing for lower respiratory tract pathogens improved safe antibiotic de-escalation in ICU patients with pneumonia, a genuine stewardship gain. More recently, the INHALE WP3 trial, a multicentre, open-label, pragmatic randomized controlled trial led by Enne and colleagues and published in Intensive Care Medicine in 2025, assessed the impact of rapid, ICU-based, syndromic PCR against standard-of-care on antibiotic stewardship and clinical outcomes in hospital-acquired and ventilator-associated pneumonia. That study found effects on antibiotic use that were real but modest, and it did not translate into the kind of dramatic clinical improvements that the technology’s advocates had hoped for.

The central paradox highlighted by Goury and colleagues is that the speed of a diagnostic result is meaningless unless it is embedded in a workflow that converts information into action. A PCR result that lands in the electronic medical record at three in the morning, or that reaches a covering physician without clear guidance on how to interpret it, may simply sit unread until the morning round, by which point the theoretical time advantage has evaporated. The correspondence argues that the bottleneck in ventilator-associated pneumonia management is not analytical turnaround time but the human and organizational steps that follow: result notification, interpretation, and the willingness of clinicians to act on molecular data in the absence of conventional culture and susceptibility confirmation.

Interpretation itself is far from trivial. Multiplex panels detect nucleic acids, not necessarily viable, disease-causing organisms, so positive results must be weighed against colonization, which is extremely common in mechanically ventilated patients. Quantitative thresholds offered by some panels attempt to distinguish infection from colonization, but their performance in the critically ill population remains imperfect. Conversely, a negative panel does not exclude all pathogens, because the panels cover a defined target list. Berteau and colleagues, in a retrospective multicentre analysis published in Annals of Intensive Care in 2025, examined the epidemiology and prediction of bacteria not targeted by the FilmArray Pneumonia Plus panel in culture-positive ventilator-associated pneumonia, underscoring that a meaningful fraction of causative organisms can fall outside the panel’s detection range. Clinicians who understand these limitations may reasonably hesitate to de-escalate on the basis of a single molecular result.

Resistance gene detection adds another layer of complexity. Panels report markers such as those associated with methicillin resistance in staphylococci or extended-spectrum beta-lactamase production in enterobacterales, but the genotype-phenotype relationship is incomplete. A negative resistance result does not guarantee susceptibility to narrower agents, particularly in organisms with diverse and evolving resistance mechanisms. For intensivists trained to treat the sickest patients with the broadest initial coverage, the perceived medico-legal and clinical risk of narrowing therapy on incomplete molecular information can outweigh the theoretical benefits, leading to what the correspondence implicitly identifies as the core failure mode: results that are available quickly but are not acted upon quickly.

Prior experience during the COVID-19 pandemic illustrates both the potential and the pitfalls. Novy and colleagues described an algorithm for the rational use of the FilmArray Pneumonia panel in bacterial coinfections of critically ill ventilated COVID-19 patients, published in Diagnostic Microbiology and Infectious Disease in 2021. Their work emphasized that the value of the panel depends on disciplined, protocolized interpretation rather than on the raw speed of the assay. Where such algorithms exist and are enforced, molecular results can meaningfully shape therapy; where they are absent, the same results risk becoming an expensive add-on that changes little at the bedside.

The Reims group is not a disinterested observer of this debate. The correspondence discloses that the corresponding author, Antoine Goury, is the coordinating investigator of the VAMPAIR trial, an ongoing randomized study registered with the French medicines agency ANSM under identifier 2024-A00908-39 and sponsored by CHU de Reims, which is evaluating multiplex PCR in ventilator-associated pneumonia. This positioning suggests that the correspondence is intended less as a rejection of molecular diagnostics than as a design brief for the next generation of studies: trials that measure decision latency, antibiotic duration, and patient-centered outcomes rather than turnaround time alone, and that build prespecified de-escalation rules directly into the diagnostic pathway.

The broader lesson for intensive care is that diagnostic innovation succeeds only when it is matched by therapeutic governance. Rapid syndromic PCR in ventilator-associated pneumonia can shorten the time to pathogen identification, support safe de-escalation in selected settings, and reduce unnecessary broad-spectrum exposure, but the randomized evidence to date shows that these benefits are contingent on workflow integration, clinician education, and honest accounting of the panels’ blind spots. As Goury and colleagues conclude, faster results are a necessary but not sufficient condition for faster decisions; closing the gap between the two is now the central challenge for molecular diagnostics in the ICU.

Subject of Research: Rapid molecular diagnostics and antibiotic decision-making in ventilator-associated pneumonia

Article Title: Rapid molecular diagnostics in VAP: when faster results do not mean faster decisions

Article References: Rapid molecular diagnostics in VAP: when faster results do not mean faster decisions. (n.d.). https://doi.org/10.1007/s00134-026-08631-y

Image Credits: AI Generated

DOI: 10.1007/s00134-026-08631-y

Keywords: ventilator-associated pneumonia, multiplex PCR, rapid diagnostics, antibiotic stewardship, intensive care, de-escalation, resistance genes, FilmArray pneumonia panel, randomized controlled trial, ICU workflow, hospital-acquired pneumonia, molecular point-of-care testing

The review, conducted by Emmanuel Kaboja Magna of the University of Environment and Sustainable Development in Somanya, Ghana, followed the PRISMA framework for systematic reviews. The initial search identified 1,246 records from databases including Scopus, Web of Science, PubMed and Google Scholar, supplemented by reports from the World Health Organisation, the United Nations Environment Programme, the Ghana Environmental Protection Agency and the Food and Agriculture Organisation. After rigorous screening, 46 studies met the inclusion criteria, of which 21 were judged high quality, 18 moderate and 7 low. Where methodologies were comparable, 32 studies were pooled into a quantitative synthesis. Concentration values reported in different units were standardised to allow comparison across water, sediment, soil and waste matrices.

The headline numbers are striking. Hospital effluents in Sunyani contained amoxicillin at concentrations reaching 8,760 micrograms per litre, alongside ciprofloxacin at 4,740 micrograms per litre and doxycycline at 2,930 micrograms per litre, figures the review describes as among the highest environmental antibiotic concentrations reported globally. In Kumasi, leachate from the Dompoase landfill recorded penicillin concentrations as high as 67,420 micrograms per litre, a level approaching therapeutic doses. For context, published predicted no-effect concentrations for resistance selection in aquatic environments are around 0.25 micrograms per litre for amoxicillin and 0.064 micrograms per litre for ciprofloxacin. The Ghanaian effluent values therefore exceed these thresholds by tens of thousands of times, indicating that untreated pharmaceutical waste is being discharged directly into the environment.

Three urban hotspots emerge consistently from the evidence: Kumasi, Sunyani and Sefwi Wiawso. These cities combine intensive healthcare activity, high population density, widespread pharmaceutical consumption and inadequate wastewater treatment infrastructure. In Sefwi Wiawso, ciprofloxacin concentrations in dumpsite soils ranged from 2,140 to 4,060 micrograms per kilogram, while antibiotic-related compounds reached 670 micrograms per litre in water samples. The review attributes these patterns to a combination of continuous source loading, leachate infiltration into organic-rich soils, and episodic runoff into receiving waters. Poorly engineered landfills that lack containment systems allow contaminants to migrate into groundwater and surface water, turning municipal waste sites into continuous secondary sources of pollution.

Yet contamination is not confined to these hotspots. A comprehensive 118-kilometre transect study of the Lower Volta River, one of Ghana’s most critical freshwater resources, detected antibiotics at every sampled location, generally in the low nanogram-per-litre range, together with antibiotic resistance genes. The authors of that study also found per- and polyfluoroalkyl substances, or PFAS, in the same system, highlighting the co-occurrence of multiple classes of emerging contaminants. In fish farms on the Lower Volta Lake, antibiotics including ciprofloxacin, sulfamethoxazole, sulfadiazine, chlortetracycline and tetracycline were measured at concentrations up to 9.14 micrograms per litre in farm waters, with residues also detected in fish tissues. Even the Owabi and Barekese reservoirs, which supply drinking water, contained antibiotics at levels between 0.06 and 36.51 micrograms per litre, suggesting incomplete removal during water treatment.

The review also exposes a technical weakness in Ghana’s monitoring capacity. Among the principal residue-monitoring studies with identifiable analytical platforms, 62.5 per cent relied on high-performance liquid chromatography with ultraviolet or diode-array detection, methods that are accessible but less sensitive than mass spectrometry. Only 25 per cent used tandem mass spectrometry, which offers superior sensitivity and the ability to quantify many compounds simultaneously. The review cautions that differences in reported concentrations, and even some non-detections, may partly reflect analytical performance rather than genuine differences in contamination. Greater adoption of validated multi-residue LC-MS/MS methods, harmonised sampling protocols and consistent reporting of detection limits and recoveries would substantially strengthen the reliability of environmental monitoring.

The public health consequences flow through several pathways. Humans are exposed through contaminated drinking water, the consumption of fish and vegetables grown with polluted irrigation water, occupational contact and recreational use of polluted water bodies. More alarmingly, the review documents antibiotic-resistant bacteria and resistance genes across rivers, reservoirs, drinking water systems and sediments. Urban rivers such as the Odaw and Okurudu carry especially high resistance burdens, including extended-spectrum beta-lactamase-producing Escherichia coli. Warm temperatures, high organic loading and dense microbial populations in tropical aquatic systems favour horizontal gene transfer through conjugation, transformation and transduction, mechanisms that allow resistance genes to spread rapidly between bacterial species. Mobile genetic elements associated with carbapenem and aminoglycoside resistance have been detected in Ghanaian hospital and urban wastewater systems, underscoring the potential for environmental resistance to reach clinical settings.

Ecologically, the picture is equally concerning. Antibiotic contamination alters microbial community structure, disrupts nutrient cycling and organic matter decomposition, and may reduce microbial diversity in heavily impacted receiving environments. Aquatic ecosystems face risks to phytoplankton productivity, food-web dynamics and fish health, while sediments and soils act as long-term reservoirs that can prolong impacts even after direct discharges decline. In terrestrial systems, disruption of beneficial soil organisms such as nitrogen-fixing bacteria and mycorrhizal fungi could undermine soil fertility and agricultural productivity. Compound chemistry shapes where these effects concentrate: strongly sorbing fluoroquinolones like ciprofloxacin accumulate in soils and sediments, whereas more hydrophilic sulfonamides remain mobile in water.

The sources of this pollution are diverse. Hospitals discharge wastewater containing unmetabolised antibiotics and resistant bacteria, often without specialised treatment. Households discard expired medicines with domestic refuse, and over-the-counter access to antibiotics compounds the problem. In agriculture and aquaculture, antibiotics are used not only to treat disease but also to promote growth, with residues excreted in partially metabolised form and entering soils and waterways through manure and medicated feed. Pharmaceutical manufacturing may add localised industrial discharges, though empirical evidence in Ghana remains limited. The review notes that these patterns mirror those seen elsewhere in sub-Saharan Africa, with river sediments in Kenya reaching 4,125 micrograms per kilogram and Lake Victoria sediments in Uganda up to 130 micrograms per kilogram, suggesting a regional crisis driven by rapid urbanisation and weak regulatory enforcement.

Addressing the problem, the review concludes, will require coordinated national action spanning environmental monitoring, pharmaceutical waste management, wastewater treatment upgrades, antimicrobial stewardship and regulatory reform. Ghana’s current framework is fragmented, with overlapping responsibilities among the Environmental Protection Agency, the Food and Drug Administration and the ministries of health and agriculture, and no specific permissible limits for most pharmaceuticals in wastewater or surface waters. The review recommends specialised pharmaceutical waste treatment in hospitals, take-back programmes for unused medicines, engineered landfills, veterinary oversight and antibiotic stewardship in farming. Advanced treatment technologies such as activated carbon adsorption, membrane bioreactors and advanced oxidation processes show promise but are costly, so nature-based alternatives like constructed wetlands and algae-based treatment may offer more sustainable options. Above all, long-term surveillance programmes that integrate chemical monitoring with antimicrobial resistance tracking are essential to identify emerging hotspots and guide evidence-based policy before environmental reservoirs of resistance further erode the effectiveness of life-saving antibiotics.

Subject of Research: Antibiotic residue contamination and antimicrobial resistance in Ghanaian environmental systems

Article Title: Antibiotic residues in Ghanaian environmental systems: sources, distribution patterns, and public health implications

Article References: Magna, E. K. (2026). Antibiotic residues in Ghanaian environmental systems: sources, distribution patterns, and public health implications. Discover Chemistry, 3(1), Article 498. https://doi.org/10.1007/s44371-026-00955-4

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00955-4

Keywords: antibiotic residues, Ghana, antimicrobial resistance, hospital effluents, landfill leachate, water pollution, pharmaceutical pollution, systematic review, aquaculture, resistance genes, wastewater treatment, environmental monitoring

The study, led by soil ecologist Franciska de Vries of the University of Amsterdam together with colleagues across Europe, set out to answer a question that had largely been overlooked. Much of the existing literature assumes that climate change will gradually accelerate the spread of antibiotic resistance genes in the environment, as warmer and wetter conditions favour microbial growth and the exchange of genetic material. But climate change does not arrive only as a slow, steady warming. It also delivers sudden shocks: heatwaves, droughts, floods and freeze-thaw cycles that hit ecosystems with little warning. What those abrupt extremes do to the resistance repertoire of soils was, until now, poorly understood.

De Vries explains that many people simply do not realise how important soils are as reservoirs of both antibiotics and resistance genes. Most of our antibiotic classes were originally discovered in soil-dwelling microorganisms, and the same soils harbour an enormous diversity of genes that confer resistance to those compounds. In the soil, she notes, a kind of war is constantly underway: bacteria produce antibiotics and simultaneously defend themselves against them with resistance genes. Understanding how climate disturbances perturb this equilibrium is therefore not an abstract ecological curiosity but a question with direct implications for public health.

The research unfolded in two phases. In the first, the team wanted to establish a general picture of how soil organisms respond to extreme weather. Soils, De Vries points out, perform functions that society depends on, not least the sequestration of carbon dioxide from the atmosphere. If extreme events impair those functions, the consequences extend far beyond the microbial community. To probe this, the researchers collected soils from across the breadth of Europe, from Iceland to Greece and from Sweden to Spain, and even from the Russian steppe. The samples were then subjected to a battery of simulated extremes in climate chambers: severe drought, flooding, alternating frost and thaw, and a short but intense heatwave.

One of the most striking results of this first phase was how predictable the responses turned out to be. The researchers could forecast, with considerable accuracy, how a given soil would react to a given extreme. The logic, De Vries says, is quite straightforward: hot soils can withstand heat better than cold and wet soils of the kind found in Sweden, Iceland and the Netherlands. Soils from warm, dry countries are already accustomed to heat and drought, and their communities of bacteria and fungi remain relatively stable even when conditions turn extreme. In cold, wet soils, by contrast, the organisms are disrupted far more quickly. Those soils lose their functions, such as carbon storage, more easily under heat and drought, and it is precisely these historically cool, damp regions that are warming most rapidly. The Netherlands, with its wet climate and accelerating heat extremes, exemplifies the vulnerability.

With that foundation in place, the team moved to the second phase, a new collaboration employing fresh DNA techniques to ask a sharper question: what do these extreme conditions do to the type and quantity of antibiotic resistance genes in soils, and are those effects also predictable? The answer differed sharply depending on the kind of extreme. Droughts, floods and freeze-thaw periods caused only mild changes in the resistance repertoire, and those changes were reasonably predictable from climate and soil type. The microbial communities bent under the stress but did not fundamentally alter their genetic defences.

Heatwaves were another matter entirely. Of all the extremes tested, heatwaves produced the least predictable responses, and the bacteria visibly struggled. According to De Vries, under heatwave conditions the bacteria exchange fewer resistance genes and produce fewer antibiotics. That was very surprising, she says: just like plants, the microorganisms go into survival mode. And crucially, after the extreme has passed, those genes do not grow back quickly. The temporary suppression of the resistance repertoire is not a rapid rebound; the microbial community needs time to rebuild its arsenal of antibiotics and defensive genes once temperatures return to normal.

Geography, it turned out, was the single most important indicator of how a soil’s resistance genes respond to extremes. Where the soil comes from, De Vries explains, matters more than what extreme weather is unleashed upon it. Wet soils find it much harder to cope with drought and heat, whereas the researchers observed much larger quantities of resistance genes in countries such as Greece and Spain. This means that the baseline climate of a region, rather than the specific disturbance it experiences, largely determines both the size of the resistance gene pool and the way it shifts under stress. For modellers and risk assessors, that is a valuable simplification: knowing where a soil is from tells you a great deal about how it will behave.

At first glance, the headline finding might sound like a rare piece of good news about climate change. If heatwaves temporarily reduce the number of resistance genes circulating in soils, could extreme heat actually help contain the environmental reservoir of antibiotic resistance? De Vries is emphatic that this interpretation would be a mistake. The same heat and drought that suppress the resistance genes are simultaneously causing significant damage to soils and ecosystems, degrading functions such as carbon sequestration and disrupting communities that took millennia to assemble. A short-lived dip in resistance gene abundance does nothing to remove the underlying health risks of antibiotic resistance, which remain a global concern regardless of what the weather does. The dip is a symptom of microbial distress, not of a safer environment.

What the study does offer is a clearer map of where the risks actually lie. As De Vries concludes, we now know that climate extremes do not always affect antibiotic resistance in the same way, and that knowledge makes it easier to predict where the real risks are concentrated and to tailor policy and monitoring to particular soils and regions. Warm, dry soils with naturally high resistance gene loads may need different surveillance than cold, wet soils that are newly exposed to heat extremes they have never evolved to tolerate. The research, published in the Proceedings of the National Academy of Sciences as an experimental study, thus reframes the conversation about climate change and antibiotic resistance: the relationship is neither uniformly negative nor uniformly benign, but contingent on geography, soil history and the character of the disturbance. In the hidden war beneath our feet, the weather decides when the fighting pauses, but the landscape decides who is fighting in the first place.

Subject of Research: The effects of extreme climatic events on antibiotic resistance genes in European soils

Article Title: Heatwaves inhibit antibiotic resistance in soils, but at a price

Article References: Heatwaves inhibit antibiotic resistance in soils, but at a price. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: antibiotic resistance, soil bacteria, heatwaves, climate extremes, soil ecology, resistance genes, drought, carbon sequestration, University of Amsterdam, Europe, PNAS, microbiology

The timing of this warning could hardly be more significant. Wastewater-based surveillance earned its reputation during the COVID-19 pandemic, when measurements of SARS-CoV-2 RNA in sewage proved to be a leading indicator of clinical case waves across cities and continents. That success spawned an entire discipline, and models such as the wastewater-based epidemic model developed for SARS-CoV-2 in three Canadian cities demonstrated that, under the right conditions, gene copy concentrations in influent sewage could be translated into estimates of infected individuals in a catchment. The European Union has since embedded wastewater surveillance into law through the recast Urban Wastewater Treatment Directive of 2024, and the European Centre for Disease Prevention and Control has published a framework for integrating wastewater data into infectious disease surveillance at the EU level. Antimicrobial resistance is now a priority target of these systems.

Yet the Cyprus-based authors argue that the epidemiological machinery that made viral surveillance interpretable does not yet exist for resistance. For viruses, researchers have invested heavily in quantifying shedding dynamics: how many genome copies an infected person excretes per gram of faeces, how those rates change over the course of infection, and how they differ between variants. Longitudinal studies of SARS-CoV-2, pepper mild mottle virus and crAssphage shedding, together with time-varying shedding models revisiting the 2013 poliovirus outbreak in Israel, have provided the conversion factors that turn a wastewater concentration into an approximate count of infected people. For antimicrobial resistance genes and resistant bacteria, no equivalent body of calibration data exists. The authors point out that faecal carriage of extended-spectrum beta-lactamase-producing Enterobacteriaceae in the general population, the duration of colonisation after international travel, and the effects of antibiotic exposure on the gut resistome are all documented in clinical studies, but these threads have never been woven into transfer functions that connect a gene abundance measured in sewage to a prevalence of carriage in the community above.

The technical reasons for this gap are formidable. A wastewater concentration is the product of a long and noisy chain of processes. It begins with the heterogeneous shedding of resistance determinants by carriers, which depends on the species of bacterium, the type of gene, whether the gene is carried on a chromosome or a plasmid, and whether it resides inside intact cells, in faecal particles, or as free extracellular DNA. It continues with in-sewer decay and partitioning, processes that have been characterised for pathogens such as Campylobacter jejuni and Campylobacter coli but that differ for every gene and microbe of interest. Hydraulic conditions, temperature, sewer biofilms and sediment resuspension all modulate what arrives at the sampling point. Sampling itself, whether flow-weighted composite or grab, introduces further uncertainty. By the time a sample reaches the laboratory, the signal is a composite whose relationship to the original biological state in the population is mediated by dozens of parameters, most of which are unknown for antimicrobial resistance.

Measurement technology compounds the problem. Quantitative metagenomics, which promises absolute quantification of resistance genes across thousands of loci simultaneously, is advancing quickly, and recent work has begun to establish detection limits for environmental monitoring of antibiotic resistance and for viruses. But the Cyprus team emphasises that analytical quantification is not the same as epidemiological calibration. A measurement can be perfectly reproducible and still be uninterpretable if nobody knows what concentration corresponds to what burden of carriage, what change in concentration corresponds to what change in incidence, or what effluent concentration corresponds to what environmental exposure risk. The authors describe this as quantifying variation without resolving biological states, a phrase that captures the epistemological core of their argument: surveillance data are being collected and compared, but the mapping from data to meaning remains undefined.

The downstream half of the problem, the effluent side, is equally under-calibrated. Wastewater treatment plants are known to substantially reduce the load of resistance genes and resistant bacteria leaving a catchment, with studies showing that extended-spectrum beta-lactamase and carbapenemase genes are substantially and sequentially reduced during conveyance and treatment of urban sewage. But removal efficiency varies enormously with treatment technology, capacity overloading, and the fate of intracellular versus extracellular DNA during processes such as ultrafiltration, ultraviolet disinfection and chlorination. Paradoxically, some disinfection steps may promote rather than reduce resistance spread: chlorine disinfection has been shown to facilitate natural transformation of bacteria through reactive oxygen species-mediated oxidative stress, and disinfection byproducts can increase transformation rates of environmental DNA in model organisms such as Acinetobacter baylyi. Without calibrated models of these processes, an effluent measurement cannot be translated into a statement about the resistance burden delivered to a receiving river, coastal water or irrigation system.

That environmental endpoint matters because the receiving environments are not passive sinks. Research along the wastewater-river continuum has documented the dissemination and persistence of antimicrobial resistance far downstream of discharge points. Treated wastewater irrigation has been shown to alter the resistance profiles of agricultural soils, subsoil pore-water and rhizospheres, while biofilms in reclaimed water distribution systems act as hot spots of horizontal gene transfer. Heavy metals such as copper accelerate the conjugative transfer of resistance genes in freshwater microcosms, and even herbicide selection can promote antibiotic resistance in soil microbiomes. Sludge and compost application to land introduces further pathways. Each of these environmental compartments hosts its own ecology of gene exchange, shaped by pH, soil type, moisture and microbial community composition. The authors argue that a calibrated surveillance framework must therefore serve two distinct interpretive goals simultaneously: translating influent signals into population-level epidemiological burden, and translating effluent signals into quantified risk of environmental introduction and subsequent exposure of humans, animals and crops.

The Perspective, illustrated with a conceptual overview of the calibration gap and a proposed calibration solution for interpreting epidemiological data and environmental introduction risk, does not merely diagnose the problem; it sketches what a solution would require. Drawing on the authors’ experience validating the national-scale SARS-CoV-2 surveillance system in Cyprus, and on emerging methods such as metagenomic absolute quantification with cellular internal standards and microbiome-based microbial risk assessment across multiple environments, they call for systematic studies that establish the missing transfer functions. These include quantifying shedding of resistance determinants by carriers in the community, characterising in-sewer and treatment-plant fate for priority genes and bacteria, and linking measured effluent concentrations to quantified exposure in receiving environments through models that account for dilution, decay, regrowth and gene transfer. Global comparative work, such as the exploration of human faecal and sewage resistomes as a function of socio-economic status, and metagenomic source attribution of resistance in wastewater, provides the kind of comparative baseline that calibration will ultimately require.

The stakes of getting this right are considerable. Antimicrobial resistance is one of the leading global threats to public health, and wastewater offers something clinical surveillance cannot: a continuous, catchment-wide, pathogen-agnostic signal that does not depend on patients seeking care or on laboratories reporting results. Wastewater surveillance has already revealed potential underreporting of disease cases in the Detroit area for Salmonella enterica, Campylobacter jejuni and norovirus, and has detected early introductions of the emerging fungal pathogen Candida auris in Utah. Small-scale wastewater-based epidemiology studies of antibiotic resistance are proliferating worldwide. But the Cyprus authors warn that without calibration, these signals risk being over-interpreted, with policy decisions made on the basis of numbers whose epidemiological and environmental meaning is unknown. Conversely, a properly calibrated system could convert routine sewage measurements into actionable estimates of community carriage prevalence and quantified environmental release, transforming wastewater plants from passive sentinels into genuine early-warning infrastructure.

The message of the Perspective is ultimately one of disciplined optimism. The raw ingredients for calibration already exist, scattered across clinical cohort studies of gut colonisation, environmental microbiology of sewers and treatment plants, and risk assessment frameworks developed for water reuse under EU Regulation 2020/741. What is missing is the deliberate, coordinated effort to assemble these ingredients into validated models, much as the viral surveillance community did in the years after 2020. The authors, writing with support from the SPORE-MED project under the PRIMA Programme and the EU-WISH joint action on integrated wastewater surveillance for public health, frame calibration not as an academic luxury but as the precondition for the next phase of the field. As regulators across Europe and beyond write antimicrobial resistance monitoring into wastewater law, the question they pose is blunt: a signal is only as valuable as the model that gives it meaning, and for antimicrobial resistance, that model has yet to be built.

Subject of Research: Calibration of wastewater-based antimicrobial resistance surveillance signals for epidemiological and environmental risk interpretation

Article Title: Calibrating antimicrobial resistance influent and effluent signals in wastewater systems

Article References: Naziri, Α., Chatzimichail, S., Karaolia, P., & Fatta-Kassinos, D. (2026). Calibrating antimicrobial resistance influent and effluent signals in wastewater systems. Nature Water. https://doi.org/10.1038/s44221-026-00701-1

Image Credits: AI Generated

DOI: 10.1038/s44221-026-00701-1

Keywords: antimicrobial resistance, wastewater surveillance, wastewater-based epidemiology, resistance genes, sewage, wastewater treatment plants, environmental risk, public health, metagenomics, horizontal gene transfer, effluent, Nature Water

The receptors in question belong to the nucleotide-binding leucine-rich repeat family, the workhorse intracellular immune sensors of plants. NLR proteins carry a modular architecture: a variable N-terminal signalling domain, a central nucleotide-binding domain that acts as a molecular switch, and a C-terminal leucine-rich repeat domain that serves as the recognition module. In the resting state, the receptor is autoinhibited, folded upon itself. When the leucine-rich repeat domain perceives, directly or indirectly, the presence or activity of a pathogen effector protein, the switch flips, the receptor oligomerises into a resistosome, and a cascade of defensive responses follows, often culminating in a localised cell death that walls off the invader.

The trouble with engineering these receptors has always been the recognition surface. Leucine-rich repeats are exquisitely tuned by evolution to particular effector proteins, and their binding interfaces are diffuse, conformationally dynamic and poorly tolerant of casual mutation. Attempts to retune an existing NLR to recognise a new effector have met with limited success, because the coupling between recognition and activation is idiosyncratic to each receptor. Natural diversity, meanwhile, is finite. When a pathogen delivers an effector for which no plant in the gene pool carries a matching sensor, breeders have no card to play. This is the gap that synthetic receptors are designed to close.

The new approach sidesteps the problem of retuning natural recognition surfaces by building the sensing module afresh. Advances in de novo protein design, accelerated by deep-learning structure prediction tools such as AlphaFold and by generative design methods demonstrated over the past several years, allow researchers to specify a protein binder with a chosen shape and interaction profile and then compute an amino acid sequence that should fold into it. Rather than asking an existing NLR to learn a new partner, the strategy designs a synthetic binder against a defined pathogen effector and wires that binder into an immune receptor scaffold, so that effector binding triggers the conserved activation machinery of the NLR.

Wiring is the crux. A binder that merely sticks to an effector accomplishes nothing unless binding is mechanically transduced into receptor activation. The engineering challenge is therefore one of allostery: the designed recognition domain must be coupled to the nucleotide-binding switch such that the receptor sits stably in its off state in the absence of pathogen, yet flips decisively when the effector is present. Getting this balance wrong in either direction is costly. A receptor that fires without its ligand would impose autoimmune damage and yield penalties, while one that fails to respond leaves the plant defenceless. The design-build-test cycle must therefore evaluate both specificity and the absence of spontaneous activation.

This is where the second half of the strategy, evolution in vivo, earns its place. Computational design produces starting points, not finished products; predicted interfaces routinely require empirical optimisation. Directed evolution, in which libraries of receptor variants are generated and screened for the desired activity, has already proven its worth in plant immunity. Previous work showed that natural NLRs can be turned into robust sensors of specific effectors through targeted mutagenesis of their recognition domains, and that such engineered receptors can be deployed in crops. The synthetic pipeline extends this logic: rather than evolving a natural receptor toward a new specificity, researchers evolve a designed receptor toward reliable function, screening variants in planta for strong responses to the target effector and no response to plant proteins.

The significance of combining these steps is that each compensates for the other’s weakness. De novo design offers unlimited starting diversity, unconstrained by what nature has provided, but its predictions are imperfect. Directed evolution offers empirical optimisation with exquisite sensitivity to function, but it needs a plausible starting scaffold to improve upon. Designed receptors give evolution a head start; evolution gives design its final polish. The result, as the Nature Plants commentary describes it, is on-demand design and refinement of resistance genes: a workflow in which a pathogen effector of agricultural concern can be identified, a synthetic receptor raised against it in silico, and functional variants selected in plants within a timeframe that conventional breeding cannot approach.

The broader context makes the timing notable. Structure prediction has matured to the point that protein complexes and designed binders can be modelled with remarkable fidelity, and generative protein design has produced functional enzymes, sensors and therapeutics in other domains. Plant immunology, meanwhile, has accumulated a detailed mechanistic understanding of how NLRs activate, including structural snapshots of resistosomes that reveal how effector perception is coupled to signalling. The convergence of these threads is what makes synthetic immune receptors plausible now, when the same attempt even five years ago would have lacked both the design tools and the mechanistic template.

There are, of course, substantial hurdles between a working prototype and a deployed resistance gene. Pathogens evolve; an effector targeted by a synthetic receptor can mutate its surface, and durable resistance may require stacking multiple sensors or targeting effectors whose function the pathogen cannot easily relinquish. Regulatory frameworks for crops carrying designed genes, and public acceptance of them, remain open questions. There is also the matter of scale: each new effector target demands its own design and evolution campaign, and the reliability of the pipeline across diverse effector families has yet to be demonstrated broadly. The commentary’s authors, writing from a laboratory with deep roots in plant immunity research, frame the advance as the opening of a route rather than its completion.

Even so, the conceptual shift is hard to overstate. Plant immunity has until now been a scavenging enterprise, drawing on variation that pathogens and plants co-authored over millions of years. If synthetic receptors can be designed against arbitrary pathogen proteins and matured by directed evolution in planta, the defensive repertoire of crops becomes a matter of engineering choice rather than evolutionary inheritance. For a world in which plant diseases claim a substantial share of harvests and climate change keeps redistributing pathogen pressure, the ability to write a resistance gene to order, and to have it refined in the very organisms it will protect, marks a genuine inflection point in how humanity arms its crops.

Subject of Research: Engineering synthetic plant NLR immune receptors through de novo protein design and directed evolution in planta

Article Title: Plant immune receptors built in silico and evolved in vivo

Article References: Jones, J. D. G., & Zhao, H. (2026). Plant immune receptors built in silico and evolved in vivo. Nature Plants. https://doi.org/10.1038/s41477-026-02398-2

Image Credits: AI Generated

DOI: 10.1038/s41477-026-02398-2

Keywords: plant immunity, NLR receptors, de novo protein design, directed evolution, synthetic biology, crop disease resistance, pathogen effectors, protein engineering, plant biotechnology, resistance genes, AlphaFold, resistosome

The authors argue that the core of viral infection lies in the intricate interaction network between viral proteins and host proteins. As obligate intracellular parasites, plant viruses carry compact genomes encoding only a handful to a few dozen proteins, and they depend extensively on host factors to accomplish entry, replication, assembly, movement and release of progeny virions. Crucially, these interactions also serve as molecular interfaces linking infection to plant defense. Many viral proteins physically interact with key components of the salicylic acid, jasmonic acid and abscisic acid signaling pathways, often suppressing host immunity to promote infection, while plants can exploit specific interactions as molecular cues to activate immune signaling and restrict viral spread. This bidirectional character makes protein interactions simultaneously virulence factors and defense regulators.

A substantial portion of the review is devoted to the technical arsenal available for detecting these interactions. Biophysical techniques such as microscale thermophoresis, isothermal titration calorimetry and biolayer interferometry quantify binding affinities with high sensitivity, minimal sample volumes and low false-positive rates. Microscale thermophoresis monitors the thermophoretic movement of fluorescently labeled proteins across a temperature gradient, and is particularly useful for proteins that are difficult to express or unstable. Isothermal titration calorimetry directly yields full thermodynamic profiles, including enthalpy, entropy and Gibbs free energy, without the need for labeling. Biolayer interferometry measures binding-induced shifts in the interference pattern of light reflected from fiber-optic biosensors, enabling real-time observation of association and dissociation kinetics, and has been applied to quantify binding between viral effectors and host receptors.

Biochemical and cell-based methods complement these quantitative approaches. Co-immunoprecipitation examines interactions in their natural state inside cells, whereas GST pull-down assays test direct bait-prey interactions in vitro, albeit with the risk of tag-induced nonspecific binding. Bimolecular fluorescence complementation reconstitutes a fluorescent protein from two nonfluorescent fragments fused to the proteins of interest, allowing direct visualization of interactions in living cells, though the technique is notoriously temperature sensitive and can fail at higher physiological temperatures. On the computational side, databases such as STRING and Pfam integrate experimental evidence, domain annotations and literature data to predict and visualize interaction networks, providing structural and functional context for experimentally detected pairs.

The review highlights the growing dominance of mass spectrometry-based proteomics in interaction discovery. By the end of 2023, the BioGRID database had compiled more than 2.63 million protein interaction entries, with mass spectrometry techniques such as affinity capture-MS, proximity labeling-MS and co-fractionation collectively contributing over 45 percent of the data. Affinity purification coupled with mass spectrometry remains the predominant high-throughput method, but it struggles with membrane proteins and transient or weak interactions. Proximity labeling overcomes these limits by biotinylating proteins near a target of interest in living cells; the engineered ligases TurboID and miniTurbo, developed through directed evolution, achieve substantial biotinylation within ten minutes, dramatically shortening experimental timelines. Cofractionation mass spectrometry infers interactions from co-elution during chromatographic separation, while chemical cross-linking mass spectrometry captures direct physical contacts by covalently linking proximal amino acid residues, providing distance constraints for structural modeling. The lysis-free Virotrap method, which packages bait proteins into virus-like particles to capture associated host factors under near-native conditions, further reduces purification artifacts.

Despite these advances, the authors caution that no single method suffices. Mass spectrometry generates vast datasets that demand sophisticated processing, and variability in protein abundance complicates detection of low-abundance interactors. Protein interactions are inherently transient, low-affinity and dynamic, varying across tissues, developmental stages and infection time points. Artificial intelligence tools such as AlphaFold and RoseTTAFold have accelerated structure-based prediction of interactions, but their accuracy depends heavily on the quality of multiple sequence alignments and they perform poorly on orphan proteins and complexes with limited homologous sequences. The review therefore advocates an integrative, dynamic and network-centric strategy combining in vitro, in vivo and computational approaches.

The mechanistic core of the review documents how viruses manipulate host proteins at nearly every regulatory layer. RNA silencing is a central antiviral defense in plants, and viruses counter it with dedicated suppressors. The 38 kDa coat protein of turnip crinkle virus interacts with SGS3 to enhance its suppressor activity; the p19 protein of tomato bushy stunt virus sequesters small interfering RNAs and prevents their incorporation into the RNA-induced silencing complex; and the F-box protein P0 of potato leafroll virus promotes the autophagic degradation of ARGONAUTE1. Beyond post-transcriptional silencing, the P3 protein of rice grassy stunt virus triggers P3IP1- and SERK4-dependent degradation of NRPD1a, the largest subunit of RNA polymerase IV, thereby suppressing RNA-directed DNA methylation. A plant bunyaviral protein has also been shown to disrupt the phase separation of SERRATE, dismantling dicing bodies and reducing microRNA biogenesis.

Viruses likewise target signaling cascades and cellular quality-control systems. The coat protein of beet black scorch virus suppresses MAPKKKα-mediated innate immunity through interaction with 14-3-3a, while the βC1 protein of cotton leaf curl Multan virus inhibits MKK2 and MPK4. The NIb protein of turnip mosaic virus blocks SUMOylation-dependent phosphorylation of the salicylic acid receptor NPR1, and the P2 capsid protein of rice dwarf virus competes with the auxin receptor OsTIR1 for binding to OsIAA10, rewiring auxin signaling to promote symptoms. Tobacco mosaic virus coat protein suppresses the calmodulin-like protein NbCML30, and the RNA-dependent RNA polymerases of cucumber mosaic virus, potato virus Y and tobacco mosaic virus disrupt the phyA-FHY1 interaction to impair far-red light-mediated immunity. Autophagy is another contested hub: the γb protein of barley stripe mosaic virus interferes with the ATG7-ATG8 interaction, while the host receptor NBR1 mediates autophagic degradation of turnip mosaic virus HCpro, which the virus counteracts through VPg and 6K2.

Viruses also co-opt host machinery for replication and movement. Potyviruses use their genome-linked VPg protein to mimic a cap structure and recruit translation initiation factors of the eIF4E family, with different potyviruses requiring different eIF4E isoforms in different hosts. The conserved chaperone HSP70 supports the assembly of tomato bushy stunt virus replication complexes on peroxisomal membranes and the cell-to-cell movement of abutilon mosaic virus, and silencing HSP70 attenuates symptoms. Translationally controlled tumor protein supports potyvirus multiplication, and its silencing in tobacco nearly abolishes potato virus Y symptoms. Conversely, plants deploy sensors and resistance proteins: the E3 ubiquitin ligase RBRL recognizes the coat proteins of rice stripe virus and rice dwarf virus to activate jasmonate-mediated immunity; the tomato Tm-22 and Sw-5b immune receptors recognize viral movement proteins; the RTM genes restrict phloem-based systemic movement of potyviruses; and host kinases such as PKA and CK2 phosphorylate viral proteins to impair their function.

These insights are now feeding directly into crop protection. The review outlines how interaction maps distinguish susceptibility genes, which encode host factors hijacked by viruses, from resistance genes, which mediate immune recognition, enabling targeted genome editing of the former and overexpression of the latter. CRISPR/Cas systems have been used both to cleave viral genomes, as demonstrated for geminiviruses and, using FnCas9 and Cas13a, for RNA viruses such as cucumber mosaic virus and tobacco mosaic virus, and to edit host factors such as the cassava eIF4E-family proteins nCBP-1 and nCBP-2 that interact with cassava brown streak virus VPg. In a striking example of precision editing, base editing of a single residue in the rice strigolactone receptor D14 abolished binding by the rice grassy stunt virus P3 protein while preserving hormone perception, conferring robust resistance in both japonica and indica rice. The authors conclude that integrating interactome mapping, AI-assisted structural prediction and CRISPR-based functional validation offers a rational path toward broad-spectrum, durable virus resistance, while warning that single-point edits can be bypassed by viral mutation and that plant virus interaction databases remain far less mature than their animal-virus counterparts, underscoring the need for sustained, systematic data generation.

Subject of Research: Virus-host protein-protein interactions and their role in plant antiviral defense and crop resistance breeding

Article Title: The multidimensional significance of virus-host protein interactions and their implications in the antiviral defense of plants

Article References: Zhang, J., Qi, C., Wu, Z., Zhang, Y., Shi, J., Li, Z., Guo, J., Zhou, X., Tang, S., Yang, J., & Liu, P. (2026). The multidimensional significance of virus-host protein interactions and their implications in the antiviral defense of plants. Stress Biology, 6(1), Article 39. https://doi.org/10.1007/s44154-026-00309-1

Image Credits: AI Generated

DOI: 10.1007/s44154-026-00309-1

Keywords: plant viruses, protein-protein interactions, antiviral defense, RNA silencing, mass spectrometry, proximity labeling, AlphaFold, CRISPR, susceptibility genes, resistance genes, crop breeding, phytohormone signaling

The World Health Organization ranks antimicrobial resistance among the leading global health challenges, and the stakes of getting this science right could hardly be higher. When resistance is misjudged, antibiotics fail in the clinic, infections spread, and the pipeline of effective drugs narrows further. The new opinion piece, authored by Professor Frank Møller Aarestrup of the DTU National Food Institute and colleagues including Professor Thomas Bjarnsholt of the University of Copenhagen and Copenhagen University Hospital, draws on recent experimental findings suggesting that factors such as temperature, oxygen availability, and pH can determine whether a bacterium carrying a resistance gene actually behaves in a resistant manner.

Two underlying studies anchor the argument. One examined how the contrasting pH optima of the beta-lactamase enzymes CTX-M and CMY influence the fitness and resistance ecology of Escherichia coli. The other showed that environmental factors, specifically pH and redox potential, modulate beta-lactamase phenotypes and thereby alter beta-lactam resistance. Together, these findings indicate that the expression of resistance is not an intrinsic, unvarying trait encoded neatly in a gene, but a phenotype that depends on the microenvironment in which the bacterium finds itself at a given moment.

According to Aarestrup, this realization demands that researchers ask a far more granular set of questions. Is a bacterium carrying a resistance gene resistant at a pH of 5 or 8, when standard laboratory testing is performed at a fixed pH of 7.2? What oxygen levels and temperatures permit resistance to manifest? Does a patient’s fever change the answer? Is the bacterium residing in the oxygen-poor environment of the gut or in the oxygenated bloodstream? Current diagnostic protocols, he notes, take none of these biological conditions into account, even though they are precisely the conditions a bacterium encounters inside the human body.

Bjarnsholt frames the conceptual shift in equally stark terms. Resistance genes, he emphasizes, do not function in a vacuum. They exist in different bacterial species and in varying microenvironments, and the scientific community must therefore stop asking only which resistance genes a bacterium possesses and start asking when those genes actually render the bacterium resistant. The distinction is more than semantic. It implies that a bacterium classified as resistant in a standardized assay could behave as fully susceptible in the tissue of a patient, and vice versa, potentially explaining the frustrating clinical scenarios in which a course of antibiotics fails despite a laboratory report predicting success, or succeeds when the laboratory predicted failure.

The researchers acknowledge that embracing this context-dependent view of resistance will make laboratory measurement considerably harder. For decades, enormous effort has gone into standardizing susceptibility testing worldwide, so that a result produced in Copenhagen can be compared with one produced in Nairobi or São Paulo. Measuring resistance across a matrix of pH values, oxygen concentrations, temperatures, and host conditions multiplies the experimental burden many times over. Yet the researchers contend that the payoff justifies the effort, because a richer dataset would capture the true behavior of resistance genes under the conditions that matter in real infections.

Perhaps the most provocative implication concerns treatment strategy. If resistance manifests only when certain conditions are met, then it may become possible to select antibiotics that trigger the development of resistance only under circumstances that never occur in the human body, for example at a temperature far above physiological norms. Such a strategy would, in principle, allow clinicians to treat infections while deliberately choosing drugs whose resistance pathways remain switched off in the patient. Aarestrup suggests that this line of thinking could open entirely new approaches to combating resistance in humans, animals, and the wider environment, moving beyond the current reactive cycle of drug use followed by resistance emergence.

The environmental dimension of the proposal is equally significant. Resistance genes circulate through soil, water, wastewater, and animal populations, and monitoring efforts have long struggled to interpret what the presence of a gene in these reservoirs actually means for human health. If gene presence no longer equates to functional resistance, environmental surveillance could be refined to identify the conditions under which environmental resistance genes become clinically relevant, offering a better chance of intervening before dangerous resistance traits migrate into human pathogens. More targeted treatment of animals could similarly reduce the selective pressure that farms currently exert on bacterial communities.

Realizing this vision will require an enormous collective undertaking. The researchers argue that large volumes of new data on resistance across a range of biological conditions must be collected, effectively restarting resistance gene research from square one. Aarestrup envisions grouping resistance genes into categories and then deploying computational models and artificial intelligence to identify the relationships between genes and varying conditions, a task well suited to machine learning given the combinatorial complexity of gene-by-environment interactions. Such an effort would revisit and reassess much of the knowledge accumulated over decades of research built on the old binary model.

The opinion piece, titled From resistance genes to resistance states and enzymatic context-dependence in antimicrobial resistance, was published on 16 September 2026 and declares no competing interests. Whether the field adopts the proposed framework will depend on whether laboratories, regulators, and diagnostic manufacturers are willing to abandon a century of standardized practice in favor of a messier but potentially far more accurate picture of microbial behavior. If the Danish team is right, the future of antibiotic stewardship may lie not in discovering new drugs alone, but in understanding precisely when, where, and under what conditions the drugs already in use lose their power, and in engineering treatment strategies that keep resistance from ever switching on.

Subject of Research: Context-dependent antibiotic resistance and the environmental conditions that determine whether resistance genes make bacteria resistant

Article Title: Researchers in Denmark aim to find new solutions in the fight against antibiotic resistance

Article References: Researchers in Denmark aim to find new solutions in the fight against antibiotic resistance. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: antibiotic resistance, antimicrobial resistance, Trends in Microbiology, Technical University of Denmark, beta-lactamase, pH, microenvironment, diagnostics, Escherichia coli, resistance genes, public health, WHO