Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis.

The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated action. This is partly because a comprehensive survey of past research activity has never performed due to the massive scale and diversity of published information. Here we compiled 254,738 articles on AMR using Artificial Intelligence (AI; i.e., Natural Language Processing, NLP) methods to create a database and information retrieval system for knowledge extraction on research perfomed over the last 20 years. Global maps were created that describe regional, methodological, and sectoral AMR research activities that confirm limited intersectoral research has been performed, which is key to guiding science-informed policy solutions to AMR, especially in low-income countries (LICs). Further, we show greater harmonisation in research methods across sectors and regions is urgently needed. For example, differences in analytical methods used among sectors in AMR research, such as employing culture-based versus genomic methods, results in poor communication between sectors and partially explains why One Health-based solutions are not ensuing. Therefore, our analysis suggest that performing culture-based and genomic AMR analysis in tandem in all sectors is crucial for data integration and holistic One Health solutions. Finally, increased investment in capacity development in LICs should be prioritised as they are places where the AMR burden is often greatest. Our open-access database and AI methodology can be used to further develop, disseminate, and create new tools and practices for AMR knowledge and information sharing.

Antimicrobial resistance in rural rivers: Comparative study of the Coquet (Northumberland) and Eden (Cumbria) River catchments.

Many studies have characterised resistomes in river microbial communities. However, few have compared resistomes in parallel rural catchments that have few point-source inputs of antimicrobial genes (ARGs) and organisms (i.e., AMR) - catchments where one can contrast more nebulous drivers of AMR in rural rivers. Here, we used quantitative microbial profiling (QMP) to compare resistomes and microbiomes in two rural river catchments in Northern England, the Coquet and Eden in Northumberland and Cumbria, respectively, with different hydrological and geographical conditions. The Eden has higher flow rates, higher annual surface runoff, and longer periods of soil saturation, whereas the Coquet is drier and has lower flowrates. QMP analysis showed the Eden contained significantly more abundant microbes associated with soil sources, animal faeces, and wastewater than the Coquet, which had microbiomes like less polluted rivers (Wilcoxon test, p < 0.01). The Eden also had greater ARG abundances and resistome diversity (Kruskal Wallis, p < 0.05), and higher levels of potentially clinically relevant ARGs. The Eden catchment had greater and flashier runoff and more extensive agricultural land use in its middle reach, which explains higher levels of AMR in the river. Hydrological and geographic factors drive AMR in rural rivers, which must be considered in environmental monitoring programmes.

Comparison of gene targets and sampling regimes for SARS-CoV-2 quantification for wastewater epidemiology in UK prisons.

Prisons are high-risk settings for infectious disease transmission, due to their enclosed and semi-enclosed environments. The proximity between prisoners and staff, and the diversity of prisons reduces the effectiveness of non-pharmaceutical interventions, such as social distancing. Therefore, alternative health monitoring methods, such as wastewater-based epidemiology (WBE), are needed to track pathogens, including SARS-CoV-2. This pilot study assessed WBE to quantify SARS-CoV-2 prevalence in prison wastewater to determine its utility within a health protection system for residents. The study analysed 266 samples from six prisons in England over a 12-week period for nucleoprotein 1 (N1 gene) and envelope protein (E gene) using quantitative reverse transcriptase-polymerase chain reaction. Both gene assays successfully detected SARS-CoV-2 fragments in wastewater samples, with both genes significantly correlating with COVID-19 case numbers across the prisons (p < 0.01). However, in 25% of the SARS-positive samples, only one gene target was detected, suggesting that both genes be used to reduce false-negative results. No significant differences were observed between 14- and 2-h composite samples, although 2-h samples showed greater signal variance. Population normalisation did not improve correlations between the N1 and E genes and COVID-19 case data. Overall, WBE shows considerable promise for health protection in prison settings.

Fate and transport modelling for evaluating antibiotic resistance in aquatic environments: Current knowledge and research priorities.

Antibiotics have revolutionised medicine in the last century and enabled the prevention of bacterial infections that were previously deemed untreatable. However, in parallel, bacteria have increasingly developed resistance to antibiotics through various mechanisms. When resistant bacteria find their way into terrestrial and aquatic environments, animal and human exposures increase, e.g., via polluted soil, food, and water, and health risks multiply. Understanding the fate and transport of antibiotic resistant bacteria (ARB) and the transfer mechanisms of antibiotic resistance genes (ARGs) in aquatic environments is critical for evaluating and mitigating the risks of resistant-induced infections. The conceptual understanding of sources and pathways of antibiotics, ARB, and ARGs from society to the water environments is essential for setting the scene and developing an appropriate framework for modelling. Various factors and processes associated with hydrology, ecology, and climate change can significantly affect the fate and transport of ARB and ARGs in natural environments. This article reviews current knowledge, research gaps, and priorities for developing water quality models to assess the fate and transport of ARB and ARGs. The paper also provides inputs on future research needs, especially the need for new predictive models to guide risk assessment on AR transmission and spread in aquatic environments.

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective.

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Toward a Universal Unit for Quantification of Antibiotic Resistance Genes in Environmental Samples.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the "One-Health" framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.

Exploring resistomes and microbiomes in pilot-scale microalgae-bacteria wastewater treatment systems for use in low-resource settings.

Antibiotic resistance genes (ARGs) released into the environment are an emerging human and environmental health concern, including ARGs spread in wastewater treatment effluents. In low-to-middle income countries (LMICs), an alternate wastewater treatment option instead of conventional systems are low-energy, high-rate algal ponds (HRAP) that use microalgae-bacteria aggregates (MABA) for waste degradation. Here we studied the robustness of ARG removal in MABA-based pilot-scale outdoor systems for 140 days of continuous operation. The HRAP system successfully removed 73 to 88 % chemical oxygen demand and up to 97.4 % ammonia, with aggregate size increasing over operating time. Fourteen ARG classes were identified in the HRAP influent, MABA, and effluent using metagenomics, with the HRAP process reducing total ARG abundances by up to 5-fold from influent to effluent. Parallel qPCR analyses showed the HRAP system significantly reduced exemplar ARGs (p < 0.05), with 1.2 to 4.9, 2.7 to 6.3, 0 to 1.5, and 1.2 to 4.8 log-removals for sul1, tetQ, blaKPC, and intl1 genes, respectively. Sequencing of influent, effluent and MABAs samples showed associated microbial communities differed significantly, with influent communities by Enterobacteriales (clinically relevant ARGs carrying bacteria), which were less evident in MABA and effluent. In this sense, such bacteria might be excluded from MABA due to their good settling properties and the presence of antimicrobial peptides. Microalgae-bacteria treatment systems steadily reduced ARGs from wastewater during operation time, using sunlight as the energetic driver, making them ideal for use in LMIC wastewater treatment applications.

Explaining the resistomes in a megacity's water supply catchment: Roles of microbial assembly-dominant taxa, niched environments and pathogenic bacteria.

Antibiotic resistance genes (ARGs) in drinking water sources suggest the possible presence of resistant microorganisms that jeopardize human health. However, explanations for the presence of specific ARGs in situ are largely unknown, especially how their prevalence is affected by local microbial ecology, taxa assembly and community-wide gene transfer. Here, we characterized resistomes and bacterial communities in the Taipu River catchment, which feeds a key drinking water reservoir to a global megacity, Shanghai. Overall, ARG abundances decreased significantly as the river flowed downstream towards the reservoir (P < 0.01), whereas the waterborne bacteria assembled deterministically (|ßNRI| > 2.0) as a function of temperature and dissolved oxygen conditions with the assembly-dominant taxa (e.g. Ilumatobacteraceae and Cyanobiaceae) defining local resistomes (P < 0.01, Cohen's D = 4.22). Bacterial hosts of intragenomic ARGs stayed at the same level across the catchment (60 ∼ 70 genome copies per million reads). Among them, the putative resistant pathogens (e.g. Burkholderiaceae) carried mixtures of ARGs that exhibited high transmission probability (transfer counts = 126, P < 0.001), especially with the microbial assembly-dominant taxa. These putative resistant pathogens had densities ranging form 3.0 to 4.0 × 106 cell/L, which was more pronouncedly affected by resistome and microbial assembly structures than environmental factors (SEM, std-coeff ß = 0.62 vs. 0.12). This work shows that microbial assembly and resistant pathogens play predominant roles in prevelance and dissemination of resistomes in receiving water, which deserves greater attention in devisng control strategies for reducing in-situ ARGs and resistant strains in a catchment.

Exploring the impacts of physicochemical characteristics and heavy metals fractions on bacterial communities in four rivers.

Heavy metals contamination in sediment poses serious threats to bacterial communities that play critical roles in sediment biogeochemical processes. However, the physicochemical factors and the major heavy metals fractions that affect sediment bacterial communities are still unclear. Here, we performed heatmap and redundancy analyses to examine the effects of physico-chemical characteristics and heavy metals fractions on the sediment bacterial community from rivers in the UK (River Tyne and Ouseburn) and India (River Ganga and Yamuna). The results revealed that physicochemical characteristics and heavy metals fractions altered the diversity, richness, and structures of the bacterial community. Moreover, the fractions of Co, Zn, Pb, Cr, and Cu played significant roles in shaping the bacterial community structure, and physicochemical variables, particularly NH4+-N and NO2--N, also influenced the bacterial diversity and structure. Firmicutes showed strong associations with both physicochemical factors and heavy metals fractions. Chloroflexi and Actinobacteriota can be used as biomarkers for Zn contamination. Overall, our study identified the significance of sediment chemical characteristics and heavy metals fractions in determining the bacterial community structure as well as bioremediation and environmental management of metals contaminated sites.

Heavy metal and antibiotic resistance in four Indian and UK rivers with different levels and types of water pollution.

Heavy metal pollution can enhance the level of antibiotic resistance, posing concerns to ecosystem and public health. Here, we investigated heavy metal concentrations, heavy metal resistant bacteria and antibiotic resistant bacteria and their corresponding resistant genes, and integrons in four different river environments, i.e., low heavy metals and low wastewater, high heavy metals and low wastewater, low heavy metals and high wastewater, and high heavy metals and high wastewater levels. Heavy metals were found to show positive and significant correlations with heavy metal resistance and antibiotic resistance and integrons (r > 0.60, p < 0.05), indicating that heavy metal selective pressure can cause heavy metal and antibiotic resistance to be transmitted simultaneously via integrons, which can result in the development of multi-resistant bacteria in the heavy metal-polluted environments. Moreover, there were significant associations between heavy metal resistance and antibiotic resistance (r > 0.60, p < 0.05), demonstrating heavy metal and antibiotic resistance are connected via a same or related mechanism. Class 1 integrons were found to have strong correlations with heavy metals and heavy metal resistance and antibiotic resistance (r > 0.60, p < 0.05), indicating a higher occurrence of antibiotic resistance co-selection in the heavy metal-polluted environments.

The Complex Interplay Between Antibiotic Resistance and Pharmaceutical and Personal Care Products in the Environment.

Antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) are important environmental contaminants. Nonetheless, what drives the evolution, spread, and transmission of antibiotic resistance dissemination is still poorly understood. The abundance of ARB and ARGs is often elevated in human-impacted areas, especially in environments receiving fecal wastes, or in the presence of complex mixtures of chemical contaminants, such as pharmaceuticals and personal care products. Self-replication, mutation, horizontal gene transfer, and adaptation to different environmental conditions contribute to the persistence and proliferation of ARB in habitats under strong anthropogenic influence. Our review discusses the interplay between chemical contaminants and ARB and their respective genes, specifically in reference to co-occurrence, potential biostimulation, and selective pressure effects, and gives an overview of mitigation by existing man-made and natural barriers. Evidence and strategies to improve the assessment of human health risks due to environmental antibiotic resistance are also discussed. Environ Toxicol Chem 2023;00:1-16. © 2022 SETAC.

Rapid Proteomic Characterization of Bacteriocin-Producing Enterococcus faecium Strains from Foodstuffs.

Enterococcus belongs to a group of microorganisms known as lactic acid bacteria (LAB), which constitute a broad heterogeneous group of generally food-grade microorganisms historically used in food preservation. Enterococci live as commensals of the gastrointestinal tract of warm-blooded animals, although they also are present in food of animal origin (milk, cheese, fermented sausages), vegetables, and plant materials because of their ability to survive heat treatments and adverse environmental conditions. The biotechnological traits of enterococci can be applied in the food industry; however, the emergence of enterococci as a cause of nosocomial infections makes their food status uncertain. Recent advances in high-throughput sequencing allow the subtyping of bacterial pathogens, but it cannot reflect the temporal dynamics and functional activities of microbiomes or bacterial isolates. Moreover, genetic analysis is based on sequence homologies, inferring functions from databases. Here, we used an end-to-end proteomic workflow to rapidly characterize two bacteriocin-producing Enterococcus faecium (Efm) strains. The proteome analysis was performed with liquid chromatography coupled to a trapped ion mobility spectrometry-time-of-flight mass spectrometry instrument (TimsTOF) for high-throughput and high-resolution characterization of bacterial proteins. Thus, we identified almost half of the proteins predicted in the bacterial genomes (>1100 unique proteins per isolate), including quantifying proteins conferring resistance to antibiotics, heavy metals, virulence factors, and bacteriocins. The obtained proteomes were annotated according to function, resulting in 22 complete KEGG metabolic pathway modules for both strains. The workflow used here successfully characterized these bacterial isolates and showed great promise for determining and optimizing the bioengineering and biotechnology properties of other LAB strains in the food industry.

Draft Genome Sequences of Two Bacteriocin-Producing Enterococcus faecium Strains Isolated from Nonfermented Animal Foods in Spain.

Here, we report the draft genome sequences of two bacteriocin-producing Enterococcus faecium strains isolated from nonfermented animal foods in Spain. The genomes of the strains contain at least three different regions encoding bacteriocins, and the strains comply with the European Food Safety Authority guidance for use in animal nutrition.

Nearly Complete Genome Sequence of Raoultella ornithinolytica Strain MQB_Silv_108, Carrying an Uncommon Extended-Spectrum-ß-Lactamase-like blaBEL Gene.

Raoultella ornithinolytica has become increasingly important in human diseases. Here, we report the nearly complete genome sequence of a multidrug-resistant strain, R. ornithinolytica MQB_Silv_108, which was isolated from the effluent from a domestic wastewater treatment plant in Spain. Therefore, its release into the environment poses a possible exposure risk for humans and animals.

Research needs for optimising wastewater-based epidemiology monitoring for public health protection.

Wastewater-based epidemiology (WBE) is an unobtrusive method used to observe patterns in illicit drug use, poliovirus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The pandemic and need for surveillance measures have led to the rapid acceleration of WBE research and development globally. With the infrastructure available to monitor SARS-CoV-2 from wastewater in 58 countries globally, there is potential to expand targets and applications for public health protection, such as other viral pathogens, antimicrobial resistance (AMR), pharmaceutical consumption, or exposure to chemical pollutants. Some applications have been explored in academic research but are not used to inform public health decision-making. We reflect on the current knowledge of WBE for these applications and identify barriers and opportunities for expanding beyond SARS-CoV-2. This paper critically reviews the applications of WBE for public health and identifies the important research gaps for WBE to be a useful tool in public health. It considers possible uses for pathogenic viruses, AMR, and chemicals. It summarises the current evidence on the following: (1) the presence of markers in stool and urine; (2) environmental factors influencing persistence of markers in wastewater; (3) methods for sample collection and storage; (4) prospective methods for detection and quantification; (5) reducing uncertainties; and (6) further considerations for public health use.

Bioavailability of potentially toxic elements influences antibiotic resistance gene and mobile genetic element abundances in urban and rural soils.

Antibiotic resistance genes (ARGs) that can encode resistance traits in bacteria are found across the environment. While it is often difficult to discern their origin, their prevalence and diversity depends on many factors, one of which is their exposure to potentially toxic elements (PTE, i.e., metals and metalloids) in soils. Here, we investigated how ambient ARGs and mobile genetic elements (MGEs) relate to the relative bioavailability of different PTEs (total versus exchangeable and carbonate-bound PTE) in rural and urban soils in northeast England. The average relative abundances of ARGs in rural sites varied over a 3-log range (7.24 × 10-7 to 1.0 × 10-4 genes/16S rRNA), and relative ARG abundances in urban sites varied by four orders of magnitude (1.75 × 10-6 to 2.85 × 10-2 genes/16S rRNA). While beta-lactam and aminoglycoside resistance genes dominated rural and urban sites, respectively, non-specific ARGs, also called multidrug-resistance genes, were significantly more abundant in urban sites (p < 0.05). Urban sites also had higher concentrations of total and exchangeable forms of PTE than rural sites, whereas rural sites were higher in carbonate-bound forms. Significant positive Spearman correlations between PTEs, ARGs and MGEs were apparent, especially with bioavailable PTE fractions and at urban sites. This study found significant positive correlations between ARGs and beryllium (Be), which has not previously been reported. Overall, our results show that PTE bioavailability is important in explaining the relative selection of ARGs in soil settings and must be considered in future co-selection and ARG exposure studies.

Genetic sequencing detected the SARS-CoV-2 delta variant in wastewater a month prior to the first COVID-19 case in Ahmedabad (India).

Wastewater-based genomic surveillance can identify a huge majority of variants shed by the infected individuals within a population, which goes beyond genomic surveillance based on clinical samples (i.e., symptomatic patients only). We analyzed four samples to detect key mutations in the SARS-CoV-2 genome and track circulating variants in Ahmedabad during the first wave (Sep/Nov 2020) and before the second wave (in Feb 2021) of COVID-19 in India. The analysis identified a total of 34 mutations in the spike protein across samples categorized into 23 types. The spike protein mutations were linked to the VOC-21APR-02; B.1.617.2 lineage (Delta variant) with 57% frequency in wastewater samples of Feb 2021. The key spike protein mutations were T19R, L452R, T478K, D614G, & P681R and deletions at 22029 (6 bp), 28248 (6 bp), & 28271 (1 bp). Interestingly, these mutations were not seen in the samples from Sep/Nov 2020 but did appear before the massive second wave of COVID-19 cases, which in India started in early April 2021. In fact, genetic traces of the Delta variant were found in samples of early Feb 2021, more than a month before the first clinically confirmed case of this in March 2021 in Ahmedabad, Gujarat. The present work describes the circulating of SARS-CoV-2 variants in Ahmedabad and confirms the consequential value of wastewater surveillance for the early detection of variants of concerns (VOCs). Such monitoring must be included as a major component of future health protection systems.

Effects of heavy metals pollution on the co-selection of metal and antibiotic resistance in urban rivers in UK and India.

Heavy metal pollution and the potential for co-selection of resistance to antibiotics in the environment is growing concern. However, clear associations between heavy metals and antibiotic resistance in river systems have not been developed. Here we investigated relationships between total and bioavailable heavy metals concentrations; metal resistance gene (MRG) and antibiotic resistance gene (ARG) abundances; mobile genetic elements; and the composition of local bacterial communities in low and high metal polluted rivers in UK and India. The results indicated that MRGs conferring resistance to cobalt (Co) and nickel (Ni) (rcnA), and Co, zinc (Zn), and cadmium (Cd) (czcA), and ARGs conferring resistance to carbapenem and erythromycin were the dominating resistant genes across the samples. The relative MRGs, ARGs, and integrons abundances tended to increase at high metal polluted environments, suggesting high metals concentrations have a strong potential to promote metal and antibiotic resistance by horizontal gene transmission and affecting bacterial communities, leading to the development of multi-metal and multi-antibiotic resistance. Network analysis demonstrated the positive and significant relationships between MRGs and ARGs as well as the potential for integrons playing a role in the co-transmission of MRGs and ARGs (r > 0.80, p < 0.05). Additionally, the major host bacteria of various MRGs and ARGs that could be accountable for greater MRGs and ARGs levels at high metal polluted environments were also identified by network analysis. Spearman's rank-order correlations and RDA analysis further confirm relationships between total and bioavailable heavy metals concentrations and the relative MRG, ARG, and integron abundances, as well as the composition of related bacterial communities (r > 0.80 (or < -0.80), p < 0.05). These findings are critical for assessing the possible human health concerns associated with metal-driven antibiotic resistance and highlight the need of considering metal pollution for developing appropriate measures to control ARG transmission.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes.

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

Deep-mantle krypton reveals Earth's early accretion of carbonaceous matter.

Establishing when, and from where, carbon, nitrogen and water were delivered to Earth is a fundamental objective in understanding the origin of habitable planets such as Earth. Yet, volatile delivery to Earth remains controversial1-5. Krypton isotopes provide insights on volatile delivery owing to their substantial isotopic variations among sources6-10, although pervasive atmospheric contamination has hampered analytical efforts. Here we present the full suite of krypton isotopes from the deep mantle of the Galápagos and Iceland plumes, which have the most primitive helium, neon and tungsten isotopic compositions11-16. Except for 86Kr, the krypton isotopic compositions are similar to a mixture of chondritic and atmospheric krypton. These results suggest early accretion of carbonaceous material by proto-Earth and rule out any combination of hydrodynamic loss with outgassing of the deep or shallow mantle to explain atmospheric noble gases. Unexpectedly, the deep-mantle sources have a deficit in the neutron-rich 86Kr relative to the average composition of carbonaceous meteorites, which suggests a nucleosynthetic anomaly. Although the relative depletion of neutron-rich isotopes on Earth compared with carbonaceous meteorites has been documented for a range of refractory elements1,17,18, our observations suggest such a depletion for a volatile element. This finding indicates that accretion of volatile and refractory elements occurred simultaneously, with krypton recording concomitant accretion of non-solar volatiles from more than one type of material, possibly including outer Solar System planetesimals.