Low-abundance Species Research Articles

Investigating the Role of Gut Microbiota in Pediatric Patients with Severe COVID-19 or MIS-C.

Severe COVID-19 and MIS-C are rare but serious outcomes associated with SARS-CoV-2 infection. The onset of MIS-C often involves the gastrointestinal system, suggesting a potential connection with gut microbiota. This study aims to compare the gut microbiota of children with severe COVID-19 and those with MIS-C using various biomolecular approaches. Gut microbiota composition and specific microbial modulations were analyzed using fecal samples collected at hospital admission. The study included hospitalized patients (mean age 6 ± 5 years) diagnosed with severe COVID-19 (37 patients) or MIS-C (37 patients). Microbial differences were assessed using both NGS and qRT-PCR methodologies. In 75% of cases, pharmacological treatments included antibiotics and corticosteroids, which influenced the microbiota composition. Early age was found to have the most significant impact on microbiota diversity. Significant differences in alpha and beta diversity were observed between COVID-19 and MIS-C patients, particularly concerning low-abundance species. Levels of Bacteroides spp., Bifidobacterium spp., and Akkermansia muciniphila were comparable between groups, while an increased activity of Bifidobacterium spp. was noted in children with positive fecal samples (p = 0.019). An in-depth evaluation of lesser-known gut species may be key to reducing the risk of severe outcomes and developing microbiota-based biomarkers for the early diagnosis of MIS-C.

Enhancing recovery from gut microbiome dysbiosis and alleviating DSS-induced colitis in mice with a consortium of rare short-chain fatty acid-producing bacteria

ABSTRACT The human gut microbiota is a complex community comprising hundreds of species, with a few present in high abundance and the vast majority in low abundance. The biological functions and effects of these low-abundant species on their hosts are not yet fully understood. In this study, we assembled a bacterial consortium (SC-4) consisting of B. paravirosa, C. comes, M. indica, and A. butyriciproducens, which are low-abundant, short-chain fatty acid (SCFA)-producing bacteria isolated from healthy human gut, and tested its effect on host health using germ-free and human microbiota-associated colitis mouse models. The selection also favored these four bacteria being reduced in abundance in either Ulcerative Colitis (UC) or Crohn’s disease (CD) metagenome samples. Our findings demonstrate that SC-4 can colonize germ-free (GF) mice, increasing mucin thickness by activating MUC-1 and MUC-2 genes, thereby protecting GF mice from Dextran Sodium Sulfate (DSS)-induced colitis. Moreover, SC-4 aided in the recovery of human microbiota-associated mice from DSS-induced colitis, and intriguingly, its administration enhanced the alpha diversity of the gut microbiome, shifting the community composition closer to control levels. The results showed enhanced phenotypes across all measures when the mice were supplemented with inulin as a dietary fiber source alongside SC-4 administration. We also showed a functional redundancy existing in the gut microbiome, resulting in the low abundant SCFA producers acting as a form of insurance, which in turn accelerates recovery from the dysbiotic state upon the administration of SC-4. SC-4 colonization also upregulated iNOS gene expression, further supporting its ability to produce an increasing number of goblet cells. Collectively, our results provide evidence that low-abundant SCFA-producing species in the gut may offer a novel therapeutic approach to IBD.

Cultivated genome references for protein database construction and high-resolution taxonomic annotation in metaproteomics.

Metaproteomics offers a profound understanding of the functional dynamics of the gut microbiome, which is crucial for personalized healthcare strategies. The selection of an appropriate database is a critical step for the identification of peptides and proteins, as well as for the provision of accurate taxonomic and functional annotations. The matched metagenomic-derived database is considered to be the best, but its limitations include the identification of low-abundance organisms and taxonomic resolution. Herein, we constructed a protein database (DBCGR2) based on Cultivated Genome Reference 2 (CGR2) and developed a complete peptide-centric analysis workflow for database searching and for the annotation of taxonomy and function. This workflow was subsequently appraised in comparison with metagenomics-derived databases for the analysis of metaproteomic data. Our findings suggested that the performance of DBCGR2 in identification was comparable with metagenomics-derived databases with improvement in identification rates of peptides from low-abundance species. The database searching results could be fully annotated using the pepTaxa taxonomic annotation approach developed in this study, and the taxonomic resolution was enhanced to strain level. Additionally, the results demonstrated that the sensitivity of functional annotation could be enhanced by employing DBCGR2. Overall, the DBCGR2 combined with pepTaxa can be considered an alternative for metaproteomic data analysis with superior analysis performances.IMPORTANCEMass spectrometry-based metaproteomics offers a profound understanding of the gut microbial taxonomy and functionality. The databases utilized in the analysis of metaproteomic data are crucial, as they determine the identification of proteins that can be recognized and linked to overall human health, in addition to the quality of taxonomic and functional annotation. Among the most effective approaches for constructing protein databases is the utilization of metagenomic sequencing to create matched databases. However, the database, derived from isolated genomes, has yet to undergo rigorous testing for their efficacy and accuracy in protein identification and taxonomic and functional annotation. Here, we constructed a protein database DBCGR2 derived from Cultivated Genome Reference 2 (CGR2) and a complete workflow for data analysis. We compared the performances of DBCGR2 and metagenomics-derived databases. Our results indicated that DBCGR2 can be regarded as an alternative to metagenomics-derived databases, which contribute to metaproteomic data analysis.

Polystyrene microplastic exposure modulates gut microbiota and gut-liver axis in gilthead seabream (Sparus aurata)

Microplastics (MPs) are a threat of growing concern for living organisms as they exist in all ecosystems. The bidirectional communication between the gut, its microbiota, and the liver, has been conceptualized as gut-liver axis and may be influenced by environmental factors. MPs can cause intestinal and hepatic injuries, but there is still limited research exploring their impact on gut-liver axis. The aim of this study was to assess the effects of MP ingestion on gut-liver axis balance in gilthead seabream (Sparus aurata) fed with a diet enriched with polystyrene (PS)-MPs (0, 25, or 250 mg/kg b.w./day) for 21 days. PS-MPs affected the composition of gut microbiota, enhancing the evenness of gut microbial species. We also observed the impoverishment of core microbiota, suggesting reduced stability and permanence of microbiota members. Furthermore, PS-MPs reduced predominant bacteria in the gut of gilthead seabreams, increasing low-abundance species, including potential harmful taxa. On the other hand, PS-MPs increased the gene expression of immune and inflammatory mediators (i.e., TLR2, TLR5, and COX-2) in the liver. PS-MP exposure also increased serum triglycerides and bile acids (BAs) without modifying cholesterol. Moreover, the hepatic BA metabolism was impacted by PS-MPs which increased the expression of genes involved in primary BA kinetic (i.e., CYP27A1 and LXRa), which in turn can modulate intestinal microbial community. Indeed, PICRUSt2 mapping of BA-related functions predicted the increase of factors involved in BA metabolism. Specifically, K01442 (choloylglycine hydrolase) and K00076 (7α-hydroxysteroid dehydrogenase) were augmented by PS-MPs, suggesting a possible adaptation or co-evolution of gut microbiota to the modified hepatic BA metabolism. Thus, the obtained results showed that ingested PS-MPs impact the gut microbiota architecture and functions, the hepatic innate immunity, and the BA metabolism, suggesting the involvement of the gut-liver axis in MP-induced toxicity.

A Simple and Cost-Effective Extraction for Piscine Environmental DNA Metabarcoding Using Guanidine Hydrochloride Method.

Environmental DNA (eDNA) metabarcoding is a valuable tool for assessing aquatic biodiversity, but the high cost and complexity of DNA extraction pose challenges for widespread adoption, especially in developing countries. This study presents a cost-effective eDNA extraction method using a guanidine hydrochloride (GuHCl) buffer, proteinase-K digestion, and isopropanol precipitation to improve the detection of fish communities. Comparison with the Qiagen DNeasy Blood & Tissue Kit using MiFish universal primers showed that the GuHCl protocol detected more fish species in freshwater samples, with comparable performance in relative read abundance metrics. However, the GuHCl method exhibited higher PCR inhibition in brackish samples, likely due to salinity and natural inhibitors. The results suggest that the GuHCl-based method is a viable alternative, offering enhanced sensitivity for low-abundance species in freshwater samples and cost savings. This protocol facilitates large-scale eDNA metabarcoding for ecological studies and conservation management efforts.•The GuHCl protocol identified a greater diversity of fish species in freshwater samples than the Qiagen kit, but detected fewer species in brackish water samples.•Both extraction methods demonstrated robust positive correlations in metrics of relative read abundance.

Large-scale investigation for antimicrobial activity reveals novel defensive species across the healthy skin microbiome.

The human skin microbiome constitutes a dynamic barrier that can impede pathogen invasion by producing antimicrobial natural products. Gene clusters encoding for production of secondary metabolites, biosynthetic gene clusters (BGCs), that are enriched in the human skin microbiome relative to other ecological settings, position this niche as a promising source for new natural product mining. Here, we introduce a new human microbiome isolate collection, the EPithelial Isolate Collection (EPIC). It includes a large phylogenetically diverse set of human skin-derived bacterial strains from eight body sites. This skin collection, consisting of 980 strains is larger and more diverse than existing resources, includes hundreds of rare and low-abundance species, and hundreds of unique BGCs. Using a large-scale co-culture screen to assess 8,756 pairwise interactions between skin-associated bacteria and potential pathogens, we reveal broad antifungal activity by skin microbiome members. Integrating 287 whole isolate genomes and 268 metagenomes from sampling sites demonstrates that while the distribution of BGC types is stable across body sites, specific gene cluster families (GCFs), each predicted to encode for a distinct secondary metabolite, can substantially vary. Sites that are dry or rarely moist harbor the greatest potential for discovery of novel bioactive metabolites. Among our discoveries are four novel bacterial species, three of which exert significant and broad-spectrum antifungal activity. This comprehensive isolate collection advances our understanding of the skin microbiomes biosynthetic capabilities and pathogen-fighting mechanisms, opening new avenues towards antimicrobial drug discovery and microbiome engineering.

Atlantic Forest Regeneration Dynamics Following Human Disturbance Cessation in Brazil

The Brazilian Atlantic Forest (BAF) is one of the most important biodiversity hotspots and species-rich ecosystems globally. Due to human activities, it has been significantly reduced and fragmented. This study examined both biotic (floristic composition, diversity, and structure) and abiotic (topographic and soil) factors in BAF fragments undergoing varying levels and durations of human disturbance cessation: approximately 20 years (20 y), ~30 years (30 y), and over 40 years (>40 y). We aimed to understand the recovery dynamics of floristic composition, diversity, and structure in BAF fragments in relation to abiotic factors. Several statistical tools were employed to examine similarities/differences and relationships. Forests of the 30 y group exhibit significantly greater homogeneity in terms of floristic composition, while forests of the 20 y group are characterized by lower species abundance and diversity. The floristic composition was primarily influenced by soil features and the time of disturbance. Under “Environmental Protection Areas”, soil–vegetation recovery can occur more swiftly than usually observed for BAF. A significant BAF recovery was observed approximately 40 years after the end of human disturbance. A partial recovery featured 30 y disturbed areas, while in 20 y forests, recovery is in its early stages. Human-disturbed BAF can gradually rebound when effective management practices are implemented.

I want to climb to the tops of trees! Factors facilitating the development of ivy vines in central European forests

Abstract Lianas, which are considered to form tree-related microhabitats, are known as important elements of tropical forests; however, their ecological function and relationships with host trees (phorophytes) in temperate forests are poorly known. This gap in knowledge stems from a low species diversity and abundance of lianas in temperate forests. An exception is common ivy (Hedera helix), which is widely distributed and is currently increasing its abundance in temperate forests. In this study, we examined the relationships between ivy vines with features of their phorophytes, using Central European upland mixed forests as an example. We assess the presence and density of ivy within 69 study plots, established in the forest interior and ecotone. We use generalized linear mixed-effects models to assess drivers of ivy’s presence and its density, while accounting for the tree diameter at breast height, bark roughness, and the canopy light transmittance. We show that ivy is able to grow on nearly all tree species, although it prefers phorophytes with rough bark and a large diameter. Large generative individuals (ivy vines that produce fruits) were found mostly on veteran trees (usually oaks, alders, or pines). For its growth, ivy requires tree phorophytes with only a moderate transparency of light through the tree crowns, which is likely related to evergreen leaves that enable ivy vines to also develop during leaf-off periods. The features of phorophytes preferred by ivy indicate that the vine finds optimal conditions for development in old patches of tree stand, often in areas inaccessible or unprofitable for forest management. We propose using large and fruiting ivy vines as indicators of old-growth forests that deserve protection, which would be in line with the current policy of sustaining and restoring close-to-natural forests in Europe.

Evaluating Environmental Programs: Long-Term Monitoring of Crustacean Assemblages in a Polluted Estuary

We assessed the environmental quality of the Odiel-Tinto estuary, one of the most polluted in the world, by analysing the spatial variation of subtidal soft-bottom crustacean assemblages from 2000 to 2016. Our primary goal was to evaluate whether corrective measures implemented since 1986 have resulted in significant ecological improvement. The assemblages were structured according to the natural gradient from the estuary to the marine environment. Throughout the study, the assemblages exhibited low species richness and abundance (e.g., over 3 species and 180 individuals/m2 in the inner areas; 19 species and 510 individuals/m2 in the mouth zone). However, 2016 saw an increase in both species number and total abundance (e.g., over 5 and 24 species in the inner and mouth areas, respectively). Despite these observations, the Odiel-Tinto system harboured fewer species (24 species) compared to nearby estuaries like the Guadiana and Guadalquivir (over 50 species). Although there were signs of changes in the estuary over the sampling periods (e.g., a slight increase in richness and diversity in 2016 compared to 2002 and 2004), these fluctuations are likely characteristic of a highly dynamic environment rather than indications of genuine ecological recovery. These findings highlight the need for a long-term monitoring program, which should also encompass intertidal mudflats due to their higher density and biomass, easy accessibility, and reduced exposure to the impacts of recurrent maintenance dredging of the navigation channel.

Whole genome sequencing approaches for taxonomic profiling and evaluation of wastewater quality

Tracking metagenomic abundance in wastewater is undoubtedly a powerful tool to detect emerging variants and improve community health. However, there are a few factors that limit environmental water-based genomic monitoring: sampling variability, incomplete coverage, genetic fragmentation, degradation, data analysis and interpretation. The decreasing costs of high-throughput sequencing and high-end supercomputers have increased the use and accuracy of genomic data for microbial detection and monitoring in wastewater samples within any given region. To better understand the microbial dynamics and to determine the target sequencing throughput required to establish taxa that may pose as bio-indicators of an epidemiological outbreak, wastewater samples were collected from distinct locations within the Emirate of Abu Dhabi, United Arab Emirates using appropriate sampling methods. A reference database of ∼27,000 known species was developed and used for further analysis. The results showed that 15 % of data in each sample matched any of ∼27,000 known bacterial, viral, fungal, or protozoan species. Despite the high fraction of unclassified data (85 %), more than 2000 species from >800 genera across >30 phyla were detected in each sample. Both 5 Gb and 10 Gb of sequenced data detected the top ∼2000 species with highest abundance. Doubling the target sequencing throughput (i.e., 10 Gb vs 5 Gb) detected ∼500 additional low-abundance species per sample however it did not affect the overall sample composition or translate into higher per-sample species diversity captured. There was a marginal increase in the number of species detected in each sample beyond 0.20 Gb of classified data. Overall, the results indicate that sequencing to a 3 Gb throughput detects nearly 95 % of all species in the samples.

MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.

The Effect of Spatio‐Temporal Sampling and Biological Replication on the Detection of Kelp Forest Fish Communities Using eDNA Metabarcoding

ABSTRACTEnvironmental DNA (eDNA) metabarcoding surveys can support the acquisition of extensive biodiversity data to support ecosystem monitoring and conservation actions. However, the optimization of eDNA metabarcoding project design is essential to capture spatio‐temporal heterogeneity of eDNA signals and maximize diversity detection. In this study, we developed a system‐specific approach to detect fish communities in kelp forests, by analyzing fine‐scale spatio‐temporal patterns in eDNA signals at two sites along the South African coastline, as well as testing the effect of biological replication and pooling of replicates on species detection. At each site, samples were collected at two stations along the shoreline at two depth zones, and this was repeated at two time points (24 h apart). We detected 113 operational taxonomic units (OTUs) across 32 families, but fewer than 20% of OTUs could be assigned to species, indicating that barcode reference libraries need to be drastically improved. We detected significant differences in communities across small spatial scales (< 600 m) and time points, suggesting that to best capture a site's diversity patterns, samples should be collected at multiple points and times within at least 24 h. To detect ~80% of the fish community, including some low abundance species, a minimum of four samples appear sufficient. In addition, a higher number of OTUs (76 vs. 65) were found in individual replicates than in any of the pools. However, pooling samples prior to sequencing can still detect valuable broad‐scale biodiversity patterns for monitoring and can offset the decrease in data resolution with the benefit of accumulating comprehensive data from increased sampling efforts over time. As a pilot investigation into how best to maximize kelp forest‐associated fish communities, this study provides a basis for optimizing sampling design for coastal eDNA‐based surveys in southern Africa and strengthens the development of long‐term eDNA monitoring programs to better support conservation and management actions.

Long-distance Southern Ocean environmental DNA (eDNA) transect provides insights into spatial marine biota and invasion pathways for non-native species

The Southern Ocean surrounding Antarctica harbours some of the most pristine marine environments remaining, but is increasingly vulnerable to anthropogenic pressures, climate change, and invasion by non-native species. Monitoring biotic responses to cumulative impacts requires temporal and spatial baselines and ongoing monitoring - traditionally, this has been obtained by continuous plankton recorder (CPR) surveys. Here, we conduct one of the longest environmental DNA (eDNA) transects yet, spanning over 3000 nautical miles from Hobart (Australia) to Davis Station (Antarctica). We evaluate eDNA sampling strategies for long-term open ocean biomonitoring by comparing two water volume and filter pore size combinations: large (12 l with 20 μm) and small (2 l with 0.45 μm). Employing a broad COI metabarcoding assay, we found the large sample/pore combination was better suited to open ocean monitoring, detecting more target DNA and rare or low abundance species. Comparisons with four simultaneously conducted CPR transects revealed that eDNA detections were more diverse than CPR, with 7 (4 unique) and 4 (1 unique) phyla detections respectively. While both methods effectively delineated biodiversity patterns across the Southern Ocean, eDNA enables surveys in the presence of sea-ice where CPR cannot be conducted. Accordingly, 16 species of concern were detected along the transect using eDNA, notably in the Antarctic region (south of 60°S). These were largely attributed to hull biofouling, a recognized pathway for marine introductions into Antarctica. Given the vulnerability of Antarctic environments to potential introductions in a warming Southern Ocean, this work underscores the importance of continued biosecurity vigilance. We advocate integrating eDNA metabarcoding with long-term CPR surveys in the Southern Ocean, emphasising the urgency of its implementation. We anticipate temporal and spatial interweaving of CPR, eDNA, and biophysical data will generate a more nuanced picture of Southern Ocean ecosystems, with significant implications for the conservation and preservation of Antarctic ecosystems.

Evaluating the applicability of high-density UAV LiDAR data for monitoring tundra grassland vegetation

ABSTRACT Grasslands are one of the most widespread biomes on Earth. The interaction of UAV LiDAR with grasses and herbaceous plants is an infrequently covered area of research, apart from its utilisation for the estimation of above ground biomass. To evaluate the applicability of LiDAR for monitoring grassland vegetation, two model plots in the arctic-alpine tundra (Krkonoše Mountains, Czech Republic) were selected. Throughout the growing season, UAV LiDAR point clouds (800 points/m2) and multispectral imagery (9 cm) were acquired in monthly intervals, along with reference botanical and terrestrial LiDAR data. The study provides insight into the analysis of compact low-lying vegetation at the species level. A set of experiments was conducted focusing on the analysis of LiDAR information loss, vertical strata, and structural metrics computed over the grass species/communities. Random forest was used to determine the importance of metrics by out-of-bag permutation of predictors and to classify vegetation species using UAV LiDAR-based metrics, as well as image-based digital surface models alone and in fusion with multispectral data. The vertical distribution of the UAV LiDAR points varied significantly between species and throughout the growing season. Loss at the canopy bottoms was apparent, with the lowest points corresponding to dry grass matter rather than relief. Grasslands had the highest penetration capability at the start of the growing season. In terms of metrics, maximum canopy height was the most important. The multitemporal LiDAR-derived structural metrics were able to differentiate (F-1 score above 90%) all the shrubs/trees and dominant grass Calamagrostis villosa. Mixed and low-abundance species were indistinguishable. The overall accuracy scores in a 9 (27) cm grid reached 75.1% (78.1) and 63.5% (66.4) for Bílá louka meadow and Úpské rašeliniště bog, respectively. Fusing the LiDAR-derived features with multispectral imagery did not enhance the classification results apart from the delineation of shrubs and trees.

Community Structure of Sea Cucumbers (Holothuroidea) in The Intertidal Zone of Koepisino Beach, North Buton

Sea cucumbers are marine invertebrates belonging to the class Holothuroidea, living in various aquatic environments ranging from shallow coastal waters to deep seas. Sea cucumbers have an important ecological function in coral reef ecosystems. The aim of the research is to determine the community structure of sea cucumbers (Holothuroidea) in the intertidal zone of Koepisino Beach, North Buton. The research method used was quantitative descriptive research conducted in the intertidal zone of North Koepisino Buton Beach. Data collection was carried out by exploring each station measuring 50 × 100 meters for 3 stations. Data analysis was descriptive quantitative, In the intertidal zone of Koepisino Beach, North Buton, 12 species of sea cucumbers belonging to two orders, Aspidochirotida (genera Holothuria, Bohadschia, Telonata, and Stichopus) and Apodida (genera Synapta and Opheodesoma), were discovered. The community structure components analyzed in this study were abundance, diversity index, uniformity index, and dominance index.The highest abundance of sea cucumber species was at station I (sand substrate) at 0.009 (ind/m2). The lowest species abundance was at station III (coral rubble substrate) at 0.005 (ind/m2). H. scabra is the species with the highest abundance, namely 0.0026 ind/m2, while Bohadschia similis, Bohadschia vitiensis, Opheodesoma spectabilis, Telonata ananas are the species with the lowest abundance, namely 0 ind/m2. The Shannon-Wiener sea cucumber diversity index (H') is in the medium category 2.144. The sea cucumber uniformity index at the research location is high (E > 0.6) and there is no dominant species.

Prospective One-Health investigation into low-abundant extended-spectrum β-lactamase producing Enterobacterales enables detection of potential dissemination events and persistence

BackgroundFollowing a one-health approach, we sought to determine reservoirs of extended-spectrum β-lactamase (ESBL)-producing Enterobacterales (ESBL-PE), other than Escherichia coli or Klebsiella pneumoniae complex species (i.e., low-abundant species), and their associated ESBL genes and plasmid-replicon profiles. MethodsFrom 06/2017–05/2019, ESBL-PE isolates were recovered from clinical samples routinely collected at the University Hospital Basel (Basel, Switzerland), as well as from wastewater and foodstuffs collected monthly at predefined locations throughout the city of Basel. Whole-genome sequencing was performed for characterization of ESBL-PE isolates. ResultsAmong 1634 isolates recovered, 114 (7%) belonged to 17 low-abundant ESBL-PE species.Seven species originated from more than one compartment, mainly from clinical and wastewater samples (6/17). Sixteen different ESBL genes were identified, with blaCTX-M-15 (27%), blaFONA-6 (23%) and blaSHV-12 (16%) being most frequent. The blaCTX-M-1 gene was the only ESBL gene recovered from all three compartments. Putative plasmids constituted 60% of ESBL gene-containing contigs, while chromosomes comprised 40%. Foodstuff isolates showed the highest proportion (91%, 41/45) of ESBL genes located on chromosomes, whereas wastewater isolates had the highest proportion (95%, 37/39) of putative plasmids. Multi-replicon combinations were identified in 81% of the isolates. Epidemiological links were found among some clinical and wastewater isolates. ConclusionsThe dominance of blaCTX-M-15 among low-abundant ESBL-PE species supports its species-independent transmission potential beyond the E. coli and K. pneumoniae complex, and blaCTX-M-1 may be transmitted between strains recovered from different compartments. The substantial overlap between low-abundant ESBL-PE present in wastewater and clinical samples supports the utility of wastewater surveillance for antibiotic resistance monitoring.

Targeted whole-genome recovery of single viral species in a complex environmental sample

Characterizing unknown viruses is essential for understanding viral ecology and preparing against viral outbreaks. Recovering complete genome sequences from environmental samples remains computationally challenging using metagenomics, especially for low-abundance species with uneven coverage. We present an experimental method for reliably recovering complete viral genomes from complex environmental samples. Individual genomes are encapsulated into droplets and amplified using multiple displacement amplification. A unique gene detection assay, which employs an RNA-based probe and an exonuclease, selectively identifies droplets containing the target viral genome. Labeled droplets are sorted using a microfluidic sorter, and genomes are extracted for sequencing. We demonstrate this method's efficacy by spiking two known viral genomes, Simian virus 40 (SV40, 5,243 bp) and Human Adenovirus 5 (HAd5, 35,938 bp), into a sewage sample with a final abundance in the droplets of around 0.1% and 0.015%, respectively. We achieve 100% recovery of the complete sequence of the spiked-in SV40 genome with uniform coverage distribution. For the larger HAd5 genome, we cover approximately 99.4% of its sequence. Notably, genome recovery is achieved with as few as one sorted droplet, which enables the recovery of any desired genomes in complex environmental samples, regardless of their abundance. This method enables single-genome whole-genome amplification and targeting characterizations of rare viral species and will facilitate our ability to access the mutational profile in single-virus genomes and contribute to an improved understanding of viral ecology.

Strain tracking with uncertainty quantification.

The ability to detect and quantify microbiota over time has a plethora of clinical, basic science, and public health applications. One of the primary means of tracking microbiota is through sequencing technologies. When the microorganism of interest is well characterized or known a priori , targeted sequencing is often used. In many applications, however, untargeted bulk (shotgun) sequencing is more appropriate; for instance, the tracking of infection transmission events and nucleotide variants across multiple genomic loci, or studying the role of multiple genes in a particular phenotype. Given these applications, and the observation that pathogens (e.g. Clostridioides difficile, Escherichia coli, Salmonella enterica ) and other taxa of interest can reside at low relative abundance in the gastrointestinal tract, there is a critical need for algorithms that accurately track low-abundance taxa with strain level resolution. Here we present a sequence quality- and time-aware model, ChronoStrain , that introduces uncertainty quantification to gauge low-abundance species and significantly outperforms the current state-of-the-art on both real and synthetic data. ChronoStrain leverages sequences' quality scores and the samples' temporal information to produce a probability distribution over abundance trajectories for each strain tracked in the model. We demonstrate Chronostrain's improved performance in capturing post-antibiotic Escherichia coli strain blooms among women with recurrent urinary tract infections (UTIs) from the UTI Microbiome (UMB) Project. Other strain tracking models on the same data either show inconsistent temporal colonization or can only track consistently using very coarse groupings. In contrast, our probabilistic outputs can reveal the relationship between low-confidence strains present in the sample that cannot be reliably assigned a single reference label (either due to poor coverage or novelty) while simultaneously calling high-confidence strains that can be unambiguously assigned a label. We also analyze samples from the Early Life Microbiota Colonisation (ELMC) Study demonstrating the algorithm's ability to correctly identify Enterococcus faecalis strains using paired sample isolates as validation.

Microbiodiversity Landscape Present in the Mine-Tailings of the “Sierra de Huautla” Biosphere Reserve, Mexico

Large-scale mining activities generate significant amounts of waste that accumulates in the environment. These wastes, known as mine tailings, contain high levels of heavy metals, posing risks to human health and causing severe damage to ecosystems. In this study, we determined the heavy metal content of mine tailings in the Sierra de Huautla Biosphere Reserve (REBIOSH), Mexico, and investigated their effect on microbial composition. One of the sites historically contaminated with metals was sampled in three different locations, labeled S1, S2, and S3. A fourth site free of heavy metals (S4) was also used as a control. Our results showed high levels of As, Pb, Cd, and Ag, potentially dangerous metals that exceed thresholds set by international regulatory agencies. Metal contamination indices indicated moderate to extreme enrichment for As, Cd, and Pb, posing potential ecological risks. A metagenomic study of mine tailings showed a core specie-specific microbiome covered by Sinimarinibacterium flocculans, Jiangella anatolica, Thiobacillus denitrificans, Fontimonas thermophile, Sphingomonas koreensis. These may be associated with the processing of heavy metals. A comparative study using the ALDEx2 revealed that less represented species like Variovorax paradoxus, Usitatibacter rugosus, Usitatibacter palustris, Sphingosinicella microcystinivorans, Sphingobium yanoikuyae, and Stella humosa may serve as microbial markers in metal-contaminated environments. In addition, we detected rare or low-abundance species belonging to the phylum Armatimonadota, Candidatus Melainobacteriota, Candidatus Saccharimonadota, Chlamydiota, Deinococcota, Elusimicrobiota, Bacillota, Rhodothermota and Verrucomicrobiota, which could play an important role in ecosystems contaminated with heavy metals. Also, we found site-specific taxonomic representatives such as Nitrososphaera gargensis and Nitrospira nitrificans dominating the S3 ecosystem; Ensifer aridi (S2 and S1), N. nitrificans (S2), while Reyranella soli dominate the S1 soil. These organisms could be crucial for nitrogen access in oligotrophic environments and underscore the adaptability of microbial life to extreme conditions. This is the first comprehensive study of the microbial composition in this important ecological site of the Mexican geography and can provide future guidance for the management and biological treatment of mining wastes.

Bacterial community in apparently healthy and asymptomatic Eucalyptus trees and those with symptoms of bacterial wilt

Ralstonia solanacearum and R. pseudosolanacearum are well-known bacterial plant pathogens that cause significant losses to both ornamental and agricultural plants. It has been suggested that they are not the primary cause of bacterial wilt in Eucalyptus species, but rather are opportunistic, taking advantage of trees predisposed to infection by abiotic and biotic factors. To test this hypothesis, the bacterial community within the vascular tissue of asymptomatic Eucalyptus grandis x E. urophylla trees, and those displaying varying stages of infection in China and Indonesia were compared using 16S rRNA profiling. Asymptomatic trees growing in areas where bacterial infections had never previously been reported to occur were included as controls. Ralstonia species were found within the vascular tissue of both asymptomatic and symptomatic trees, in high abundance. In the control samples, bacterial diversity within the vascular tissue was high with a low abundance of Ralstonia species. The presence of Ralstonia species in asymptomatic and control samples supports the hypothesis that these species are latent and/or opportunistic pathogens in E. grandis x E. urophylla trees.