Functional meta-omics provide critical insights into long- and short-read assemblies.

Real-world evaluations of metagenomic reconstructions are challenged by distinguishing reconstruction artifacts from genes and proteins present in situ. Here, we evaluate short-read-only, long-read-only and hybrid assembly approaches on four different metagenomic samples of varying complexity. We demonstrate how different assembly approaches affect gene and protein inference, which is particularly relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic and metaproteomic data to assess the metagenomic data-based protein predictions. Our findings pave the way for critical assessments of metagenomic reconstructions. We propose a reference-independent solution, which exploits the synergistic effects of multi-omic data integration for the in situ study of microbiomes using long-read sequencing data.

Assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates.

High-throughput next-generation shotgun sequencing of pathogenic bacteria is growing in clinical relevance, especially for chromosomal DNA-based taxonomic identification and for antibiotic resistance prediction. Genetic exchange is facilitated for extrachromosomal DNA, e.g. plasmid-borne antibiotic resistance genes. Consequently, accurate identification of plasmids from whole-genome sequencing (WGS) data remains one of the major challenges for sequencing-based precision medicine in infectious diseases. Here, we assess the heterogeneity of four state-of-the-art tools (cBar, PlasmidFinder, plasmidSPAdes and Recycler) for the in silico prediction of plasmid-derived sequences from WGS data. Heterogeneity, sensitivity and precision were evaluated by reference-independent and reference-dependent benchmarking using 846 Gram-negative clinical isolates. Interestingly, the majority of predicted sequences were tool-specific, resulting in a pronounced heterogeneity across tools for the reference-independent assessment. In the reference-dependent assessment, sensitivity and precision values were found to substantially vary between tools and across taxa, with cBar exhibiting the highest median sensitivity (87.45%) but a low median precision (27.05%). Furthermore, integrating the individual tools into an ensemble approach showed increased sensitivity (95.55%) while reducing the precision (25.62%). CBar and plasmidSPAdes exhibited the strongest concordance with respect to identified antibiotic resistance factors. Moreover, false-positive plasmid predictions typically contained only few antibiotic resistance factors. In conclusion, while high degrees of heterogeneity and variation in sensitivity and precision were observed across the different tools and taxa, existing tools are valuable for investigating the plasmid-borne resistome. Nevertheless, additional studies on representative clinical data sets will be necessary to translate in silico plasmid prediction approaches from research to clinical application.

PLSDB: a resource of complete bacterial plasmids.

The study of bacterial isolates or communities requires the analysis of the therein included plasmids in order to provide an extensive characterization of the organisms. Plasmids harboring resistance and virulence factors are of especial interest as they contribute to the dissemination of antibiotic resistance. As the number of newly sequenced bacterial genomes is growing a comprehensive resource is required which will allow to browse and filter the available plasmids, and to perform sequence analyses. Here, we present PLSDB, a resource containing 13 789 plasmid records collected from the NCBI nucleotide database. The web server provides an interactive view of all obtained plasmids with additional meta information such as sequence characteristics, sample-related information and taxonomy. Moreover, nucleotide sequence data can be uploaded to search for short nucleotide sequences (e.g. specific genes) in the plasmids, to compare a given plasmid to the records in the collection or to determine whether a sample contains one or multiple of the known plasmids (containment analysis). The resource is freely accessible under https://ccb-microbe.cs.uni-saarland.de/plsdb/.

The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.

The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.

An estimate of the total number of true human miRNAs.

While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

Comparing genome versus proteome-based identification of clinical bacterial isolates.

Whole-genome sequencing (WGS) is gaining importance in the analysis of bacterial cultures derived from patients with infectious diseases. Existing computational tools for WGS-based identification have, however, been evaluated on previously defined data relying thereby unwarily on the available taxonomic information.Here, we newly sequenced 846 clinical gram-negative bacterial isolates representing multiple distinct genera and compared the performance of five tools (CLARK, Kaiju, Kraken, DIAMOND/MEGAN and TUIT). To establish a faithful 'gold standard', the expert-driven taxonomy was compared with identifications based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) analysis. Additionally, the tools were also evaluated using a data set of 200 Staphylococcus aureus isolates.CLARK and Kraken (with k =31) performed best with 626 (100%) and 193 (99.5%) correct species classifications for the gram-negative and S. aureus isolates, respectively. Moreover, CLARK and Kraken demonstrated highest mean F-measure values (85.5/87.9% and 94.4/94.7% for the two data sets, respectively) in comparison with DIAMOND/MEGAN (71 and 85.3%), Kaiju (41.8 and 18.9%) and TUIT (34.5 and 86.5%). Finally, CLARK, Kaiju and Kraken outperformed the other tools by a factor of 30 to 170 fold in terms of runtime.We conclude that the application of nucleotide-based tools using k-mers-e.g. CLARK or Kraken-allows for accurate and fast taxonomic characterization of bacterial isolates from WGS data. Hence, our results suggest WGS-based genotyping to be a promising alternative to the MS-based biotyping in clinical settings. Moreover, we suggest that complementary information should be used for the evaluation of taxonomic classification tools, as public databases may suffer from suboptimal annotations.

MicroRNA signature in spermatozoa and seminal plasma of proven fertile men and in testicular tissue of men with obstructive azoospermia.

MicroRNAs (miRNAs) have recently received a significant amount of attention due to their remarkable influence on post-transcriptional gene regulation. In this study, we aim to provide a catalogue of miRNAs present in spermatozoa, seminal plasma and testicular tissue. Expression profiles of miRNA in spermatozoa and seminal plasma of 16 proven fertile men and testicular tissue of eight men with morphologically and/or histologically confirmed obstructive azoospermia were determined by microarray and RT-qPCR in combination with bioinformatics analyses. A total of 123, 156 and 133 miRNAs were consistently detected in spermatozoa, seminal plasma and testicular tissue respectively. Sixty-four miRNAs were shared across all sample types. Based on miRNAs expression level present in each group, correlation analysis showed moderate-to-strong correlations within the spermatozoa and seminal plasma samples and a wider range of correlations within the testicular tissue samples. The target genes of known miRNAs appeared to be involved in a wide range of biological processes related to reproduction, development and differentiation of germ cells. Our results suggest that there is a certain similarity between spermatozoa and seminal plasma for the relative miRNA expression changes with respect to testicular tissue and provide an overview of the miRNAs present in each sample type.

MicroRNA profiling from dried blood samples.

MicroRNAs (miRNAs) hold great promise as blood-borne and circulating biomarkers for numerous diseases. However, the reliability of such liquid biopsies is particularly impacted by problems associated with the handling of biological liquids in the pre-analytical stage of biomarker processing. Dried blood spots (DBS) and other capillary blood microsampling devices offer a way to circumvent many of these complications. DBS are supposed to be far less sensitive to collection protocols, storage conditions, and transport processes, while offering the possibility for a decentralized sample collection. In addition, DBS are minimally invasive and require very small amounts of blood, thereby facilitating blood collection from small children or patients at risk by blood drawing. Here, we summarize the current state of knowledge about DBS-derived miRNAs. Experimental studies on miRNA from DBS especially emphasize the influence of the adsorptive material and the importance of drying and rehydration protocols. The present studies are, however, difficult to compare as they use different readout-systems, ranging from PCR-based quantification of single miRNAs to next-generation sequencing (NGS) of the entire miRNome. The data underscore the need for procedure standardization and the development of general guidelines on handling and evaluating miRNA biomarkers derived from DBS.

The composition of the pulmonary microbiota in sarcoidosis - an observational study.

BACKGROUND: Sarcoidosis is a systemic disease of unknown etiology. The disease mechanisms are largely speculative and may include the role microbial patterns that initiate and drive an underlying immune process. The aim of this study was to characterize the microbiota of the lung of patients with sarcoidosis and compare its composition and diversity with the results from patients with other interstitial lung disease (ILD) and historic healthy controls. METHODS: Patients (sarcoidosis, n = 31; interstitial lung disease, n = 19) were recruited within the PULMOHOM study, a prospective cohort study to characterize inflammatory processes in pulmonary diseases. Bronchoscopy of the middle lobe or the lingula was performed and the recovered fluid was immediately sent for analysis of the pulmonary microbiota by 16sRNA gene sequencing. Subsequent bioinformatic analysis was performed to compare the groups. RESULTS: There were no significant differences between patients with sarcoidosis or other ILDs with regard to microbiome composition and diversity. In addition, the abundance of the genera Atopobium, Fusobacterium, Mycobacterium or Propionibacterium were not different between the two groups. There were no gross differences to historical healthy controls. CONCLUSION: The analysis of the pulmonary microbiota based on 16sRNA gene sequencing did not show a significant dysbiosis in patients with sarcoidosis as compared to other ILD patients. These data do not exclude a microbiological component in the pathogenesis of sarcoidosis.

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity.

The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( https://mircarta.cs.uni-saarland.de ).

BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation.

Metagenomics-based studies of mixed microbial communities are impacting biotechnology, life sciences and medicine. Computational binning of metagenomic data is a powerful approach for the culture-independent recovery of population-resolved genomic sequences, i.e. from individual or closely related, constituent microorganisms. Existing binning solutions often require a priori characterized reference genomes and/or dedicated compute resources. Extending currently available reference-independent binning tools, we developed the BusyBee Web server for the automated deconvolution of metagenomic data into population-level genomic bins using assembled contigs (Illumina) or long reads (Pacific Biosciences, Oxford Nanopore Technologies). A reversible compression step as well as bootstrapped supervised binning enable quick turnaround times. The binning results are represented in interactive 2D scatterplots. Moreover, bin quality estimates, taxonomic annotations and annotations of antibiotic resistance genes are computed and visualized. Ground truth-based benchmarks of BusyBee Web demonstrate comparably high performance to state-of-the-art binning solutions for assembled contigs and markedly improved performance for long reads (median F1 scores: 70.02-95.21%). Furthermore, the applicability to real-world metagenomic datasets is shown. In conclusion, our reference-independent approach automatically bins assembled contigs or long reads, exhibits high sensitivity and precision, enables intuitive inspection of the results, and only requires FASTA-formatted input. The web-based application is freely accessible at: https://ccb-microbe.cs.uni-saarland.de/busybee.

miRNAs in Ancient Tissue Specimens of the Tyrolean Iceman.

The analysis of nucleic acids in ancient samples is largely limited to DNA. Small noncoding RNAs (microRNAs) are known to be evolutionary conserved and stable. To gain knowledge on miRNAs measured from ancient samples, we profiled microRNAs in cryoconserved mummies. First, we established the approach on a World War One warrior, the "Kaiserjäger", which has been preserved for almost one century. Then, we profiled seven ancient tissue specimens including skeletal muscle, stomach mucosa, stomach content and two corpus organ tissues of the 5,300-year-old copper age mummy Iceman and compared these profiles to the presence of organ-specific miRNAs in modern tissues. Our analyses suggest the presence of specific miRNAs in the different Iceman's tissues. Of 1,066 analyzed human miRNAs, 31 were discovered across all biopsies and 87 miRNAs were detected only in a single sample. To check for potential microbiological contaminations, all miRNAs detected in Iceman samples and not present in ancient samples were mapped to 14,582 bacterial and viral genomes. We detected few hits (3.9% of miRNAs compared with 3.6% of miRNAs). Interestingly, the miRNAs with higher abundance across all ancient tissues were significantly enriched for Guanine (P value of 10-13) and Cytosine (P value of 10-7). The same pattern was observed for modern tissues. Comparing miRNAs measured from ancient organs to modern tissue patterns highlighted significant similarities, e.g., for miRNAs present in the muscle. Our first comprehensive analysis of microRNAs in ancient human tissues indicates that these stable molecules can be detected in tissue specimens after 5,300 years.

Small ncRNA-Seq Results of Human Tissues: Variations Depending on Sample Integrity.

BACKGROUND: Although mature miRNAs are relatively stable in vivo, RNA degradation can have a substantial influence on small noncoding RNA (sncRNA) profiles. METHODS: Using different tissue storage conditions and RNA isolation procedures, we analyzed the integrity and quality of RNA isolates from human lung and heart tissues. We sequenced a total of 64 RNA samples and quantified the effect of RNA degradation, DNA contamination, and other confounding factors on the sncRNA-seq data. Besides microRNAs, other noncoding RNA species (piRNAs, tRNAs, snoRNAs, rRNAs) were investigated. RESULTS: Consistent with previous results, we found that the tissue specificity of microRNAs is generally well preserved. The distribution of microRNA isoforms was similar to the distribution of canonical forms. New miRNAs were more frequently discovered in degraded samples. sncRNA Reads generated from degraded samples mapped frequently to piRNAs, tRNAs, snoRNAs, or scaRNAs. Sequencing reads that were depleted of sncRNAs showed an increased mapping frequency to bacterial species. CONCLUSIONS: Our data emphasize the importance of sample integrity, especially for next-generation sequencing (NGS)-based high-throughput sncRNA profiles. For the prediction of novel miRNAs in particular, only samples with the highest RNA integrity should be used in order to avoid identification of false "miRNAs."

Prioritizing and selecting likely novel miRNAs from NGS data.

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

Deep characterization of blood cell miRNomes by NGS.

A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.

Secretion and immunogenicity of the meningioma-associated antigen TXNDC16.

In a previous study, we identified thioredoxin domain containing 16 (TXNDC16) as a meningioma-associated Ag by protein macroarray screening. Serological screening detected autoantibodies against TXNDC16 exclusively in meningioma patients' sera and not in sera of healthy controls. TXNDC16 was previously found to be an endoplasmic reticulum (ER)-luminal glycoprotein. In this study, we show an additional ER-associated localization of TXNDC16 in the cytosol by in vitro synthesis, molecular mass shift assay, and flow cytometry. We were able to show TXNDC16 secretion in different human cell lines due to masked and therefore nonfunctional ER retrieval motif. A previously indicated exosomal TXNDC16 secretion could not be confirmed in HEK293 cells. The secreted serum protein TXNDC16 is bound in circulating immune complexes, which were found both in meningioma and healthy blood donor sera. Employing a customized array with 163 overlapping TXNDC16 peptides and measuring autoantibody reactivity, we achieved discrimination of meningioma sera from healthy controls with an accuracy of 87.2% using a set of only five immunogenic TXNDC16 epitopes.

Validating Alzheimer's disease micro RNAs using next-generation sequencing.

INTRODUCTION: Molecular biomarkers for Alzheimer's disease (AD) can support detection and improved care for patients, but novel candidates require verification. We previously reported a 12-micro RNA (miRNA) blood-based signature using next-generation sequencing (NGS) of 54 AD cases and 22 controls. METHODS: We performed validation of 49 AD cases and 55 controls using NGS and also included 20 mild cognitive impairment and 90 multiple sclerosis samples to identify nonspecific markers. Thus, 103 AD cases, 77 unaffected controls, and 110 diseased controls were sequenced. Although the initial cohort came predominantly from the United States, the validation samples were collected in Germany. RESULTS: Five hundred eighty miRNAs were detected in the blood. In the initial cohort, we observed 203, in the validation cohort, 146 dysregulated miRNAs at a significance level of 0.05. With 68 miRNAs, the overlap was significant (P = .0003). Likewise, the area under the receiver operator characteristic curve values of the miRNAs correlated (correlation of 0.93; 95% confidence interval 0.89-0.96; P <10(-16)). DISCUSSION: MiRNAs have the potential to support AD diagnosis and patient care.

Influence of next-generation sequencing and storage conditions on miRNA patterns generated from PAXgene blood.

Whole blood derived miRNA signatures determined by Next-Generation Sequencing (NGS) offer themselves as future minimally invasive biomarkers for various human diseases. The PAXgene system is a commonly used blood storage system for miRNA analysis. Central to all miRNA analyses that aim to identify disease specific miRNA signatures, is the question of stability and variability of the miRNA profiles that are generated by NGS. We characterized the influence of five different conditions on the genome wide miRNA expression pattern of human blood isolated in PAXgene RNA tubes. In detail, we analyzed 15 miRNomes from three individuals. The blood was subjected to different numbers of freeze/thaw cycles and analyzed for the influence of storage at -80 or 8 °C. We also determined the influence of blood collection and NGS preparations on the miRNA pattern isolated from a single individual, which has been sequenced 10 times. Here, five PAXGene tubes were consecutively collected that have been split in two replicates, representing two experimental batches. All samples were analyzed by Illumina NGS. For each sample, approximately 20 million NGS reads have been generated. Hierarchical clustering and Principal Component Analysis (PCA) showed an influence of the different conditions on the miRNA patterns. The effects of the different conditions on miRNA abundance are, however, smaller than the differences that are due to interindividual variability. We also found evidence for an influence of the NGS measurement on the miRNA pattern. Specifically, hsa-miR-1271-5p and hsa-miR-182-5p showed coefficients of variation above 100% indicating a strong influence of the NGS protocol on the abundance of these miRNAs.

miRNAs can be generally associated with human pathologies as exemplified for miR-144.

BACKGROUND: miRNA profiles are promising biomarker candidates for a manifold of human pathologies, opening new avenues for diagnosis and prognosis. Beyond studies that describe miRNAs frequently as markers for specific traits, we asked whether a general pattern for miRNAs across many diseases exists. METHODS: We evaluated genome-wide circulating profiles of 1,049 patients suffering from 19 different cancer and non-cancer diseases as well as unaffected controls. The results were validated on 319 individuals using qRT-PCR. RESULTS: We discovered 34 miRNAs with strong disease association. Among those, we found substantially decreased levels of hsa-miR-144* and hsa-miR-20b with AUC of 0.751 (95% CI: 0.703-0.799), respectively. We also discovered a set of miRNAs, including hsa-miR-155*, as rather stable markers, offering reasonable control miRNAs for future studies. The strong downregulation of hsa-miR-144* and the less variable pattern of hsa-miR-155* has been validated in a cohort of 319 samples in three different centers. Here, breast cancer as an additional disease phenotype not included in the screening phase has been included as the 20th trait. CONCLUSIONS: Our study on 1,368 patients including 1,049 genome-wide miRNA profiles and 319 qRT-PCR validations further underscores the high potential of specific blood-borne miRNA patterns as molecular biomarkers. Importantly, we highlight 34 miRNAs that are generally dysregulated in human pathologies. Although these markers are not specific to certain diseases they may add to the diagnosis in combination with other markers, building a specific signature. Besides these dysregulated miRNAs, we propose a set of constant miRNAs that may be used as control markers.

Glacier-Fed Stream Biofilms Harbor Diverse Resistomes and Biosynthetic Gene Clusters.

Antimicrobial resistance (AMR) is a universal phenomenon the origins of which lay in natural ecological interactions such as competition within niches, within and between micro- to higher-order organisms. To study these phenomena, it is crucial to examine the origins of AMR in pristine environments, i.e., limited anthropogenic influences. In this context, epilithic biofilms residing in glacier-fed streams (GFSs) are an excellent model system to study diverse, intra- and inter-domain, ecological crosstalk. We assessed the resistomes of epilithic biofilms from GFSs across the Southern Alps (New Zealand) and the Caucasus (Russia) and observed that both bacteria and eukaryotes encoded twenty-nine distinct AMR categories. Of these, beta-lactam, aminoglycoside, and multidrug resistance were both abundant and taxonomically distributed in most of the bacterial and eukaryotic phyla. AMR-encoding phyla included Bacteroidota and Proteobacteria among the bacteria, alongside Ochrophyta (algae) among the eukaryotes. Additionally, biosynthetic gene clusters (BGCs) involved in the production of antibacterial compounds were identified across all phyla in the epilithic biofilms. Furthermore, we found that several bacterial genera (Flavobacterium, Polaromonas, Superphylum Patescibacteria) encode both atimicrobial resistance genes (ARGs) and BGCs within close proximity of each other, demonstrating their capacity to simultaneously influence and compete within the microbial community. Our findings help unravel how naturally occurring BGCs and AMR contribute to the epilithic biofilms mode of life in GFSs. Additionally, we report that eukaryotes may serve as AMR reservoirs owing to their potential for encoding ARGs. Importantly, these observations may be generalizable and potentially extended to other environments that may be more or less impacted by human activity. IMPORTANCE Antimicrobial resistance is an omnipresent phenomenon in the anthropogenically influenced ecosystems. However, its role in shaping microbial community dynamics in pristine environments is relatively unknown. Using metagenomics, we report the presence of antimicrobial resistance genes and their associated pathways in epilithic biofilms within glacier-fed streams. Importantly, we observe biosynthetic gene clusters associated with antimicrobial resistance in both pro- and eukaryotes in these biofilms. Understanding the role of resistance in the context of this pristine environment and complex biodiversity may shed light on previously uncharacterized mechanisms of cross-domain interactions.