Co-localization of antibiotic resistance genes is widespread in the infant gut microbiome and associates with an immature gut microbial composition.

BACKGROUND: In environmental bacteria, the selective advantage of antibiotic resistance genes (ARGs) can be increased through co-localization with genes such as other ARGs, biocide resistance genes, metal resistance genes, and virulence genes (VGs). The gut microbiome of infants has been shown to contain numerous ARGs, however, co-localization related to ARGs is unknown during early life despite frequent exposures to biocides and metals from an early age. RESULTS: We conducted a comprehensive analysis of genetic co-localization of resistance genes in a cohort of 662 Danish children and examined the association between such co-localization and environmental factors as well as gut microbial maturation. Our study showed that co-localization of ARGs with other resistance and virulence genes is common in the early gut microbiome and is associated with gut bacteria that are indicative of low maturity. Statistical models showed that co-localization occurred mainly in the phylum Proteobacteria independent of high ARG content and contig length. We evaluated the stochasticity of co-localization occurrence using enrichment scores. The most common forms of co-localization involved tetracycline and fluoroquinolone resistance genes, and, on plasmids, co-localization predominantly occurred in the form of class 1 integrons. Antibiotic use caused a short-term increase in mobile ARGs, while non-mobile ARGs showed no significant change. Finally, we found that a high abundance of VGs was associated with low gut microbial maturity and that VGs showed even higher potential for mobility than ARGs. CONCLUSIONS: We found that the phenomenon of co-localization between ARGs and other resistance and VGs was prevalent in the gut at the beginning of life. It reveals the diversity that sustains antibiotic resistance and therefore indirectly emphasizes the need to apply caution in the use of antimicrobial agents in clinical practice, animal husbandry, and daily life to mitigate the escalation of resistance. Video Abstract.

Escherichia coli CRISPR arrays from early life fecal samples preferentially target prophages.

CRISPR-Cas systems are defense mechanisms against phages and other nucleic acids that invade bacteria and archaea. In Escherichia coli, it is generally accepted that CRISPR-Cas systems are inactive in laboratory conditions due to a transcriptional repressor. In natural isolates, it has been shown that CRISPR arrays remain stable over the years and that most spacer targets (protospacers) remain unknown. Here, we re-examine CRISPR arrays in natural E. coli isolates and investigate viral and bacterial genomes for spacer targets using a bioinformatics approach coupled to a unique biological dataset. We first sequenced the CRISPR1 array of 1769 E. coli isolates from the fecal samples of 639 children obtained during their first year of life. We built a network with edges between isolates that reflect the number of shared spacers. The isolates grouped into 34 modules. A search for matching spacers in bacterial genomes showed that E. coli spacers almost exclusively target prophages. While we found instances of self-targeting spacers, those involving a prophage and a spacer within the same bacterial genome were rare. The extensive search for matching spacers also expanded the library of known E. coli protospacers to 60%. Altogether, these results favor the concept that E. coli's CRISPR-Cas is an antiprophage system and highlight the importance of reconsidering the criteria use to deem CRISPR-Cas systems active.

The infant gut virome is associated with preschool asthma risk independently of bacteria.

Bacteriophage (also known as phage) communities that inhabit the gut have a major effect on the structure and functioning of bacterial populations, but their roles and association with health and disease in early life remain unknown. Here, we analyze the gut virome of 647 children aged 1 year from the Copenhagen Prospective Studies on Asthma in Childhood2010 (COPSAC2010) mother-child cohort, all deeply phenotyped from birth and with longitudinally assessed asthma diagnoses. Specific temperate gut phage taxa were found to be associated with later development of asthma. In particular, the joint abundances of 19 caudoviral families were found to significantly contribute to this association. Combining the asthma-associated virome and bacteriome signatures had additive effects on asthma risk, implying an independent virome-asthma association. Moreover, the virome-associated asthma risk was modulated by the host TLR9 rs187084 gene variant, suggesting a direct interaction between phages and the host immune system. Further studies will elucidate whether phages, alongside bacteria and host genetics, can be used as preclinical biomarkers for asthma.

The airway microbiota of neonates colonized with asthma-associated pathogenic bacteria.

Culture techniques have associated colonization with pathogenic bacteria in the airways of neonates with later risk of childhood asthma, whereas more recent studies utilizing sequencing techniques have shown the same phenomenon with specific anaerobic taxa. Here, we analyze nasopharyngeal swabs from 1 month neonates in the COPSAC2000 prospective birth cohort by 16S rRNA gene sequencing of the V3-V4 region in relation to asthma risk throughout childhood. Results are compared with previous culture results from hypopharyngeal aspirates from the same cohort and with hypopharyngeal sequencing data from the later COPSAC2010 cohort. Nasopharyngeal relative abundance values of Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis are associated with the same species in the hypopharyngeal cultures. A combined pathogen score of these bacteria's abundance values is associated with persistent wheeze/asthma by age 7. No other taxa are associated. Compared to the hypopharyngeal aspirates from the COPSAC2010 cohort, the anaerobes Veillonella and Prevotella, which have previously been implicated in asthma development, are less commonly detected in the COPSAC2000 nasopharyngeal samples, but correlate with the pathogen score, hinting at latent community structures that bridge current and previous results. These findings have implications for future asthma prevention efforts.

Expanding known viral diversity in the healthy infant gut.

The gut microbiome is shaped through infancy and impacts the maturation of the immune system, thus protecting against chronic disease later in life. Phages, or viruses that infect bacteria, modulate bacterial growth by lysis and lysogeny, with the latter being especially prominent in the infant gut. Viral metagenomes (viromes) are difficult to analyse because they span uncharted viral diversity, lacking marker genes and standardized detection methods. Here we systematically resolved the viral diversity in faecal viromes from 647 1-year-olds belonging to Copenhagen Prospective Studies on Asthma in Childhood 2010, an unselected Danish cohort of healthy mother-child pairs. By assembly and curation we uncovered 10,000 viral species from 248 virus family-level clades (VFCs). Most (232 VFCs) were previously unknown, belonging to the Caudoviricetes viral class. Hosts were determined for 79% of phage using clustered regularly interspaced short palindromic repeat spacers within bacterial metagenomes from the same children. Typical Bacteroides-infecting crAssphages were outnumbered by undescribed phage families infecting Clostridiales and Bifidobacterium. Phage lifestyles were conserved at the viral family level, with 33 virulent and 118 temperate phage families. Virulent phages were more abundant, while temperate ones were more prevalent and diverse. Together, the viral families found in this study expand existing phage taxonomy and provide a resource aiding future infant gut virome research.

UG/Abi: a highly diverse family of prokaryotic reverse transcriptases associated with defense functions.

Reverse transcriptases (RTs) are enzymes capable of synthesizing DNA using RNA as a template. Within the last few years, a burst of research has led to the discovery of novel prokaryotic RTs with diverse antiviral properties, such as DRTs (Defense-associated RTs), which belong to the so-called group of unknown RTs (UG) and are closely related to the Abortive Infection system (Abi) RTs. In this work, we performed a systematic analysis of UG and Abi RTs, increasing the number of UG/Abi members up to 42 highly diverse groups, most of which are predicted to be functionally associated with other gene(s) or domain(s). Based on this information, we classified these systems into three major classes. In addition, we reveal that most of these groups are associated with defense functions and/or mobile genetic elements, and demonstrate the antiphage role of four novel groups. Besides, we highlight the presence of one of these systems in novel families of human gut viruses infecting members of the Bacteroidetes and Firmicutes phyla. This work lays the foundation for a comprehensive and unified understanding of these highly diverse RTs with enormous biotechnological potential.

A short prokaryotic Argonaute activates membrane effector to confer antiviral defense.

Argonaute (Ago) proteins are widespread nucleic-acid-guided enzymes that recognize targets through complementary base pairing. Although, in eukaryotes, Agos are involved in RNA silencing, the functions of prokaryotic Agos (pAgos) remain largely unknown. In particular, a clade of truncated and catalytically inactive pAgos (short pAgos) lacks characterization. Here, we reveal that a short pAgo protein in the archaeon Sulfolobus islandicus, together with its two genetically associated proteins, Aga1 and Aga2, provide robust antiviral protection via abortive infection. Aga2 is a toxic transmembrane effector that binds anionic phospholipids via a basic pocket, resulting in membrane depolarization and cell killing. Ago and Aga1 form a stable complex that exhibits nucleic-acid-directed nucleic-acid-recognition ability and directly interacts with Aga2, pointing to an immune sensing mechanism. Together, our results highlight the cooperation between pAgos and their widespread associated proteins, suggesting an uncharted diversity of pAgo-derived immune systems.

Genome binning of viral entities from bulk metagenomics data.

Despite the accelerating number of uncultivated virus sequences discovered in metagenomics and their apparent importance for health and disease, the human gut virome and its interactions with bacteria in the gastrointestinal tract are not well understood. This is partly due to a paucity of whole-virome datasets and limitations in current approaches for identifying viral sequences in metagenomics data. Here, combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome datasets, we develop Phages from Metagenomics Binning (PHAMB), an approach that allows the binning of thousands of viral genomes directly from bulk metagenomics data, while simultaneously enabling clustering of viral genomes into accurate taxonomic viral populations. When applied on the Human Microbiome Project 2 (HMP2) dataset, PHAMB recovered 6,077 high-quality genomes from 1,024 viral populations, and identified viral-microbial host interactions. PHAMB can be advantageously applied to existing and future metagenomes to illuminate viral ecological dynamics with other microbiome constituents.

Vaginal dysbiosis in pregnancy associates with risk of emergency caesarean section: a prospective cohort study.

OBJECTIVES: To investigate changes in vaginal microbiota during pregnancy, and the association between vaginal dysbiosis and reproductive outcomes. METHODS: A total of 730 (week 24) and 666 (week 36) vaginal samples from 738 unselected pregnant women were studied by microscopy (Nugent score) and characterized by 16S rRNA gene sequencing. A novel continuous vaginal dysbiosis score was developed based on these methods using a supervised partial least squares model. RESULTS: Among women with bacterial vaginosis in week 24 (n = 53), 47% (n = 25) also had bacterial vaginosis in week 36. In contrast, among women without bacterial vaginosis in week 24, only 3% (n = 18) developed bacterial vaginosis in week 36. Vaginal samples dominated by Lactobacillus crispatus (OR 0.35, 95% CI 0.20-0.60) and Lactobacillus iners (OR 0.40, 95% CI 0.23-0.68) in week 24 were significantly more stable by week 36 when compared with other vaginal community state types. Vaginal dysbiosis score at week 24 was associated with a significant increased risk of emergency, but not elective, caesarean section (OR 1.37, 955 CI 1.15-1.64, p < 0.001), suggesting a 37% increased risk per standard deviation increase in vaginal dysbiosis score. CONCLUSIONS: Changes in vaginal microbiota from week 24 to week 36 of pregnancy correlated with bacterial vaginosis status and vaginal community state type. A novel vaginal dysbiosis score was associated with a significantly increased risk of emergency, but not elective, caesarean section. This was not found for bacterial vaginosis or any vaginal community state type and could point to the importance of investigating vaginal dysbiosis as a nuanced continuum instead of crude clusters.

CRISPR-Cas systems are widespread accessory elements across bacterial and archaeal plasmids.

Many prokaryotes encode CRISPR-Cas systems as immune protection against mobile genetic elements (MGEs), yet a number of MGEs also harbor CRISPR-Cas components. With a few exceptions, CRISPR-Cas loci encoded on MGEs are uncharted and a comprehensive analysis of their distribution, prevalence, diversity, and function is lacking. Here, we systematically investigated CRISPR-Cas loci across the largest curated collection of natural bacterial and archaeal plasmids. CRISPR-Cas loci are widely but heterogeneously distributed across plasmids and, in comparison to host chromosomes, their mean prevalence per Mbp is higher and their distribution is distinct. Furthermore, the spacer content of plasmid CRISPRs exhibits a strong targeting bias towards other plasmids, while chromosomal arrays are enriched with virus-targeting spacers. These contrasting targeting preferences highlight the genetic independence of plasmids and suggest a major role for mediating plasmid-plasmid conflicts. Altogether, CRISPR-Cas are frequent accessory components of many plasmids, which is an overlooked phenomenon that possibly facilitates their dissemination across microbiomes.

CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems.

CRISPR-Cas systems are adaptive immune systems in prokaryotes, providing resistance against invading viruses and plasmids. The identification of CRISPR loci is currently a non-standardized, ambiguous process, requiring the manual combination of multiple tools, where existing tools detect only parts of the CRISPR-systems, and lack quality control, annotation and assessment capabilities of the detected CRISPR loci. Our CRISPRloci server provides the first resource for the prediction and assessment of all possible CRISPR loci. The server integrates a series of advanced Machine Learning tools within a seamless web interface featuring: (i) prediction of all CRISPR arrays in the correct orientation; (ii) definition of CRISPR leaders for each locus; and (iii) annotation of cas genes and their unambiguous classification. As a result, CRISPRloci is able to accurately determine the CRISPR array and associated information, such as: the Cas subtypes; cassette boundaries; accuracy of the repeat structure, orientation and leader sequence; virus-host interactions; self-targeting; as well as the annotation of cas genes, all of which have been missing from existing tools. This annotation is presented in an interactive interface, making it easy for scientists to gain an overview of the CRISPR system in their organism of interest. Predictions are also rendered in GFF format, enabling in-depth genome browser inspection. In summary, CRISPRloci constitutes a full suite for CRISPR-Cas system characterization that offers annotation quality previously available only after manual inspection.

The infant gut resistome associates with E. coli, environmental exposures, gut microbiome maturity, and asthma-associated bacterial composition.

Antimicrobial resistance (AMR) is an accelerating global threat, yet the nature of AMR in the gut microbiome and how AMR is acquired during early life remain largely unknown. In a cohort of 662 Danish children, we characterized the antibiotic resistance genes (ARGs) acquired during the first year of life and assessed the impacts of diverse environmental exposures on ARG load. Our study reveals a clear bimodal distribution of ARG richness that is driven by the composition of the gut microbiome, especially E. coli. ARG profiles were significantly affected by various environmental factors. Among these factors, the importance of antibiotics diminished with time since treatment. Finally, ARG load and ARG clusters were also associated with the maturity of the gut microbiome and a bacterial composition associated with increased risk of asthma. These findings broaden our understanding of AMR in early life and have critical implications for efforts to mitigate its spread.

Streamlining CRISPR spacer-based bacterial host predictions to decipher the viral dark matter.

Thousands of new phages have recently been discovered thanks to viral metagenomics. These phages are extremely diverse and their genome sequences often do not resemble any known phages. To appreciate their ecological impact, it is important to determine their bacterial hosts. CRISPR spacers can be used to predict hosts of unknown phages, as spacers represent biological records of past phage-bacteria interactions. However, no guidelines have been established to standardize host prediction based on CRISPR spacers. Additionally, there are no tools that use spacers to perform host predictions on large viral datasets. Here, we developed a set of tools that includes all the necessary steps for predicting the hosts of uncharacterized phages. We created a database of >11 million spacers and a program to execute host predictions on large viral datasets. Our host prediction approach uses biological criteria inspired by how CRISPR-Cas naturally work as adaptive immune systems, which make the results easy to interpret. We evaluated the performance using 9484 phages with known hosts and obtained a recall of 49% and a precision of 69%. We also found that this host prediction method yielded higher performance for phages that infect gut-associated bacteria, suggesting it is well suited for gut-virome characterization.

Large-scale association analyses identify host factors influencing human gut microbiome composition.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10-10 < P < 5 × 10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

Casboundary: automated definition of integral Cas cassettes.

MOTIVATION: CRISPR-Cas are important systems found in most archaeal and many bacterial genomes, providing adaptive immunity against mobile genetic elements in prokaryotes. The CRISPR-Cas systems are encoded by a set of consecutive cas genes, here termed cassette. The identification of cassette boundaries is key for finding cassettes in CRISPR research field. This is often carried out by using Hidden Markov Models and manual annotation. In this article, we propose the first method able to automatically define the cassette boundaries. In addition, we present a Cas-type predictive model used by the method to assign each gene located in the region defined by a cassette's boundaries a Cas label from a set of pre-defined Cas types. Furthermore, the proposed method can detect potentially new cas genes and decompose a cassette into its modules. RESULTS: We evaluate the predictive performance of our proposed method on data collected from the two most recent CRISPR classification studies. In our experiments, we obtain an average similarity of 0.86 between the predicted and expected cassettes. Besides, we achieve F-scores above 0.9 for the classification of cas genes of known types and 0.73 for the unknown ones. Finally, we conduct two additional study cases, where we investigate the occurrence of potentially new cas genes and the occurrence of module exchange between different genomes. AVAILABILITY AND IMPLEMENTATION: https://github.com/BackofenLab/Casboundary. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci.

Automated classification of CRISPR-Cas systems has been challenged by their dynamic nature and expanding classification. Here, we developed CRISPRCasTyper, an automated tool with improved capabilities for identifying and typing CRISPR arrays and cas loci based on the latest nomenclature (44 subtypes/variants). As a novel feature, CRISPRCasTyper uses a machine learning approach to subtype CRISPR arrays based on the sequences of the repeats, which allows the typing of orphan and distant arrays. CRISPRCasTyper provides a graphical output, where CRISPRs and cas operons are visualized as gene maps, thus aiding annotation of partial and novel systems through synteny. CRISPRCasTyper was benchmarked against a manually curated set of 31 subtypes with a median accuracy of 98.6% and used to explore CRISPR-Cas diversity across >3,000 metagenomes. Altogether, we present an up-to-date software for improved automated prediction of CRISPR-Cas loci. CRISPRCasTyper is available through conda and as a web server (cctyper.crispr.dk).

CRISPRcasIdentifier: Machine learning for accurate identification and classification of CRISPR-Cas systems.

BACKGROUND: CRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas systems is no longer viable. Thus, an automated approach is required for advancing our understanding of the evolution and diversity of these systems and for finding new candidates for genome engineering in eukaryotic models. RESULTS: We introduce CRISPRcasIdentifier, a new machine learning-based tool that combines regression and classification models for the prediction of potentially missing proteins in instances of CRISPR-Cas systems and the prediction of their respective subtypes. In contrast to other available tools, CRISPRcasIdentifier can both detect cas genes and extract potential association rules that reveal functional modules for CRISPR-Cas systems. In our experimental benchmark on the most recently published and comprehensive CRISPR-Cas system dataset, CRISPRcasIdentifier was compared with recent and state-of-the-art tools. According to the experimental results, CRISPRcasIdentifier presented the best Cas protein identification and subtype classification performance. CONCLUSIONS: Overall, our tool greatly extends the classification of CRISPR cassettes and, for the first time, predicts missing Cas proteins and association rules between Cas proteins. Additionally, we investigated the properties of CRISPR subtypes. The proposed tool relies not only on the knowledge of manual CRISPR annotation but also on models trained using machine learning.

Prenatal dietary supplements influence the infant airway microbiota in a randomized factorial clinical trial.

Maternal dietary interventions during pregnancy with fish oil and high dose vitamin D have been shown to reduce the incidence of asthma and wheeze in offspring, potentially through microbial effects in pregnancy or early childhood. Here we analyze the bacterial compositions in longitudinal samples from 695 pregnant women and their children according to intervention group in a nested, factorial, double-blind, placebo-controlled, randomized trial of n-3 long-chain fatty acids and vitamin D supplementation. The dietary interventions affect the infant airways, but not the infant fecal or maternal vaginal microbiota. Changes in overall beta diversity are observed, which in turn associates with a change in immune mediator profile. In addition, airway microbial maturation and the relative abundance of specific bacterial genera are altered. Furthermore, mediation analysis reveals the changed airway microbiota to be a minor and non-significant mediator of the protective effect of the dietary interventions on risk of asthma. Our results demonstrate the potential of prenatal dietary supplements as manipulators of the early airway bacterial colonization.

Virulent coliphages in 1-year-old children fecal samples are fewer, but more infectious than temperate coliphages.

Bacteriophages constitute an important part of the human gut microbiota, but their impact on this community is largely unknown. Here, we cultivate temperate phages produced by 900 E. coli strains isolated from 648 fecal samples from 1-year-old children and obtain coliphages directly from the viral fraction of the same fecal samples. We find that 63% of strains hosted phages, while 24% of the viromes contain phages targeting E. coli. 150 of these phages, half recovered from strain supernatants, half from virome (73% temperate and 27% virulent) were tested for their host range on 75 E. coli strains isolated from the same cohort. Temperate phages barely infected the gut strains, whereas virulent phages killed up to 68% of them. We conclude that in fecal samples from children, temperate coliphages dominate, while virulent ones have greater infectivity and broader host range, likely playing a role in gut microbiota dynamics.

Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants.

The number and diversity of known CRISPR-Cas systems have substantially increased in recent years. Here, we provide an updated evolutionary classification of CRISPR-Cas systems and cas genes, with an emphasis on the major developments that have occurred since the publication of the latest classification, in 2015. The new classification includes 2 classes, 6 types and 33 subtypes, compared with 5 types and 16 subtypes in 2015. A key development is the ongoing discovery of multiple, novel class 2 CRISPR-Cas systems, which now include 3 types and 17 subtypes. A second major novelty is the discovery of numerous derived CRISPR-Cas variants, often associated with mobile genetic elements that lack the nucleases required for interference. Some of these variants are involved in RNA-guided transposition, whereas others are predicted to perform functions distinct from adaptive immunity that remain to be characterized experimentally. The third highlight is the discovery of numerous families of ancillary CRISPR-linked genes, often implicated in signal transduction. Together, these findings substantially clarify the functional diversity and evolutionary history of CRISPR-Cas.