Comparative Analysis of 16S rRNA Gene and Metagenome Sequencing in Pediatric Gut Microbiomes

Compositional Changes in the Vaginal Bacterial Microbiome of Healthy Pregnant Women across the Three Gestational Trimesters in Ismailia, Egypt

The composition of the vaginal microbiome may lead to adverse pregnancy outcomes. Normal pregnancy is associated with changes in the vaginal bacterial community composition, which tend to be more enriched with one or two Lactobacillus species promoting a healthy vagina and favorable birth outcomes. The aim of the current study was to determine compositional changes in the healthy vaginal microbiome composition during the three trimesters of pregnancy in Ismailia, Egypt using Illumina MiSeq sequencing of the V3-V4 region of the 16S rRNA. The phylum Firmicutes and the genus Lactobacillus dominated across the three trimesters of pregnancy. L. iners was the most abundant species. However, L. coleohominis and L. reuteri represented the least dominant vaginal lactobacilli. Core microbiome analyses showed the Lactobacillus genus and L. iners species to have the highest prevalence in all the samples of our study groups. The phylum Firmicutes was found to be negatively correlated with almost all other vaginal phyla during pregnancy. Likewise, a negative correlation between Lactobacillus and almost all other genera was detected, including significant negative correlations with Dialister and Prevotella. Furthermore, negative correlations of L. iners were detected with almost all other species, including a significant negative correlation with L. helveticus, G. vaginalis, S. anginosus, and S. agalactiae.

Bioinformatic and Statistical Analysis of Microbiome Data

Since advances in next-generation sequencing (NGS) technique enabled to investigate uncultured microbiota and their genomes in unbiased manner, many microbiome researches have been reporting strong evidences for close links of microbiome to human health and disease. Bioinformatic and statistical analysis of NGS-based microbiome data are essential components in those microbiome researches to explore the complex composition of microbial community and understand the functions of community members in relation to host and environment. This chapter introduces bioinformatic analysis methods that generate taxonomy and functional feature count table along with phylogenetic tree from raw NGS microbiome data and then introduce statistical methods and machine learning approaches for analyzing the outputs of the bioinformatic analysis to infer the biodiversity of a microbial community and unravel host-microbiome association. Understanding the advantages and limitations of the analysis methods will help readers use the methods correctly in microbiome data analysis and may give a new opportunity to develop new analytic techniques for microbiome research.

DNA extraction protocol impacts ocular surface microbiome profile

Purpose

The aim of this study is to provide a reference frame to allow the comparison and interpretation of currently published studies on 16S ribosomal ribonucleic acid amplicon sequencing of ocular microbiome samples using different DNA extraction protocols. Alongside, the quantitative and qualitative yield and the reproducibility of different protocols has been assessed.

Methods

Both eyes of 7 eligible volunteers were sampled. Five commercially available DNA extraction protocols were selected based on previous publications in the field of the ocular surface microbiome and 2 host DNA depletion protocols were added based on their reported effective host DNA depletion without significant reduction in bacterial DNA concentration. The V3-V4 region of the 16S rRNA gene was targeted using Illumina MiSeq sequencing. The DADA2 pipeline in R was used to perform the bio-informatic processing and taxonomical assignment was done using the SILVA v132 database. The Vegdist function was used to calculate Bray-Curtis distances and the Galaxy web application was used to identify potential metagenomic biomarkers via linear discriminant analysis Effect Size (LEfSe). The R package Decontam was applied to control for potential contaminants.

Results

Samples analysed with PowerSoil, RNeasy and NucleoSpin had the highest DNA yield. The host DNA depletion kits showed a very low microbial DNA yield; and these samples were pooled per kit before sequencing. Despite pooling, 1 of both failed to construct a library.Looking at the beta-diversity, clear microbial compositional differences - dependent on the extraction protocol used - were observed and remained present after decontamination. Eighteen genera were consistently retrieved from the ocular surface of every volunteer by all non-pooled extraction kits and a comprehensive list of differentially abundant bacteria per extraction method was generated using LefSe analysis.

Conclusion

High-quality papers have been published in the field of the ocular surface microbiome but consensus on the importance of the extraction protocol used are lacking. Potential contaminants and discriminative genera per extraction protocol used, were introduced and a reference frame was built to facilitate both the interpretation of currently published papers and to ease future choice - making based on the research question at hand.

Phage-Host Prediction Using a Computational Tool Coupled with 16S rRNA Gene Amplicon Sequencing

Metagenomics studies have revealed tremendous viral diversity in aquatic environments. Yet, while the genomic data they have provided is extensive, it is unannotated. For example, most phage sequences lack accurate information about their bacterial host, which prevents reliable phage identification and the investigation of phage-host interactions. This study aimed to take this knowledge further, using a viral metagenomic framework to decipher the composition and diversity of phage communities and to predict their bacterial hosts. To this end, we used water and sediment samples collected from seven sites with varying contamination levels in the Ebrié Lagoon in Abidjan, Ivory Coast. The bacterial communities were characterized using the 16S rRNA metabarcoding approach, and a framework was developed to investigate the virome datasets that: (1) identified phage contigs with VirSorter and VIBRANT; (2) classified these contigs with MetaPhinder using the phage database (taxonomic annotation); and (3) predicted the phages' bacterial hosts with a machine learning-based tool: the Prokaryotic Virus-Host Predictor. The findings showed that the taxonomic profiles of phages and bacteria were specific to sediment or water samples. Phage sequences assigned to the Microviridae family were widespread in sediment samples, whereas phage sequences assigned to the Siphoviridae, Myoviridae and Podoviridae families were predominant in water samples. In terms of bacterial communities, the phyla Latescibacteria, Zixibacteria, Bacteroidetes, Acidobacteria, Calditrichaeota, Gemmatimonadetes, Cyanobacteria and Patescibacteria were most widespread in sediment samples, while the phyla Epsilonbacteraeota, Tenericutes, Margulisbacteria, Proteobacteria, Actinobacteria, Planctomycetes and Marinimicrobia were most prevalent in water samples. Significantly, the relative abundance of bacterial communities (at major phylum level) estimated by 16S rRNA metabarcoding and phage-host prediction were significantly similar. These results demonstrate the reliability of this novel approach for predicting the bacterial hosts of phages from shotgun metagenomic sequencing data.

Alterations of the vaginal microbiome in healthy pregnant women positive for group B Streptococcus colonization during the third trimester

BACKGROUND

Streptococcus agalactiae or group B Streptococcus (GBS) asymptomatically colonizes the genitourinary tracts of up to 30% of pregnant women. Globally, GBS is an important cause of neonatal morbidity and mortality. GBS has recently been linked to adverse pregnancy outcomes. The potential interactions between GBS and the vaginal microbiome composition remain poorly understood. In addition, little is known about the vaginal microbiota of pregnant Egyptian women.

RESULTS

Using V3-V4 16S rRNA next-generation sequencing, we examined the vaginal microbiome in GBS culture-positive pregnant women (22) and GBS culture-negative pregnant women (22) during the third trimester in Ismailia, Egypt. According to the alpha-diversity indices, the vaginal microbiome of pregnant GBS culture-positive women was significantly more diverse and less homogenous. The composition of the vaginal microbiome differed significantly based on beta-diversity between GBS culture-positive and culture-negative women. The phylum Firmicutes and the family Lactobacillaceae were significantly more abundant in GBS-negative colonizers. In contrast, the phyla Actinobacteria, Tenericutes, and Proteobacteria and the families Bifidobacteriaceae, Mycoplasmataceae, Streptococcaceae, Corynebacteriaceae, Staphylococcaceae, and Peptostreptococcaceae were significantly more abundant in GBS culture-positive colonizers. On the genus and species levels, Lactobacillus was the only genus detected with significantly higher relative abundance in GBS culture-negative status (88%), and L. iners was the significantly most abundant species. Conversely, GBS-positive carriers exhibited a significant decrease in Lactobacillus abundance (56%). In GBS-positive colonizers, the relative abundance of the genera Ureaplasma, Gardnerella, Streptococcus, Corynebacterium, Staphylococcus, and Peptostreptococcus and the species Peptostreptococcus anaerobius was significantly higher. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to the metabolism of cofactors and vitamins, phosphatidylinositol signaling system, peroxisome, host immune system pathways, and host endocrine system were exclusively enriched among GBS culture-positive microbial communities. However, lipid metabolism KEGG pathways, nucleotide metabolism, xenobiotics biodegradation and metabolism, genetic information processing pathways associated with translation, replication, and repair, and human diseases (Staphylococcus aureus infection) were exclusively enriched in GBS culture-negative communities.

CONCLUSIONS

Understanding how perturbations of the vaginal microbiome contribute to pregnancy complications may result in the development of alternative, targeted prevention strategies to prevent maternal GBS colonization. We hypothesized associations between inferred microbial function and GBS status that would need to be confirmed in larger cohorts.

Exploring the Connection Between the Gut Microbiome and Parkinson's Disease Symptom Progression and Pathology: Implications for Supplementary Treatment Options

The contribution of the microbiota to induce gastrointestinal inflammation is hypothesized to be a key component of alpha-synuclein (aSyn) aggregation within the gastrointestinal (GI) tract in the pathological progression of Parkinson's disease (PD). The function of the GI tract is governed by a system of neurons that form part of the enteric nervous system (ENS). The ENS hosts  100-500 million nerve cells within two thin layers lining the GI tract. The gut-brain axis (GBA) is the major communication pathway between the ENS and the central nervous system. It has become increasingly clear that the microbiota in the gut are key regulators of GBA function and help to maintain homeostasis in the immune and endocrine systems. The GBA may act as a possible etiological launching pad for the pathogenesis of age-related neurodegenerative diseases, such as PD, because of an imbalance in the gut microbiota. PD is a multi-faceted illness with multiple biological, immunological, and environmental factors contributing to its pathological progression. Interestingly, individuals with PD have an altered gut microbiota compared to healthy individuals. However, there is a lack of literature describing the relationship between microbiota composition in the gut and symptom progression in PD patients. This review article examines how the pathology and symptomology of PD may originate from dysregulated signaling in the ENS. We then discuss by targeting the imbalance within the gut microbiota such as prebiotics and probiotics, some of the prodromal symptoms might be alleviated, possibly curtailing the pathological spread of aSyn and ensuing debilitating motor symptoms.

Oral Microbiome in Nonsmoker Patients with Oral Cavity Squamous Cell Carcinoma, Defined by Metagenomic Shotgun Sequencing

Objectives: Smoking is the commonest cause of oral cavity squamous cell carcinoma (OC-SCC), but the etiology of OC-SCC in nonsmokers is unknown. Our primary goal was to use metagenomic shotgun sequencing (MSS) to define the taxonomic composition and functional potential of oral metagenome in nonsmokers with OC-SCC. Methods: We conducted a case-control study with 42 OC-SCC case and 45 control nonsmokers. MSS was performed on DNA extracted from mouthwash samples. Taxonomic analysis and pathway analysis were done using MetaPhlAn2 and HUMAnN2, respectively. Statistical difference was determined using the Mann-Whitney test controlling false discovery rate. Results: There was no significant difference in age, sex, race, or alcohol consumption between OC-SCC and control patients. There was a significant difference in beta diversity between OC-SCC and controls. At the phylum level, Bacteroidetes and Synergistetes were overly represented in OC-SCC while Actinobacteria and Firmicutes were overly represented in controls. At the genus level, Fusobacterium was overly represented in OC-SCC compared with controls, while Corynebacterium, Streptococcus, Actinomyces, Cryptobacterium, and Selenomonas were overly represented in controls. Bacterial pathway analysis identified overrepresentation in OC-SCC of pathways related to metabolism of flavin, biotin, thiamin, heme, sugars, fatty acids, peptidoglycans, and tRNA and overrepresentation of nucleotides and essential amino acids in controls. Conclusions: The oral microbiome in nonsmoker patients with OC-SCC is significantly different from that of nonsmoker control patients in taxonomic compositions and functional potentials. Our study's MSS findings matched with previous 16S-based methods in taxonomic differentiation but varied greatly in functional differentiation of microbiomes in OC-SCC and controls.

Multi-Omics Nutritional Approaches Targeting Metabolic-Associated Fatty Liver Disease

Currently, metabolic-associated fatty liver disease (MAFLD) is a leading global cause of chronic liver disease, and is expected to become one of the most common indications of liver transplantation. MAFLD is associated with obesity, involving multiple mechanisms such as alterations in lipid metabolism, insulin resistance, hyperinflammation, mitochondrial dysfunction, cell apoptosis, oxidative stress, and extracellular matrix formation. However, the onset and progression of MAFLD is variable among individuals, being influenced by intrinsic (personal) and external environmental factors. In this context, sequence structural variants across the human genome, epigenetic phenomena (i.e., DNA methylation, histone modifications, and long non-coding RNAs) affecting gene expression, gut microbiota dysbiosis, and metabolomics/lipidomic fingerprints may account for differences in MAFLD outcomes through interactions with nutritional features. This knowledge may contribute to gaining a deeper understanding of the molecular and physiological processes underlying MAFLD pathogenesis and phenotype heterogeneity, as well as facilitating the identification of biomarkers of disease progression and therapeutic targets for the implementation of tailored nutritional strategies. This comprehensive literature review highlights the potential of nutrigenetic, nutriepigenetic, nutrimetagenomic, nutritranscriptomics, and nutrimetabolomic approaches for the prevention and management of MAFLD in humans through the lens of precision nutrition.

Wochenende - modular and flexible alignment-based shotgun metagenome analysis

BACKGROUND

Shotgun metagenome analysis provides a robust and verifiable method for comprehensive microbiome analysis of fungal, viral, archaeal and bacterial taxonomy, particularly with regard to visualization of read mapping location, normalization options, growth dynamics and functional gene repertoires. Current read classification tools use non-standard output formats, or do not fully show information on mapping location. As reference datasets are not perfect, portrayal of mapping information is critical for judging results effectively.

RESULTS

Our alignment-based pipeline, Wochenende, incorporates flexible quality control, trimming, mapping, various filters and normalization. Results are completely transparent and filters can be adjusted by the user. We observe stringent filtering of mismatches and use of mapping quality sharply reduces the number of false positives. Further modules allow genomic visualization and the calculation of growth rates, as well as integration and subsequent plotting of pipeline results as heatmaps or heat trees. Our novel normalization approach additionally allows calculation of absolute abundance profiles by comparison with reads assigned to the human host genome.

CONCLUSION

Wochenende has the ability to find and filter alignments to all kingdoms of life using both short and long reads, and requires only good quality reference genomes. Wochenende automatically combines multiple available modules ranging from quality control and normalization to taxonomic visualization. Wochenende is available at https://github.com/MHH-RCUG/nf_wochenende .

Proof of principle study replicating microbial clusters in connection to birth mode and diet in the early life intestine

The human gut ecosystem starts developing at birth and is influenced by many factors during early life. In this study we make use of a Belgian cohort of 64 children, followed until the age of 6 years, to analyze different phases of microbiota development. We analyzed fecal samples taken before weaning (age 1 month), shortly after weaning (age 6 months), when milk feeding has been discontinued completely (age 1 year), and at the age of 6 years. We performed 16S rRNA gene amplicon sequencing on the collected fecal samples and analyzed the compositional data in relation to dietary metadata and birth mode. Human and formula milk feeding promotes a microbiota dominated by either Bacteroides or Bifidobacterium, respectively. Into later life stages, the microbiota composition follows distinct microbiota clusters, related to abundance dynamics of certain bacterial groups. Furthermore, it becomes apparent that a formula diet leads to early maturation of the infant gut microbiota. Despite other clinical variables within the infant cohort, they did not significantly contribute to the microbiota patterns we observed. Our data provide a proof of principle study of the importance of diet to the development of the microbiota in early life that replicates earlier findings in other cohorts.

Long-Read 16S rRNA Amplicon and Metagenomic Data of Swine Feed-Additive Probiotics Product

Swine feed-additive probiotics products play a major role in swine performance and welfare by promoting gut health. Here, we present two types of data, including a full-length 16S rRNA amplicon sequence data and a long-read metagenomic sequence data obtained from the same commercial probiotic product.

Functionally diverse microbial communities show resilience in response to a record-breaking rain event

Estuaries provide many ecosystem services and host a majority of the world's population. Here, the response of microbial communities after a record-breaking flood event in a highly urbanized estuary was followed. Hurricane Harvey (hereafter Harvey) was a category 4 hurricane that made landfall on the Texas coast in 2017 and lashed the Houston area with 1.4-1.7 × 1010 m3 of rainfall, disrupting the natural gradients of nutrients and salinity. Here, we utilized metagenomics to analyze how Harvey altered the microbial community of Galveston Bay over five weeks following the storm. We hypothesized that the community would shift from a marine dominated community to that of a terrestrial and freshwater origin. We found that following the storm there were changes in the distribution of species with specific metabolic capacities, such as Cyanobacteria, enriched in oxygenic photosynthesis and nitrogen fixation genes, as well as Verrucomicrobia and Betaproteobacteria, with high prevalence of the SOX complex and anoxygenic photosynthesis genes. On the other hand, dominant members of the community with more diverse metabolic capabilities showed less fluctuations in their distribution. Our results highlight how massive precipitation disturbances can alter microbial communities and how the coalescence of diverse microorganisms creates a resilient community able to maintain ecosystem services even when the system is in an altered state.

Crosstalk between mucosal microbiota, host gene expression, and sociomedical factors in the progression of colorectal cancer

Various omics-based biomarkers related to the occurrence, progression, and prognosis of colorectal cancer (CRC) have been identified. In this study, we attempted to identify gut microbiome-based biomarkers and detect their association with host gene expression in the initiation and progression of CRC by integrating analysis of the gut mucosal metagenome, RNA sequencing, and sociomedical factors. We performed metagenome and RNA sequencing on colonic mucosa samples from 13 patients with advanced CRC (ACRC), 10 patients with high-risk adenoma (HRA), and 7 normal control (NC) individuals. All participants completed a questionnaire on sociomedical factors. The interaction and correlation between changes in the microbiome and gene expression were assessed using bioinformatic analysis. When comparing HRA and NC samples, which can be considered to represent the process of tumor initiation, 28 genes and five microbiome species were analyzed with correlation plots. When comparing ACRC and HRA samples, which can be considered to represent the progression of CRC, seven bacterial species and 21 genes were analyzed. When comparing ACRC and NC samples, 16 genes and five bacterial species were analyzed, and four correlation plots were generated. A network visualizing the relationship between bacterial and host gene expression in the initiation and progression of CRC indicated that Clostridium spiroforme and Tyzzerella nexilis were hub bacteria in the development and progression of CRC. Our study revealed the interactions of and correlation between the colonic mucosal microbiome and host gene expression to identify potential roles of the microbiome in the initiation and progression of CRC. Our results provide gut microbiome-based biomarkers that may be potential diagnostic markers and therapeutic targets in patients with CRC.

Effect of Intensity and Duration of Exercise on Gut Microbiota in Humans: A Systematic Review

(1) Background: The gut microbiota might play a part in affecting athletic performance and is of considerable importance to athletes. The aim of this study was to search the recent knowledge of the protagonist played by high-intensity and high-duration aerobic exercise on gut microbiota composition in athletes and how these effects could provide disadvantages in sports performance. (2) Methods: This systematic review follows the PRISMA guidelines. An exhaustive bibliographic search in Web of Science, PubMed, and Scopus was conducted considering the articles published in the last 5 years. The selected articles were categorized according to the type of study. The risk of bias was assessed using the Joanna Briggs Institute's Critical Appraisal Tool for Systematic Reviews. (3) Results: Thirteen studies had negative effects of aerobic exercise on intestinal microbiota such as an upsurge in I-FABP, intestinal distress, and changes in the gut microbiota, such as an increase in Prevotella, intestinal permeability and zonulin. In contrast, seven studies observed positive effects of endurance exercise, including an increase in the level of bacteria such as increased microbial diversity and increased intestinal metabolites. (4) Conclusions: A large part of the studies found reported adverse effects on the intestinal microbiota when performing endurance exercises. In studies carried out on athletes, more negative effects on the microbiota were found than in those carried out on non-athletic subjects.

Effect of Tanshinone IIA on Gut Microbiome in Diabetes-Induced Cognitive Impairment

Diabetes-induced cognitive impairment (DCI) presents a major public health risk among the aging population. Previous clinical attempts on known therapeutic targets for DCI, such as depleted insulin secretion, insulin resistance, and hyperglycaemia have delivered poor patient outcomes. However, recent evidence has demonstrated that the gut microbiome plays an important role in DCI by modulating cognitive function through the gut–brain crosstalk. The bioactive compound tanshinone IIA (TAN) has shown to improve cognitive and memory function in diabetes mellitus models, though the pharmacological actions are not fully understood. This study aims to investigate the effect and underlying mechanism of TAN in attenuating DCI in relation to regulating the gut microbiome. Metagenomic sequencing analyses were performed on a group of control rats, rats with diabetes induced by a high-fat/high-glucose diet (HFD) and streptozotocin (STZ) (model group) and TAN-treated diabetic rats (TAN group). Cognitive and memory function were assessed by the Morris water maze test, histopathological assessment of brain tissues, and immunoblotting of neurological biomarkers. The fasting blood glucose (FBG) level was monitored throughout the experiments. The levels of serum lipopolysaccharide (LPS) and tumor necrosis factor-α (TNF-α) were measured by enzyme-linked immunoassays to reflect the circulatory inflammation level. The morphology of the colon barrier was observed by histopathological staining. Our study confirmed that TAN reduced the FBG level and improved the cognitive and memory function against HFD- and STZ-induced diabetes. TAN protected the endothelial tight junction in the hippocampus and colon, regulated neuronal biomarkers, and lowered the serum levels of LPS and TNF-α. TAN corrected the reduced abundance of Bacteroidetes in diabetic rats. At the species level, TAN regulated the abundance of B. dorei, Lachnoclostridium sp. YL32 and Clostridiodes difficile. TAN modulated the lipid metabolism and biosynthesis of fatty acids in related pathways as the main functional components. TAN significantly restored the reduced levels of isobutyric acid and butyric acid. Our results supported the use of TAN as a promising therapeutic agent for DCI, in which the underlying mechanism may be associated with gut microbiome regulation.

Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Flow cytometry can reliably capture gut microbial composition in healthy adults as well as dysbiosis dynamics in patients with aggressive B-cell non-Hodgkin lymphoma

Modulation of commensal gut microbiota is increasingly recognized as a promising strategy to reduce mortality in patients with malignant diseases, but monitoring for dysbiosis is generally not routine clinical practice due to equipment, expertise and funding required for sequencing analysis. A low-threshold alternative is microbial diversity profiling by single-cell flow cytometry (FCM), which we compared to 16S rRNA sequencing in human fecal samples and employed to characterize longitudinal changes in the microbiome composition of patients with aggressive B-cell non-Hodgkin lymphoma undergoing chemoimmunotherapy. Diversity measures obtained from both methods were correlated and captured identical trends in microbial community structures, finding no difference in patients' pretreatment alpha or beta diversity compared to healthy controls and a significant and progressive loss of alpha diversity during chemoimmunotherapy. Our results highlight the potential of FCM-based microbiome profiling as a reliable and accessible diagnostic tool that can provide novel insights into cancer therapy-associated dysbiosis dynamics.

High-Resolution Metagenomics of Human Gut Microbiota Generated by Nanopore and Illumina Hybrid Metagenome Assembly

Metagenome assembly is a core yet methodologically challenging step for taxonomic classification and functional annotation of a microbiome. This study aims to generate the high-resolution human gut metagenome using both Illumina and Nanopore platforms. Assembly was achieved using four assemblers, including Flye (Nanopore), metaSPAdes (Illumina), hybridSPAdes (Illumina and Nanopore), and OPERA-MS (Illumina and Nanopore). Hybrid metagenome assembly was shown to generate contigs with almost same sizes comparable to those produced using Illumina reads alone, but was more contiguous, informative, and longer compared with those assembled with Illumina reads only. In addition, hybrid metagenome assembly enables us to obtain complete plasmid sequences and much more AMR gene-encoding contigs than the Illumina method. Most importantly, using our workflow, 58 novel high-quality metagenome bins were obtained from four assembly algorithms, particularly hybrid assembly (47/58), although metaSPAdes could provide 11 high-quality bins independently. Among them, 29 bins were currently uncultured bacterial metagenome-assembled genomes. These findings were highly consistent and supported by mock community data tested. In the analysis of biosynthetic gene clusters (BGCs), the number of BGCs in the contigs from hybridSPAdes (241) is higher than that of contigs from metaSPAdes (233). In conclusion, hybrid metagenome assembly could significantly enhance the efficiency of contig assembly, taxonomic binning, and genome construction compared with procedures using Illumina short-read data alone, indicating that nanopore long reads are highly useful in metagenomic applications. This technique could be used to create high-resolution references for future human metagenome studies.

Longitudinal and Comparative Analysis of Gut Microbiota of Tunisian Newborns According to Delivery Mode

Microbiota colonization is a dynamic process that impacts the health status during an individual's lifetime. The composition of the gut microbiota of newborns is conditioned by multiple factors, including the delivery mode (DM). Nonetheless, the DM's influence remains uncertain and is still the subject of debate. In this context, the medical indication and the emergency of a cesarean delivery might have led to confounding conclusions regarding the composition and diversity of the neonatal microbiome. Herein, we used high-resolution shotgun sequencing to decipher the composition and dynamics of the gut microbiota composition of Tunisian newborns. Stool samples were collected from 5 elective cesarean section (ECS) and 5 vaginally delivered (VD) newborns at the following time points: Day 0, Day 15, and Day 30. The ECS and VD newborns showed the same level of bacterial richness and diversity. In addition, our data pointed to a shift in microbiota community composition during the first 2 weeks, regardless of the DM. Both ECS and VD showed a profile dominated by Proteobacteria, Actinobacteria, and Firmicutes. However, ECS showed an underrepresentation of Bacteroides and an enrichment of opportunistic pathogenic species of the ESKAPE group, starting from the second week. Besides revealing the intestinal microbiota of Tunisian newborns, this study provides novel insights into the microbiota perturbations caused by ECS.

Next-generation sequencing: insights to advance clinical investigations of the microbiome

Next-generation sequencing (NGS) technology has advanced our understanding of the human microbiome by allowing for the discovery and characterization of unculturable microbes with prediction of their function. Key NGS methods include 16S rRNA gene sequencing, shotgun metagenomic sequencing, and RNA sequencing. The choice of which NGS methodology to pursue for a given purpose is often unclear for clinicians and researchers. In this Review, we describe the fundamentals of NGS, with a focus on 16S rRNA and shotgun metagenomic sequencing. We also discuss pros and cons of each methodology as well as important concepts in data variability, study design, and clinical metadata collection. We further present examples of how NGS studies of the human microbiome have advanced our understanding of human disease pathophysiology across diverse clinical contexts, including the development of diagnostics and therapeutics. Finally, we share insights as to how NGS might further be integrated into and advance microbiome research and clinical care in the coming years.

De Novo Assembly and Annotation of the Vaginal Metatranscriptome Associated with Bacterial Vaginosis

The vaginal microbiome plays an important role in women’s health and disease. Here we reanalyzed 40 vaginal transcriptomes from a previous study of de novo assembly (metaT-Assembly) followed by functional annotation. We identified 286,293 contigs and further assigned them to 25 phyla, 209 genera, and 339 species. Lactobacillus iners and Lactobacillus crispatus dominated the microbiome of non-bacterial vaginosis (BV) samples, while a complex of microbiota was identified from BV-associated samples. The metaT-Assembly identified a higher number of bacterial species than the 16S rRNA amplicon and metaT-Kraken methods. However, metaT-Assembly and metaT-Kraken exhibited similar major bacterial composition at the species level. Binning of metatranscriptome data resulted in 176 bins from major known bacteria and several unidentified bacteria in the vagina. Functional analyses based on Clusters of Orthologous Genes (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways suggested that a higher number of transcripts were expressed by the microbiome complex in the BV-associated samples than in non-BV-associated samples. The KEGG pathway analysis with an individual bacterial genome identified specific functions of the identified bacterial genome. Taken together, we demonstrated that the metaT-Assembly approach is an efficient tool to understand the dynamic microbial communities and their functional roles associated with the human vagina.

Reconstitution and Transmission of Gut Microbiomes and Their Genes between Generations

Microbiomes are transmitted between generations by a variety of different vertical and/or horizontal modes, including vegetative reproduction (vertical), via female germ cells (vertical), coprophagy and regurgitation (vertical and horizontal), physical contact starting at birth (vertical and horizontal), breast-feeding (vertical), and via the environment (horizontal). Analyses of vertical transmission can result in false negatives (failure to detect rare microbes) and false positives (strain variants). In humans, offspring receive most of their initial gut microbiota vertically from mothers during birth, via breast-feeding and close contact. Horizontal transmission is common in marine organisms and involves selectivity in determining which environmental microbes can colonize the organism's microbiome. The following arguments are put forth concerning accurate microbial transmission: First, the transmission may be of functions, not necessarily of species; second, horizontal transmission may be as accurate as vertical transmission; third, detection techniques may fail to detect rare microbes; lastly, microbiomes develop and reach maturity with their hosts. In spite of the great variation in means of transmission discussed in this paper, microbiomes and their functions are transferred from one generation of holobionts to the next with fidelity. This provides a strong basis for each holobiont to be considered a unique biological entity and a level of selection in evolution, largely maintaining the uniqueness of the entity and conserving the species from one generation to the next.

Undervalued Pseudo-nifH Sequences in Public Databases Distort Metagenomic Insights into Biological Nitrogen Fixers

Nitrogen fixation, a distinct process incorporating the inactive atmospheric nitrogen into the active biological processes, has been a major topic in biological and geochemical studies. Currently, insights into diversity and distribution of nitrogen-fixing microbes are dependent upon homology-based analyses of nitrogenase genes, especially the nifH gene, which are broadly conserved in nitrogen-fixing microbes. Here, we report the pitfall of using nifH as a marker of microbial nitrogen fixation. We exhaustively analyzed genomes in RefSeq (231,908 genomes) and KEGG (6,509 genomes) and cooccurrence and gene order patterns of nitrogenase genes (including nifH) therein. Up to 20% of nifH-harboring genomes lacked nifD and nifK, which encode essential subunits of nitrogenase, within 10 coding sequences upstream or downstream of nifH or on the same genome. According to a phenotypic database of prokaryotes, no species and strains harboring only nifH possess nitrogen-fixing activities, which shows that these nifH genes are "pseudo"-nifH genes. Pseudo-nifH sequences mainly belong to anaerobic microbes, including members of the class Clostridia and methanogens. We also detected many pseudo-nifH reads from metagenomic sequences of anaerobic environments such as animal guts, wastewater, paddy soils, and sediments. In some samples, pseudo-nifH overwhelmed the number of "true" nifH reads by 50% or 10 times. Because of the high sequence similarity between pseudo- and true-nifH, pronounced amounts of nifH-like reads were not confidently classified. Overall, our results encourage reconsideration of the conventional use of nifH for detecting nitrogen-fixing microbes, while suggesting that nifD or nifK would be a more reliable marker. IMPORTANCE Nitrogen-fixing microbes affect biogeochemical cycling, agricultural productivity, and microbial ecosystems, and their distributions have been investigated intensively using genomic and metagenomic sequencing. Currently, insights into nitrogen fixers in the environment have been acquired by homology searches against nitrogenase genes, particularly the nifH gene, in public databases. Here, we report that public databases include a significant amount of incorrectly annotated nifH sequences (pseudo-nifH). We exhaustively investigated the genomic structures of nifH-harboring genomes and found hundreds of pseudo-nifH sequences in RefSeq and KEGG. Over half of these pseudo-nifH sequences belonged to members of the class Clostridia, which is supposed to be a prominent nitrogen-fixing clade. We also found that the abundance of nitrogen fixers in metagenomes could be overestimated by 1.5 to >10 times due to pseudo-nifH recorded in public databases. Our results encourage reconsideration of the prevalent use of nifH as a marker of nitrogen-fixing microbes.