MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities

A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases

The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.

Insights into Prime Editing Technology: A Deep Dive into Fundamentals, Potentials and Challenges

As the most versatile and precise gene editing technology, prime editing (PE) can establish a durable cure for most human genetic disorders. Several generations of PE have been developed based on an editor machine or pegRNA to achieve any kind of genetic correction. However, due to the early stage of development, PE complex elements need to be optimized for more efficient editing. Smart optimization of editor proteins as well as pegRNA has been contemplated by many researchers but the universal PE machine's current shortcomings remain to be solved. The modification of PE elements, fine-tuning of the host genes, manipulation of epigenetics, and blockage of immune responses could be employed to reach more efficient prime editing. Moreover, the host factors involved in the PE process, such as repair and innate immune system genes have not been determined, and PE cell context-dependency is still poorly understood. Regarding the large size of the PE elements, delivery is a significant challenge and the development of a universal viral or non-viral platform is still far from complete. PE versions with shortened variants of RT are still too large to fit in common viral vectors. Immune reactions against PE elements and delivery vectors should be considered in the new versions. The prediction of the prime editing process remains to be improved for screening and validation purposes. In this review, the fundamentals of PE, including generations, potential, optimization, delivery, in vivo barriers, and the future landscape of the technology will be discussed.

Pangenome analysis reveals transposon-driven genome evolution in cotton

BACKGROUND

Transposable elements (TEs) have a profound influence on the trajectory of plant evolution, driving genome expansion and catalyzing phenotypic diversification. The pangenome, a comprehensive genetic pool encompassing all variations within a species, serves as an invaluable tool, unaffected by the confounding factors of intraspecific diversity. This allows for a more nuanced exploration of plant TE evolution.

RESULTS

Here, we constructed a pangenome for diploid A-genome cotton using 344 accessions from representative geographical regions, including 223 from China as the main component. We found 511 Mb of non-reference sequences (NRSs) and revealed the presence of 5479 previously undiscovered protein-coding genes. Our comprehensive approach enabled us to decipher the genetic underpinnings of the distinct geographic distributions of cotton. Notably, we identified 3301 presence-absence variations (PAVs) that are closely tied to gene expression patterns within the pangenome, among which 2342 novel expression quantitative trait loci (eQTLs) were found residing in NRSs. Our investigation also unveiled contrasting patterns of transposon proliferation between diploid and tetraploid cotton, with long terminal repeat (LTR) retrotransposons exhibiting a synchronized surge in polyploids. Furthermore, the invasion of LTR retrotransposons from the A subgenome to the D subgenome triggered a substantial expansion of the latter following polyploidization. In addition, we found that TE insertions were responsible for the loss of 36.2% of species-specific genes, as well as the generation of entirely new species-specific genes.

CONCLUSIONS

Our pangenome analyses provide new insights into cotton genomics and subgenome dynamics after polyploidization and demonstrate the power of pangenome approaches for elucidating transposon impacts and genome evolution.

Adverse Environmental Perturbations May Threaten Kelp Farming Sustainability by Exacerbating Enterobacterales Diseases

Globally kelp farming is gaining attention to mitigate land-use pressures and achieve carbon neutrality. However, the influence of environmental perturbations on kelp farming remains largely unknown. Recently, a severe disease outbreak caused extensive kelp mortality in Sanggou Bay, China, one of the world's largest high-density kelp farming areas. Here, through in situ investigations and simulation experiments, we find indications that an anomalously dramatic increase in elevated coastal seawater light penetration may have contributed to dysbiosis in the kelp Saccharina japonica's microbiome. This dysbiosis promoted the proliferation of opportunistic pathogenic Enterobacterales, mainly including the genera Colwellia and Pseudoalteromonas. Using transcriptomic analyses, we revealed that high-light conditions likely induced oxidative stress in kelp, potentially facilitating opportunistic bacterial Enterobacterales attack that activates a terrestrial plant-like pattern recognition receptor system in kelp. Furthermore, we uncover crucial genotypic determinants of Enterobacterales dominance and pathogenicity within kelp tissue, including pathogen-associated molecular patterns, potential membrane-damaging toxins, and alginate and mannitol lysis capability. Finally, through analysis of kelp-associated microbiome data sets under the influence of ocean warming and acidification, we conclude that such Enterobacterales favoring microbiome shifts are likely to become more prevalent in future environmental conditions. Our study highlights the need for understanding complex environmental influences on kelp health and associated microbiomes for the sustainable development of seaweed farming.

Genome-resolved metagenomics identifies novel active microbes in biogeochemical cycling within methanol-enriched soil

Metagenome assembled genomes (MAGs), generated from sequenced 13C-labelled DNA from 13C-methanol enriched soils, were binned using an ensemble approach. This method produced a significantly larger number of higher-quality MAGs compared to direct binning approaches. These MAGs represent both the primary methanol utilizers and the secondary utilizers labelled via cross-feeding and predation on the labelled methylotrophs, including numerous uncultivated taxa. Analysis of these MAGs enabled the identification of multiple metabolic pathways within these active taxa that have climatic relevance relating to nitrogen, sulfur and trace gas metabolism. This includes denitrification, dissimilatory nitrate reduction to ammonium, ammonia oxidation and metabolism of organic sulfur species. The binning of viral sequence data also yielded extensive viral MAGs, identifying active viral replication by both lytic and lysogenic phages within the methanol-enriched soils. These MAGs represent a valuable resource for characterizing biogeochemical cycling within terrestrial environments.

Recovery of 1887 metagenome-assembled genomes from the South China Sea

The South China Sea (SCS) is a marginal sea characterized by strong land-sea biogeochemical interactions. SCS has a distinctive landscape with a multitude of seamounts in its basin. Seamounts create "seamount effects" that influence the diversity and distribution of planktonic microorganisms in the surrounding oligotrophic waters. Although the vertical distribution and community structure of marine microorganisms have been explored in certain regions of the global ocean, there is a lack of comprehensive microbial genomic surveys for uncultured microorganisms in SCS, particularly in the seamount regions. Here, we employed a metagenomic approach to study the uncultured microbial communities sampled from the Xianbei seamount region to the North Coast waters of SCS. A total of 1887 non-redundant prokaryotic metagenome-assembled genomes (MAGs) were reconstructed, of which, 153 MAGs were classified as high-quality MAGs based on the MIMAG standards. The community structure and genomic information provided by this dataset could be used to analyze microbial distribution and metabolism in the SCS.

Duck pan-genome reveals two transposon insertions caused bodyweight enlarging and white plumage phenotype formation during evolution

Structural variations (SVs) are a major source of domestication and improvement traits. We present the first duck pan-genome constructed using five genome assemblies capturing ∼40.98 Mb new sequences. This pan-genome together with high-depth sequencing data (∼46.5×) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to duck's domestication and improvement. By combining quantitative genetics with molecular experiments, we, for the first time, unraveled a 6945 bp Gypsy insertion as a functional mutation of the major gene IGF2BP1 associated with duck bodyweight. This Gypsy insertion, to our knowledge, explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). In addition, we also examined another 6634 bp Gypsy insertion in MITF intron, which triggers a novel transcript of MITF, thereby contributing to the development of white plumage. Our findings highlight the importance of using a pan-genome as a reference in genomics studies and illuminate the impact of transposons in trait formation and livestock breeding.

Effective binning of metagenomic contigs using contrastive multi-view representation learning

Contig binning plays a crucial role in metagenomic data analysis by grouping contigs from the same or closely related genomes. However, existing binning methods face challenges in practical applications due to the diversity of data types and the difficulties in efficiently integrating heterogeneous information. Here, we introduce COMEBin, a binning method based on contrastive multi-view representation learning. COMEBin utilizes data augmentation to generate multiple fragments (views) of each contig and obtains high-quality embeddings of heterogeneous features (sequence coverage and k-mer distribution) through contrastive learning. Experimental results on multiple simulated and real datasets demonstrate that COMEBin outperforms state-of-the-art binning methods, particularly in recovering near-complete genomes from real environmental samples. COMEBin outperforms other binning methods remarkably when integrated into metagenomic analysis pipelines, including the recovery of potentially pathogenic antibiotic-resistant bacteria (PARB) and moderate or higher quality bins containing potential biosynthetic gene clusters (BGCs).

Alignment-based Protein Mutational Landscape Prediction: Doing More with Less

The wealth of genomic data has boosted the development of computational methods predicting the phenotypic outcomes of missense variants. The most accurate ones exploit multiple sequence alignments, which can be costly to generate. Recent efforts for democratizing protein structure prediction have overcome this bottleneck by leveraging the fast homology search of MMseqs2. Here, we show the usefulness of this strategy for mutational outcome prediction through a large-scale assessment of 1.5M missense variants across 72 protein families. Our study demonstrates the feasibility of producing alignment-based mutational landscape predictions that are both high-quality and compute-efficient for entire proteomes. We provide the community with the whole human proteome mutational landscape and simplified access to our predictive pipeline.

Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing

MOTIVATION

Metagenomic binning methods to reconstruct metagenome-assembled genomes (MAGs) from environmental samples have been widely used in large-scale metagenomic studies. The recently proposed semi-supervised binning method, SemiBin, achieved state-of-the-art binning results in several environments. However, this required annotating contigs, a computationally costly and potentially biased process.

RESULTS

We propose SemiBin2, which uses self-supervised learning to learn feature embeddings from the contigs. In simulated and real datasets, we show that self-supervised learning achieves better results than the semi-supervised learning used in SemiBin1 and that SemiBin2 outperforms other state-of-the-art binners. Compared to SemiBin1, SemiBin2 can reconstruct 8.3-21.5% more high-quality bins and requires only 25% of the running time and 11% of peak memory usage in real short-read sequencing samples. To extend SemiBin2 to long-read data, we also propose ensemble-based DBSCAN clustering algorithm, resulting in 13.1-26.3% more high-quality genomes than the second best binner for long-read data.

AVAILABILITY AND IMPLEMENTATION

SemiBin2 is available as open source software at https://github.com/BigDataBiology/SemiBin/ and the analysis scripts used in the study can be found at https://github.com/BigDataBiology/SemiBin2_benchmark.

A survey on computational strategies for genome-resolved gut metagenomics

Recovering high-quality metagenome-assembled genomes (HQ-MAGs) is critical for exploring microbial compositions and microbe-phenotype associations. However, multiple sequencing platforms and computational tools for this purpose may confuse researchers and thus call for extensive evaluation. Here, we systematically evaluated a total of 40 combinations of popular computational tools and sequencing platforms (i.e. strategies), involving eight assemblers, eight metagenomic binners and four sequencing technologies, including short-, long-read and metaHiC sequencing. We identified the best tools for the individual tasks (e.g. the assembly and binning) and combinations (e.g. generating more HQ-MAGs) depending on the availability of the sequencing data. We found that the combination of the hybrid assemblies and metaHiC-based binning performed best, followed by the hybrid and long-read assemblies. More importantly, both long-read and metaHiC sequencings link more mobile elements and antibiotic resistance genes to bacterial hosts and improve the quality of public human gut reference genomes with 32% (34/105) HQ-MAGs that were either of better quality than those in the Unified Human Gastrointestinal Genome catalog version 2 or novel.

Closed genomes uncover a saltwater species of Candidatus Electronema and shed new light on the boundary between marine and freshwater cable bacteria

Cable bacteria of the Desulfobulbaceae family are centimeter-long filamentous bacteria, which are capable of conducting long-distance electron transfer. Currently, all cable bacteria are classified into two candidate genera: Candidatus Electronema, typically found in freshwater environments, and Candidatus Electrothrix, typically found in saltwater environments. This taxonomic framework is based on both 16S rRNA gene sequences and metagenome-assembled genome (MAG) phylogenies. However, most of the currently available MAGs are highly fragmented, incomplete, and thus likely miss key genes essential for deciphering the physiology of cable bacteria. Also, a closed, circular genome of cable bacteria has not been published yet. To address this, we performed Nanopore long-read and Illumina short-read shotgun sequencing of selected environmental samples and a single-strain enrichment of Ca. Electronema aureum. We recovered multiple cable bacteria MAGs, including two circular and one single-contig. Phylogenomic analysis, also confirmed by 16S rRNA gene-based phylogeny, classified one circular MAG and the single-contig MAG as novel species of cable bacteria, which we propose to name Ca. Electronema halotolerans and Ca. Electrothrix laxa, respectively. The Ca. Electronema halotolerans, despite belonging to the previously recognized freshwater genus of cable bacteria, was retrieved from brackish-water sediment. Metabolic predictions showed several adaptations to a high salinity environment, similar to the "saltwater" Ca. Electrothrix species, indicating how Ca. Electronema halotolerans may be the evolutionary link between marine and freshwater cable bacteria lineages.