Patrick Sam Guy Chain

Untreated wastewater are reservoirs of microbial communities originating from different sources within an urbanized human-populated area and is now regularly used for tracking and assessing levels of certain human pathogens like SARS-CoV-2, Salmonella, and Poliomyelitis. Wastewater microbial communities can exhibit high diversity, comprised of mostly non-pathogens alongside a smaller population of pathogens. Much of the research on wastewater has focused on either pathogens or microbiomes in the treatment plants, but not on the microbiome of untreated wastewater, which is perhaps more reflective of community health. Moreover, as wastewater usage expands to more known and unknown pathogen detection, a deeper understanding of both wastewater’s overall genetic diversity and diversity over time is pivotal. Towards that goal, we characterized the observed microbial diversity of global untreated wastewater by analyzing 1,344 publicly available metagenomes, representing 6 continents, and created a global wastewater database hosted at https://doi.org/10.5281/zenodo.17794790 . We elucidated the full spectrum of prokaryotic diversity by recovering and characterizing high quality bins, contigs, and reads from all the data. We provide the first comprehensive, publicly available database describing global wastewater by uncovering previously uncharacterized microbes, identifying geographically specific microbial populations, and creating a high-quality dataset to advance future microbiome, epidemiological, and biosurveillance research.

In heterogeneous environments, the hyphae of filamentous fungi and oomycetes can facilitate the dispersal of other microorganisms. The use of these “fungal highways” (FH) is regulated by both physical and biological factors with their interplay resulting in variable capabilities of different microbes to establish FH. Several devices have been developed to test the movement of bacteria across mycelium. However, these methods are usually time-consuming and cannot be applied either at a large scale or in a high throughput format. In this study, we developed 3D-printed experimental devices that physically separate two environments while allowing hyphal networks to act as bridges for bacterial movement. The final design allows for the simultaneous testing of up to 10 pairs and the inclusion of any culturing media. With these devices, we investigated how fungal–bacterial pairing, nutrient conditions, and inoculation strategies influence FH formation. Bacterial transport was limited in nutrient-rich media but increased under poorer nutrient conditions, consistent with enhanced exploratory growth of the mycelium. Both cis- and trans-inoculation supported FH formation, although bacterial arrival was delayed in the absence of co-inoculation. The devices were used to demonstrate that transport of bacteria by FH was relevant for the colonization of a natural substrate. Finally, we established a novel in planta assay to evaluate FH formation during host colonization. This assay demonstrated that Fusarium graminearum can transport bacteria during wheat spike colonization. Together, these results provide accessible, scalable tools to study hyphal-mediated bacterial dispersal and highlight the combined role of biological specificity and nutrient context in the establishment of FH. Graphical

The interdisciplinary nature of microbiome research, coupled with the generation of complex multi-omics data, makes knowledge sharing challenging. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiome studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.

Wastewater surveillance has become a powerful tool to monitor circulating viruses at a community level. Currently, most wastewater surveillance efforts use target-based approaches such as quantitative PCR techniques or hybrid capture. This study explores the feasibility of using untargeted ultra-deep metagenomic sequencing as a comprehensive approach to wastewater surveillance. To test this, composite influent wastewater samples were collected weekly at a single site from January 2024 through June 2025. Sequencing was performed using random hexamers on all samples, with an average depth of 1.1 billion reads per sample. Human enteric viruses such as rotaviruses, astroviruses, and noroviruses were detected at high levels in virtually every sample. SARS-CoV-2 was also detected in most samples and the counts per sample positively correlated with digital PCR (dPCR) measurements. Less abundant respiratory pathogens such as influenza A and B, rhinoviruses, parainfluenzaviruses, and human coronaviruses 229E, OC43, NL63, and HKU1 were also regularly detected. However, those pathogens displayed distinct and reproducible winter and spring seasonality. Several unexpected viruses were also detected, such as several detections of highly pathogenic avian influenza H5N1 (HPAI H5N1) genotype B3.13, a month-long surge of hepatitis A virus, and a large season-specific surge in influenza C virus. The most abundant known virus detected was the Tobamovirus tomato brown rugose fruit virus, which was present stably year-round at high abundance. However, other tobamoviruses such as tomato mosaic virus were detected primarily in the late growing season. This eighteen-month study highlights that ultra deep sequencing enables detection of expected and unexpected viral pathogens without targeted enrichment. Importance: This study demonstrates that untargeted ultra deep metagenomic sequencing can provide a comprehensive tool for wastewater surveillance of viral pathogens. By generating approximately 1 billion reads per sample across 78 consecutive weeks, we captured expected pathogens such as SARS-CoV-2, noroviruses, and influenza viruses. Additionally, we captured unexpected viral signals such as influenza C and highly pathogenic avian influenza H5N1. The wide range of viral taxa captured in this study also displays epidemiologically relevant seasonality. We also observed a correlation between metagenomic SARS-CoV-2 read counts and dPCR values to validate this method against other wastewater surveillance methods currently in use. Our findings highlight how ultra deep metagenomics can enhance pandemic preparedness, enable early detection of non-standard and clinically overlooked species, and broaden the scope of One Health monitoring by capturing human, animal, and plant viral signatures from a composite wastewater sample.

Aerosol sampling with next-generation sequencing was used to characterize microbial communities in a cafeteria and medical facility waiting room in Los Alamos, New Mexico, USA. We detected sequences from human, bacteria, archaea, fungi, other eukaryotes, and viruses, providing insights into the diversity of the aerosol microbiome.

Microbiome research is revolutionizing human and environmental health, but the value and reuse of microbiome data are significantly hampered by the limited development and adoption of data standards. While several ongoing efforts are aimed at improving microbiome data management, significant gaps still remain in terms of defining and promoting adoption of consensus standards for these datasets. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines for human microbiome research have been endorsed and successfully utilized by many research organizations, publishers, and funding agencies, and have been recognized as a consensus community standard. No equivalent effort has occurred for environmental, synthetic, and non-human host-associated microbiomes. To address this growing need within the microbiome research community, we convened the Microbiome Data Management in Action Workshop (June 12–13, 2024, in Atlanta, GA, USA), to bring together key decision makers in microbiome science including researchers, publishers, funders, and data repositories. The 50 attendees, representing the diverse and interdisciplinary nature of microbiome research, discussed recent progress and challenges, and brainstormed actionable recommendations and paths forward for coordinated environmental microbiome data management and the modifications necessary for the STORMS guidelines to be applied to environmental, non-human host, and synthetic microbiomes. The outcomes of this workshop will form the basis of a formalized data management roadmap to be implemented across the field. These best practices will drive scientific innovation now and in years to come as these data continue to be used not only in targeted reanalyses but in large-scale models and machine learning efforts.

Aspergillus fungi are opportunistic pathogens that affect millions of people worldwide. Aspergilli produce organic acids to optimize the environmental pH and match the needs of their enzymatic machinery. In this study, we tested the hypothesis that this also occurs during infection. By producing oxalic acid (OA), Aspergillus would manipulate pH during lung infection and thus, interfering with this process could control the pathogen. To test this hypothesis, we assessed in silico the potential for OA production in a wide range of Aspergilli. A genetic marker for AO production was detected in most of the species including prevalent human pathogens. We tested OA production in vitro in four strains of A. niger and A. fumigatus , but only one of the A. niger strains produced OA consistently. For this fungal strain, oxalotrophic bacteria were able to control fungal growth via OA consumption. To translate this observation into a pre-clinical system, increasingly complex experiments were performed. In 3D-cell cultures, A. niger also secreted OA and modified pH and free Ca ²⁺ . Co-inoculation of the oxalotrophic bacterium inhibited the development of the fungus. However, biocontrol could not be replicated in Galleria mellonella , which is often used as an infection model. In contrast, the bacterium improved disease score and the absence of oxalate crystals in the lungs in the mouse model. This biocontrol interaction between oxalotrophic bacteria and A. niger represents a paradigm shift in the fight against opportunistic fungal pathogens, where the goal is to render the host environment less permissive to pathogen development One Sentence Summary: Demonstration of biocontrol as a therapeutic concept to combat Aspergillus niger with oxalotrophic bacteria in an animal infection model

The phytopathogenic fungus Sclerotinia sclerotiorum has a wide host range and causes significant economic losses in crops worldwide. This pathogen uses oxalic acid as a virulence factor; for this reason, the degradation of this organic acid by oxalotrophic bacteria has been proposed as a biological control approach. However, previous studies on the potential role of oxalotrophy in biocontrol did not investigate the differential effect of oxalic acid consumption and the subsequent pH alkalinisation on fungal growth. In this study, confrontation experiments on different media using a wild-type (WT) strain of S. sclerotiorum and an oxalate-deficient mutant (strain Δoah) with the soil oxalotrophic bacteria Cupriavidus necator and Cupriavidus oxalaticus showed the combined effect of media composition on oxalic acid production, pH, and fungal growth control. Oxalotrophic bacteria were able to control S. sclerotiorum only in the medium in which oxalic acid was produced. However, the deficient Δoah mutant was also controlled, indicating that the consumption of oxalic acid is not the sole mechanism of biocontrol. WT S. sclerotiorum acidified the medium when inoculated alone, while for both fungi, the pH of the medium changed from neutral to alkaline in the presence of bacteria. Therefore, medium alkalinisation independent of oxalotrophy contributes to fungal growth control.