Accurate and sensitive detection of microbial eukaryotes from whole metagenome shotgun sequencing

Gut microbiota and microbial metabolites for osteoporosis

Osteoporosis is an age-related bone metabolic disease. As an essential endocrine organ, the skeletal system is intricately connected with extraosseous organs. The crosstalk between bones and other organs supports this view. In recent years, the link between the gut microecology and bone metabolism has become an important research topic, both in preclinical studies and in clinical trials. Many studies have shown that skeletal changes are accompanied by changes in the composition and structure of the gut microbiota (GM). At the same time, natural or artificial interventions targeting the GM can subsequently affect bone metabolism. Moreover, microbiome-related metabolites may have important effects on bone metabolism. We aim to review the relationships among the GM, microbial metabolites, and bone metabolism and to summarize the potential mechanisms involved and the theory of the gut‒bone axis. We also describe existing bottlenecks in laboratory studies, as well as existing challenges in clinical settings, and propose possible future research directions.

VirNucPro: an identifier for the identification of viral short sequences using six-frame translation and large language models

Viruses are ubiquitous in nature, yet our understanding of them remains limited. High-throughput sequencing technology facilitates the unbiased revelation of genetic composition in samples; however, viral sequences typically make up a small proportion of the entire sequencing data, making it challenging to accurately identify the few or fragmented viral sequences present in a sample. The limited features and information provided by short sequences result in insufficient resolution of viral sequences by existing models. Therefore, we propose a new model, VirNucPro, for short viral sequence identification. Based on a six-frame translation strategy and large language models, we combine nucleotide and amino acid sequence information to enhance feature extraction for short sequences, achieving high accuracy in identifying short viral sequences. Ablation experiments compared the contributions of nucleotide and amino acid sequence features to the model, confirming that the introduced amino acid features significantly contribute to the classification results. Our model outperforms others, such as GCNFrame, DeepVirFinder, DETIRE, and Virtifier, which have demonstrated good performance in identifying short viral sequences of 300 and 500 bp. Our model demonstrates excellent performance on carefully created real-world datasets. Additionally, it can scan for prophage regions within long bacterial fragments, offering a wide range of applications. The codes are available at: https://github.com/Li-Jing-1997/VirNucPro.

Diet shapes and maintains the personalized native gut microbiomes in mice

BACKGROUND

The gut microbiome plays a critical role in human health and disease. Different dietary backgrounds play an important role in the uniqueness and diversity of the gut microbiota in different individuals, which promotes heterogeneity in disease phenotypes and treatment responses. Here, we explored how diet affects the composition and function of the native gut microbiome of model mice, based on the shotgun metagenomic and metabolomic, by analyzing the gut microbiome of C57B/6J mice in different dietary backgrounds.

RESULTS

The gut microbiomes of mice receiving different diets consistently exhibit distinct compositions across bacterial species, strains, fungi and phages. This implies that native microbial communities cannot 'homogenize' rapidly becaise of priority effects and unchanging diets. Notably, hotspot bacteria such as Limosilactobacillus reuteri, Parabacteroides distasonis and Akkermansia muciniphila were significantly different among the groups. These species harbor diverse adaptive mutations, reflecting genomic evolutionary diversity. The functional profiles of the gut microbiota also exhibit selective differences, involving the capacity for carbohydrate, branched-chain amino acid and fatty acid synthesis, as well as virulence factors, carbohydrate-active enzymes and antibiotic resistance. Furthermore, the differences in the gut microbiota also propagate to the host's serum, where structural and specific metabolite differences were observed. Metabolites that directly impact host health, such as d-glucosamine 6-phosphate and testolic acid, also show significant differences between the different dietary groups.

CONCLUSION

Our findings underscore the profound influence of different dietary the composition and functionality of the gut microbiome, offering valuable insights into optimizing health outcomes through personalized nutritional interventions. © 2024 Society of Chemical Industry.

Challenges in capturing the mycobiome from shotgun metagenome data: lack of software and databases

BACKGROUND

The mycobiome, representing the fungal component of microbial communities, is increasingly acknowledged as an integral part of the gut microbiome. However, research in this area remains relatively limited. The characterization of mycobiome taxa from metagenomic data is heavily reliant on the quality of the software and databases. In this study, we evaluated the feasibility of mycobiome profiling using existing bioinformatics tools on simulated fungal metagenomic data.

RESULTS

We identified seven tools claiming to perform taxonomic assignment of fungal shotgun metagenomic sequences. One of these was outdated and required substantial modifications of the code to be functional and was thus excluded. To evaluate the accuracy of identification and relative abundance of the remaining tools (Kraken2, MetaPhlAn4, EukDetect, FunOMIC, MiCoP, and HumanMycobiomeScan), we constructed 18 mock communities of varying species richness and abundance levels. The mock communities comprised up to 165 fungal species belonging to the phyla Ascomycota and Basidiomycota, commonly found in gut microbiomes. Of the tools, FunOMIC and HumanMycobiomeScan needed source code modifications to run. Notably, only one species, Candida orthopsilosis, was consistently identified by all tools across all communities where it was included. Increasing community richness improved precision of Kraken2 and the relative abundance accuracy of all tools on species, genus, and family levels. MetaPhlAn4 accurately identified all genera present in the communities and FunOMIC identified most species. The top three tools for overall accuracy in both identification and relative abundance estimation were EukDetect, MiCoP, and FunOMIC, respectively. Adding 90% and 99% bacterial background did not significantly impact these tools' performance. Among the whole genome reference tools (Kraken2, HMS, and MiCoP), MiCoP exhibited the highest accuracy when the same reference database was used.

CONCLUSION

Our survey of mycobiome-specific software revealed a very limited selection of such tools and their poor robustness due to error-prone software, along with a significant lack of comprehensive databases enabling characterization of the mycobiome. None of the implemented tools fully agreed on the mock community profiles. FunOMIC recognized most of the species, but EukDetect and MiCoP provided predictions that were closest to the correct compositions. The bacterial background did not impact these tools' performance. Video Abstract.

What defines a photosynthetic microbial mat in western Antarctica?

Antarctic microbial mats, with their significant biodiversity and key role in biogeochemical cycling, were the focus of our study. We employed a metagenomic approach to analyze 14 microbial mats from meltwater streams of western Antarctica, covering the Maritime, Peninsula, and Dry Valleys regions. Our findings revealed that the taxonomic compositional level of the microbial mat communities is characterized by similar bacterial groups, with diatoms being the main distinguishing factor between the rapidly warming Maritime Antarctica and the other mats. Bacteria were found to be the predominant component of all microbial mats (>90%), followed by Eukarya (>3%), Archaea (<1%), and Viruses (<0.1%). The average abundance of the main phyla composing Antarctic microbial mats included Bacteroidota (35%), Pseudomonadota (29%), Cyanobacteriota (19%), Verrucomicrobiota (3%), Bacillariophyta (2%), Planctomycetota (2%), Acidobacteriota (2%), Actinomycetota (2%), Bacillota (1%), and Chloroflexota (1%). We also identified some microeukaryotes that could play essential roles in the functioning of Antarctic microbial mats. Notably, all mats were found in sites with varied environmental characteristics, showed N-limitation, and shared functional patterns.

Examining the healthy human microbiome concept

Human microbiomes are essential to health throughout the lifespan and are increasingly recognized and studied for their roles in metabolic, immunological and neurological processes. Although the full complexity of these microbial communities is not fully understood, their clinical and industrial exploitation is well advanced and expanding, needing greater oversight guided by a consensus from the research community. One of the most controversial issues in microbiome research is the definition of a 'healthy' human microbiome. This concept is complicated by the microbial variability over different spatial and temporal scales along with the challenge of applying a unified definition to the spectrum of healthy microbiome configurations. In this Perspective, we examine the progress made and the key gaps that remain to be addressed to fully harness the benefits of the human microbiome. We propose a road map to expand our knowledge of the microbiome-health relationship, incorporating epidemiological approaches informed by the unique ecological characteristics of these communities.

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases

Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations within various microbiomes, including those in the mammalian gastrointestinal (GI) tract, remain relatively underexplored in metagenomic studies owing to the lack of comprehensive reference genome databases and robust bioinformatic tools. The GI tract of ruminants, particularly the rumen, contains a high eukaryotic biomass but a relatively low diversity of ciliates and fungi, which significantly impacts feed digestion, methane emissions, and rumen microbial ecology. In the present study, we developed GutEuk, a bioinformatics tool that improves upon the currently available Tiara and EukRep in accurately identifying eukaryotic sequences from metagenomes. GutEuk is optimized for high precision across different sequence lengths. It can also distinguish fungal and protozoal sequences, further elucidating their unique ecological, physiological, and nutritional impacts. GutEuk was shown to facilitate comprehensive analyses of protozoa and fungi within more than 1000 rumen metagenomes, revealing a greater genomic diversity among protozoa than previously documented. We further curated several ruminant eukaryotic protein databases, significantly enhancing our ability to distinguish the functional roles of ruminant fungi and protozoa from those of prokaryotes. Overall, the newly developed package GutEuk and its associated databases create new opportunities for the in-depth study of GI tract eukaryotes.

Delving into Roccaverano PDO cheese: A comprehensive examination of microbial diversity and flavour profiles compared to non-PDO cheeses

Roccaverano Protected Designation of Origin (PDO) is a fresh soft cheese produced in Roccaverano area (Italy). This study aimed to evaluate Roccaverano PDO microbiota, together with aromatic profile and sensory analysis to be compared with 15 non-PDO cheeses of the same type. Microbiota was evaluated through shotgun metagenomics sequencing, while GC-MS analysis was conducted to study volatile organic compounds (VOCs) presence and concentration. Sensory analyses were conducted through ONAF (Italian National Organization of Cheese Tasters) evaluation parameters followed by flash profile sensory analysis of selected cheeses. The results demonstrated Lactococcus lactis predominance in both non-PDO and PDO cheeses, while Streptococcus thermophilus was more abundant in non-PDO group. A higher abundance of Kluyveromyces lactis was observed in Roccaverano PDO, which exhibited greater fungal diversity compared to non-PDO cheeses. Metagenome-Assembled Genomes of 26 L. lactis and 19 Leuconostoc mesenteroides showed absence of significant differences in terms of average nucleotide identity and pangenomes partitions. The ONAF sensory evaluation demonstrated a higher average score of Roccaverano PDO group. Flash profile analysis demonstrated that lactic aroma/odour, acid, astringent, vegetal odour, exotic fruit and fermented aroma, hazelnut flavour and sweet were associated with high ONAF scores. The concentration of butanoic acid, 2-methyl-, ethyl ester and butanoic acid, 3-methyl- (sweat, acid, rancid related) were higher in PDO cheeses, while reads related to butanoate metabolism were less abundant compared to non-PDO samples. Several fungal species (included K. lactis) were associated with astringents, acid and chalky flavours. Roccaverano PDO demonstrates unique characteristics even maintaining a certain degree of variability between samples.

Pitfalls in gut single-cell eukaryote research

Gut single-celled eukaryotes (GSCEs) are found in billions of people worldwide, but we still know little about their functions and relationships in human gut ecology. Lately, retrospective analysis of bacterial data obtained by next-generation sequencing (NGS) methods has been used to identify links between GSCEs, gut bacteria, host metabolism, and host phenotypical traits, suggesting possible direct or indirect associations to favorable gut microbiome features and other health parameters. Here, we highlight some of the pitfalls related to the research strategy typically used so far and propose action points that could pave the way for a more accurate understanding of GSCEs in human health and disease.

Insights into gut fungi in pigs: A comprehensive review

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

Metagenomic insights into the resistome, mobilome, and virulome of dogs with diverse lifestyles

BACKGROUND

Dogs-whether pets, rural, or stray-exhibit distinct living styles that influence their fecal microbiota and resistomes, yet these dynamics remain underexplored. This study aimed to analyze and compare the fecal microbiota and resistomes of three groups of dogs (37 pets, 20 rural, and 25 stray dogs) in Shanghai, China.

RESULTS

Metagenomic analysis revealed substantial differences in fecal microbial composition and metabolic activities among the dog groups. Pet dogs displayed the lowest microbial diversity. Using Shapley Additive Explanations (SHAP), an interpretable machine learning approach, Ligilactobacillus emerged as the most diverse genus, with significantly higher SHAP values in stray dogs, suggesting enhanced adaptability to more variable and less controlled environments. Across all samples, 587 antibiotic resistance genes (ARGs) were identified, conferring resistance to 14 antibiotic classes. A striking observation was the detection of mcr-1 in one pet dog, indicating a potential public health risk. The floR gene was identified as a key differentiator in resistance profiles, particularly in pet and rural dogs, likely due to antibiotic exposure in their environments.

CONCLUSION

This study provides the first comprehensive assessment of fecal microbiota and resistome variations among dogs with different lifestyles, revealing a less resilient microbiome and heightened antimicrobial resistance in pet dogs, which could have public health implications.

Unlocking the Potential of Metagenomics with the PacBio High-Fidelity Sequencing Technology

Traditional methods for studying microbial communities have been limited due to difficulties in culturing and sequencing all microbial species. Recent advances in third-generation sequencing technologies, particularly PacBio's high-fidelity (HiFi) sequencing, have significantly advanced metagenomics by providing accurate long-read sequences. This review explores the role of HiFi sequencing in overcoming the limitations of previous sequencing methods, including high error rates and fragmented assemblies. We discuss the benefits and applications of HiFi sequencing across various environments, such as the human gut and soil, which provides broader context for further exploration. Key studies are discussed to highlight HiFi sequencing's ability to recover complete and coherent microbial genomes from complex microbiomes, showcasing its superior accuracy and continuity compared to other sequencing technologies. Additionally, we explore the potential applications of HiFi sequencing in quantitative microbial analysis, as well as the detection of single nucleotide variations (SNVs) and structural variations (SVs). PacBio HiFi sequencing is establishing a new benchmark in metagenomics, with the potential to significantly enhance our understanding of microbial ecology and drive forward advancements in both environmental and clinical applications.

4CAC: 4-class classifier of metagenome contigs using machine learning and assembly graphs

Microbial communities usually harbor a mix of bacteria, archaea, plasmids, viruses and microeukaryotes. Within these communities, viruses, plasmids, and microeukaryotes coexist in relatively low abundance, yet they engage in intricate interactions with bacteria. Moreover, viruses and plasmids, as mobile genetic elements, play important roles in horizontal gene transfer and the development of antibiotic resistance within microbial populations. However, due to the difficulty of identifying viruses, plasmids, and microeukaryotes in microbial communities, our understanding of these minor classes lags behind that of bacteria and archaea. Recently, several classifiers have been developed to separate one or more minor classes from bacteria and archaea in metagenome assemblies. However, these classifiers often overlook the issue of class imbalance, leading to low precision in identifying the minor classes. Here, we developed a classifier called 4CAC that is able to identify viruses, plasmids, microeukaryotes, and prokaryotes simultaneously from metagenome assemblies. 4CAC generates an initial four-way classification using several sequence length-adjusted XGBoost models and further improves the classification using the assembly graph. Evaluation on simulated and real metagenome datasets demonstrates that 4CAC substantially outperforms existing classifiers and combinations thereof on short reads. On long reads, it also shows an advantage unless the abundance of the minor classes is very low. 4CAC runs 1-2 orders of magnitude faster than the other classifiers. The 4CAC software is available at https://github.com/Shamir-Lab/4CAC.

Metagenomics Applied to the Respiratory Mycobiome in Cystic Fibrosis

Cystic fibrosis (CF) is a genetic disorder characterized by chronic microbial colonization and inflammation of the respiratory tract (RT), leading to pulmonary exacerbation (PEx) and lung damage. Although the lung bacterial microbiota has been extensively studied, the mycobiome remains understudied. However, its importance as a contributor to CF pathophysiology has been highlighted. The objective of this review is to provide an overview of the current state of knowledge regarding the mycobiome, as described through NGS-based studies, in patients with CF (pwCF).Several studies have demonstrated that the mycobiome in CF lungs is a dynamic entity, exhibiting a lower diversity and abundance than the bacterial microbiome. Nevertheless, the progression of lung damage is associated with a decrease in fungal and bacterial diversity. The core mycobiome of the RT in pwCFs is mainly composed of yeasts (Candida spp., Malassezia spp.) and molds with lower abundance. Some fungi (Aspergillus, Scedosporium/Pseudallescheria) have been demonstrated to play a role in PEx, while the involvement of others (Candida, Pneumocystis) remains uncertain. The "climax attack" ecological model has been proposed to explain the complexity and interplay of microbial populations in the RT, leading to PEx and lung damage. NGS-based studies also enable the detection of intra- and interkingdom correlations between fungi and bacteria. Further studies are required to ascertain the biological and pathophysiological relevance of these correlations. Finally, with the recent advent of CFTR modulators, our understanding of the pulmonary microbiome and mycobiome in pwCFs is about to change.

Turning the needle into the haystack: Culture-independent amplification of complex microbial genomes directly from their native environment

High-throughput sequencing (HTS) has revolutionized microbiology, but many microbes exist at low abundance in their natural environment and/or are difficult, if not impossible, to culture in the laboratory. This makes it challenging to use HTS to study the genomes of many important microbes and pathogens. In this review, we discuss the development and application of selective whole genome amplification (SWGA) to allow whole or partial genomes to be sequenced for low abundance microbes directly from complex biological samples. We highlight ways in which genomic data generated by SWGA have been used to elucidate the population dynamics of important human pathogens and monitor development of antimicrobial resistance and the emergence of potential outbreaks. We also describe the limitations of this method and propose some potential innovations that could be used to improve the quality of SWGA and lower the barriers to using this method across a wider range of infectious pathogens.

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

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

Occurrence of Free-Living Amoebae in Non-Human Primate Gut

The gut microbiome reflects health and predicts possible disease in hosts. A holistic view of this community is needed, focusing on identifying species and dissecting how species interact with their host and each other, regardless of whether their presence is beneficial, inconsequential, or detrimental. The distribution of gut-associated eukaryotes within and across non-human primates is likely driven by host behavior and ecology. To ascertain the existence of free-living amoebae (FLA) in the gut of wild and captive non-human primates, 101 stool samples were collected and submitted to culture-dependent microscopy examination and DNA sequencing. Free-living amoebae were detected in 45.4% (46/101) of fecal samples analyzed, and their morphological characteristics matched those of Acanthamoeba spp., Vermamoeba spp., heterolobosean amoeboflagellates and fan-shaped amoebae of the family Vannellidae. Sequence analysis of the PCR products revealed that the suspected amoebae are highly homologous (99% identity and 100% query coverage) with Acanthamoeba T4 genotype and Vermamoeba vermiformis amoebae. The results showed a great diversity of amoebae in the non-human primate's microbiome, which may pose a potential risk to the health of NHPs. To our knowledge, this is the first report of free-living amoebae in non-human primates that are naturally infected. However, it is unknown whether gut-borne amoebae exploit a viable ecological niche or are simply transient residents in the gut.

Improved sampling and DNA extraction procedures for microbiome analysis in food-processing environments

Deep investigation of the microbiome of food-production and food-processing environments through whole-metagenome sequencing (WMS) can provide detailed information on the taxonomic composition and functional potential of the microbial communities that inhabit them, with huge potential benefits for environmental monitoring programs. However, certain technical challenges jeopardize the application of WMS technologies with this aim, with the most relevant one being the recovery of a sufficient amount of DNA from the frequently low-biomass samples collected from the equipment, tools and surfaces of food-processing plants. Here, we present the first complete workflow, with optimized DNA-purification methodology, to obtain high-quality WMS sequencing results from samples taken from food-production and food-processing environments and reconstruct metagenome assembled genomes (MAGs). The protocol can yield DNA loads >10 ng in >98% of samples and >500 ng in 57.1% of samples and allows the collection of, on average, 12.2 MAGs per sample (with up to 62 MAGs in a single sample) in ~1 week, including both laboratory and computational work. This markedly improves on results previously obtained in studies performing WMS of processing environments and using other protocols not specifically developed to sequence these types of sample, in which <2 MAGs per sample were obtained. The full protocol has been developed and applied in the framework of the European Union project MASTER (Microbiome applications for sustainable food systems through technologies and enterprise) in 114 food-processing facilities from different production sectors.

Increasing transposase abundance with ocean depth correlates with a particle-associated lifestyle

Transposases are mobile genetic elements that move within and between genomes, promoting genomic plasticity in microorganisms. In marine microbial communities, the abundance of transposases increases with depth, but the reasons behind this trend remain unclear. Our analysis of metagenomes from the Tara Oceans and Malaspina Expeditions suggests that a particle-associated lifestyle is the main covariate for the high occurrence of transposases in the deep ocean, and this trend holds true for individual genomes as well as in a community-wide sense. We observed a strong and depth-independent correlation between transposase abundance and the presence of biofilm-associated genes, as well as the prevalence of secretory enzymes. This suggests that mobile genetic elements readily propagate among microbial communities within crowded biofilms. Furthermore, we show that particle association positively correlates with larger genome size, which is in turn associated with higher transposase abundance. Cassette sequences associated with transposons are enriched with genes related to defense mechanisms, which are more highly expressed in the deep sea. Thus, while transposons spread at the expense of their microbial hosts, they also introduce novel genes and potentially benefit the hosts in helping to compete for limited resources. Overall, our results suggest a new understanding of deep ocean particles as highways for gene sharing among defensively oriented microbial genomes.IMPORTANCEGenes can move within and between microbial genomes via mobile genetic elements, which include transposases and transposons. In the oceans, there is a puzzling increase in transposase abundance in microbial genomes as depth increases. To gain insight into this trend, we conducted an extensive analysis of marine microbial metagenomes and metatranscriptomes. We found a significant correlation between transposase abundance and a particle-associated lifestyle among marine microbes at both the metagenome and genome-resolved levels. We also observed a link between transposase abundance and genes related to defense mechanisms. These results suggest that as microbes become densely packed into crowded particles, mobile genes are more likely to spread and carry genetic material that provides a competitive advantage in crowded habitats. This may enable deep sea microbes to effectively compete in such environments.

Prokaryotic and eukaryotic skin microbiota modifications triggered by Leishmania infection in localized Cutaneous Leishmaniasis

Cutaneous Leishmaniasis (CL) is a tropical disease characterized by cutaneous ulcers, sometimes with satellite lesions and nodular lymphangitis. Leishmania parasites, transmitted by sandfly vectors, cause this widespread public health challenge affecting millions worldwide. CL's complexity stems from diverse Leishmania species and intricate host interactions. Therefore, this study aims to shed light on the spatial-temporal distribution of Leishmania species and exploring the influence of skin microbiota on disease progression. We analyzed 40 samples from CL patients at three military bases across Colombia. Using Oxford Nanopore's Heat Shock Protein 70 sequencing, we identified Leishmania species and profiled microbiota in CL lesions and corresponding healthy limbs. Illumina sequencing of 16S-rRNA and 18S-rRNA genes helped analyze prokaryotic and eukaryotic communities. Our research uncovered a spatial-temporal overlap between regions of high CL incidence and our sampling locations, indicating the coexistence of various Leishmania species. L. naiffi emerged as a noteworthy discovery. In addition, our study delved into the changes in skin microbiota associated with CL lesions sampled by scraping compared with healthy skin sampled by brushing of upper and lower limbs. We observed alterations in microbial diversity, both in prokaryotic and eukaryotic communities, within the lesioned areas, signifying the potential role of microbiota in CL pathogenesis. The significant increase in specific bacterial families, such as Staphylococcaceae and Streptococcaceae, within CL lesions indicates their contribution to local inflammation. In essence, our study contributes to the ongoing research into CL, highlighting the need for a multifaceted approach to decipher the intricate interactions between Leishmaniasis and the skin microbiota.

Fast detection of bacterial gut pathogens on miniaturized devices: an overview

INTRODUCTION

Gut microbes pose challenges like colon inflammation, deadly diarrhea, antimicrobial resistance dissemination, and chronic disease onset. Development of early, rapid and specific diagnosis tools is essential for improving infection control. Point-of-care testing (POCT) systems offer rapid, sensitive, low-cost and sample-to-answer methods for microbe detection from various clinical and environmental samples, bringing the advantages of portability, automation, and simple operation.

AREAS COVERED

Rapid detection of gut microbes can be done using a wide array of techniques including biosensors, immunological assays, electrochemical impedance spectroscopy, mass spectrometry and molecular biology. Inclusion of Internet of Things, machine learning, and smartphone-based point-of-care applications is an important aspect of POCT. In this review, the authors discuss various fast diagnostic platforms for gut pathogens and their main challenges.

EXPERT OPINION

Developing effective assays for microbe detection can be complex. Assay design must consider factors like target selection, real-time and multiplex detection, sample type, reagent stability and storage, primer/probe design, and optimizing reaction conditions for accuracy and sensitivity. Mitigating these challenges requires interdisciplinary collaboration among scientists, clinicians, engineers, and industry partners. Future efforts are essential to enhance sensitivity, specificity, and versatility of POCT systems for gut microbe detection and quantification, advancing infectious disease diagnostics and management.

Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing

The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics.

A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection

Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Candida spp. in Human Intestinal Health and Disease: More than a Gut Feeling

Fungi are an essential part of the normal collection of intestinal microorganisms, even though their collective abundance comprises only 0.1-1% of all fecal microbes. The composition and role of the fungal population is often studied in relation to early-life microbial colonization and development of the (mucosal) immune system. The genus Candida is frequently described as one of the most abundant genera, and altered fungal compositions (including elevated abundance of Candida spp.) have been linked with intestinal diseases such as inflammatory bowel disease and irritable bowel syndrome. These studies are performed using both culture-dependent and genomic (metabarcoding) techniques. In this review, we aimed to summarize existing data on intestinal Candida spp. colonization in relation to intestinal disease and provide a brief overview of the biological and technical challenges in this field, including the recently described role of sub-species strain variation of intestinal Candida albicans. Together, the evidence for a contributing role of Candida spp. in pediatric and adult intestinal disease is quickly expanding, even though technical and biological challenges may limit full understanding of host-microbe interactions.

Metagenomics and metabolomics approaches in the study of Candida albicans colonization of host niches: a framework for finding microbiome-based antifungal strategies

In silico and experimental approaches have allowed an ever-growing understanding of the interactions within the microbiota. For instance, recently acquired data have increased knowledge of the mechanisms that support, in the gut and vaginal microbiota, the resistance to colonization by Candida albicans, an opportunistic fungal pathogen whose overgrowth can initiate severe infections in immunocompromised patients. Here, we review how bacteria from the microbiota interact with C. albicans. We show how recent OMICs-based pipelines, using metagenomics and/or metabolomics, have identified bacterial species and metabolites modulating C. albicans growth. We finally discuss how the combined use of cutting-edge OMICs-based and experimental approaches could provide new means to control C. albicans overgrowth within the microbiota and prevent its consequences.

Metagenomics and metatranscriptomics as potential driving forces for the exploration of diversity and functions of micro-eukaryotes in soil

Micro-eukaryotes are ubiquitous and play vital roles in diverse ecological systems, yet their diversity and functions are scarcely known. This may be due to the limitations of formerly used conventional culture-based methods. Metagenomics and metatranscriptomics are enabling to unravel the genomic, metabolic, and phylogenetic diversity of micro-eukaryotes inhabiting in different ecosystems in a more comprehensive manner. The in-depth study of structural and functional characteristics of micro-eukaryote community residing in soil is crucial for the complete understanding of this major ecosystem. This review provides a deep insight into the methodologies employed under these approaches to study soil micro-eukaryotic organisms. Furthermore, the review describes available computational tools, pipelines, and database sources and their manipulation for the analysis of sequence data of micro-eukaryotic origin. The challenges and limitations of these approaches are also discussed in detail. In addition, this review summarizes the key findings of metagenomic and metatranscriptomic studies on soil micro-eukaryotes. It also highlights the exploitation of these methods to study the structural as well as functional profiles of soil micro-eukaryotic community and to screen functional eukaryotic protein coding genes for biotechnological applications along with the future perspectives in the field.

Rhizosphere shapes the associations between protistan predators and bacteria within microbiomes through the deterministic selection on bacterial communities

The assembly of bacterial communities in the rhizosphere is well-documented and plays a crucial role in supporting plant performance. However, we have limited knowledge of how plant rhizosphere determines the assembly of protistan predators and whether the potential associations between protistan predators and bacterial communities shift due to rhizosphere selection. To address this, we examined bacterial and protistan taxa from 443 agricultural soil samples including bulk and rhizosphere soils. Our results presented distinct patterns of bacteria and protistan predators in rhizosphere microbiome assembly. Community assembly of protistan predators was determined by a stochastic process in the rhizosphere and the diversity of protistan predators was reduced in the rhizosphere compared to bulk soils, these may be attributed to the indirect impacts from the altered bacterial communities that showed deterministic process assembly in the rhizosphere. Interestingly, we observed that the plant rhizosphere facilitates more close interrelationships between protistan predators and bacterial communities, which might promote a healthy rhizosphere microbial community for plant growth. Overall, our findings indicate that the potential predator-prey relationships within the microbiome, mediated by plant rhizosphere, might contribute to plant performance in agricultural ecosystems.

The role of fungi in the diagnosis of colorectal cancer

Colorectal cancer (CRC) is a prevalent tumour with high morbidity rates worldwide, and its incidence among younger populations is rising. Early diagnosis of CRC can help control the associated mortality. Fungi are common microorganisms in nature. Recent studies have shown that fungi may have a similar association with tumours as bacteria do. As an increasing number of tumour-associated fungi are discovered, this provides new ideas for the diagnosis and prognosis of tumours. The relationship between fungi and colorectal tumours has also been recently identified by scientists. Therefore, this paper describes the limitations and prospects of the application of fungi in diagnosing CRC and predicting CRC prognosis.

Nasopharyngeal fungal subtypes of infant bronchiolitis and disease severity risk

BACKGROUND

Bronchiolitis is a leading cause of infant hospitalization. Recent research suggests the heterogeneity within bronchiolitis and the relationship of airway viruses and bacteria with bronchiolitis severity. However, little is known about the pathobiological role of fungi. We aimed to identify bronchiolitis mycotypes by integrating fungus and virus data, and determine their association with bronchiolitis severity and biological characteristics.

METHODS

In a multicentre prospective cohort study of 398 infants (age <1 year, male 59%) hospitalized for bronchiolitis, we applied clustering approaches to identify mycotypes by integrating nasopharyngeal fungus (detected in RNA-sequencing data) and virus data (respiratory syncytial virus [RSV], rhinovirus [RV]) at hospitalization. We examined their association with bronchiolitis severity-defined by positive pressure ventilation (PPV) use and biological characteristics by nasopharyngeal metatranscriptome and transcriptome data.

RESULTS

In infants hospitalized for bronchiolitis, we identified four mycotypes: A) fungiM.restrictavirusRSV/RV, B) fungiM.restrictavirusRSV, C) fungiM.globosavirusRSV/RV, D) funginot-detectedvirusRSV/RV mycotypes. Compared to mycotype A infants (the largest subtype, n = 211), mycotype C infants (n = 85) had a significantly lower risk of PPV use (7% vs. 1%, adjOR, 0.21; 95% CI, 0.02-0.90; p = 0.033), while the risk of PPV use was not significantly different in mycotype B or D. In the metatranscriptome and transcriptome data, mycotype C had similar bacterial composition and microbial functions yet dysregulated pathways (e.g., Fc γ receptor-mediated phagocytosis pathway and chemokine signaling pathway; FDR <0.05).

INTERPRETATION

In this multicentre cohort, fungus-virus clustering identified distinct mycotypes of infant bronchiolitis with differential severity risks and unique biological characteristics.

FUNDING

This study was supported by the National Institutes of Health.

The endohyphal microbiome: current progress and challenges for scaling down integrative multi-omic microbiome research

As microbiome research has progressed, it has become clear that most, if not all, eukaryotic organisms are hosts to microbiomes composed of prokaryotes, other eukaryotes, and viruses. Fungi have only recently been considered holobionts with their own microbiomes, as filamentous fungi have been found to harbor bacteria (including cyanobacteria), mycoviruses, other fungi, and whole algal cells within their hyphae. Constituents of this complex endohyphal microbiome have been interrogated using multi-omic approaches. However, a lack of tools, techniques, and standardization for integrative multi-omics for small-scale microbiomes (e.g., intracellular microbiomes) has limited progress towards investigating and understanding the total diversity of the endohyphal microbiome and its functional impacts on fungal hosts. Understanding microbiome impacts on fungal hosts will advance explorations of how "microbiomes within microbiomes" affect broader microbial community dynamics and ecological functions. Progress to date as well as ongoing challenges of performing integrative multi-omics on the endohyphal microbiome is discussed herein. Addressing the challenges associated with the sample extraction, sample preparation, multi-omic data generation, and multi-omic data analysis and integration will help advance current knowledge of the endohyphal microbiome and provide a road map for shrinking microbiome investigations to smaller scales. Video Abstract.

Microbial Diversity and Functional Potential of Keem: A Traditional Starter Culture for Alcoholic Beverage-Application of Next-Generation Amplicon and Shotgun Metagenome Sequences

"Pakhoi" is an ethnic drink of the Tons valley, Uttarakhand, India produced by fermenting jaggery and barley with the help of a starter culture called "keem". In the present study, we investigated the microbial diversity and associated functional potential of "keem" using shotgun metagenome sequencing and amplicon sequencing. We also compared the taxonomic data obtained using these two sequencing techniques. The results showed that shotgun sequencing revealed a higher resolution of taxonomic profiling as compared to the amplicon sequencing. Furthermore, it was found that the genera detected by shotgun sequencing were valuable for facilitating the fermentation process. Additionally, to understand the functional profiling of the genera, different databases were used for annotation, resulting in a total of 13 metabolic pathways. The five most abundant KEGG functions were genetic information processing, metabolism, translation, cofactor and vitamin metabolism and xenobiotic degradation. In contrast, the top five COG were in order of highest frequency sequences belonging to transcription, followed by general function prediction, carbohydrate transport metabolism, amino acid transport and metabolism and translation and biogenesis. Gene ontology revealed many pathways, biochemical processes and molecular functions associated with the organisms forming the starter culture. Overall, the present study can help to understand the microbial diversity and its role in fermentation of traditional alcoholic beverages using "Keem".

Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome

Aspergillus fumigatus, an opportunistic human pathogen, frequently infects the lungs of people with cystic fibrosis and is one of the most common causes of infectious-disease death in immunocompromised patients. Here, we construct 252 strain-specific, genome-scale metabolic models of this important fungal pathogen to study and better understand the metabolic component of its pathogenic versatility. The models show that 23.1% of A. fumigatus metabolic reactions are not conserved across strains and are mainly associated with amino acid, nucleotide, and nitrogen metabolism. Profiles of non-conserved reactions and growth-supporting reaction fluxes are sufficient to differentiate strains, for example by environmental or clinical origin. In addition, shotgun metagenomics analysis of sputum from 40 cystic fibrosis patients (15 females, 25 males) before and after diagnosis with an A. fumigatus colonization suggests that the fungus shapes the lung microbiome towards a more beneficial fungal growth environment associated with aromatic amino acid availability and the shikimate pathway. Our findings are starting points for the development of drugs or microbiome intervention strategies targeting fungal metabolic needs for survival and colonization in the non-native environment of the human lung.

Multiomics characterisation of the zoo-housed gorilla gut microbiome reveals bacterial community compositions shifts, fungal cellulose-degrading, and archaeal methanogenic activity

We carried out a comparative analysis between the bacterial microbiota composition of zoo-housed western lowland gorillas and their wild counterparts through 16S rRNA gene amplicon sequencing. In addition, we characterised the carbohydrate-active and methanogenic potential of the zoo-housed gorilla (ZHG) microbiome through shotgun metagenomics and RNA sequencing. The ZHG microbiota showed increased alpha diversity in terms of bacterial species richness and a distinct composition from that of the wild gorilla microbiota, including a loss of abundant fibre-degrading and hydrogenic Chloroflexi. Metagenomic analysis of the CAZyome indicated predominant oligosaccharide-degrading activity, while RNA sequencing revealed diverse cellulase and hemi-cellulase activities in the ZHG gut, contributing to a total of 268 identified carbohydrate-active enzymes. Metatranscriptome analysis revealed a substantial contribution of 38% of the transcripts from anaerobic fungi and archaea to the gorilla microbiome. This activity originates from cellulose-degrading and hydrogenic fungal species belonging to the class Neocallimastigomycetes, as well as from methylotrophic and hydrogenotrophic methanogenic archaea belonging to the classes Thermoplasmata and Methanobacteria, respectively. Our study shows the added value of RNA sequencing in a multiomics approach and highlights the contribution of eukaryotic and archaeal activities to the gut microbiome of gorillas.

A Large-Scale Study into Protist-Animal Interactions Based on Public Genomic Data Using DNA Barcodes

With the birth of next-generation sequencing (NGS) technology, genomic data in public databases have increased exponentially. Unfortunately, exogenous contamination or intracellular parasite sequences in assemblies could confuse genomic analysis. Meanwhile, they can provide a valuable resource for studies of host-microbe interactions. Here, we used a strategy based on DNA barcodes to scan protistan contamination in the GenBank WGS/TSA database. The results showed a total of 13,952 metazoan/animal assemblies in GenBank, where 17,036 contigs were found to be protistan contaminants in 1507 assemblies (10.8%), with even higher contamination rates in taxa of Cnidaria (150/281), Crustacea (237/480), and Mollusca (107/410). Taxonomic analysis of the protists derived from these contigs showed variations in abundance and evenness of protistan contamination across different metazoan taxa, reflecting host preferences of Apicomplexa, Ciliophora, Oomycota and Symbiodiniaceae for mammals and birds, Crustacea, insects, and Cnidaria, respectively. Finally, mitochondrial proteins COX1 and CYTB were predicted from these contigs, and the phylogenetic analysis corroborated the protistan origination and heterogeneous distribution of the contaminated contigs. Overall, in this study, we conducted a large-scale scan of protistan contaminant in genomic resources, and the protistan sequences detected will help uncover the protist diversity and relationships of these picoeukaryotes with Metazoa.

Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes

The gut microbiome modulates immune and metabolic health. Human microbiome data are biased toward industrialized populations, limiting our understanding of non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing on 351 fecal samples from the Hadza hunter-gatherers of Tanzania and comparative populations in Nepal and California. We recovered 91,662 genomes of bacteria, archaea, bacteriophages, and eukaryotes, 44% of which are absent from existing unified datasets. We identified 124 gut-resident species vanishing in industrialized populations and highlighted distinct aspects of the Hadza gut microbiome related to in situ replication rates, signatures of selection, and strain sharing. Industrialized gut microbes were found to be enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource, expands our understanding of microbes capable of colonizing the human gut, and clarifies the extensive perturbation induced by the industrialized lifestyle.

Computational methods and challenges in analyzing intratumoral microbiome data

The human microbiome is intimately related to cancer biology and plays a vital role in the efficacy of cancer treatments, including immunotherapy. Extraordinary evidence has revealed that several microbes influence tumor development through interaction with the host immune system, that is, immuno-oncology-microbiome (IOM). This review focuses on the intratumoral microbiome in IOM and describes the available data and computational methods for discovering biological insights of microbial profiling from host bulk, single-cell, and spatial sequencing data. Critical challenges in data analysis and integration are discussed. Specifically, the microorganisms associated with cancer and cancer treatment in the context of IOM are collected and integrated from the literature. Lastly, we provide our perspectives for future directions in IOM research.

Biocontrol Screening of Endophytes: Applications and Limitations

The considerable loss of crop productivity each year due to plant disease or pathogen invasion during pre- or post-harvest storage conditions is one of the most severe challenges to achieving the goals of food security for the rising global population. Although chemical pesticides severally affect the food quality and health of consumers, a large population relies on them for plant disease management. But currently, endophytes have been considered one of the most suitable biocontrol agents due to better colonization and acclimatization potential. However, a very limited number of endophytes have been used commercially as biocontrol agents. Isolation of endophytes and their screening to represent potential characteristics as biocontrol agents are considered challenging by different procedures. Through a web search using the keywords "endophytes as biocontrol agents" or "biocontrol mechanism of endophytes," we have succinctly summarised the isolation strategies and different in vitro and in vivo biocontrol screening methods of endophytic biocontrol agents in the present review. In this paper, biocontrol mechanisms of endophytes and their potential application in plant disease management have also been discussed. Furthermore, the registration and regulatory mechanism of the endophytic biocontrol agents are also covered.

Current and emerging trends in techniques for plant pathogen detection

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.

Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota?

It has been shown that the gut microbiota plays a central role in human health and disease. A wide range of volatile metabolites present in exhaled breath have been linked with gut microbiota and proposed as a non-invasive marker for monitoring pathological conditions. The aim of this study was to examine the possible correlation between volatile organic compounds (VOCs) in exhaled breath and the fecal microbiome by multivariate statistical analysis in gastric cancer patients (n = 16) and healthy controls (n = 33). Shotgun metagenomic sequencing was used to characterize the fecal microbiota. Breath-VOC profiles in the same participants were identified by an untargeted gas chromatography-mass spectrometry (GC-MS) technique. A multivariate statistical approach involving a canonical correlation analysis (CCA) and sparse principal component analysis identified the significant relationship between the breath VOCs and fecal microbiota. This relation was found to differ between gastric cancer patients and healthy controls. In 16 cancer cases, 14 distinct metabolites identified from the breath belonging to hydrocarbons, alcohols, aromatics, ketones, ethers, and organosulfur compounds were highly correlated with 33 fecal bacterial taxa (correlation of 0.891, p-value 0.045), whereas in 33 healthy controls, 7 volatile metabolites belonging to alcohols, aldehydes, esters, phenols, and benzamide derivatives correlated with 17 bacterial taxa (correlation of 0.871, p-value 0.0007). This study suggested that the correlation between fecal microbiota and breath VOCs was effective in identifying exhaled volatile metabolites and the functional effects of microbiome, thus helping to understand cancer-related changes and improving the survival and life expectancy in gastric cancer patients.

Influence of Microbiota on Vaccine Effectiveness: "Is the Microbiota the Key to Vaccine-induced Responses?"

Vaccines are one of the most powerful tools for preventing infectious diseases. To effectively fight pathogens, vaccines should induce potent and long-lasting immune responses that are specific to the pathogens. However, not all vaccines can induce effective immune responses, and the responses vary greatly among individuals and populations. Although several factors, such as age, host genetics, nutritional status, and region, affect the effectiveness of vaccines, increasing data have suggested that the gut microbiota is critically associated with vaccine-induced immune responses. In this review, I discuss how gut microbiota affects vaccine effectiveness based on the clinical and preclinical data, and summarize possible underlying mechanisms related to the adjuvant effects of microbiota. A better understanding of the link between vaccine-induced immune responses and the gut microbiota using high-throughput technology and sophisticated system vaccinology approaches could provide crucial insights for designing effective personalized preventive and therapeutic vaccination strategies.

Improved eukaryotic detection compatible with large-scale automated analysis of metagenomes

BACKGROUND

Eukaryotes such as fungi and protists frequently accompany bacteria and archaea in microbial communities. Unfortunately, their presence is difficult to study with "shotgun" metagenomic sequencing since prokaryotic signals dominate in most environments. Recent methods for eukaryotic detection use eukaryote-specific marker genes, but they do not incorporate strategies to handle the presence of eukaryotes that are not represented in the reference marker gene set, and they are not compatible with web-based tools for downstream analysis.

RESULTS

Here, we present CORRAL (for Clustering Of Related Reference ALignments), a tool for the identification of eukaryotes in shotgun metagenomic data based on alignments to eukaryote-specific marker genes and Markov clustering. Using a combination of simulated datasets, mock community standards, and large publicly available human microbiome studies, we demonstrate that our method is not only sensitive and accurate but is also capable of inferring the presence of eukaryotes not included in the marker gene reference, such as novel strains. Finally, we deploy CORRAL on our MicrobiomeDB.org resource, producing an atlas of eukaryotes present in various environments of the human body and linking their presence to study covariates.

CONCLUSIONS

CORRAL allows eukaryotic detection to be automated and carried out at scale. Implementation of CORRAL in MicrobiomeDB.org creates a running atlas of microbial eukaryotes in metagenomic studies. Since our approach is independent of the reference used, it may be applicable to other contexts where shotgun metagenomic reads are matched against redundant but non-exhaustive databases, such as the identification of bacterial virulence genes or taxonomic classification of viral reads. Video Abstract.

Linking prokaryotic genome size variation to metabolic potential and environment

While theories and models have appeared to explain genome size as a result of evolutionary processes, little work has shown that genome sizes carry ecological signatures. Our work delves into the ecological implications of microbial genome size variation in benthic and pelagic habitats across environmental gradients of the brackish Baltic Sea. While depth is significantly associated with genome size in benthic and pelagic brackish metagenomes, salinity is only correlated to genome size in benthic metagenomes. Overall, we confirm that prokaryotic genome sizes in Baltic sediments (3.47 Mbp) are significantly bigger than in the water column (2.96 Mbp). While benthic genomes have a higher number of functions than pelagic genomes, the smallest genomes coded for a higher number of module steps per Mbp for most of the functions irrespective of their environment. Some examples of this functions are amino acid metabolism and central carbohydrate metabolism. However, we observed that nitrogen metabolism was almost absent in pelagic genomes and was mostly present in benthic genomes. Finally, we also show that Bacteria inhabiting Baltic sediments and water column not only differ in taxonomy, but also in their metabolic potential, such as the Wood-Ljungdahl pathway or the presence of different hydrogenases. Our work shows how microbial genome size is linked to abiotic factors in the environment, metabolic potential and taxonomic identity of Bacteria and Archaea within aquatic ecosystems.

Xanthomonas infection and ozone stress distinctly influence the microbial community structure and interactions in the pepper phyllosphere

While the physiological and transcriptional response of the host to biotic and abiotic stresses have been intensely studied, little is known about the resilience of associated microbiomes and their contribution towards tolerance or response to these stresses. We evaluated the impact of elevated tropospheric ozone (O3), individually and in combination with Xanthomonas perforans infection, under open-top chamber field conditions on overall disease outcome on resistant and susceptible pepper cultivars, and their associated microbiome structure, function, and interaction network across the growing season. Pathogen infection resulted in a distinct microbial community structure and functions on the susceptible cultivar, while concurrent O3 stress did not further alter the community structure, and function. However, O3 stress exacerbated the disease severity on resistant cultivar. This altered diseased severity was accompanied by enhanced heterogeneity in associated Xanthomonas population counts, although no significant shift in overall microbiota density, microbial community structure, and function was evident. Microbial co-occurrence networks under simultaneous O3 stress and pathogen challenge indicated a shift in the most influential taxa and a less connected network, which may reflect the altered stability of interactions among community members. Increased disease severity on resistant cultivar may be explained by such altered microbial co-occurrence network, indicating the altered microbiome-associated prophylactic shield against pathogens under elevated O3. Our findings demonstrate that microbial communities respond distinctly to individual and simultaneous stressors, in this case, O3 stress and pathogen infection, and can play a significant role in predicting how plant-pathogen interactions would change in the face of climate change.

The Cystic Fibrosis Upper and Lower Airway Metagenome

The microbial metagenome in cystic fibrosis (CF) airways was investigated by whole-genome shotgun sequencing of total DNA isolated from nasal lavage samples, oropharyngeal swabs, and induced sputum samples collected from 65 individuals with CF aged 7 to 50 years. Each patient harbored a personalized microbial metagenome unique in microbial load and composition, the exception being monocultures of the most common CF pathogens Staphylococcus aureus and Pseudomonas aeruginosa from patients with advanced lung disease. The sampling of the upper airways by nasal lavage uncovered the fungus Malassezia restricta and the bacterium Staphylococcus epidermidis as prominent species. Healthy and CF donors harbored qualitatively and quantitatively different spectra of commensal bacteria in their sputa, even in the absence of any typical CF pathogen. If P. aeruginosa, S. aureus, or Stenotrophomonas maltophilia belonged to the trio of the most abundant species in the CF sputum metagenome, common inhabitants of the respiratory tract of healthy subjects, i.e., Eubacterium sulci, Fusobacterium periodonticum, and Neisseria subflava, were present only in low numbers or not detectable. Random forest analysis identified the numerical ecological parameters of the bacterial community, such as Shannon and Simpson diversity, as the key parameters that globally distinguish sputum samples from CF and healthy donors. IMPORTANCE Cystic fibrosis (CF) is the most common life-limiting monogenetic disease in European populations and is caused by mutations in the CFTR gene. Chronic airway infections with opportunistic pathogens are the major morbidity that determines prognosis and quality of life in most people with CF. We examined the composition of the microbial communities of the oral cavity and upper and lower airways in CF patients across all age groups. From early on, the spectrum of commensals is different in health and CF. Later on, when the common CF pathogens take up residence in the lungs, we observed differential modes of depletion of the commensal microbiota in the presence of S. aureus, P. aeruginosa, S. maltophilia, or combinations thereof. It remains to be seen whether the implementation of lifelong CFTR (cystic fibrosis transmembrane conductance regulator) modulation will change the temporal evolution of the CF airway metagenome.

Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020-21 reveals widespread transcription of antibiotic resistance genes

Municipal wastewater provides a representative sample of human fecal waste across a catchment area and contains a wide diversity of microbes. Sequencing wastewater samples provides information about human-associated and medically important microbial populations, and may be useful to assay disease prevalence and antimicrobial resistance (AMR). Here, we present a study in which we used untargeted metatranscriptomic sequencing on RNA extracted from 275 sewage influent samples obtained from eight wastewater treatment plants (WTPs) representing approximately 16 million people in Southern California between August 2020 - August 2021. We characterized bacterial and viral transcripts, assessed metabolic pathway activity, and identified over 2,000 AMR genes/variants across all samples. Because we did not deplete ribosomal RNA, we have a unique window into AMR carried as ribosomal mutants. We show that AMR diversity varied between WTPs (as measured through PERMANOVA, P < 0.001) and that the relative abundance of many individual AMR genes/variants increased over time (as measured with MaAsLin2, P_adj < 0.05). Similarly, we detected transcripts mapping to human pathogenic bacteria and viruses suggesting RNA sequencing is a powerful tool for wastewater-based epidemiology and that there are geographical signatures to microbial transcription. We captured the transcription of gene pathways common to bacterial cell processes, including central carbon metabolism, nucleotide synthesis/salvage, and amino acid biosynthesis. We also posit that due to the ubiquity of many viruses and bacteria in wastewater, new biological targets for microbial water quality assessment can be developed. To the best of our knowledge, our study provides the most complete longitudinal metatranscriptomic analysis of a large population's wastewater to date and demonstrates our ability to monitor the presence and activity of microbes in complex samples. By sequencing RNA, we can track the relative abundance of expressed AMR genes/variants and metabolic pathways, increasing our understanding of AMR activity across large human populations and sewer sheds.

Deciphering the Microbiome: Integrating Theory, New Technologies, and Inclusive Science

The diversity and functional significance of microbiomes have become increasingly clear through the extensive sampling of Earth's many habitats and the rapid adoption of new sequencing technologies. However, much remains unknown about what makes a "healthy" microbiome, how to restore a disrupted microbiome, and how microbiomes assemble. In December 2019, we convened a workshop that focused on how to identify potential "rules of life" that govern microbiome structure and function. This collection of mSystems Perspective pieces reflects many of the main challenges and opportunities in the field identified by both in-person and virtual workshop participants. By borrowing conceptual and theoretical approaches from other fields, including economics and philosophy, these pieces suggest new ways to dissect microbiome patterns and processes. The application of conceptual advances, including trait-based theory and community coalescence, is providing new insights on how to predict and manage microbiome diversity and function. Technological and analytical advances, including deep transfer learning, metabolic models, and advances in analytical chemistry, are helping us sift through complex systems to pinpoint mechanisms of microbiome assembly and dynamics. Integration of all of these advancements (theory, concepts, technology) across biological and spatial scales is providing dramatically improved temporal and spatial resolution of microbiome dynamics. This integrative microbiome research is happening in a new moment in science where academic institutions, scientific societies, and funding agencies must act collaboratively to support and train a diverse and inclusive community of microbiome scientists.

Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.