Genome-resolved metagenomics using environmental and clinical samples

Metagenomic approaches and opportunities in arid soil research

Arid soils present unique challenges and opportunities for studying microbial diversity and bioactive potential due to the extreme environmental conditions they bear. This review article investigates soil metagenomics as an emerging tool to explore complex microbial dynamics and unexplored bioactive potential in harsh environments. Utilizing advanced metagenomic techniques, diverse microbial populations that grow under extreme conditions such as high temperatures, salinity, high pH levels, and exposure to metals and radiation can be studied. The use of extremophiles to discover novel natural products and biocatalysts emphasizes the role of functional metagenomics in identifying enzymes and secondary metabolites for industrial and pharmaceutical purposes. Metagenomic sequencing uncovers a complex network of microbial diversity, offering significant potential for discovering new bioactive compounds. Functional metagenomics, connecting taxonomic diversity to genetic capabilities, provides a pathway to identify microbes' mechanisms to synthesize valuable secondary metabolites and other bioactive substances. Contrary to the common perception of desert soil as barren land, the metagenomic analysis reveals a rich diversity of life forms adept at extreme survival. It provides valuable findings into their resilience and potential applications in biotechnology. Moreover, the challenges associated with metagenomics in arid soils, such as low microbial biomass, high DNA degradation rates, and DNA extraction inhibitors and strategies to overcome these issues, outline the latest advancements in extraction methods, high-throughput sequencing, and bioinformatics. The importance of metagenomics for investigating diverse environments opens the way for future research to develop sustainable solutions in agriculture, industry, and medicine. Extensive studies are necessary to utilize the full potential of these powerful microbial communities. This research will significantly improve our understanding of microbial ecology and biotechnology in arid environments.

Insights into gut fungi in pigs: A comprehensive review

Fungi in the gut microbiota of mammals play a crucial role in host physiological regulation, including intestinal homeostasis and host immune regulation. However, our understanding of gut fungi in mammals remains limited, especially in economically valuable animals, such as pigs. Therefore, this review first describes the classification and characterisation of fungi, provides insights into the methods used to study gut fungi, and summarises the recent progress on pig gut fungi. Additionally, it discusses the challenges in the study of pig gut fungi and highlights potential perspectives. The aim of this review is to serve as a valuable reference for advancing our knowledge of gut fungi in animals.

Limitation of amino acid availability by bacterial populations during enhanced colitis in IBD mouse model

IMPORTANCE

Inflammatory bowel disease is associated with an increase in Enterobacteriaceae and Enterococcus species; however, the specific mechanisms are unclear. Previous research has reported the associations between microbiota and inflammation, here we investigate potential pathways that specific bacteria populations use to drive gut inflammation. Richie et al. show that these bacterial populations utilize an alternate sulfur metabolism and are tolerant of host-derived immune-response products. These metabolic pathways drive host gut inflammation and fuel over colonization of these pathobionts in the dysbiotic colon. Cultured isolates from dysbiotic mice indicated faster growth supplemented with L-cysteine, showing these microbes can utilize essential host nutrients.

The Raphidiopsis (= Cylindrospermopsis) raciborskii pangenome updated: Two new metagenome-assembled genomes from the South American clade

Two Raphidiopsis (=Cylindrospermopsis) raciborskii metagenome-assembled genomes (MAGs) were recovered from two freshwater metagenomic datasets sampled in 2011 and 2012 in Pampulha Lake, a hypereutrophic, artificial, shallow reservoir, located in the city of Belo Horizonte (MG), Brazil. Since the late 1970s, the lake has undergone increasing eutrophication pressure, due to wastewater input, leading to the occurrence of frequent cyanobacterial blooms. The major difference observed between PAMP2011 and PAMP2012 MAGs was the lack of the saxitoxin gene cluster in PAMP2012, which also presented a smaller genome, while PAMP2011 presented the complete sxt cluster and all essential proteins and clusters. The pangenome analysis was performed with all Raphidiopsis/Cylindrospermopsis genomes available at NCBI to date, with the addition of PAMP2011 and PAMP2012 MAGs (All33 subset), but also without the South American strains (noSA subset), and only among the South American strains (SA10 and SA8 subsets). We observed a substantial increase in the core genome size for the 'noSA' subset, in comparison to 'All33' subset, and since the core genome reflects the closeness among the pangenome members, the results strongly suggest that the conservation level of the essential gene repertoire seems to be affected by the geographic origin of the strains being analyzed, supporting the existence of a distinct SA clade. The Raphidiopsis pangenome comprised a total of 7943 orthologous protein clusters, and the two new MAGs increased the pangenome size by 11%. The pangenome based phylogenetic relationships among the 33 analyzed genomes showed that the SA genomes clustered together with 99% bootstrap support, reinforcing the metabolic particularity of the Raphidiopsis South American clade, related to its saxitoxin producing unique ability, while also indicating a different evolutionary history due to its geographic isolation.

ACR: metagenome-assembled prokaryotic and eukaryotic genome refinement tool

Microbial genome recovery from metagenomes can further explain microbial ecosystem structures, functions and dynamics. Thus, this study developed the Additional Clustering Refiner (ACR) to enhance high-purity prokaryotic and eukaryotic metagenome-assembled genome (MAGs) recovery. ACR refines low-quality MAGs by subjecting them to iterative k-means clustering predicated on contig abundance and increasing bin purity through validated universal marker genes. Synthetic and real-world metagenomic datasets, including short- and long-read sequences, evaluated ACR's effectiveness. The results demonstrated improved MAG purity and a significant increase in high- and medium-quality MAG recovery rates. In addition, ACR seamlessly integrates with various binning algorithms, augmenting their strengths without modifying core features. Furthermore, its multiple sequencing technology compatibilities expand its applicability. By efficiently recovering high-quality prokaryotic and eukaryotic genomes, ACR is a promising tool for deepening our understanding of microbial communities through genome-centric metagenomics.

MGnify Genomes: A Resource for Biome-specific Microbial Genome Catalogues

An increasingly common output arising from the analysis of shotgun metagenomic datasets is the generation of metagenome-assembled genomes (MAGs), with tens of thousands of MAGs now described in the literature. However, the discovery and comparison of these MAG collections is hampered by the lack of uniformity in their generation, annotation and storage. To address this, we have developed MGnify Genomes, a growing collection of biome-specific non-redundant microbial genome catalogues generated using MAGs and publicly available isolate genomes. Genomes within a biome-specific catalogue are organised into species clusters. For species that contain multiple conspecific genomes, the highest quality genome is selected as the representative, always prioritising an isolate genome over a MAG. The species representative sequences and annotations can be visualised on the MGnify website and the full catalogue and associated analysis outputs can be downloaded from MGnify servers. A suite of online search tools is provided allowing users to compare their own sequences, ranging from a gene to sets of genomes, against the catalogues. Seven biomes are available currently, comprising over 300,000 genomes that represent 11,048 non-redundant species, and include 36 taxonomic classes not currently represented by cultured genomes. MGnify Genomes is available at https://www.ebi.ac.uk/metagenomics/browse/genomes/.

Contamination detection and microbiome exploration with GRIMER

BACKGROUND

Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.

RESULTS

We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.

CONCLUSION

GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.

Advances in experimental and computational methodologies for the study of microbial-surface interactions at different omics levels

The study of the biological response of microbial cells interacting with natural and synthetic interfaces has acquired a new dimension with the development and constant progress of advanced omics technologies. New methods allow the isolation and analysis of nucleic acids, proteins and metabolites from complex samples, of interest in diverse research areas, such as materials sciences, biomedical sciences, forensic sciences, biotechnology and archeology, among others. The study of the bacterial recognition and response to surface contact or the diagnosis and evolution of ancient pathogens contained in archeological tissues require, in many cases, the availability of specialized methods and tools. The current review describes advances in in vitro and in silico approaches to tackle existing challenges (e.g., low-quality sample, low amount, presence of inhibitors, chelators, etc.) in the isolation of high-quality samples and in the analysis of microbial cells at genomic, transcriptomic, proteomic and metabolomic levels, when present in complex interfaces. From the experimental point of view, tailored manual and automatized methodologies, commercial and in-house developed protocols, are described. The computational level focuses on the discussion of novel tools and approaches designed to solve associated issues, such as sample contamination, low quality reads, low coverage, etc. Finally, approaches to obtain a systems level understanding of these complex interactions by integrating multi omics datasets are presented.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Constructing metagenome-assembled genomes for almost all components in a real bacterial consortium for binning benchmarking

BACKGROUND

So far, a lot of binning approaches have been intensively developed for untangling metagenome-assembled genomes (MAGs) and evaluated by two main strategies. The strategy by comparison to known genomes prevails over the other strategy by using single-copy genes. However, there is still no dataset with all known genomes for a real (not simulated) bacterial consortium yet.

RESULTS

Here, we continue investigating the real bacterial consortium F1RT enriched and sequenced by us previously, considering the high possibility to unearth all MAGs, due to its low complexity. The improved F1RT metagenome reassembled by metaSPAdes here utilizes about 98.62% of reads, and a series of analyses for the remaining reads suggests that the possibility of containing other low-abundance organisms in F1RT is greatly low, demonstrating that almost all MAGs are successfully assembled. Then, 4 isolates are obtained and individually sequenced. Based on the 4 isolate genomes and the entire metagenome, an elaborate pipeline is then in-house developed to construct all F1RT MAGs. A series of assessments extensively prove the high reliability of the herein reconstruction. Next, our findings further show that this dataset harbors several properties challenging for binning and thus is suitable to compare advanced binning tools available now or benchmark novel binners. Using this dataset, 8 advanced binning algorithms are assessed, giving useful insights for developing novel approaches. In addition, compared with our previous study, two novel MAGs termed FC8 and FC9 are discovered here, and 7 MAGs are solidly unearthed for species without any available genomes.

CONCLUSION

To our knowledge, it is the first time to construct a dataset with almost all known MAGs for a not simulated consortium. We hope that this dataset will be used as a routine toolkit to complement mock datasets for evaluating binning methods to further facilitate binning and metagenomic studies in the future.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

Genome-Resolved Characterization of Structure and Potential Functions of the Zebrafish Stool Microbiome

Zebrafish have been used as a model organism for more than 50 years and are considered an excellent model for studying host-microbiome interactions. However, this largely depends on our understanding of the zebrafish gut microbiome itself. Despite advances in sequencing and data analysis methods, the zebrafish gut microbiome remains highly understudied. This study performed the de novo metagenome assembly and recovery of the metagenome-assembled genomes (MAGs) through genome binning (and refinement) of the contigs assembled from the zebrafish stool. The results indicate that majority of the MAGs had excellent quality i.e. high completeness (≥90%) and low contamination levels (≤5%). MAGs mainly belong to the taxa that are known to be members of the core zebrafish stool microbiome, including the phylum Proteobacteria, Fusobacteriota, and Actinobacteriota. However, most of the MAGs remained unclassified at the species level and reflected previously unexplored microbial taxa and their potential novelty. These MAGs also contained genes with predicted functions associated with diverse metabolic pathways that included carbohydrate, amino acid, and lipid metabolism pathways. Lastly, we performed a comparative analysis of Paucibacter MAGs and reference genomes that highlighted the presence of novel Paucibacter species and enriched metabolic potential in the recovered MAGs.

Exploring Newer Biosynthetic Gene Clusters in Marine Microbial Prospecting

Marine microbes genetically evolved to survive varying salinity, temperature, pH, and other stress factors by producing different bioactive metabolites. These microbial secondary metabolites (SMs) are novel, have high potential, and could be used as lead molecule. Genome sequencing of microbes revealed that they have the capability to produce numerous novel bioactive metabolites than observed under standard in vitro culture conditions. Microbial genome has specific regions responsible for SM assembly, termed biosynthetic gene clusters (BGCs), possessing all the necessary genes to encode different enzymes required to generate SM. In order to augment the microbial chemo diversity and to activate these gene clusters, various tools and techniques are developed. Metagenomics with functional gene expression studies aids in classifying novel peptides and enzymes and also in understanding the biosynthetic pathways. Genome shuffling is a high-throughput screening approach to improve the development of SMs by incorporating genomic recombination. Transcriptionally silent or lower level BGCs can be triggered by artificially knocking promoter of target BGC. Additionally, bioinformatic tools like antiSMASH, ClustScan, NAPDOS, and ClusterFinder are effective in identifying BGCs of existing class for annotation in genomes. This review summarizes the significance of BGCs and the different approaches for detecting and elucidating BGCs from marine microbes.

The Notable Achievements and the Prospects of Bacterial Pathogen Genomics

Throughout the entirety of human history, bacterial pathogens have played an important role and even shaped the fate of civilizations. The application of genomics within the last 27 years has radically changed the way we understand the biology and evolution of these pathogens. In this review, we discuss how the short- (Illumina) and long-read (PacBio, Oxford Nanopore) sequencing technologies have shaped the discipline of bacterial pathogen genomics, in terms of fundamental research (i.e., evolution of pathogenicity), forensics, food safety, and routine clinical microbiology. We have mined and discuss some of the most prominent data/bioinformatics resources such as NCBI pathogens, PATRIC, and Pathogenwatch. Based on this mining, we present some of the most popular sequencing technologies, hybrid approaches, assemblers, and annotation pipelines. A small number of bacterial pathogens are of very high importance, and we also present the wealth of the genomic data for these species (i.e., which ones they are, the number of antimicrobial resistance genes per genome, the number of virulence factors). Finally, we discuss how this discipline will probably be transformed in the near future, especially by transitioning into metagenome-assembled genomes (MAGs), thanks to long-read sequencing.

BugSplit enables genome-resolved metagenomics through highly accurate taxonomic binning of metagenomic assemblies

A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplit's taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplit's taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic .

A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data

Metagenomic sequencing provides a culture-independent avenue to investigate the complex microbial communities by constructing metagenome-assembled genomes (MAGs). A MAG represents a microbial genome by a group of sequences from genome assembly with similar characteristics. It enables us to identify novel species and understand their potential functions in a dynamic ecosystem. Many computational tools have been developed to construct and annotate MAGs from metagenomic sequencing, however, there is a prominent gap to comprehensively introduce their background and practical performance. In this paper, we have thoroughly investigated the computational tools designed for both upstream and downstream analyses, including metagenome assembly, metagenome binning, gene prediction, functional annotation, taxonomic classification, and profiling. We have categorized the commonly used tools into unique groups based on their functional background and introduced the underlying core algorithms and associated information to demonstrate a comparative outlook. Furthermore, we have emphasized the computational requisition and offered guidance to the users to select the most efficient tools. Finally, we have indicated current limitations, potential solutions, and future perspectives for further improving the tools of MAG construction and annotation. We believe that our work provides a consolidated resource for the current stage of MAG studies and shed light on the future development of more effective MAG analysis tools on metagenomic sequencing.