Struo2: efficient metagenome profiling database construction for ever-expanding microbial genome datasets

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

Spatial analysis of murine microbiota and bile acid metabolism during amoxicillin treatment

Antibiotics cause collateral damage to resident microbes that is associated with various health risks. To date, studies have largely focused on the impacts of antibiotics on large intestinal and fecal microbiota. Here, we employ a gastrointestinal (GI) tract-wide integrated multiomic approach to show that amoxicillin (AMX) treatment reduces bacterial abundance, bile salt hydrolase activity, and unconjugated bile acids in the small intestine (SI). Losses of fatty acids (FAs) and increases in acylcarnitines in the large intestine (LI) correspond with spatially distinct expansions of Proteobacteria. Parasutterella excrementihominis engage in FA biosynthesis in the SI, while multiple Klebsiella species employ FA oxidation during expansion in the LI. We subsequently demonstrate that restoration of unconjugated bile acids can mitigate losses of commensals in the LI while also inhibiting the expansion of Proteobacteria during AMX treatment. These results suggest that the depletion of bile acids and lipids may contribute to AMX-induced dysbiosis in the lower GI tract.

MetaBakery: a Singularity implementation of bioBakery tools as a skeleton application for efficient HPC deconvolution of microbiome metagenomic sequencing data to machine learning ready information

In this study, we present MetaBakery (http://metabakery.fe.uni-lj.si), an integrated application designed as a framework for synergistically executing the bioBakery workflow and associated utilities. MetaBakery streamlines the processing of any number of paired or unpaired fastq files, or a mixture of both, with optional compression (gzip, zip, bzip2, xz, or mixed) within a single run. MetaBakery uses programs such as KneadData (https://github.com/bioBakery/kneaddata), MetaPhlAn, HUMAnN and StrainPhlAn as well as integrated utilities and extends the original functionality of bioBakery. In particular, it includes MelonnPan for the prediction of metabolites and Mothur for calculation of microbial alpha diversity. Written in Python 3 and C++ the whole pipeline was encapsulated as Singularity container for efficient execution on various computing infrastructures, including large High-Performance Computing clusters. MetaBakery facilitates crash recovery, efficient re-execution upon parameter changes, and processing of large data sets through subset handling and is offered in three editions with bioBakery ingredients versions 4, 3 and 2 as versatile, transparent and well documented within the MetaBakery Users' Manual (http://metabakery.fe.uni-lj.si/metabakery_manual.pdf). It provides automatic handling of command line parameters, file formats and comprehensive hierarchical storage of output to simplify navigation and debugging. MetaBakery filters out potential human contamination and excludes samples with low read counts. It calculates estimates of alpha diversity and represents a comprehensive and augmented re-implementation of the bioBakery workflow. The robustness and flexibility of the system enables efficient exploration of changing parameters and input datasets, increasing its utility for microbiome analysis. Furthermore, we have shown that the MetaBakery tool can be used in modern biostatistical and machine learning approaches including large-scale microbiome studies.

Genomic representativeness and chimerism in large collections of SAGs and MAGs of marine prokaryoplankton

BACKGROUND

Single amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) are the predominant sources of information about the coding potential of uncultured microbial lineages, but their strengths and limitations remain poorly understood. Here, we performed a direct comparison of two previously published collections of thousands of SAGs and MAGs obtained from the same, global environment.

RESULTS

We found that SAGs were less prone to chimerism and more accurately reflected the relative abundance and the pangenome content of microbial lineages inhabiting the epipelagic of the tropical and subtropical ocean, as compared to MAGs. SAGs were also better suited to link genome information with taxa discovered through 16S rRNA amplicon analyses. Meanwhile, MAGs had the advantage of more readily recovering genomes of rare lineages.

CONCLUSIONS

Our analyses revealed the relative strengths and weaknesses of the two most commonly used genome recovery approaches in environmental microbiology. These considerations, as well as the need for better tools for genome quality assessment, should be taken into account when designing studies and interpreting data that involve SAGs or MAGs. Video Abstract.

Effects of combined ciprofloxacin and Neulasta therapy on intestinal pathology and gut microbiota after high-dose irradiation in mice

Introduction

Treatments that currently exist in the strategic national stockpile for acute radiation syndrome (ARS) focus on the hematopoietic subsyndrome, with no treatments on gastrointestinal (GI)-ARS. While the gut microbiota helps maintain host homeostasis by mediating GI epithelial and mucosal integrity, radiation exposure can alter gut commensal microbiota which may leave the host susceptible to opportunistic pathogens and serious sequelae such as sepsis. To mitigate the effects of hematopoietic ARS irradiation, currently approved treatments exist in the form of colony stimulating factors and antibiotics: however, there are few studies examining how these therapeutics affect GI-ARS and the gut microbiota. The aim of our study was to examine the longitudinal effects of Neulasta and/or ciprofloxacin treatment on the gut microbiota after exposure to 9.5 Gy 60Co gamma-radiation in mice.

Methods

The gut microbiota of vehicle and drug-treated mice exposed to sham or gamma-radiation was characterized by shotgun sequencing with alpha diversity, beta diversity, and taxonomy analyzed on days 2, 4, 9, and 15 post-irradiation.

Results

No significant alpha diversity differences were observed following radiation, while beta diversity shifts and taxonomic profiles revealed significant alterations in Akkermansia, Bacteroides, and Lactobacillus. Ciprofloxacin generally led to lower Shannon diversity and Bacteroides prevalence with increases in Akkermansia and Lactobacillus compared to vehicle treated and irradiated mice. While Neulasta increased Shannon diversity and by day 9 had more similar taxonomic profiles to sham than ciprofloxacin-or vehicle-treated irradiated animals. Combined therapy of Neulasta and ciprofloxacin induced a decrease in Shannon diversity and resulted in unique taxonomic profiles early post-irradiation, returning closer to vehicle-treated levels over time, but persistent increases in Akkermansia and Bacteroides compared to Neulasta alone.

Discussion

This study provides a framework for the identification of microbial elements that may influence radiosensitivity, biodosimetry and the efficacy of potential therapeutics. Moreover, increased survival from H-ARS using these therapeutics may affect the symptoms and appearance of what may have been subclinical GI-ARS.

Ferroptosis, Inflammation, and Microbiome Alterations in the Intestine in the Göttingen Minipig Model of Hematopoietic-Acute Radiation Syndrome

Hematopoietic acute radiation syndrome (H-ARS) involves injury to multiple organ systems following total body irradiation (TBI). Our laboratory demonstrated that captopril, an angiotensin-converting enzyme inhibitor, mitigates H-ARS in Göttingen minipigs, with improved survival and hematopoietic recovery, as well as the suppression of acute inflammation. However, the effects of captopril on the gastrointestinal (GI) system after TBI are not well known. We used a Göttingen minipig H-ARS model to investigate captopril's effects on the GI following TBI (60Co 1.79 or 1.80 Gy, 0.42-0.48 Gy/min), with endpoints at 6 or 35 days. The vehicle or captopril (0.96 mg/kg) was administered orally twice daily for 12 days, starting 4 h post-irradiation. Ilea were harvested for histological, protein, and RNA analyses. TBI increased congestion and mucosa erosion and hemorrhage, which were modulated by captopril. GPX-4 and SLC7A11 were downregulated post-irradiation, consistent with ferroptosis at 6 and 35 days post-irradiation in all groups. Interestingly, p21/waf1 increased at 6 days in vehicle-treated but not captopril-treated animals. An RT-qPCR analysis showed that radiation increased the gene expression of inflammatory cytokines IL1B, TNFA, CCL2, IL18, and CXCL8, and the inflammasome component NLRP3. Captopril suppressed radiation-induced IL1B and TNFA. Rectal microbiome analysis showed that 1 day of captopril treatment with radiation decreased overall diversity, with increased Proteobacteria phyla and Escherichia genera. By 6 days, captopril increased the relative abundance of Enterococcus, previously associated with improved H-ARS survival in mice. Our data suggest that captopril mitigates senescence, some inflammation, and microbiome alterations, but not ferroptosis markers in the intestine following TBI.

Interpretation of vaginal metagenomic characteristics in different types of vaginitis

Although vaginitis is closely related to vaginal microecology in females, the precise composition and functional potential of different types of vaginitis remain unclear. Here, metagenomic sequencing was applied to analyze the vaginal flora in patients with various forms of vaginitis, including cases with a clue cell proportion ranging from 1% to 20% (Clue1_20), bacterial vaginitis (BV), vulvovaginal candidiasis (VVC), and BV combined with VVC (VVC_BV). Our results identified Prevotella as an important biomarker between BV and Clue1_20. Moreover, a gradual decrease was observed in the relative abundance of shikimic acid metabolism associated with bacteria producing indole as well as a decline in the abundance of Gardnerella vaginalis in patients with BV, Clue1_20, and healthy women. Interestingly, the vaginal flora of patients in the VVC_BV group exhibited structural similarities to that of the VVC group, and its potentially functional characteristics resembled those of the BV and VVC groups. Finally, Lactobacillus crispatus was found in high abundance in healthy samples, greatly contributing to the stability of the vaginal environment. For the further study of L. crispatus, we isolated five strains of L. crispatus from healthy samples and evaluated their capacity to inhibit G. vaginalis biofilms and produce lactic acid in vitro to select the potential probiotic candidate for improving vaginitis in future clinical studies. Overall, we successfully identified bacterial biomarkers of different vaginitis and characterized the dynamic shifts in vaginal flora between patients with BV and healthy females. This research advances our understanding and holds great promise in enhancing clinical approaches for the treatment of vaginitis.

IMPORTANCE

Vaginitis is one of the most common gynecological diseases, mostly caused by infections of pathogens such as Candida albicans and Gardnerella vaginalis. In recent years, it has been found that the stability of the vaginal flora plays an important role in vaginitis. Furthermore, the abundant Lactobacillus-producing rich lactic acid in the vagina provides a healthy acidic environment such as Lactobacillus crispatus. The metabolites of Lactobacillus can inhibit the colonization of pathogens. Here, we collected the vaginal samples of patients with bacterial vaginitis (BV), vulvovaginal candidiasis (VVC), and BV combined with VVC to discover the differences and relationships among the different kinds of vaginitis by metagenomic sequencing. Furthermore, because of the importance of L. crispatus in promoting vaginal health, we isolated multiple strains from vaginal samples of healthy females and chose the most promising strain with potential probiotic benefits to provide clinical implications for treatment strategies.

Unveiling the Microbial Realm with VEBA 2.0: A modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic, and viral multi-omics from either short- or long-read sequencing

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible platform that bridges the gap between genomics and biotechnological solutions.

MCSS: microbial community simulator based on structure

De novo assembly plays a pivotal role in metagenomic analysis, and the incorporation of third-generation sequencing technology can significantly improve the integrity and accuracy of assembly results. Recently, with advancements in sequencing technology (Hi-Fi, ultra-long), several long-read-based bioinformatic tools have been developed. However, the validation of the performance and reliability of these tools is a crucial concern. To address this gap, we present MCSS (microbial community simulator based on structure), which has the capability to generate simulated microbial community and sequencing datasets based on the structure attributes of real microbiome communities. The evaluation results indicate that it can generate simulated communities that exhibit both diversity and similarity to actual community structures. Additionally, MCSS generates synthetic PacBio Hi-Fi and Oxford Nanopore Technologies (ONT) long reads for the species within the simulated community. This innovative tool provides a valuable resource for benchmarking and refining metagenomic analysis methods. Code available at: https://github.com/panlab-bio/mcss.

Temporal differentiation in the adaptation of functional bacteria to low-temperature stress in partial denitrification and anammox system

Despite reliable nitrite supply through partial denitrification, the adaptation of denitrifying bacteria to low temperatures remains elusive in partial denitrification and anammox (PDA) systems. Here, temporal differentiations of the structure, activity, and relevant cold-adaptation mechanism of functional bacteria were investigated in a lab-scale PDA bioreactor at decreased temperature. Although distinct denitrifying bacteria dominated after low-temperature stress, both short- and long-term stresses exerted differential selectivity towards the species with close phylogenetic distance. Species Azonexus sp.149 showed high superiority over Azonexus sp.384 under short-term stress, and long-term stress improved the adaptation of Aquabacterium sp.93 instead of Aquabacterium sp.184. The elevated transcription of nitrite reductase genes suggested that several denitrifying bacteria (e.g., Azonexus sp.149) could compete with anammox bacteria for nitrite. Species Rivicola pingtungensis and Azonexus sp.149 could adapt through various adaptation pathways, such as the two-component system, cold shock protein (CSP), membrane alternation, and electron transport chain. By contrast, species Zoogloea sp.273 and Aquabacterium sp.93 mainly depended on the CSP and oxidative stress response. This study largely deepens our understanding of the performance deterioration in PDA systems during cold shock and provides several references for efficient adaptation to seasonal temperature fluctuation.

The keystone gut species Christensenella minuta boosts gut microbial biomass and voluntary physical activity in mice

The gut bacteria of the family Christensenellaceae are consistently associated with metabolic health, but their role in promoting host health is not fully understood. Here, we explored the effect of Christensenella minuta amendment on voluntary physical activity and the gut microbiome. We inoculated male and female germ-free mice with an obese human donor microbiota together with live or heat-killed C. minuta for 28 days and measured physical activity in respirometry cages. Compared to heat-killed, the live-C. minuta treatment resulted in reduced feed efficiency and higher levels of physical activity, with significantly greater distance traveled for males and higher levels of small movements and resting metabolic rate in females. Sex-specific effects of C. minuta treatment may be in part attributable to different housing conditions for males and females. Amendment with live C. minuta boosted gut microbial biomass in both sexes, immobilizing dietary carbon in the microbiome, and mice with high levels of C. minuta lose more energy in stool. Live C. minuta also reduced within and between-host gut microbial diversity. Overall, our results showed that C. minuta acts as a keystone species: despite low relative abundance, it has a large impact on its ecosystem, from the microbiome to host energy homeostasis.IMPORTANCEThe composition of the human gut microbiome is associated with human health. Within the human gut microbiome, the relative abundance of the bacterial family Christensenellaceae has been shown to correlate with metabolic health and a lean body type. The mechanisms underpinning this effect remain unclear. Here, we show that live C. minuta influences host physical activity and metabolic energy expenditure, accompanied by changes in murine metabolism and the gut microbial community in a sex-dependent manner in comparison to heat-killed C. minuta. Importantly, live C. minuta boosts the biomass of the microbiome in the gut, and a higher level of C. minuta is associated with greater loss of energy in stool. These observations indicate that modulation of activity levels and changes to the microbiome are ways in which the Christensenellaceae can influence host energy homeostasis and health.

Precision microbial intervention improves social behavior but not autism severity: A pilot double-blind randomized placebo-controlled trial

Autism spectrum disorder (ASD) is characterized by the presence of restricted/repetitive behaviors and social communication deficits. Because effective treatments for ASD remain elusive, novel therapeutic strategies are necessary. Preclinical studies show that L. reuteri selectively reversed social deficits in several models for ASD. Here, in a double-blind, randomized, placebo-controlled trial, we tested the effect of L. reuteri (a product containing a combination of strains ATCC-PTA-6475 and DSM-17938) in children with ASD. The treatment does not alter overall autism severity, restricted/repetitive behaviors, the microbiome composition, or the immune profile. However, L. reuteri combination yields significant improvements in social functioning that generalized across different measures. Interestingly, ATCC-PTA-6475, but not the parental strain of DSM-17938, reverses the social deficits in a preclinical mouse model for ASD. Collectively, our findings show that L. reuteri enhances social behavior in children with ASD, thereby warranting larger trials in which strain-specific effects should also be investigated.

The edible plant microbiome: evidence for the occurrence of fruit and vegetable bacteria in the human gut

Diversity of the gut microbiota is crucial for human health. However, whether fruit and vegetable associated bacteria contribute to overall gut bacterial diversity is still unknown. We reconstructed metagenome-assembled genomes from 156 fruit and vegetable metagenomes to investigate the prevalence of associated bacteria in 2,426 publicly available gut metagenomes. The microbiomes of fresh fruits and vegetables and the human gut are represented by members in common such as Enterobacterales, Burkholderiales, and Lactobacillales. Exposure to bacteria via fruit and vegetable consumption potentially has a beneficial impact on the functional diversity of gut microbiota particularly due to the presence of putative health-promoting genes for the production of vitamin and short-chain fatty acids. In the human gut, they were consistently present, although at a low abundance, approx. 2.2%. Host age, vegetable consumption frequency, and the diversity of plants consumed were drivers favoring a higher proportion. Overall, these results provide one of the primary links between the human microbiome and the environmental microbiome. This study revealed evidence that fruit and vegetable-derived microbes could be found in the human gut and contribute to gut microbiome diversity.

Metagenomic data from surface seawater of the east coast of South Korea

The East Sea, also known as the Sea of Japan, is a marginal sea located in the western Pacific Ocean, displaying comparable characteristics to Earth's oceans, thereby meriting its recognition as a "miniature ocean". The East Sea exhibits a range of annually-recurring biogeochemical features in accordance with seasonal fluctuations, such as phytoplankton blooms during the spring and autumn seasons. Despite ongoing monitoring efforts focused on water quality and physicochemical parameters, the investigation of prokaryotic assemblages in the East Sea, encompassing seasonal variations, has been infrequently pursued. Here, we present a monthly time-series metagenomic dataset spanning a one-year period in 2009, obtained from surface (10 m) seawater samples collected off the coast of the East Sea. The dataset encompasses 12 metagenomes, amounting 195 Gbp, with 14.73-22.52 Gbp per sample. This dataset is accompanied by concurrently measured physicochemical parameters. Our anticipation is that these metagenomes will facilitate extensive investigations aimed at elucidating various aspects of the marine microbial ecosystems in the East Sea.

Microbial composition and metabolic profiles during machine-controlled intra-factory fermentation of cocoa beans harvested in semitropical area of Japan

Cocoa bean fermentation is typically performed in a spontaneous manner on farms in tropical countries or areas and involves several microbial groups. Metabolism by microbes markedly affects the quality of cocoa beans fermented and the chocolate produced thereof. The present study characterized the microbiota and their metabolic profiles in temperature- and humidity-controlled intra-factory cocoa fermentation in a semitropical area of Japan. Although environmental factors were uniform, the microbiota of cocoa beans subjected to intra-factory fermentation was not stable between tests, particularly in terms of the cell count levels and species observed. Fermentation was sometimes delayed, and fermenting microbes were present at very low levels after 24 hr of fermentation. Due to the unstable microbiota, the profiles of water-soluble compounds differed between tests, indicating the unstable qualities of the fermented cocoa beans. These results suggest the necessity of starter cultures not only in on-farm fermentation but also in machine-controlled intra-factory cocoa fermentation.

Short-Term Dietary Intervention with Whole Oats Protects from Antibiotic-Induced Dysbiosis

Antibiotic-induced gut microbiome dysbiosis (AID) is known to be influenced by host dietary composition. However, how and when diet modulates gut dysbiosis remains poorly characterized. Thus, here, we utilize a multi-omics approach to characterize how a diet supplemented with oats, a rich source of microbiota-accessible carbohydrates, or dextrose impacts amoxicillin-induced changes to gut microbiome structure and transcriptional activity. We demonstrate that oat administration during amoxicillin challenge provides greater protection from AID than the always oats or recovery oats diet groups. In particular, the group in which oats were provided at the time of antibiotic exposure induced the greatest protection against AID while the other oat diets saw greater effects after amoxicillin challenge. The oat diets likewise reduced amoxicillin-driven elimination of Firmicutes compared to the dextrose diet. Functionally, gut communities fed dextrose were carbohydrate starved and favored respiratory metabolism and consequent metabolic stress management while oat-fed communities shifted their transcriptomic profile and emphasized antibiotic stress management. The metabolic trends were exemplified when assessing transcriptional activity of the following two common gut commensal bacteria: Akkermansia muciniphila and Bacteroides thetaiotaomicron. These findings demonstrate that while host diet is important in shaping how antibiotics effect the gut microbiome composition and function, diet timing may play an even greater role in dietary intervention-based therapeutics. IMPORTANCE We utilize a multi-omics approach to demonstrate that diets supplemented with oats, a rich source of microbiota-accessible carbohydrates, are able to confer protection against antibiotic-induced dysbiosis (AID). Our findings affirm that not only is host diet important in shaping antibiotics effects on gut microbiome composition and function but also that the timing of these diets may play an even greater role in managing AID. This work provides a nuanced perspective on dietary intervention against AID and may be informative on preventing AID during routine antibiotic treatment.

Metagenomic Analysis of a Concrete Bridge Reveals a Microbial Community Dominated by Halophilic Bacteria and Archaea

Concrete hosts a small but diverse microbiome that changes over time. Shotgun metagenomic sequencing would enable assessment of both the diversity and function of the microbial community in concrete, but a number of unique challenges make this difficult for concrete samples. The high concentration of divalent cations in concrete interferes with nucleic acid extraction, and the extremely low biomass in concrete means that DNA from laboratory contamination may be a large fraction of the sequence data. Here, we develop an improved method for DNA extraction from concrete, with higher yield and lower laboratory contamination. To show that this method provides DNA of sufficient quality and quantity to do shotgun metagenomic sequencing, DNA was extracted from a sample of concrete obtained from a road bridge and sequenced with an Illumina MiSeq system. This microbial community was dominated by halophilic Bacteria and Archaea, with enriched functional pathways related to osmotic stress responses. Although this was a pilot-scale effort, we demonstrate that metagenomic sequencing can be used to characterize microbial communities in concrete and that older concrete structures may host different microbes than recently poured concrete. IMPORTANCE Prior work on the microbial communities of concrete focused on the surfaces of concrete structures such as sewage pipes or bridge pilings, where thick biofilms were easy to observe and sample. Because the biomass inside concrete is so low, more recent analyses of the microbial communities inside concrete used amplicon sequencing methods to describe those communities. However, to understand the activity and physiology of microbes in concrete, or to develop living infrastructure, we must develop more direct methods of community analysis. The method developed here for DNA extraction and metagenomic sequencing can be used for analysis of microbial communities inside concrete and can likely be adapted for other cementitious materials.

The Western Lake Erie culture collection: A promising resource for evaluating the physiological and genetic diversity of Microcystis and its associated microbiome

Cyanobacterial harmful algal blooms (cyanoHABs) dominated by Microcystis spp. have significant public health and economic implications in freshwater bodies around the world. These blooms are capable of producing a variety of cyanotoxins, including microcystins, that affect fishing and tourism industries, human and environmental health, and access to drinking water. In this study, we isolated and sequenced the genomes of 21 primarily unialgal Microcystis cultures collected from western Lake Erie between 2017 and 2019. While some cultures isolated in different years have a high degree of genetic similarity (genomic Average Nucleotide Identity >99%), genomic data show that these cultures also represent much of the breadth of known Microcystis diversity in natural populations. Only five isolates contained all the genes required for microcystin biosynthesis while two isolates contained a previously described partial mcy operon. Microcystin production within cultures was also assessed using Enzyme-Linked Immunosorbent Assay (ELISA) and supported genomic results with high concentrations (up to 900 μg L⁻¹) in cultures with complete mcy operons and no or low toxin detected otherwise. These xenic cultures also contained a substantial diversity of bacteria associated with Microcystis, which has become increasingly recognized as an essential component of cyanoHAB community dynamics. These results highlight the genomic diversity among Microcystis strains and associated bacteria in Lake Erie, and their potential impacts on bloom development, toxin production, and toxin degradation. This culture collection significantly increases the availability of environmentally relevant Microcystis strains from temperate North America.

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning

The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging to detect for taxonomically novel genomic data. Assembly errors can affect all downstream analyses of the assemblies. Accuracy for the state of the art in reference-free misassembly prediction does not exceed an AUPRC of 0.57, and it is not clear how well these models generalize to real-world data. Here, we present the Residual neural network for Misassembled Contig identification (ResMiCo), a deep learning approach for reference-free identification of misassembled contigs. To develop ResMiCo, we first generated a training dataset of unprecedented size and complexity that can be used for further benchmarking and developments in the field. Through rigorous validation, we show that ResMiCo is substantially more accurate than the state of the art, and the model is robust to novel taxonomic diversity and varying assembly methods. ResMiCo estimated 7% misassembled contigs per metagenome across multiple real-world datasets. We demonstrate how ResMiCo can be used to optimize metagenome assembly hyperparameters to improve accuracy, instead of optimizing solely for contiguity. The accuracy, robustness, and ease-of-use of ResMiCo make the tool suitable for general quality control of metagenome assemblies and assembly methodology optimization.

Complet+: a computationally scalable method to improve completeness of large-scale protein sequence clustering

A major challenge for clustering algorithms is to balance the trade-off between homogeneity, i.e., the degree to which an individual cluster includes only related sequences, and completeness, the degree to which related sequences are broken up into multiple clusters. Most algorithms are conservative in grouping sequences with other sequences. Remote homologs may fail to be clustered together and instead form unnecessarily distinct clusters. The resulting clusters have high homogeneity but completeness that is too low. We propose Complet+, a computationally scalable post-processing method to increase the completeness of clusters without an undue cost in homogeneity. Complet+ proves to effectively merge closely-related clusters of protein that have verified structural relationships in the SCOPe classification scheme, improving the completeness of clustering results at little cost to homogeneity. Applying Complet+ to clusters obtained using MMseqs2's clusterupdate achieves an increased V-measure of 0.09 and 0.05 at the SCOPe superfamily and family levels, respectively. Complet+ also creates more biologically representative clusters, as shown by a substantial increase in Adjusted Mutual Information (AMI) and Adjusted Rand Index (ARI) metrics when comparing predicted clusters to biological classifications. Complet+ similarly improves clustering metrics when applied to other methods, such as CD-HIT and linclust. Finally, we show that Complet+ runtime scales linearly with respect to the number of clusters being post-processed on a COG dataset of over 3 million sequences. Code and supplementary information is available on Github: https://github.com/EESI/Complet-Plus.

Metagenome-assembled genome extraction and analysis from microbiomes using KBase

Uncultivated Bacteria and Archaea account for the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only become possible recently. To realize the hope of capturing Earth's microbial genetic complement and to facilitate the investigation of the functional roles of specific lineages in a given ecosystem, technologies that accelerate the recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high-quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform ( http://www.kbase.us/ ). Overall, these steps take about a day to obtain extracted genomes when starting from smaller environmental shotgun read libraries, or up to about a week from larger libraries. In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAGs, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq and others. While portions of such capabilities are available individually from other resources, the combination of the intuitive usability, data interoperability and integration of tools in a freely available computational resource makes KBase a powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended with additional MAG recovery and analysis tools, via the KBase software development kit (SDK).

Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing

To understand the role of the skin commensal bacterial community in skin health and the spread of pathogens, it is crucial to identify genetic differences in the bacterial strains corresponding to human individuals. A culture-independent genomics approach is an effective tool for obtaining massive high-quality bacterial genomes. Here we present a single-cell genome sequencing to obtain comprehensive whole-genome sequences of uncultured skin bacteria from skin swabs. We recovered 281 high-quality (HQ) and 244 medium-quality single-amplified genomes (SAGs) of multiple skin bacterial species from eight individuals, including cohabiting group. Single-cell sequencing outperformed in the genome recovery from the same skin swabs, showing 10-fold non-redundant strain genomes compared to the shotgun metagenomic sequencing and binning approach. We then focused on the abundant skin bacteria and identified intra-species diversity, especially in 47 Moraxella osloensis derived HQ SAGs, characterizing the strain-level heterogeneity at mobile genetic element profiles, including plasmids and prophages. Even between the cohabiting individual hosts, they have unique skin bacterial strains in the same species, which shows microdiversity in each host. Genetic and functional differences between skin bacterial strains are predictive of in vivo competition to adapt bacterial genome to utilize the sparse nutrients available on the skin or produce molecules that inhibit the colonization of other microbes or alter their behavior. Thus, single-cell sequencing provides a large number of genomes of higher resolution and quality than conventional metagenomic analysis and helps explore the skin commensal bacteria at the strain level, linking taxonomic and functional information.

Archaea: An under-estimated kingdom in livestock animals

Archaea are considered an essential group of gut microorganisms in both humans and animals. However, they have been neglected in previous studies, especially those involving non-ruminants. In this study, we re-analyzed published metagenomic and metatranscriptomic data sequenced from matched samples to explore the composition and the expression activity of gut archaea in ruminants (cattle and sheep) and monogastric animals (pig and chicken). Our results showed that the alpha and beta diversity of each host species, especially cattle and chickens, calculated from metagenomic and metatranscriptomic data were significantly different, suggesting that metatranscriptomic data better represent the functional status of archaea. We detected that the relative abundance of 17 (cattle), 7 (sheep), 20 (pig), and 2 (chicken) archaeal species were identified in the top 100 archaeal taxa when analyzing the metagenomic datasets, and these species were classified as the “active archaeal species” for each host species by comparison with corresponding metatranscriptomic data. For example, The expressive abundance in metatranscriptomic dataset of Methanosphaera cuniculi and Methanosphaera stadtmanae were 30- and 27-fold higher than that in metagenomic abundance, indicating their potentially important function in the pig gut. Here we aim to show the potential importance of archaea in the livestock digestive tract and encourage future research in this area, especially on the gut archaea of monogastric animals.

Weaning Time Affects the Archaeal Community Structure and Functional Potential in Pigs

Archaea are considered a “keystone” of the gut microbiome and are linked with the host’s energy harvest and health. Although a few studies have investigated the gut archaea in pigs, especially piglets, little is known about the effects of weaning on archaeal structure and function. In this study, we explored the effects of weaning on the longitudinal changes of archaeal composition, diversity, and functional potential in pigs overtime by re-analyzing a recently published metagenomic dataset that included 176 fecal samples collected from commercial pigs on days 7, 14, 21, 28, 35, 70, and 140 after birth. Overall, the richness and diversity of archaeal species showed an increasing trend, and weaning significantly affected the richness of archaeal species. Methanobrevibacter A smithii significantly decreased and was replaced by Methanobrevibacter A sp900769095 within 2 weeks after weaning. For the functional potential, the richness of KEGG KOs increased over time. LEfSe analysis identified 18 KOs, including for example, ko04623 (cytosolic DNA-sensing pathway), ko00500 (starch and sucrose metabolism), and so on, significantly enriched in the weaning pigs, suggesting the involvement of archaea in the piglets’ adaptation to the new diet after weaning. Correlation analysis based on Random Forest regression and Pearson correlation showed that archaeal species richness was significantly associated with pig bodyweight on both days 70 and 140. Methanobrevibacter A sp900769095 (R = 0.405, p = 0.040) and Methanobrevibacter A smithii (R = 0.535, p = 0.004) were positively linked with pigs’ bodyweight on days 70 and 140, respectively. Our results revealed the dynamic changes of archaeal diversity and functions and demonstrated the effects of weaning on the gut archaea of pigs, suggesting archaea might play essential roles in swine nutrition, metabolism, and growth performance, especially during the critical weaning process.

Incorporating genome-based phylogeny and functional similarity into diversity assessments helps to resolve a global collection of human gut metagenomes

Tree-based diversity measures incorporate phylogenetic or functional relatedness into comparisons of microbial communities. This can improve the identification of explanatory factors compared to tree-agnostic diversity measures. However, applying tree-based diversity measures to metagenome data is more challenging than for single-locus sequencing (e.g., 16S rRNA gene). Utilizing the Genome Taxonomy Database (GTDB) for species-level metagenome profiling allows for functional diversity measures based on genomic content or traits inferred from it. Still, it is unclear how metagenome-based assessments of microbiome diversity benefit from incorporating phylogeny or function into measures of diversity. We assessed this by measuring phylogeny-based, function-based, and tree-agnostic diversity measures from a large, global collection of human gut metagenomes composed of 30 studies and 2943 samples. We found tree-based measures to explain phenotypic variation (e.g., westernization, disease status, and gender) better or equivalent to tree-agnostic measures. Ecophylogenetic and functional diversity measures provided unique insight into how microbiome diversity was partitioned by phenotype. Tree-based measures greatly improved machine learning model performance for predicting westernization, disease status, and gender, relative to models trained solely on tree-agnostic measures. Our findings illustrate the usefulness of tree- and function-based measures for metagenomic assessments of microbial diversity, which is a fundamental component of microbiome science. This article is protected by copyright. All rights reserved.