The past, present and future of microbiome analyses

Microbial DNA sample preservation and possible artifacts for field-based research in remote tropical peatlands

Surveying bacterial and archaeal microbial communities in host and environmental studies requires the collection and storage of samples. Many studies are conducted in distant locations challenging these prerequisites. The use of preserving buffers is an important alternative when lacking access to cryopreservation, however, its effectivity for samples with challenging chemistry or samples that provide opportunities for fast bacterial or archaeal growth upon exposure to an aerobic environment, like peat samples, requires methodological assessment. Here, in combination with an identified optimal DNA extraction kit for peat soil samples, we test the application of several commercial and a homemade preservation buffer and make recommendations on the method that can most effectively preserve a microbiome reflective of the original state. In treatments with a non-optimal buffer or in the absence, we observed notable community shifts beginning as early as three days post-preservation lowering diversity and community evenness, with growth-driven artifacts from a few specific phyla. However other buffers retain a very close composition relative to the original state, and we described several metrics to understand some variation across them. Due to the chemical effects of preservation buffers, it is critical to test their compatibility and reliability to preserve the original bacterial and archaeal community in different environments.

Fine-scale characterization of the soybean rhizosphere microbiome via synthetic long reads and avidity sequencing

BACKGROUND

The rhizosphere microbiome displays structural and functional dynamism driven by plant, microbial, and environmental factors. While such plasticity is a well-evidenced determinant of host health, individual and community-level microbial activity within the rhizosphere remain poorly understood, due in part to the insufficient taxonomic resolution achieved through traditional marker gene amplicon sequencing. This limitation necessitates more advanced approaches (e.g., long-read sequencing) to derive ecological inferences with practical application. To this end, the present study coupled synthetic long-read technology with avidity sequencing to investigate eukaryotic and prokaryotic microbiome dynamics within the soybean (Glycine max) rhizosphere under field conditions.

RESULTS

Synthetic long-read sequencing permitted de novo reconstruction of the entire 18S-ITS1-ITS2 region of the eukaryotic rRNA operon as well as all nine hypervariable regions of the 16S rRNA gene. All full-length, mapped eukaryotic amplicon sequence variants displayed genus-level classification, and 44.77% achieved species-level classification. The resultant eukaryotic microbiome encompassed five kingdoms (19 genera) of protists in addition to fungi - a depth unattainable with conventional short-read methods. In the prokaryotic fraction, every full-length, mapped amplicon sequence variant was resolved at the species level, and 23.13% at the strain level. Thirteen species of Bradyrhizobium were thereby distinguished in the prokaryotic microbiome, with strain-level identification of the two Bradyrhizobium species most reported to nodulate soybean. Moreover, the applied methodology delineated structural and compositional dynamism in response to experimental parameters (i.e., growth stage, cultivar, and biostimulant application), unveiled a saprotroph-rich core microbiome, provided empirical evidence for host selection of mutualistic taxa, and identified key microbial co-occurrence network members likely associated with edaphic and agronomic properties.

CONCLUSIONS

This study is the first to combine synthetic long-read technology and avidity sequencing to profile both eukaryotic and prokaryotic fractions of a plant-associated microbiome. Findings herein provide an unparalleled taxonomic resolution of the soybean rhizosphere microbiota and represent significant biological and technological advancements in crop microbiome research.

A metagenomic assessment of bacterial community in spices sold open-air markets in Saint-Louis, Senegal

Natural spices play an essential role in human nutrition and well-being. However, their processing on different scales can expose them to potential sources of contamination. This study aimed to describe the bacterial community genomic footprint in spices sold in Senegal. Spice samples were collected in August 2022 in Saint-Louis, Senegal. The genomic region coding bacterial 16S rRNA was then amplified and sequenced using Oxford Nanopore Technology (ONT). Sequencing was carried out on two batches of samples, one containing part of the "Local Spices or Herbs" (n = 10), and the other, a mixture of 7 spices, Curcuma, Thyme and the other part of the "Local Spices or Herbs" (n = 39). Results showed high bacterial diversity and the predominance of Escherichia coli and Salmonella enterica in samples, with total reads of 65,744 and 165,325 for the two batches, respectively. The sample category "Homemade mixture of food condiments ", which includes all "Local Spices or Herbs" samples, showed remarkable bacterial diversity. These were followed by Curcuma, a blend of 7 spices and thyme. Also, the different categories of spices studied show similarities in their bacterial composition. These results highlight the microbial community's highly diverse genomic profile, including pathogenic bacteria, in spice samples.

The Breast Microbiome in Breast Cancer Risk and Progression: A Narrative Review

A decade ago, studies in human populations first revealed the existence of a unique microbial community in the breast, a tissue historically viewed as sterile, with microbial origins seeded through the nipple and/or translocation from other body sites. Since then, research efforts have been made to characterize the microbiome in healthy and cancerous breast tissues. The purpose of this review is to summarize the current evidence for the association of the breast microbiome with breast cancer risk and progression. Briefly, while many studies have examined the breast microbiome in patients with breast cancer, and compared it with the microbiome of benign breast disease tissue or normal breast tissue, these studies have varied widely in their sample sizes, methods, and quality of evidence. Thus, while several large and rigorous cross-sectional studies have provided key evidence of an altered microbiome in breast tumors compared with normal adjacent and healthy control tissue, there are few consistent patterns of perturbed microbial taxa. In addition, only one large prospective study has provided evidence of a relationship between the breast tumor microbiota and cancer prognosis. Future research studies featuring large, well-characterized cohorts with prospective follow-up for breast cancer incidence, progression, and response to treatment are warranted.

Dynamic Changes in the Microbial Composition and Spoilage Characteristics of Refrigerated Large Yellow Croaker (Larimichthys crocea) during Storage

The quality changes, dynamic changes in microbial composition, and diversity changes in large yellow croaker (Larimichthys crocea) during 4 °C refrigeration were studied using 16S rDNA high-throughput sequencing technology, and the total viable count (TVC), total volatile basic nitrogen (TVB-N), and thiobarbituric acid-reactive substances (TBARS) were determined. The results revealed a consistent increase in TVC, TVB-N, and TBARS levels over time. On the 9th day, TVC reached 7.43 lg/(CFU/g), while on the 15th day, TVB-N exceeded the upper limit for acceptable quality, reaching 42.56 mg/100 g. Based on the 16S rDNA sequencing results, we categorized the storage period into three phases: early storage (0th and 3rd days), middle storage (6th day), and late storage (9th, 12th, and 15th days). As the storage time increased, both the species richness and diversity exhibited a declining trend. The dominant genus identified among the spoilage bacteria in refrigerated large yellow croaker was Pseudomonas, accounting for a high relative abundance of 82.33%. A comparison was carried out of the spoilage-causing ability of three strains of Pseudomonas screened and isolated from the fish at the end of storage, and they were ranked as follows, from strongest to weakest: P. fluorescen, P. lundensis, and P. psychrophila. This study will provide a theoretical basis for extending the shelf life of large yellow croaker.

Linking plant functional genes to rhizosphere microbes: a review

The importance of rhizomicrobiome in plant development, nutrition acquisition and stress tolerance is unquestionable. Relevant plant genes corresponding to the above functions also regulate rhizomicrobiome construction. Deciphering the molecular regulatory network of plant-microbe interactions could substantially contribute to improving crop yield and quality. Here, the plant gene-related nutrient uptake, biotic and abiotic stress resistance, which may influence the composition and function of microbial communities, are discussed in this review. In turn, the influence of microbes on the expression of functional plant genes, and thereby plant growth and immunity, is also reviewed. Moreover, we have specifically paid attention to techniques and methods used to link plant functional genes and rhizomicrobiome. Finally, we propose to further explore the molecular mechanisms and signalling pathways of microbe-host gene interactions, which could potentially be used for managing plant health in agricultural systems.

Dynamic Changes of Bacterial Communities and Microbial Association Networks in Ready-to-Eat Chicken Meat during Storage

Ready-to-eat (RTE) chicken is a popular food in China, but its lack of food safety due to bacterial contamination remains a concern, and the dynamic changes of microbial association networks during storage are not fully understood. This study investigated the impact of storage time and temperature on bacterial compositions and microbial association networks in RTE chicken using 16S rDNA high-throughput sequencing. The results show that the predominant phyla present in all samples were Proteobacteria and Firmicutes, and the most abundant genera were Weissella, Pseudomonas and Proteus. Increased storage time and temperature decreased the richness and diversity of the microorganisms of the bacterial communities. Higher storage temperatures impacted the bacterial community composition more significantly. Microbial interaction analyses showed 22 positive and 6 negative interactions at 4 °C, 30 positive and 12 negative interactions at 8 °C and 44 positive and 45 negative interactions at 22 °C, indicating an increase in the complexity of interaction networks with an increase in the storage temperature. Enterobacter dominated the interactions during storage at 4 and 22 °C, and Pseudomonas did so at 22 °C. Moreover, interactions between pathogenic and/or spoilage bacteria, such as those between Pseudomonas fragi and Weissella viridescens, Enterobacter unclassified and Proteus unclassified, or those between Enterobacteriaceae unclassified and W.viridescens, were observed. This study provides insight into the process involved in RTE meat spoilage and can aid in improving the quality and safety of RTE meat products to reduce outbreaks of foodborne illness.

Spotlight on the Gut Microbiome in Menopause: Current Insights

The gut microbiome is an important contributor to human health, shaped by many endogenous and exogenous factors. The gut microbiome displays sexual dimorphism, suggesting influence of sex hormones, and also has been shown to change with aging. Yet, little is known regarding the influence of menopause - a pivotal event of reproductive aging in women - on the gut microbiome. Here, we summarize what is known regarding the interrelationships of female sex hormones and the gut microbiome, and review the available literature on menopause, female sex hormones, and the gut microbiome in humans. Taken together, research suggests that menopause is associated with lower gut microbiome diversity and a shift toward greater similarity to the male gut microbiome, however more research is needed in large study populations to identify replicable patterns in taxa impacted by menopause. Many gaps in knowledge remain, including the role the gut microbiome may play in menopause-related disease risks, and whether menopausal hormone therapy modifies menopause-related change in the gut microbiome. Given the modifiable nature of the gut microbiome, better understanding of its role in menopause-related health will be critical to identify novel opportunities for improvement of peri- and post-menopausal health and well-being.

Diversity of Fusarium community assembly shapes mycotoxin accumulation of diseased wheat heads

Fusarium head blight (FHB) is a major disease worldwide on cultivated cereals, caused by several Fusarium species. FHB can cause not only yield reduction but also accumulation of mycotoxins in the grain contaminating the food supply. Much of the earlier research has focused on Fusarium pathogenesis, conditions required for disease development and toxin accumulation, and FHB management. However, the Fusarium community composition within the micro-habitat of a single diseased wheat head in the field has had limited investigation. Similarly, the relationship between the Fusarium community structure and mycotoxin accumulation within diseased heads remains unclear. In the present study, we investigated the Fusarium community in diseased heads sampled from different geographical sites in China. Several sites in Shandong province formed a transitional region which contained highly variable profiles of Fusarium OTUs, where a single diseased head could contain more than 10 Fusarium OTUs. Mycotoxin accumulation was independent of geographical properties, however, deoxynivalenol, 15-acetyldeoxynivalenol and zearalenone concentrations showed a significant negative correlation with Fusarium diversity on diseased heads while a significant positive correlation between nivalenol concentration and Fusarium diversity was observed. Taken together, the Fusarium OTU diversity within diseased heads in the field significantly influences mycotoxin accumulation, providing an important point to consider in FHB disease management and mycotoxin research.

Ensuring future food security and resource sustainability: insights into the rhizosphere

Feeding the world’s growing population requires continuously increasing crop yields with less fertilizers and agrochemicals on limited land. Focusing on plant belowground traits, especially root-soil-microbe interactions, holds a great promise for overcoming this challenge. The belowground root-soil-microbe interactions are complex and involve a range of physical, chemical, and biological processes that influence nutrient-use efficiency, plant growth and health. Understanding, predicting, and manipulating these rhizosphere processes will enable us to harness the relevant interactions to improve plant productivity and nutrient-use efficiency. Here, we review the recent progress and challenges in root-soil-microbe interactions. We also highlight how root-soil-microbe interactions could be manipulated to ensure food security and resource sustainability in a changing global climate, with an emphasis on reducing our dependence on fertilizers and agrochemicals.

Microbial iron and carbon metabolism as revealed by taxonomy-specific functional diversity in the Southern Ocean

Marine microbes are major drivers of all elemental cycles. The processing of organic carbon by heterotrophic prokaryotes is tightly coupled to the availability of the trace element iron in large regions of the Southern Ocean. However, the functional diversity in iron and carbon metabolism within diverse communities remains a major unresolved issue. Using novel Southern Ocean meta-omics resources including 133 metagenome-assembled genomes (MAGs), we show a mosaic of taxonomy-specific ecological strategies in naturally iron-fertilized and high nutrient low chlorophyll (HNLC) waters. Taxonomic profiling revealed apparent community shifts across contrasting nutrient regimes. Community-level and genome-resolved metatranscriptomics evidenced a moderate association between taxonomic affiliations and iron and carbon-related functional roles. Diverse ecological strategies emerged when considering the central metabolic pathways of individual MAGs. Closely related lineages appear to adapt to distinct ecological niches, based on their distribution and gene regulation patterns. Our in-depth observations emphasize the complex interplay between the genetic repertoire of individual taxa and their environment and how this shapes prokaryotic responses to iron and organic carbon availability in the Southern Ocean.

Recent progress in the application of omics technologies in the study of bio-mining microorganisms from extreme environments

Bio-mining microorganisms are a key factor affecting the metal recovery rate of bio-leaching, which inevitably produces an extremely acidic environment. As a powerful tool for exploring the adaptive mechanisms of microorganisms in extreme environments, omics technologies can greatly aid our understanding of bio-mining microorganisms and their communities on the gene, mRNA, and protein levels. These omics technologies have their own advantages in exploring microbial diversity, adaptive evolution, changes in metabolic characteristics, and resistance mechanisms of single strains or their communities to extreme environments. These technologies can also be used to discover potential new genes, enzymes, metabolites, metabolic pathways, and species. In addition, integrated multi-omics analysis can link information at different biomolecular levels, thereby obtaining more accurate and complete global adaptation mechanisms of bio-mining microorganisms. This review introduces the current status and future trends in the application of omics technologies in the study of bio-mining microorganisms and their communities in extreme environments.

A global overview of the trophic structure within microbiomes across ecosystems

The colossal project of mapping the microbiome on Earth is rapidly advancing, with a focus on individual microbial groups. However, a global assessment of the associations between predatory protists and their bacterial prey is still missing at a cross-ecosystem level. This knowledge is critical to better understand the importance of top-down links in structuring microbiomes. Here, we examined 38 sequence-based datasets of paired bacterial and protistan taxa, covering 3,178 samples from diverse habitats including freshwater, marine and soils. We show that community profiles of protists and bacteria strongly correlated across and within habitats, with trophic microbiome structures fundamentally differing across habitats. Soils hosted the most heterogenous and diverse microbiomes. Protist communities were dominated by predators in soils and phototrophs in aquatic environments. This led to changes in the ratio of total protists to bacteria richness, which was highest in marine, while that of predatory protists to bacteria was highest in soils. Taxon richness and relative abundance of predatory protists positively correlated with bacterial richness in marine habitats. These links differed between soils, predatory protist richness and the relative abundance of predatory protists positively correlated with bacterial richness in forest and grassland soils, but not in agricultural soils. Our results suggested that anthropogenic pressure affects higher trophic levels more than lower ones leading to a decoupled trophic structure in microbiomes. Together, our cumulative overview of microbiome patterns of bacteria and protists at the global scale revealed major patterns and differences of the trophic structure of microbiomes across Earth's habitats, and show that anthropogenic factors might have negative effects on the trophic structure within microbiomes. Furthermore, the increased impact of anthropogenic factors on especially higher trophic levels suggests that often-observed reduced ecosystem functions in anthropogenic systems might be partly attributed to a reduction of trophic complexity.

A multiplex bacterial assay using an element-labeled strategy for 16S rRNA detection

A multiplex bacterial assay method that combines S1 nuclease pretreatment and ICP-MS-based elemental labels is presented in this work. Six intestinal related bacteria were identified at the species level and quantified simultaneously without isolation culturing. This method could be extended to assay a mixed bacterial community for point-of-care diagnosis.

Revealing taxon-specific heavy metal-resistance mechanisms in denitrifying phosphorus removal sludge using genome-centric metaproteomics

BACKGROUND

Denitrifying phosphorus removal sludge (DPRS) is widely adopted for nitrogen and phosphorus removal in wastewater treatment but faces threats from heavy metals. However, a lack of understanding of the taxon-specific heavy metal-resistance mechanisms hinders the targeted optimization of DPRS's robustness in nutrient removal.

RESULTS

We obtained 403 high- or medium-quality metagenome-assembled genomes from DPRS treated by elevating cadmium, nickel, and chromium pressure. Then, the proteomic responses of individual taxa under heavy metal pressures were characterized, with an emphasis on functions involving heavy metal resistance and maintenance of nutrient metabolism. When oxygen availability was constrained by high-concentration heavy metals, comammox Nitrospira overproduced highly oxygen-affinitive hemoglobin and electron-transporting cytochrome c-like proteins, underpinning its ability to enhance oxygen acquisition and utilization. In contrast, Nitrosomonas overexpressed ammonia monooxygenase and nitrite reductase to facilitate the partial nitrification and denitrification process for maintaining nitrogen removal. Comparisons between phosphorus-accumulating organisms (PAOs) demonstrated different heavy metal-resistance mechanisms adopted by Dechloromonas and Candidatus Accumulibacter, despite their high genomic similarities. In particular, Dechloromonas outcompeted the canonical PAO Candidatus Accumulibacter in synthesizing polyphosphate, a potential public good for heavy metal detoxification. The superiority of Dechloromonas in energy utilization, radical elimination, and damaged cell component repair also contributed to its dominance under heavy metal pressures. Moreover, the enrichment analysis revealed that functions involved in extracellular polymeric substance formation, siderophore activity, and heavy metal efflux were significantly overexpressed due to the related activities of specific taxa.

CONCLUSIONS

Our study demonstrates that heavy metal-resistance mechanisms within a multipartite community are highly heterogeneous between different taxa. These findings provide a fundamental understanding of how the heterogeneity of individual microorganisms contributes to the metabolic versatility and robustness of microbiomes inhabiting dynamic environments, which is vital for manipulating the adaptation of microbial assemblages under adverse environmental stimuli. Video abstract.

Role of the gut microbiome in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia, affecting millions of individuals each year and this number is expected to significantly increase. The complicated microorganisms residing in human gut are closely associated with our health. Emerging evidence has suggested possible involvement of human gut microbiome in AD. Symbiotic gut microbiomes are known to maintain brain health by modulating host's barriers integrity, metabolic system, immune system, nervous system and endocrine system. However, in the event of gut dysbiosis and barriers disruption, gut pathobionts disrupt homeostasis of the metabolic system, immune system, nervous system, and endocrine system, resulting in deterioration of neurological functions and subsequently promoting development of AD. Multiple therapeutic approaches, such as fecal microbiome transplant, antibiotics, prebiotics, probiotics, symbiotic, and diet are discussed as potential treatment options for AD by manipulating the gut microbiome to reverse pathological alteration in the systems above.

MetaLab 2.0 Enables Accurate Post-Translational Modifications Profiling in Metaproteomics

Studying the structure and function of microbiomes is an emerging research field. Metaproteomic approaches focusing on the characterization of expressed proteins and post-translational modifications (PTMs) provide a deeper understanding of microbial communities. Previous research has highlighted the value of examining microbiome-wide protein expression in studying the roles of the microbiome in human diseases. Nevertheless, the regulation of protein functions in complex microbiomes remains underexplored. This is mainly due to the lack of efficient bioinformatics tools to identify and quantify PTMs in the microbiome. We have developed comprehensive software termed MetaLab for the data analysis of metaproteomic data sets. Here, we build an open search workflow within MetaLab for unbiased identification and quantification of unmodified peptides as well as peptides with various PTMs from microbiome samples. This bioinformatics platform provides information about proteins, PTMs, taxa, functions, and pathways of microbial communities. The performance of the workflow was evaluated using conventional proteomics, metaproteomics from mouse and human gut microbiomes, and modification-specific enriched data sets. Superior accuracy and sensitivity were obtained simultaneously by using our method compared with the traditional closed search strategy.

Sequencing barcode construction and identification methods based on block error-correction codes

Multiplexed sequencing relies on specific sample labels, the barcodes, to tag DNA fragments belonging to different samples and to separate the output of the sequencers. However, the barcodes are often corrupted by insertion, deletion and substitution errors introduced during sequencing, which may lead to sample misassignment. In this paper, we propose a barcode construction method, which combines a block error-correction code with a predetermined pseudorandom sequence to generate a base sequence for labeling different samples. Furthermore, to identify the corrupted barcodes for assigning reads to their respective samples, we present a soft decision identification method that consists of inner decoding and outer decoding. The inner decoder establishes the hidden Markov model (HMM) for base insertion/deletion estimation with the pseudorandom sequence, and adapts the forward-backward (FB) algorithm to output the soft information of each bit in the block code. The outer decoder performs soft decision decoding using the soft information to effectively correct multiple errors in the barcodes. Simulation results show that the proposed methods are highly robust to high error rates of insertions, deletions and substitutions in the barcodes. In addition, compared with the inner decoding algorithm of the barcodes based on watermarks, the proposed inner decoding algorithm can greatly reduce the decoding complexity.

AutoTuner: High Fidelity and Robust Parameter Selection for Metabolomics Data Processing

Untargeted metabolomics experiments provide a snapshot of cellular metabolism but remain challenging to interpret due to the computational complexity involved in data processing and analysis. Prior to any interpretation, raw data must be processed to remove noise and to align mass-spectral peaks across samples. This step requires selection of dataset-specific parameters, as erroneous parameters can result in noise inflation. While several algorithms exist to automate parameter selection, each depends on gradient descent optimization functions. In contrast, our new parameter optimization algorithm, AutoTuner, obtains parameter estimates from raw data in a single step as opposed to many iterations. Here, we tested the accuracy and the run-time of AutoTuner in comparison to isotopologue parameter optimization (IPO), the most commonly used parameter selection tool, and compared the resulting parameters’ influence on the properties of feature tables after processing. We performed a Monte Carlo experiment to test the robustness of AutoTuner parameter selection and found that AutoTuner generated similar parameter estimates from random subsets of samples. We conclude that AutoTuner is a desirable alternative to existing tools, because it is scalable, highly robust, and very fast (∼100–1000× speed improvement from other algorithms going from days to minutes). AutoTuner is freely available as an R package through BioConductor.

Identifying microbial species by single-molecule DNA optical mapping and resampling statistics

Single-molecule DNA mapping has the potential to serve as a powerful complement to high-throughput sequencing in metagenomic analysis. Offering longer read lengths and forgoing the need for complex library preparation and amplification, mapping stands to provide an unbiased view into the composition of complex viromes and/or microbiomes. To fully enable mapping-based metagenomics, sensitivity and specificity of DNA map analysis and identification need to be improved. Using detailed simulations and experimental data, we first demonstrate how fluorescence imaging of surface stretched, sequence specifically labeled DNA fragments can yield highly sensitive identification of targets. Second, a new analysis technique is introduced to increase specificity of the analysis, allowing even closely related species to be resolved. Third, we show how an increase in resolution improves sensitivity. Finally, we demonstrate that these methods are capable of identifying species with long genomes such as bacteria with high sensitivity.

Metagenomic Insights of the Root Colonizing Microbiome Associated with Symptomatic and Non-Symptomatic Bananas in Fusarium Wilt Infected Fields

Plants tissues are colonized by diverse communities of microorganisms called endophytes. They are key determinants of plant production and health, for example by facilitating nutrient exchanges or limiting disease development. Endophytic communities of banana plants have not been studied until very recently, and their potential role in disease development has not been explored so far. Roots from symptomatic and non-symptomatic banana plants were sampled from fields infected by Fusarium oxysporum f.sp. cubense race 1. The goal was to compare the endophytic microbiota between symptomatic and non-symptomatic plants through high throughput sequencing of 16s rDNA and shotgun metagenome sequencing. The results revealed that the endophytic root microbiome in bananas is dominated by Proteobacteria and Bacteroidetes followed to a lesser extent by Actinobacteria. The development of disease greatly impacted the endophytic microbial communities. For example, Flavobacteriales abundance was correlated with symptom development.

An Integrated Pipeline for Annotation and Visualization of Metagenomic Contigs

Here, we describe MetaErg, a standalone and fully automated metagenome and metaproteome annotation pipeline. Annotation of metagenomes is challenging. First, metagenomes contain sequence data of many organisms from all domains of life. Second, many of these are from understudied lineages, encoding genes with low similarity to experimentally validated reference genes. Third, assembly and binning are not perfect, sometimes resulting in artifactual hybrid contigs or genomes. To address these challenges, MetaErg provides graphical summaries of annotation outcomes, both for the complete metagenome and for individual metagenome-assembled genomes (MAGs). It performs a comprehensive annotation of each gene, including taxonomic classification, enabling functional inferences despite low similarity to reference genes, as well as detection of potential assembly or binning artifacts. When provided with metaproteome information, it visualizes gene and pathway activity using sequencing coverage and proteomic spectral counts, respectively. For visualization, MetaErg provides an HTML interface, bringing all annotation results together, and producing sortable and searchable tables, collapsible trees, and other graphic representations enabling intuitive navigation of complex data. MetaErg, implemented in Perl, HTML, and JavaScript, is a fully open source application, distributed under Academic Free License at https://github.com/xiaoli-dong/metaerg. MetaErg is also available as a docker image at https://hub.docker.com/r/xiaolidong/docker-metaerg.

Modelling approaches for studying the microbiome

Advances in metagenome sequencing of the human microbiome have provided a plethora of new insights and revealed a close association of this complex ecosystem with a range of human diseases. However, there is little knowledge about how the different members of the microbial community interact with each other and with the host, and we lack basic mechanistic understanding of these interactions related to health and disease. Mathematical modelling has been demonstrated to be highly advantageous for gaining insights into the dynamics and interactions of complex systems and in recent years, several modelling approaches have been proposed to enhance our understanding of the microbiome. Here, we review the latest developments and current approaches, and highlight how different modelling strategies have been applied to unravel the highly dynamic nature of the human microbiome. Furthermore, we discuss present limitations of different modelling strategies and provide a perspective of how modelling can advance understanding and offer new treatment routes to impact human health.

Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action

BACKGROUND

Post-translational modification (PTM) crosstalk is a young research field. However, there is now evidence of the extraordinary characterization of the different proteoforms and their interactions in a biological environment that PTM crosstalk studies can describe. Besides gene expression and phosphorylation profiling of acute myeloid leukemia (AML) samples, the functional combination of several PTMs that might contribute to a better understanding of the complexity of the AML proteome remains to be discovered.

OBJECTIVE

By reviewing current workflows for the simultaneous enrichment of several PTMs and bioinformatics tools to analyze mass spectrometry (MS)-based data, our major objective is to introduce the PTM crosstalk field to the AML research community.

RESULTS

After an introduction to PTMs and PTM crosstalk, this review introduces several protocols for the simultaneous enrichment of PTMs. Two of them allow a simultaneous enrichment of at least three PTMs when using 0.5-2 mg of cell lysate. We have reviewed many of the bioinformatics tools used for PTM crosstalk discovery as its complex data analysis, mainly generated from MS, becomes challenging for most AML researchers. We have presented several non-AML PTM crosstalk studies throughout the review in order to show how important the characterization of PTM crosstalk becomes for the selection of disease biomarkers and therapeutic targets.

CONCLUSION

Herein, we have reviewed the advances and pitfalls of the emerging PTM crosstalk field and its potential contribution to unravel the heterogeneity of AML. The complexity of sample preparation and bioinformatics workflows demands a good interaction between experts of several areas.

Methods for extracting 'omes from microbialites

Microbialites are organo-sedimentary structures formed by complex microbial communities that interact with abiotic factors to form carbonate rich fabrics. Extraction of DNA or total RNA from microbialites can be difficult because of the high carbonate mineral concentration and exopolymeric substances. The methods employed until now include substances such as cetyltrimethylammonium bromide, sodium dodecyl sulfate, xanthogenate, lysozyme and proteinase K, as well as mechanical disruption. Additionally, several commercial kits have been used to improve DNA and total RNA extraction. This minireview presents different methods applied for DNA and RNA extraction from microbialites and discusses their advantages and disadvantages. Moreover, extraction of all 'omes (DNA, RNA, Protein, Lipids, polar metabolites) using multiomic extraction methods (MPlex), as well as the state of art for extraction of viruses from microbialites, are also discussed.

RefSoil+: a Reference Database for Genes and Traits of Soil Plasmids

Soil-associated plasmids have the potential to transfer antibiotic resistance genes from environmental to clinical microbial strains, which is a public health concern. A specific resource is needed to aggregate the knowledge of soil plasmid characteristics so that the content, host associations, and dynamics of antibiotic resistance genes can be assessed and then tracked between the environment and the clinic. Here, we present RefSoil+, a database of soil-associated plasmids. RefSoil+ presents a contemporary snapshot of antibiotic resistance genes in soil that can serve as a reference as novel plasmids and transferred antibiotic resistances are discovered. Our study broadens our understanding of plasmids in soil and provides a community resource of important plasmid-associated genes, including antibiotic resistance genes.

Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve the understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were larger than other described plasmids, which is a trait associated with plasmid mobility. There was a weak relationship between chromosome size and plasmid size and no relationship between chromosome size and plasmid number, suggesting that these genomic traits are independent in soil. We used RefSoil+ to inform the distributions of antibiotic resistance genes among soil microorganisms compared to those among nonsoil microorganisms. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a reference for the diversity, composition, and host associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves the understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.

IMPORTANCE Soil-associated plasmids have the potential to transfer antibiotic resistance genes from environmental to clinical microbial strains, which is a public health concern. A specific resource is needed to aggregate the knowledge of soil plasmid characteristics so that the content, host associations, and dynamics of antibiotic resistance genes can be assessed and then tracked between the environment and the clinic. Here, we present RefSoil+, a database of soil-associated plasmids. RefSoil+ presents a contemporary snapshot of antibiotic resistance genes in soil that can serve as a reference as novel plasmids and transferred antibiotic resistances are discovered. Our study broadens our understanding of plasmids in soil and provides a community resource of important plasmid-associated genes, including antibiotic resistance genes.

Targeted Metagenomics of Microbial Diversity in Free-Living Amoebae and Water Samples

The presence of Legionella spp. in natural and man-made water systems is a great public health concern and heavily depends on the presence of free-living amoebae. Taking advantage of the development and affordability of next-generation sequencing technology, we present here a method to characterize the whole bacterial community directly from water samples, as well as from isolated free-living amoebae.

The Complete Genome and Physiological Analysis of the Microbialite-Dwelling Agrococcus pavilionensis sp. nov; Reveals Genetic Promiscuity and Predicted Adaptations to Environmental Stress

Members of the bacterial genus Agrococcus are globally distributed and found across environments so highly diverse that they include forests, deserts, and coal mines, as well as in potatoes and cheese. Despite how widely Agrococcus occurs, the extent of its physiology, genomes, and potential roles in the environment are poorly understood. Here we use whole-genome analysis, chemotaxonomic markers, morphology, and 16S rRNA gene phylogeny to describe a new isolate of the genus Agrococcus from freshwater microbialites in Pavilion Lake, British Columbia, Canada. We characterize this isolate as a new species Agrococcus pavilionensis strain RW1 and provide the first complete genome from a member of the genus Agrococcus. The A. pavilionensis genome consists of one chromosome (2,627,177 bp) as well as two plasmids (HC-CG1 1,427 bp, and LC-RRW783 31,795 bp). The genome reveals considerable genetic promiscuity via mobile elements, including a prophage and plasmids involved in integration, transposition, and heavy-metal stress. A. pavilionensis strain RW1 differs from other members of the Agrococcus genus by having a novel phospholipid fatty acid iso-C15:1Δ⁴, β-galactosidase activity and amygdalin utilization. Carotenoid biosynthesis is predicted by genomic metabolic reconstruction, which explains the characteristic yellow pigmentation of A. pavilionensis. Metabolic reconstructions of strain RW1 genome predicts a pathway for releasing ammonia via ammonification amino acids, which could increase the saturation index leading to carbonate precipitation. Our genomic analyses suggest signatures of environmental adaption to the relatively cold and oligotrophic conditions of Pavilion Lake microbialites. A. pavilionensis strain RW1 in modern microbialites has an ecological significance in Pavilion Lake microbialites, which include potential roles in heavy-metal cycling and carbonate precipitation (e.g., ammonification of amino acids and filamentation which many trap carbonate minerals).

Proteomics and the microbiome: pitfalls and potential

Introduction: Human symbiotic microbiota are now known to play important roles in human health and disease. Significant progress in our understanding of the human microbiome has been driven by recent technological advances in the fields of genomics, transcriptomics, and proteomics. As a complementary method to metagenomics, proteomics is enabling detailed protein profiling of the microbiome to decipher its structure and function and to analyze its relationship with the human body. Fecal proteomics is being increasingly applied to discover and validate potential health and disease biomarkers, and Therapeutic Goods Administration (TGA)-approved instrumentation and a range of clinical assays are being developed that will collectively play key roles in advancing personalized medicine. Areas covered: This review will introduce the complexity of the microbiome and its role in health and disease (in particular the gastrointestinal tract or gut microbiome), discuss current genomic and proteomic methods for studying this system, including the discovery of potential biomarkers, and outline the development of clinically accepted protocols leading to personalized medicine. Expert commentary: Recognition of the important role the microbiome plays in both health and disease is driving current research in this key area. A proteogenomics approach will be essential to unravel the biologies underlying this complex network.

Assessment of the physicochemical properties and bacterial composition of Lactobacillus plantarum and Enterococcus faecium-fermented Astragalus membranaceus using single molecule, real-time sequencing technology

We investigated if fermentation with probiotic cultures could improve the production of health-promoting biological compounds in Astragalus membranaceus. We tested the probiotics Enterococcus faecium, Lactobacillus plantarum and Enterococcus faecium + Lactobacillus plantarum and applied PacBio single molecule, real-time sequencing technology (SMRT) to evaluate the quality of Astragalus fermentation. We found that the production rates of acetic acid, methylacetic acid, aethyl acetic acid and lactic acid using E. faecium + L. plantarum were 1866.24 mg/kg on day 15, 203.80 mg/kg on day 30, 996.04 mg/kg on day 15, and 3081.99 mg/kg on day 20, respectively. Other production rates were: polysaccharides, 9.43%, 8.51%, and 7.59% on day 10; saponins, 19.6912 mg/g, 21.6630 mg/g and 20.2084 mg/g on day 15; and flavonoids, 1.9032 mg/g, 2.0835 mg/g, and 1.7086 mg/g on day 20 using E. faecium, L. plantarum and E. faecium + L. plantarum, respectively. SMRT was used to analyze microbial composition, and we found that E. faecium and L. plantarum were the most prevalent species after fermentation for 3 days. E. faecium + L. plantarum gave more positive effects than single strains in the Astragalus solid state fermentation process. Our data demonstrated that the SMRT sequencing platform is applicable to quality assessment of Astragalus fermentation.

Metagenomic Analysis of Microbial Community Compositions and Cold-Responsive Stress Genes in Selected Antarctic Lacustrine and Soil Ecosystems

This study describes microbial community compositions, and various cold-responsive stress genes, encompassing cold-induced proteins (CIPs) and cold-associated general stress-responsive proteins (CASPs) in selected Antarctic lake water, sediment, and soil metagenomes. Overall, Proteobacteria and Bacteroidetes were the major taxa in all metagenomes. Prochlorococcus and Thiomicrospira were highly abundant in waters, while Myxococcus, Anaeromyxobacter, Haliangium, and Gloeobacter were dominant in the soil and lake sediment metagenomes. Among CIPs, genes necessary for DNA replication, translation initiation, and transcription termination were highly abundant in all metagenomes. However, genes for fatty acid desaturase (FAD) and trehalose synthase (TS) were common in the soil and lake sediment metagenomes. Interestingly, the Lake Untersee water and sediment metagenome samples contained histone-like nucleoid structuring protein (H-NS) and all genes for CIPs. As for the CASPs, high abundances of a wide range of genes for cryo- and osmo-protectants (glutamate, glycine, choline, and betaine) were identified in all metagenomes. However, genes for exopolysaccharide biosynthesis were dominant in Lake Untersee water, sediment, and other soil metagenomes. The results from this study indicate that although diverse microbial communities are present in various metagenomes, they share common cold-responsive stress genes necessary for their survival and sustenance in the extreme Antarctic conditions.

The soil microbiome-from metagenomics to metaphenomics

Soil microorganisms carry out important processes, including support of plant growth and cycling of carbon and other nutrients. However, the majority of soil microbes have not yet been isolated and their functions are largely unknown. Although metagenomic sequencing reveals microbial identities and functional gene information, it includes DNA from microbes with vastly varying physiological states. Therefore, metagenomics is only predictive of community functional potential. We posit that the next frontier lies in understanding the metaphenome, the product of the combined genetic potential of the microbiome and available resources. Here we describe examples of opportunities towards gaining understanding of the soil metaphenome.

Strategies to increase the efficacy of using gut microbiota for the modulation of obesity

Obesity is one of the most serious global public health challenges of the 21st century. The adjustment of gut microbiota is often recommended as an efficient strategy to treat obesity. This modulation of gut microbiota can be performed by many methods, including dietary intervention, antibiotic application, the use of prebiotics and probiotics, bariatric surgery and faecal microbiota transplantation. In most cases, positive effects have been observed in response to treatment, but invalid and even contrary effects have also been observed in some cases due to factors that are unrelated to intervention methods, such as genetic factors, patient age or gender, environmental microbiota, climate, geography and lifestyle. These factors can cause variation of gut microbial populations and thus should also be taken into consideration when selecting modulation strategies.

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics

BACKGROUND

During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community.

RESULTS

We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples.

CONCLUSION

MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/ .

Rumen Microbiome, Probiotics, and Fermentation Additives

Fermentation of a variety of feedstuffs by the ruminal microbiome is the distinctive feature of the ruminant digestive tract. The host derives energy and nutrients from microbiome activity; these organisms are essential to survival. Advances in DNA sequencing and bioinformatics have redefined the rumen microbial community. Current research seeks to connect our understanding of the rumen microbiome with nutritional strategies in ruminant livestock systems and their associated digestive disorders. These efforts align with a growing number of products designed to improve ruminal fermentation to benefit the overall efficiency of ruminant livestock production and health.