Microbiome research outlook: past, present, and future

Engineered Tissue Models to Decode Host-Microbiota Interactions

A mutualistic co-evolution exists between the host and its associated microbiota in the human body. Bacteria establish ecological niches in various tissues of the body, locally influencing their physiology and functions, but also contributing to the well-being of the whole organism through systemic communication with other distant niches (axis). Emerging evidence indicates that when the composition of the microbiota inhabiting the niche changes toward a pathogenic state (dysbiosis) and interactions with the host become unbalanced, diseases may present. In addition, imbalances within a single niche can cause dysbiosis in distant organs. Current research efforts are focused on elucidating the mechanisms leading to dysbiosis, with the goal of restoring tissue homeostasis. In vitro models can provide critical experimental platforms to address this need, by reproducing the niche cyto-architecture and physiology with high fidelity. This review surveys current in in vitro host-microbiota research strategies and provides a roadmap that can guide the field in further developing physiologically relevant in vitro models of ecological niches, thus enabling investigation of the role of the microbiota in human health and diseases. Lastly, given the Food and Drug Administration Modernization Act 2.0, this review highlights emerging in vitro strategies to support the development and validation of new therapies on the market.

A novel robust network construction and analysis workflow for mining infant microbiota relationships

The gut microbiota plays a crucial role in infant health, with its development during the first 1,000 days influencing health outcomes. Understanding the relationships within the microbiota is essential to linking its maturation process to these outcomes. Several network-based methods have been developed to analyze the developing patterns of infant microbiota, but evaluating the reliability and effectiveness of these approaches remains a challenge. In this study, we created a test data pool using public infant microbiome data sets to assess the performance of four different network-based methods, employing repeated sampling strategies. We found that our proposed Probability-Based Co-Detection Model (PBCDM) demonstrated the best stability and robustness, particularly in network attributes such as node counts, average links per node, and the positive-to-negative link (P/N) ratios. Using the PBCDM, we constructed microbial co-existence networks for infants at various ages, identifying core genera networks through a novel network shearing method. Analysis revealed that core genera were more similar between adjacent age ranges, with increasing competitive relationships among microbiota as the infant microbiome matured. In conclusion, the PBCDM-based networks reflect known features of infant microbiota and offer a promising approach for investigating microbial relationships. This methodology could also be applied to future studies of genomic, metabolic, and proteomic data.

IMPORTANCE

As a research method and strategy, network analysis holds great potential for mining the relationships of bacteria. However, consistency and solid workflows to construct and evaluate the process of network analysis are lacking. Here, we provide a solid workflow to evaluate the performance of different microbial networks, and a novel probability-based co-existence network construction method used to decipher infant microbiota relationships. Besides, a network shearing strategy based on percolation theory is applied to find the core genera and connections in microbial networks at different age ranges. And the PBCDM method and the network shearing workflow hold potential for mining microbiota relationships, even possibly for the future deciphering of genome, metabolite, and protein data.

MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics

The rapid growth of microbiome research has generated an unprecedented amount of multi-omics data, presenting challenges in data analysis and visualization. To address these issues, we present MicrobiomeStatPlots, a comprehensive platform offering streamlined, reproducible tools for microbiome data analysis and visualization. This platform integrates essential bioinformatics workflows with multi-omics pipelines and provides 82 distinct visualization cases for interpreting microbiome datasets. By incorporating basic tutorials and advanced R-based visualization strategies, MicrobiomeStatPlots enhances accessibility and usability for researchers. Users can customize plots, contribute to the platform's expansion, and access a wealth of bioinformatics knowledge freely on GitHub (https://github.com/YongxinLiu/MicrobiomeStatPlot). Future plans include extending support for metabolomics, viromics, and metatranscriptomics, along with seamless integration of visualization tools into omics workflows. MicrobiomeStatPlots bridges gaps in microbiome data analysis and visualization, paving the way for more efficient, impactful microbiome research.

EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research

Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in-depth analysis of microbial communities at both the high-resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers. To address these challenges, we developed EasyMetagenome, a user-friendly pipeline that supports multiple analysis methods, including quality control and host removal, read-based, assembly-based, and binning, along with advanced genome analysis. The pipeline also features customizable settings, comprehensive data visualizations, and detailed parameter explanations, ensuring its adaptability across a wide range of data scenarios. Looking forward, we aim to refine the pipeline by addressing host contamination issues, optimizing workflows for third-generation sequencing data, and integrating emerging technologies like deep learning and network analysis, to further enhance microbiome insights and data accuracy. EasyMetageonome is freely available at https://github.com/YongxinLiu/EasyMetagenome.

Benchmarking short-read metagenomics tools for removing host contamination

BACKGROUND

The rapid evolution of metagenomic sequencing technology offers remarkable opportunities to explore the intricate roles of microbiome in host health and disease, as well as to uncover the unknown structure and functions of microbial communities. However, the swift accumulation of metagenomic data poses substantial challenges for data analysis. Contamination from host DNA can substantially compromise result accuracy and increase additional computational resources by including nontarget sequences.

RESULTS

In this study, we assessed the impact of computational host DNA decontamination on downstream analyses, highlighting its importance in producing accurate results efficiently. We also evaluated the performance of conventional tools like KneadData, Bowtie2, BWA, KMCP, Kraken2, and KrakenUniq, each offering unique advantages for different applications. Furthermore, we highlighted the importance of an accurate host reference genome, noting that its absence negatively affected the decontamination performance across all tools.

CONCLUSIONS

Our findings underscore the need for careful selection of decontamination tools and reference genomes to enhance the accuracy of metagenomic analyses. These insights provide valuable guidance for improving the reliability and reproducibility of microbiome research.

Nanopore sequencing: flourishing in its teenage years

Over the past decade, nanopore sequencing has experienced significant advancements and changes, transitioning from an initially emerging technology to a significant instrument in the field of genomic sequencing. However, as advancements in next-generation sequencing technology persist, nanopore sequencing also improves. This paper reviews the developments, applications, and outlook on nanopore sequencing technology. Currently, nanopore sequencing supports both DNA and RNA sequencing, making it widely applicable in areas such as telomere-to-telomere (T2T) genome assembly, direct RNA sequencing (DRS), and metagenomics. The openness and versatility of nanopore sequencing have established it as a preferred option for an increasing number of research teams, signaling a transformative influence on life science research. As the nanopore sequencing technology advances, it provides a faster, more cost-effective approach with extended read lengths, demonstrating the significant potential for complex genome assembly, pathogen detection, environmental monitoring, and human disease research, offering a fresh perspective in sequencing technologies.

iMeta Conference 2024: Building an innovative scientific research ecosystem for microbiome and One Health

The iMeta Conference 2024 provides a platform to promote the development of an innovative scientific research ecosystem for microbiome and One Health. The four key components - Technology, Research (Biology), Academic journals, and Social media - form a synergistic ecosystem. Advanced technologies drive biological research, which generates novel insights that are disseminated through academic journals. Social media plays a crucial role in engaging the public and facilitating scientific communication, thus amplifying the impact of research. Together, these elements create a self-sustaining loop that fosters continuous innovation and collaboration in the field of bioinformatics, biotechnology and microbiome research.

Exploring protein natural diversity in environmental microbiomes with DeepMetagenome

Protein natural diversity offers a vast sequence space for protein engineering, and deep learning enables its detection from metagenomes/proteomes without prior assumptions. DeepMetagenome, a Python-based method, explores protein diversity through modules for training and analyzing sequence datasets. The deep learning model includes Embedding, Conv1D, LSTM, and Dense layers, with sequence feature analysis for data cleaning. Applied to metallothioneins from a database of over 146 million coding features, DeepMetagenome identified over 500 high-confidence metallothionein sequences, outperforming DIAMOND and CNN-based models. It showed stable performance compared to a Transformer-based model over 25 epochs. Among 23 synthesized sequences, 20 exhibited metal resistance. The tool also successfully explored the diversity of three additional protein families and is freely available on GitHub with detailed instructions.

Exploring the Frontier: The Human Microbiome's Role in Rare Childhood Neurological Diseases and Epilepsy

Emerging research into the human microbiome, an intricate ecosystem of microorganisms residing in and on our bodies, reveals that it plays a pivotal role in maintaining our health, highlighting the potential for microbiome-based interventions to prevent, diagnose, treat, and manage a myriad of diseases. The objective of this review is to highlight the importance of microbiome studies in enhancing our understanding of rare genetic epilepsy and related neurological disorders. Studies suggest that the gut microbiome, acting through the gut-brain axis, impacts the development and severity of epileptic conditions in children. Disruptions in microbial composition can affect neurotransmitter systems, inflammatory responses, and immune regulation, which are all critical factors in the pathogenesis of epilepsy. This growing body of evidence points to the potential of microbiome-targeted therapies, such as probiotics or dietary modifications, as innovative approaches to managing epilepsy. By harnessing the power of the microbiome, we stand to develop more effective and personalized treatment strategies for children affected by this disease and other rare neurological diseases.

The role of KLF5 in gut microbiota and lung adenocarcinoma: unveiling programmed cell death pathways and prognostic biomarkers

Lung adenocarcinoma (LUAD) is the most important subtype of lung cancer. It is well known that the gut microbiome plays an important role in the pathophysiology of various diseases, including cancer, but little research has been done on the intestinal microbiome associated with LUAD. Utilizing bioinformatics tools and data analysis, we identified novel potential prognostic biomarkers for LUAD. To integrate differentially expressed genes and clinical significance modules, we used a weighted correlation network analysis system. According to the Peryton database and the gutMGene database, the composition and structure of gut microbiota in LUAD patients differed from those in healthy individuals. LUAD was associated with 150 gut microbiota and 767 gut microbiota targets, with Krüppel-like factor 5 (KLF5) being the most closely related. KLF5 was associated with immune status and correlated well with the prognosis of LUAD patients. The identification of KLF5 as a potential prognostic biomarker suggests its utility in improving risk stratification and guiding personalized treatment strategies for LUAD patients. Altogether, KLF5 could be a potential prognostic biomarker in LUAD.

The vaginal microbiota of healthy female cats

The vaginal microbiota of the queen (i.e., female cat) has never been described using culture independent methods. The objectives of the present research were to describe the vaginal microbiota of healthy domestic shorthair queens using both 16S rRNA sequencing and culture, and to assess the effects of age, living environment, and reproductive season on its composition. Thirty queens undergoing elective ovariectomy were included in the study. The vaginal samples were collected just before surgery, from animals under general anaesthesia. Two consecutive mini-swabs were introduced in the queens' vaginal tract. A preliminary study with 10 healthy queens aimed to negate sampling order's effect. Two consecutive samples for sequencing (5 queens, 10 swabs) and culture (5 queens, 10 swabs) were collected, confirming a match (100 % in culture, Bray-Curtis P = 0.96 in sequencing). The experiment included 20 queens that were prospectively grouped based on age (prepubertal N = 10, adult N = 10), living environment (indoor N = 10, outdoor N = 10), and time of the year, whether during the reproductive season (N = 10) or during seasonal anoestrous (N = 10). Bacteria were identified through metataxonomic analysis, amplifying the V1-V2 regions of 16S rRNA gene, and through standard culture followed by MALDI-TOF MS. The feline vaginal microbiota is dominated by Proteobacteria, Firmicutes, Bacteroidota, and Actinobacteria. Escherichia-Shigella, Streptococcus, and Pasteurella were the most abundant genera. Although culture underestimated bacterial richness and diversity compared to sequencing, Escherichia and Streptococcus were the most isolated bacteria. No bacterial growth was observed in 15 % of samples (N = 3/20), whereas growth of one or two bacterial species was observed in 64.7 % (N = 11/17) and 35.3 % (N = 6/17) of cases, respectively. No differences in terms of alpha (Kruskal-Wallis rank sum test P = 0.65) and beta diversity (Bray-Curtis, Unweighted and Weighted UniFrac analyses P > 0.5) were observed. Although a difference in alpha diversity based on phylogenetic tree (P = 0.02) was detected between indoor and outdoor queens. In conclusion, mixed and monoculture of Escherichia coli, Streptococcus canis, Staphylococcus felis, and Enterococcus spp. are normal findings within the cat vagina. Age and reproductive season do not influence the feline vaginal microbiota, whereas further research is needed to elucidate the role of the living environment.

The Relationship Between Gut Microbiome and Ophthalmologic Diseases: A Comprehensive Review

The gut microbiome has been studied in recent years due to its association with various pathological pathways involved in different diseases, caused by its structure, function, and diversity alteration. The knowledge of this mechanism has generated interest in the investigation of its relationship with ophthalmologic diseases. Recent studies infer the existence of a gut-eye microbiota axis, influenced by the intestinal barrier, the blood-retina barrier, and the immune privilege of the eye. A common denominator among ophthalmologic diseases that have been related to this axis is inflammation, which is perpetuated by dysbiosis, causing an alteration of the intestinal barrier leading to increased permeability and, in turn, the release of components such as lipopolysaccharides (LPS), trimethylamine oxide (TMAO), and bacterial translocation. Some theories explain that depending on how the microbiome is composed, a different type of T cells will be activated, while others say that some bacteria can pre-activate T cells that mimic ocular structures and intestinal permeability that allow leakage of metabolites into the circulation. In addition, therapies such as probiotics, diet, and fecal microbiota transplantation (FMT) have been shown to favor the presence of a balanced population of microorganisms that limit inflammation and, in turn, generate a beneficial effect in these eye pathologies. This review aims to analyze how the intestinal microbiome influences various ocular pathologies based on microbial composition and pathological mechanisms, which may provide a better understanding of the diseases and their therapeutic potential.

Vaginal microbiota are associated with in vitro fertilization during female infertility

The vaginal microbiome plays an essential role in the reproductive health of human females. As infertility increases worldwide, understanding the roles that the vaginal microbiome may have in infertility and in vitro fertilization (IVF) treatment outcomes is critical. To determine the vaginal microbiome composition of 1411 individuals (1255 undergoing embryo transplantation) and their associations with reproductive outcomes, clinical and biochemical features are measured, and vaginal samples are 16S rRNA sequenced. Our results suggest that both too high and too low abundance of Lactobacillus is not beneficial for pregnancy; a moderate abundance is more beneficial. A moderate abundance of Lactobacillus crispatus and Lactobacillus iners (~80%) (with a pregnancy rate of I-B: 54.35% and III-B: 57.73%) is found beneficial for pregnancy outcomes compared with a higher abundance (>90%) of Lactobacillus (I-A: 44.81% and III-A: 51.06%, respectively). The community state type (CST) IV-B (contains a high to moderate relative abundance of Gardnerella vaginalis) shows a similar pregnant ratio (48.09%) with I-A and III-A, and the pregnant women in this CST have a higher abundance of Lactobacillus species. Metagenome analysis of 71 samples shows that nonpregnant women are detected with more antibiotic-resistance genes, and Proteobacteria and Firmicutes are the main hosts. The inherent differences within and between women in different infertility groups suggest that vaginal microbes might be used to detect infertility and potentially improve IVF outcomes.

Evaluation of Safety and Beneficial Health Effects of the Human-Milk Strain Bifidobacterium breve DSM32583: An Infant Pilot Trial

Human milk promotes the growth of bifidobacteria in the infant gut. Adding bifidobacterial species to infant formula may contribute to increasing their presence in the gut of formula-fed infants. Therefore, the safety and anti-infectious effects of Bifidobacterium breve DSM32583, a breast milk isolate, were assessed in a pilot trial involving 3-month-old infants. The infants were randomly assigned to either the probiotic (PG) or the control (CG) groups. All the infants consumed the same formula, although it was supplemented with the strain (1 × 107 cfu/g of formula) in the PG. Overall, 160 infants (80 per group) finished the intervention. Infants in CG gained more weight compared to PG (p < 0.05), but the weights for age Z-scores at 6 months were within the normal distribution for this age group. The rates of infections affecting the gastrointestinal and respiratory tracts and antibiotic therapy were significantly lower in the PG. The bifidobacterial population and the level of short-chain fatty acids were higher (p < 0.05) in the fecal samples of PG infants. No adverse events related to formula consumption were observed. In conclusion, the administration of an infant formula with B. breve DSM32583 was safe and exerted potential beneficial effects on gut health.

The Microbiome Protocols eBook initiative: Building a bridge to microbiome research

The Microbiome Protocols eBook (MPB) serves as a crucial bridge, filling gaps in microbiome protocols for both wet experiments and data analysis. The first edition, launched in 2020, featured 152 meticulously curated protocols, garnering widespread acclaim. We now extend a sincere invitation to researchers to participate in the upcoming 2nd version of MPB, contributing their valuable protocols to advance microbiome research.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Changes in seminal plasma microecological dynamics and the mechanistic impact of core metabolite hexadecanamide in asthenozoospermia patients

Asthenozoospermia (AZS) is a prevalent contributor to male infertility, characterized by a substantial decline in sperm motility. In recent years, large-scale studies have explored the interplay between the male reproductive system's microecology and its implications for reproductive health. Nevertheless, the direct association between seminal microecology and male infertility pathogenesis remains inconclusive. This study used 16S rDNA sequencing and multi-omics analysis to conduct a comprehensive investigation of the seminal microbial community and metabolites in AZS patients. Patients were categorized into four distinct groups: Normal, mild AZS (AZS-I), moderate AZS (AZS-II), and severe AZS (AZS-III). Microbiome differential abundance analysis revealed significant differences in microbial composition and metabolite profiles within the seminal plasma of these groups. Subsequently, patients were classified into a control group (Normal and AZS-I) and an AZS group (AZS-II and AZS-III). Correlation and cross-reference analyses identified distinct microbial genera and metabolites. Notably, the AZS group exhibited a reduced abundance of bacterial genera such as Pseudomonas, Serratia, and Methylobacterium-Methylorubrum in seminal plasma, positively correlating with core differential metabolite (hexadecanamide). Conversely, the AZS group displayed an increased abundance of bacterial genera such as Uruburuella, Vibrio, and Pseudoalteromonas, with a negative correlation with core differential metabolite (hexadecanamide). In vitro and in vivo experiments validated that hexadecanamide significantly enhanced sperm motility. Using predictive metabolite-targeting gene analysis and single-cell transcriptome sequencing, we profiled the gene expression of candidate target genes PAOX and CA2. Protein immunoblotting techniques validated the upregulation protein levels of PAOX and CA2 in sperm samples after hexadecanamide treatment, enhancing sperm motility. In conclusion, this study uncovered a significant correlation between six microbial genera in seminal plasma and the content of the metabolite hexadecanamide, which is related to AZS. Hexadecanamide notably enhances sperm motility, suggesting its potential integration into clinical strategies for managing AZS, providing a foundational framework for diagnostic and therapeutic advancements.

Intestinal flora and pregnancy complications: Current insights and future prospects

Numerous studies have demonstrated the pivotal roles of intestinal microbiota in many physiopathological processes through complex interactions with the host. As a unique period in a woman's lifespan, pregnancy is characterized by changes in hormones, immunity, and metabolism. The gut microbiota also changes during this period and plays a crucial role in maintaining a healthy pregnancy. Consequently, anomalies in the composition and function of the gut microbiota, namely, gut microbiota dysbiosis, can predispose individuals to various pregnancy complications, posing substantial risks to both maternal and neonatal health. However, there are still many controversies in this field, such as "sterile womb" versus "in utero colonization." Therefore, a thorough understanding of the roles and mechanisms of gut microbiota in pregnancy and its complications is essential to safeguard the health of both mother and child. This review provides a comprehensive overview of the changes in gut microbiota during pregnancy, its abnormalities in common pregnancy complications, and potential etiological implications. It also explores the potential of gut microbiota in diagnosing and treating pregnancy complications and examines the possibility of gut-derived bacteria residing in the uterus/placenta. Our aim is to expand knowledge in maternal and infant health from the gut microbiota perspective, aiding in developing new preventive and therapeutic strategies for pregnancy complications based on intestinal microecology.

Update on the gut microbiome in health and diseases

The Human Microbiome Project, Earth Microbiome Project, and next-generation sequencing have advanced novel genome association, host genetic linkages, and pathogen identification. The microbiome is the sum of the microbes, their genetic information, and their ecological niche. This study will describe how millions of bacteria in the gut affect the human body in health and disease. The gut microbiome changes in relation with age, with an increase in Bacteroidetes and Firmicutes. Host and environmental factors affecting the gut microbiome are diet, drugs, age, smoking, exercise, and host genetics. In addition, changes in the gut microbiome may affect the local gut immune system and systemic immune system. In this study, we discuss how the microbiome may affect the metabolism of healthy subjects or may affect the pathogenesis of metabolism-generating metabolic diseases. Due to the high number of publications on the argument, from a methodologically point of view, we decided to select the best papers published in referred journals in the last 3 years. Then we selected the previously published papers. The major goals of our study were to elucidate which microbiome and by which pathways are related to healthy and disease conditions.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

Antibiotic failure: Beyond antimicrobial resistance

Despite significant progress in antibiotic discovery, millions of lives are lost annually to infections. Surprisingly, the failure of antimicrobial treatments to effectively eliminate pathogens frequently cannot be attributed to genetically-encoded antibiotic resistance. This review aims to shed light on the fundamental mechanisms contributing to clinical scenarios where antimicrobial therapies are ineffective (i.e., antibiotic failure), emphasizing critical factors impacting this under-recognized issue. Explored aspects include biofilm formation and sepsis, as well as the underlying microbiome. Therapeutic strategies beyond antibiotics, are examined to address the dimensions and resolution of antibiotic failure, actively contributing to this persistent but escalating crisis. We discuss the clinical relevance of antibiotic failure beyond resistance, limited availability of therapies, potential of new antibiotics to be ineffective, and the urgent need for novel anti-infectives or host-directed therapies directly addressing antibiotic failure. Particularly noteworthy is multidrug adaptive resistance in biofilms that represent 65 % of infections, due to the lack of approved therapies. Sepsis, responsible for 19.7 % of all deaths (as well as severe COVID-19 deaths), is a further manifestation of this issue, since antibiotics are the primary frontline therapy, and yet 23 % of patients succumb to this condition.