A multi-omic future for microbiome studies

A panoramic view of the virosphere in three wastewater treatment plants by integrating viral-like particle-concentrated and traditional non-concentrated metagenomic approaches

Wastewater biotreatment systems harbor a rich diversity of microorganisms, and the effectiveness of biotreatment systems largely depends on the activity of these microorganisms. Specifically, viruses play a crucial role in altering microbial behavior and metabolic processes throughout their infection phases, an aspect that has recently attracted considerable interest. Two metagenomic approaches, viral-like particle-concentrated (VPC, representing free viral-like particles) and non-concentrated (NC, representing the cellular fraction), were employed to assess their efficacy in revealing virome characteristics, including taxonomy, diversity, host interactions, lifestyle, dynamics, and functional genes across processing units of three wastewater treatment plants (WWTPs). Our findings indicate that each approach offers unique insights into the viral community and functional composition. Their combined use proved effective in elucidating WWTP viromes. We identified nearly 50,000 viral contigs, with Cressdnaviricota and Uroviricota being the predominant phyla in the VPC and NC fractions, respectively. Notably, two pathogenic viral families, Asfarviridae and Adenoviridae, were commonly found in these WWTPs. We also observed significant differences in the viromes of WWTPs processing different types of wastewater. Additionally, various phage-derived auxiliary metabolic genes (AMGs) were active at the RNA level, contributing to the metabolism of the microbial community, particularly in carbon, sulfur, and phosphorus cycling. Moreover, we identified 29 virus-carried antibiotic resistance genes (ARGs) with potential for host transfer, highlighting the role of viruses in spreading ARGs in the environment. Overall, this study provides a detailed and integrated view of the virosphere in three WWTPs through the application of VPC and NC metagenomic approaches. Our findings enhance the understanding of viral communities, offering valuable insights for optimizing the operation and regulation of wastewater treatment systems.

Comparative analysis of prokaryotic microbiomes in high-altitude active layer soils: insights from Ladakh and global analogues using In-Silico approaches

The active layer is the portion of soil overlaying the permafrost that freezes and thaws seasonally. It is a harsh habitat in which a varied and vigorous microbial population thrives. The high-altitude active layer soil in northern India is a unique and important cryo-ecosystem. However, its microbiology remains largely unexplored. It represents a unique reservoir for microbial communities with adaptability to harsh environmental conditions. In the Changthang region of Ladakh, the Tsokar area is a high-altitude permafrost-affected area situated in the southern part of Ladakh, at a height of 4530 m above sea level. Results of the comparison study with the QTP, Himalayan, Alaskan, Russian, Canadian and Polar active layers showed that the alpha diversity was significantly higher in the Ladakh and QTP active layers as the environmental condition of both the sites were similar. Moreover, the sampling site in the Ladakh region was in a thawing condition at the time of sampling which possibly provided nutrients and access to alternative nitrogen and carbon sources to the microorganisms thriving in it. Analysis of the samples suggested that the geochemical parameters and environmental conditions shape the microbial alpha diversity and community composition. Further analysis revealed that the cold-adapted methanogens were present in the Ladakh, Himalayan, Polar and Alaskan samples and absent in QTP, Russian and Canadian active layer samples. These methanogens could produce methane at slow rates in the active layer soils that could increase the atmospheric temperature owing to climate change.

Microbial evolution-An under-appreciated driver of soil carbon cycling

Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.

The implication of microbiome in lungs cancer: mechanisms and strategies of cancer growth, diagnosis and therapy

Available evidence illustrates that microbiome is a promising target for the study of growth, diagnosis and therapy of various types of cancer. Lung cancer is a leading cause of cancer death worldwide. The relationship of microbiota and their products with diverse pathologic conditions has been getting large attention. The novel research suggests that the microbiome plays an important role in the growth and progression of lung cancer. The lung microbiome plays a crucial role in maintaining mucosal immunity and synchronizing the stability between tolerance and inflammation. Alteration in microbiome is identified as a critical player in the progression of lung cancer and negatively impacts the patient. Studies suggest that healthy microbiome is essential for effective therapy. Various clinical trials and research are focusing on enhancing the treatment efficacy by altering the microbiome. The regulation of microbiota will provide innovative and promising treatment strategies for the maintenance of host homeostasis and the prevention of lung cancer in lung cancer patients. In the current review article, we presented the latest progress about the involvement of microbiome in the growth and diagnosis of lung cancer. Furthermore, we also assessed the therapeutic status of the microbiome for the management and treatment of lung cancer.

Designing host-associated microbiomes using the consumer/resource model

A key step towards rational microbiome engineering is the in silico sampling of realistic microbial communities that correspond to desired host phenotypes, and vice versa. This remains challenging due to a lack of generative models that simultaneously model compositions of host-associated microbiomes and host phenotypes. To that end, we present a machine learning model based on the consumer/resource (C/R) framework. In the model, variation in microbial ecosystem composition arises due to differences in the availability of effective resources (latent variables) while species' resource preferences remain conserved. Variation in the same latent variables is used to model phenotypic variation across hosts. In silico microbiomes generated by our model accurately reproduce universal and dataset-specific statistics of bacterial communities. The model allows us to address two salient questions in microbiome design: (1) which host phenotypes maximally constrain the composition of the host-associated microbiome? and (2) what are plausible microbiome compositions corresponding to user-specified host phenotypes? Thus, our model aids the design and analysis of microbial communities associated with host phenotypes of interest.

Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts

The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.

The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises

The study of the respiratory microbiome has entered a multi-omic era. Through integrating different omic data types such as metagenome, metatranscriptome, metaproteome, metabolome, culturome and radiome surveyed from respiratory specimens, holistic insights can be gained on the lung microbiome and its interaction with host immunity and inflammation in respiratory diseases. The power of multi-omics have moved the field forward from associative assessment of microbiome alterations to causative understanding of the lung microbiome in the pathogenesis of chronic, acute and other types of respiratory diseases. However, the application of multi-omics in respiratory microbiome remains with unique challenges from sample processing, data integration, and downstream validation. In this review, we first introduce the respiratory sample types and omic data types applicable to studying the respiratory microbiome. We next describe approaches for multi-omic integration, focusing on dimensionality reduction, multi-omic association and prediction. We then summarize progresses in the application of multi-omics to studying the microbiome in respiratory diseases. We finally discuss current challenges and share our thoughts on future promises in the field.

Consistency across multi-omics layers in a drug-perturbed gut microbial community

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

The Cytotoxic Properties of Extreme Fungi's Bioactive Components-An Updated Metabolic and Omics Overview

Fungi are the most diverse living organisms on planet Earth, where their ubiquitous presence in various ecosystems offers vast potential for the research and discovery of new, naturally occurring medicinal products. Concerning human health, cancer remains one of the leading causes of mortality. While extensive research is being conducted on treatments and their efficacy in various stages of cancer, finding cytotoxic drugs that target tumor cells with no/less toxicity toward normal tissue is a significant challenge. In addition, traditional cancer treatments continue to suffer from chemical resistance. Fortunately, the cytotoxic properties of several natural products derived from various microorganisms, including fungi, are now well-established. The current review aims to extract and consolidate the findings of various scientific studies that identified fungi-derived bioactive metabolites with antitumor (anticancer) properties. The antitumor secondary metabolites identified from extremophilic and extremotolerant fungi are grouped according to their biological activity and type. It became evident that the significance of these compounds, with their medicinal properties and their potential application in cancer treatment, is tremendous. Furthermore, the utilization of omics tools, analysis, and genome mining technology to identify the novel metabolites for targeted treatments is discussed. Through this review, we tried to accentuate the invaluable importance of fungi grown in extreme environments and the necessity of innovative research in discovering naturally occurring bioactive compounds for the development of novel cancer treatments.

Analysis of endoglucanases production using metatranscriptomics and proteomics approach

The cellulases are among the most used enzyme in industries for various purposes. They add up to the green economy perspective and cost-effective production of enterprises. Biorefineries, paper industries, and textile industries are foremost in their usage. The production of endoglucanases from microorganisms is a valuable resource and can be exploited with the help of biotechnology. The present review provides some insight into the uses of endoglucanases in different industries and the potent fungal source of these enzymes. The advances in the enzyme technology has helped towards understanding some pathways to increase the production of industrial enzymes from microorganisms. The proteomics analysis and systems biology tools also help to identify these pathways for the enhanced production of such enzymes. This review deciphers the use of proteomics tools to analyze the potent microorganisms and identify suitable culture conditions to increase the output of endoglucanases. The review also includes the role of quantitative proteomics which is a powerful technique to get results faster and more timely. The role of metatranscriptomic approaches are also described which are helpful in the enzyme engineering for their efficient use under industrial conditions. Conclusively, this review helps to understand the challenges faced in the industrial use of endoglucanases and their further improvement.

Role of Microbiota-Modified Bile Acids in the Regulation of Intracellular Organelles and Neurodegenerative Diseases

Bile acids (BAs) are amphiphilic steroidal molecules generated from cholesterol in the liver and facilitate the digestion and absorption of fat-soluble substances in the gut. Some BAs in the intestine are modified by the gut microbiota. Because BAs are modified in a variety of ways by different types of bacteria present in the gut microbiota, changes in the gut microbiota can affect the metabolism of BAs in the host. Although most BAs absorbed from the gut are transferred to the liver, some are transferred to the systemic circulation. Furthermore, BAs have also been detected in the brain and are thought to migrate into the brain through the systemic circulation. Although BAs are known to affect a variety of physiological functions by acting as ligands for various nuclear and cell-surface receptors, BAs have also been found to act on mitochondria and autophagy in the cell. This review focuses on the BAs modified by the gut microbiota and their roles in intracellular organelles and neurodegenerative diseases.

Toward Understanding Microbial Ecology to Restore a Degraded Ecosystem

The microbial community plays an important role in maintaining human health, addressing climate change, maintaining environmental quality, etc. High-throughput sequencing leads to the discovery and identification of more microbial community composition and function in diverse ecosystems. Microbiome therapeutics such as fecal microbiota transplantation for human health and bioaugmentation for activated sludge restoration have drawn great attention. However, microbiome therapeutics cannot secure the success of microbiome transplantation. This paper begins with a view on fecal microbiota transplantation and bioaugmentation and is followed by a parallel analysis of these two microbial therapeutic strategies. Accordingly, the microbial ecology mechanisms behind them were discussed. Finally, future research on microbiota transplantation was proposed. Successful application of both microbial therapeutics for human disease and bioremediation for contaminated environments relies on a better understanding of the microbial "entangled bank" and microbial ecology of these environments.

Deciphering the rhizosphere bacteriome associated with biological control of tobacco black shank disease

Introduction

The black shank disease seriously affects the health of tobacco plants. Conventional control methods have limitations in terms of effectiveness or economic aspects and cause public health concerns. Thus, biological control methods have come into the field, and microorganisms play a key role in suppressing tobacco black shank disease.

Methods

In this study, we examined the impact of soil microbial community on black shank disease basing on the structural difference of bacterial communities in rhizosphere soils. We used Illumina sequencing to compare the bacterial community diversity and structure in different rhizosphere soil samples in terms of healthy tobacco, tobacco showing typical black shank symptoms, and tobacco treated with the biocontrol agent, Bacillus velezensis S719.

Results

We found that Alphaproteobacteria in the biocontrol group, accounted for 27.2% of the ASVs, was the most abundant bacterial class among three groups. Heatmap and LEfSe analyses were done to determine the distinct bacterial genera in the three sample groups. For the healthy group, Pseudomonas was the most significant genus; for the diseased group, Stenotrophomonas exhibited the strongest enrichment trend, and Sphingomonas showed the highest linear discriminant analysis score, and was even more abundant than Bacillus; for the biocontrol group, Bacillus, and Gemmatimonas were the largely distributed genus. In addition, co-occurrence network analysis confirmed the abundance of taxa, and detected a recovery trend in the network topological parameters of the biocontrol group. Further functional prediction also provided a possible explanation for the bacterial community changes with related KEGG annotation terms.

Discussion

These findings will improve our knowledge of plant-microbe interactions and the application of biocontrol agents to improve plant fitness, and may contribute to the selection of biocontrol strains.

Integrating Rehabilomics into the Multi-Omics Approach in the Management of Multiple Sclerosis: The Way for Precision Medicine?

Over recent years, significant improvements have been made in the understanding of (epi)genetics and neuropathophysiological mechanisms driving the different forms of multiple sclerosis (MS). For example, the role and importance of the bidirectional communications between the brain and the gut-also referred to as the gut-brain axis-in the pathogenesis of MS is receiving increasing interest in recent years and is probably one of the most promising areas of research for the management of people with MS. However, despite these important advances, it must be noted that these data are not-yet-used in rehabilitation. Neurorehabilitation is a cornerstone of MS patient management, and there are many techniques available to clinicians and patients, including technology-supported rehabilitation. In this paper, we will discuss how new findings on the gut microbiome could help us to better understand how rehabilitation can improve motor and cognitive functions. We will also see how the data gathered during the rehabilitation can help to get a better diagnosis of the patients. Finally, we will discuss how these new techniques can better guide rehabilitation to lead to precision rehabilitation and ultimately increase the quality of patient care.

Advances in fermented foods revealed by multi-omics: A new direction toward precisely clarifying the roles of microorganisms

Fermented foods generally comprise a complex micro-ecosystem with beneficial microbiota, functional products, and special flavors and qualities that are welcomed globally. Single-omics analysis allows for a comprehensive characterization of the main microbial factors influencing the function, flavor, and quality of fermented foods. However, the species, relative abundance, viability, growth patterns, and metabolic processes of microorganisms vary with changes in processing and environmental conditions during fermentation. Furthermore, the mechanisms underlying the complex interaction among microorganisms are still difficult to completely understand and analyze. Recently, multi-omics analysis and the integration of multiple types of omics data allowed researchers to more comprehensively explore microbial communities and understand the precise relationship between fermented foods and their functions, flavors, and qualities. Multi-omics approaches might help clarify the mechanisms underpinning the fermentation processes, metabolites, and functional components of these communities. This review clarified the recent advances in the roles of microorganisms in fermented foods based on multi-omics data. Current research achievements may allow for the precise control of the whole industrial processing technology of fermented foods, meeting consumers' expectations of healthy products.

Deciphering chloramphenicol biotransformation mechanisms and microbial interactions via integrated multi-omics and cultivation-dependent approaches

BACKGROUND

As a widely used broad-spectrum antibiotic, chloramphenicol is prone to be released into environments, thus resulting in the disturbance of ecosystem stability as well as the emergence of antibiotic resistance genes. Microbes play a vital role in the decomposition of chloramphenicol in the environment, and the biotransformation processes are especially dependent on synergistic interactions and metabolite exchanges among microbes. Herein, the comprehensive chloramphenicol biotransformation pathway, key metabolic enzymes, and interspecies interactions in an activated sludge-enriched consortium were elucidated using integrated multi-omics and cultivation-based approaches.

RESULTS

The initial biotransformation steps were the oxidization at the C₁-OH and C₃-OH groups, the isomerization at C₂, and the acetylation at C₃-OH of chloramphenicol. Among them, the isomerization is an entirely new biotransformation pathway of chloramphenicol discovered for the first time. Furthermore, we identified a novel glucose-methanol-choline oxidoreductase responsible for the oxidization of the C₃-OH group in Sphingomonas sp. and Caballeronia sp. Moreover, the subsequent biotransformation steps, corresponding catalyzing enzymes, and the microbial players responsible for each step were deciphered. Synergistic interactions between Sphingomonas sp. and Caballeronia sp. or Cupriavidus sp. significantly promoted chloramphenicol mineralization, and the substrate exchange interaction network occurred actively among key microbes.

CONCLUSION

This study provides desirable strain and enzyme resources for enhanced bioremediation of chloramphenicol-contaminated hotspot sites such as pharmaceutical wastewater and livestock and poultry wastewater. The in-depth understanding of the chloramphenicol biotransformation mechanisms and microbial interactions will not only guide the bioremediation of organic pollutants but also provide valuable knowledge for environmental microbiology and biotechnological exploitation. Video Abstract.

The human lung microbiome-A hidden link between microbes and human health and diseases

Once thought to be sterile, the human lung is now well recognized to harbor a consortium of microorganisms collectively known as the lung microbiome. The lung microbiome is altered in an array of lung diseases, including chronic lung diseases such as chronic obstructive pulmonary disease, asthma, and bronchiectasis, acute lung diseases caused by pneumonia, sepsis, and COVID-19, and other lung complications such as those related to lung transplantation, lung cancer, and human immunodeficiency virus. The effects of lung microbiome in modulating host immunity and inflammation in the lung and distal organs are being elucidated. However, the precise mechanism by which members of microbiota produce structural ligands that interact with host genes and pathways remains largely uncharacterized. Multiple unique challenges, both technically and biologically, exist in the field of lung microbiome, necessitating the development of tailored experimental and analytical approaches to overcome the bottlenecks. In this review, we first provide an overview of the principles and methodologies in studying the lung microbiome. We next review current knowledge of the roles of lung microbiome in human diseases, highlighting mechanistic insights. We finally discuss critical challenges in the field and share our thoughts on broad topics for future investigation.

Hydrocarbon bioremediation on Arctic shorelines: Historic perspective and roadway to the future

Climate change has become one of the greatest concerns of the past few decades. In particular, global warming is a growing threat to the Canadian high Arctic and other polar regions. By the middle of this century, an increase in the annual mean temperature of 1.8 °C-2.7 °C for the Canadian North is predicted. Rising temperatures lead to a significant decrease of the sea ice area covered in the Northwest Passage. As a consequence, a surge of maritime activity in that region increases the risk of hydrocarbon pollution due to accidental fuel spills. In this review, we focus on bioremediation approaches on Arctic shorelines. We summarize historical experimental spill studies conducted at Svalbard, Baffin Island, and the Kerguelen Archipelago, and review contemporary studies that used modern omics techniques in various environments. We discuss how omics approaches can facilitate our understanding of Arctic shoreline bioremediation and identify promising research areas that should be further explored. We conclude that specific environmental conditions strongly alter bioremediation outcomes in Arctic environments and future studies must therefore focus on correlating these diverse parameters with the efficacy of hydrocarbon biodegradation.

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

Omics technologies in poultry health and productivity - part 1: current use in poultry research

In biology, molecular terms with the suffix "-omics" refer to disciplines aiming at the collective characterization of pools of molecules derived from different layers (DNA, RNA, proteins, metabolites) of living organisms using high-throughput technologies. Such omics analyses have been widely implemented in poultry research in recent years. This first part of a bipartite review on omics technologies in poultry health and productivity examines the use of multiple omics and multi-omics techniques in poultry research. More specific present and future applications of omics technologies, not only for the identification of specific diagnostic biomarkers, but also for potential future integration in the daily monitoring of poultry production, are discussed in part 2. Approaches based on omics technologies are particularly used in poultry research in the hunt for genetic markers of economically important phenotypical traits in the host, and in the identification of key bacterial species or functions in the intestinal microbiome. Integrative multi-omics analyses, however, are still scarce. Host physiology is investigated via genomics together with transcriptomics, proteomics and metabolomics techniques, to understand more accurately complex production traits such as disease resistance and fertility. The gut microbiota, as a key player in chicken productivity and health, is also a main subject of such studies, investigating the association between its composition (16S rRNA gene sequencing) or function (metagenomics, metatranscriptomics, metaproteomics, metabolomics) and host phenotypes. Applications of these technologies in the study of other host-associated microbiota and other host characteristics are still in their infancy.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Life from a Snowflake: Diversity and Adaptation of Cold-Loving Bacteria among Ice Crystals

Incredible as it is, researchers have now the awareness that even the most extreme environment includes special habitats that host several forms of life. Cold environments cover different compartments of the cryosphere, as sea and freshwater ice, glaciers, snow, and permafrost. Although these are very particular environmental compartments in which various stressors coexist (i.e., freeze–thaw cycles, scarce water availability, irradiance conditions, and poorness of nutrients), diverse specialized microbial communities are harbored. This raises many intriguing questions, many of which are still unresolved. For instance, a challenging focus is to understand if microorganisms survive trapped frozen among ice crystals for long periods of time or if they indeed remain metabolically active. Likewise, a look at their site-specific diversity and at their putative geochemical activity is demanded, as well as at the equally interesting microbial activity at subzero temperatures. The production of special molecules such as strategy of adaptations, cryoprotectants, and ice crystal-controlling molecules is even more intriguing. This paper aims at reviewing all these aspects with the intent of providing a thorough overview of the main contributors in investigating the microbial life in the cryosphere, touching on the themes of diversity, adaptation, and metabolic potential.

Impacts of the Biocontrol Strain Pseudomonas simiae PICF7 on the Banana Holobiont: Alteration of Root Microbial Co-occurrence Networks and Effect on Host Defense Responses

The impact of the versatile biocontrol and plant-growth-promoting rhizobacteria Pseudomonas simiae PICF7 on the banana holobiont under controlled conditions was investigated. We examine the fate of this biological control agent (BCA) upon introduction in the soil, the effect on the banana root microbiota, and the influence on specific host genetic defense responses. While the presence of strain PICF7 significantly altered neither the composition nor the structure of the root microbiota, a significant shift in microbial community interactions through co-occurrence network analysis was observed. Despite the fact that PICF7 did not constitute a keystone, the topology of this network was significantly modified-the BCA being identified as a constituent of one of the main network modules in bacterized plants. Gene expression analysis showed the early suppression of several systemic acquired resistance and induced systemic resistance (ISR) markers. This outcome occurred at the time in which the highest relative abundance of PICF7 was detected. The absence of major and permanent changes on the banana holobiont upon PICF7 introduction poses advantages regarding the use of this beneficial rhizobacteria under field conditions. Indeed a BCA able to control the target pathogen while altering as little as possible the natural host-associated microbiome should be a requisite when developing effective bio-inoculants.

Multi-omics analyses of the ulcerative colitis gut microbiome link Bacteroides vulgatus proteases with disease severity

Ulcerative colitis (UC) is driven by disruptions in host-microbiota homoeostasis, but current treatments exclusively target host inflammatory pathways. To understand how host-microbiota interactions become disrupted in UC, we collected and analysed six faecal- or serum-based omic datasets (metaproteomic, metabolomic, metagenomic, metapeptidomic and amplicon sequencing profiles of faecal samples and proteomic profiles of serum samples) from 40 UC patients at a single inflammatory bowel disease centre, as well as various clinical, endoscopic and histologic measures of disease activity. A validation cohort of 210 samples (73 UC, 117 Crohn's disease, 20 healthy controls) was collected and analysed separately and independently. Data integration across both cohorts showed that a subset of the clinically active UC patients had an overabundance of proteases that originated from the bacterium Bacteroides vulgatus. To test whether B. vulgatus proteases contribute to UC disease activity, we first profiled B. vulgatus proteases found in patients and bacterial cultures. Use of a broad-spectrum protease inhibitor improved B. vulgatus-induced barrier dysfunction in vitro, and prevented colitis in B. vulgatus monocolonized, IL10-deficient mice. Furthermore, transplantation of faeces from UC patients with a high abundance of B. vulgatus proteases into germfree mice induced colitis dependent on protease activity. These results, stemming from a multi-omics approach, improve understanding of functional microbiota alterations that drive UC and provide a resource for identifying other pathways that could be inhibited as a strategy to treat this disease.

Genome-Resolved Metagenomics Reveals Distinct Phosphorus Acquisition Strategies between Soil Microbiomes

Enhancing soil phosphate solubilization is a promising strategy for agricultural sustainability, while little is known about the mechanisms of how microorganisms cope with differing phosphorus availability. Using a combination of genome-resolved metagenomics and amplicon sequencing, we investigated the microbial mechanisms involved in phosphorus cycling under three agricultural treatments in a wheat-maize rotation system and two natural reforestation treatments. Available soil phosphorus was the key factor shaping bacterial and fungal community composition and function across our agricultural and reforestation sites. Membrane-bound quinoprotein glucose dehydrogenase (PQQGDH) and exopolyphosphatases (PPX) governed microbial phosphate solubilization in agroecosystems. In contrast, genes encoding glycerol-3-phosphate transporters (ugpB, ugpC, and ugpQ) displayed a significantly greater abundance in the reforestation soils. The gcd gene encoding PQQGDH was found to be the best determinant for bioavailable soil phosphorus. Metagenome-assembled genomes (MAGs) affiliated with Cyclobacteriaceae and Vicinamibacterales were obtained from agricultural soils. Their MAGs harbored not only gcd but also the pit gene encoding low-affinity phosphate transporters. MAGs obtained from reforestation soils were affiliated with Microtrichales and Burkholderiales. These contain ugp genes but no gcd, and thereby are indicative of a phosphate transporter strategy. Our study demonstrates that knowledge of distinct microbial phosphorus acquisition strategies between agricultural and reforestation soils could help in linking microbial processes with phosphorus cycling.

IMPORTANCE The soil microbiome is the key player regulating phosphorus cycling processes. Identifying phosphate-solubilizing bacteria and utilizing them for release of recalcitrant phosphate that is bound to rocks or minerals have implications for improving crop nutrient acquisition and crop productivity. In this study, we combined functional metagenomics and amplicon sequencing to analyze microbial phosphorus cycling processes in natural reforestation and agricultural soils. We found that the phosphorus acquisition strategies significantly differed between these two ecosystems. A microbial phosphorus solubilization strategy dominated in the agricultural soils, while a microbial phosphate transporter strategy was observed in the reforestation soils. We further identified microbial taxa that contributed to enhanced phosphate solubilization in the agroecosystem. These microbes are predicted to be beneficial for the increase in phosphate bioavailability through agricultural practices.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Evaluation of Sample Preservation and Storage Methods for Metaproteomics Analysis of Intestinal Microbiomes

A critical step in studies of the intestinal microbiome using meta-omics approaches is the preservation of samples before analysis. Preservation is essential for approaches that measure gene expression, such as metaproteomics, which is used to identify and quantify proteins in microbiomes. Intestinal microbiome samples are typically stored by flash-freezing and storage at -80°C, but some experimental setups do not allow for immediate freezing of samples. In this study, we evaluated methods to preserve fecal microbiome samples for metaproteomics analyses when flash-freezing is not possible. We collected fecal samples from C57BL/6 mice and stored them for 1 and 4 weeks using the following methods: flash-freezing in liquid nitrogen, immersion in RNAlater, immersion in 95% ethanol, immersion in a RNAlater-like buffer, and combinations of these methods. After storage, we extracted protein and prepared peptides for liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis to identify and quantify peptides and proteins. All samples produced highly similar metaproteomes, except for ethanol-preserved samples that were distinct from all other samples in terms of protein identifications and protein abundance profiles. Flash-freezing and RNAlater (or RNAlater-like treatments) produced metaproteomes that differed only slightly, with less than 0.7% of identified proteins differing in abundance. In contrast, ethanol preservation resulted in an average of 9.5% of the identified proteins differing in abundance between ethanol and the other treatments. Our results suggest that preservation at room temperature in RNAlater or an RNAlater-like solution performs as well as freezing for the preservation of intestinal microbiome samples before metaproteomics analyses. IMPORTANCE Metaproteomics is a powerful tool to study the intestinal microbiome. By identifying and quantifying a large number of microbial, dietary, and host proteins in microbiome samples, metaproteomics provides direct evidence of the activities and functions of microbial community members. A critical step for metaproteomics workflows is preserving samples before analysis because protein profiles are susceptible to fast changes in response to changes in environmental conditions (air exposure, temperature changes, etc.). This study evaluated the effects of different preservation treatments on the metaproteomes of intestinal microbiome samples. In contrast to prior work on preservation of fecal samples for metaproteomics analyses, we ensured that all steps of sample preservation were identical so that all differences could be attributed to the preservation method.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Toward a Framework for Assessing Privacy Risks in Multi-Omic Research and Databases

While the accumulation and increased circulation of genomic data have captured much attention over the past decade, privacy risks raised by the diversification and integration of omics have been largely overlooked. In this paper, we propose the outline of a framework for assessing privacy risks in multi-omic research and databases. Following a comparison of privacy risks associated with genomic and epigenomic data, we dissect ten privacy risk-impacting omic data properties that affect either the risk of re-identification of research participants, or the sensitivity of the information potentially conveyed by biological data. We then propose a three-step approach for the assessment of privacy risks in the multi-omic era. Thus, we lay grounds for a data property-based, 'pan-omic' approach that moves away from genetic exceptionalism. We conclude by inviting our peers to refine these theoretical foundations, put them to the test in their respective fields, and translate our approach into practical guidance.

Tools and challenges to exploit microbial communities in agriculture

Plants contain diverse microbial communities. The associated microorganisms confer advantages to the host plant, which include growth promotion, nutrient absorption, stress tolerance, and pathogen and disease resistance. In this review, we explore how agriculture is implementing the use of microbial inoculants (single species or consortia) to improve crop yields, and discuss current strategies to study plant-associated microorganisms and how their diversity varies under unconventional agriculture. It is predicted that microbial inoculation will continue to be used in agriculture.

Evaluation of the effect of antibiotics on gut microbiota in early life based on culturomics, SMRT sequencing and metagenomics sequencing methods

Symbiotic gut microbiota in early life plays a vital role in human health, and changes in its communication and function are associated with various complex disorders. In this study, we analyzed the gut flora communication of 6 infants at 4 months of age and determined the disturbances related to antibiotic treatment. By the culturomics and Single Molecule Real-time sequencing methods, a total of 6234 strains were divided into 16 genera and 45 species. The alpha diversity of culturable microorganisms in amoxicillin-treated infants was significantly less than that in healthy infants (p <0.05), as indicated by Chao 1, observed species and Faith's PD index. According to metagenomics, the dominant genus and species were Bifidobacterium and B. longum in the healthy group. After treatment with amoxicillin, the dominant genus and species shifted to Enterococcus and E. faecium. Based on the functional annotation of metagenomics, amoxicillin affected the metabolic function of the gut microbiome by activating carbohydrate and lipid metabolism and inhibiting amino acid metabolism. Besides, the intake of antibiotics in early life increased the risk of neurodegenerative disease, virus infectious disease and antimicrobial resistance. The Antibiotic Resistance Genes Database annotation result indicated that the abundance of drug-resistance genes in the antibiotic group was higher than that in the healthy group. These genes were associated with resistance to bacitracin, most of which were associated with K. pneumonia. These findings can provide guidance in the clinic on the proper usage of antibiotics.

Integration of transcriptomic and proteomic approaches unveils the molecular mechanism of membrane disintegration in Escherichia coli O157:H7 with ultrasonic treatment

Ultrasonic disinfection in wastewater treatment has been studied for years at the phenotypic level, while the understanding of the molecular inactivation mechanism is still not clear. Here, the responses of Escherichia coli O157:H7 to ultrasound treatment were investigated using RNA sequencing (RNA-Seq) and tandem mass tags (TMT) based quantitative proteomics methods. The analyses revealed that 770 genes and 201 proteins were significantly changed upon ultrasound treatment. Moreover, the integrated transcriptomic and proteomic analyses uncovered a set of 59 genes or proteins were differentially expressed in ultrasound-treated cells, providing an overview of the cellular responses to ultrasonic field. According to the bioinformatic analyses, genes and proteins that may be involved in lipid asymmetry preservation and outer membrane homeostasis maintenance (including phospholipid metabolism, lipopolysaccharide biosynthesis and transport, and fatty acid metabolism) were specifically up-regulated. Therefore, we proposed that the metabolism disorder of cellular membrane lipids (lipopolysaccharide, phospholipid, and fatty acid included) was one of the main challenges for the bacteria upon ultrasonic stress. In this study, we initially proposed a novel mechanism regarding the ultrasound-induced membrane disintegration from a multi-omics perspective, which may present an important step toward deciphering the molecular inactivation mechanism of ultrasonic field and provide a theoretical foundation for the application of ultrasound technology for the control of waterborne pathogens.

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.

Amadis: A Comprehensive Database for Association Between Microbiota and Disease

The human gastrointestinal tract represents a symbiotic bioreactor that can mediate the interaction of the human host. The deployment and integration of multi-omics technologies have depicted a more complete image of the functions performed by microbial organisms. In addition, a large amount of data has been generated in a short time. However, researchers struggling to keep track of these mountains of information need a way to conveniently gain a comprehensive understanding of the relationship between microbiota and human diseases. To tackle this issue, we developed Amadis (http://gift2disease.net/GIFTED), a manually curated database that provides experimentally supported microbiota-disease associations and a dynamic network construction method. The current version of the Amadis database documents 20167 associations between 221 human diseases and 774 gut microbes across 17 species, curated from more than 1000 articles. By using the curated data, users can freely select and combine modules to obtain a specific microbe-based human disease network. Additionally, Amadis provides a user-friendly interface for browsing, searching and downloading. We hope it can serve as a useful and valuable resource for researchers exploring the associations between gastrointestinal microbiota and human diseases.

Linking meta-omics to the kinetics of denitrification intermediates reveals pH-dependent causes of N2O emissions and nitrite accumulation in soil

Soil pH is a key controller of denitrification. We analysed the metagenomics/transcriptomics and phenomics of two soils from a long-term liming experiment, SoilN (pH 6.8) and un-limed SoilA (pH 3.8). SoilA had severely delayed N₂O reduction despite early transcription of nosZ (mainly clade I), encoding N₂O reductase, by diverse denitrifiers. This shows that post-transcriptionally hampered maturation of the NosZ apo-protein at low pH is a generic phenomenon. Identification of transcript reads of several accessory genes in the nos cluster indicated that enzymes for NosZ maturation were present across a range of organisms, eliminating their absence as an explanation for the failure to produce a functional enzyme. nir transcript abundances (for NO₂⁻ reductase) in SoilA suggest that low NO₂⁻ concentrations in acidic soils, often ascribed to abiotic degradation, are primarily due to biological activity. The accumulation of NO₂⁻ in neutral soil was ascribed to high nar expression (nitrate reductase). The -omics results revealed dominance of nirK over nirS in both soils while qPCR showed the opposite, demonstrating that standard primer pairs only capture a fraction of the nirK pool. qnor encoding NO reductase was strongly expressed in SoilA, implying an important role in controlling NO. Production of HONO, for which some studies claim higher, others lower, emissions from NO₂⁻ accumulating soil, was estimated to be ten times higher from SoilA than from SoilN. The study extends our understanding of denitrification-driven gas emissions and the diversity of bacteria involved and demonstrates that gene and transcript quantifications cannot always reliably predict community phenotypes.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Microbiome Modulation-Toward a Better Understanding of Plant Microbiome Response to Microbial Inoculants

Plant-associated microorganisms are involved in important functions related to growth, performance and health of their hosts. Understanding their modes of action is important for the design of promising microbial inoculants for sustainable agriculture. Plant-associated microorganisms are able to interact with their hosts and often exert specific functions toward potential pathogens; the underlying in vitro interactions are well studied. In contrast, in situ effects of inoculants, and especially their impact on the plant indigenous microbiome was mostly neglected so far. Recently, microbiome research has revolutionized our understanding of plants as coevolved holobionts but also of indigenous microbiome-inoculant interactions. Here we disentangle the effects of microbial inoculants on the indigenous plant microbiome and point out the following types of plant microbiome modulations: (i) transient microbiome shifts, (ii) stabilization or increase of microbial diversity, (iii) stabilization or increase of plant microbiome evenness, (iv) restoration of a dysbiosis/compensation or reduction of a pathogen-induced shift, (v) targeted shifts toward plant beneficial members of the indigenous microbiota, and (vi) suppression of potential pathogens. Therefore, we suggest microbiome modulations as novel and efficient mode of action for microbial inoculants that can also be mediated via the plant.

MegaGO: A Fast Yet Powerful Approach to Assess Functional Gene Ontology Similarity across Meta-Omics Data Sets

The study of microbiomes has gained in importance over the past few years and has led to the emergence of the fields of metagenomics, metatranscriptomics, and metaproteomics. While initially focused on the study of biodiversity within these communities, the emphasis has increasingly shifted to the study of (changes in) the complete set of functions available in these communities. A key tool to study this functional complement of a microbiome is Gene Ontology (GO) term analysis. However, comparing large sets of GO terms is not an easy task due to the deeply branched nature of GO, which limits the utility of exact term matching. To solve this problem, we here present MegaGO, a user-friendly tool that relies on semantic similarity between GO terms to compute the functional similarity between multiple data sets. MegaGO is high performing: Each set can contain thousands of GO terms, and results are calculated in a matter of seconds. MegaGO is available as a web application at https://megago.ugent.be and is installable via pip as a standalone command line tool and reusable software library. All code is open source under the MIT license and is available at https://github.com/MEGA-GO/.

A multi-omic screening approach for the discovery of thermoactive glycoside hydrolases

Next-generation sequencing and computational biology have facilitated the implementation of new combinatorial screening approaches to discover novel enzymes of biotechnological interest. In this study, we describe the successful establishment of a multi-omic approach for the identification of thermostable hydrolase-encoding genes by determination of gene expression levels. We applied this combinatorial approach using an anaerobic enrichment culture from an Azorean hot spring sample grown on green coffee beans as recalcitrant substrate. An in-depth analysis of the microbial community resulted in microorganisms capable of metabolizing the selected substrate, such as the genera Caloramator, Dictyoglomus and Thermoanaerobacter as active and abundant microorganisms. To discover glycoside hydrolases, 90,342 annotated genes were screened for specific reaction types. A total number of 106 genes encoding cellulases (EC 3.2.1.4), beta-glucosidases (EC 3.2.1.21) and endo-1,4-beta-mannosidases (EC 3.2.1.78) were selected. Mapping of RNA-Seq reads to the related metagenome led to expression levels for each gene. Amongst those, 14 genes, encoding glycoside hydrolases, showed highest expression values, and were used for further cloning. Four proteins were biochemically characterized and were identified as thermoactive glycoside hydrolases with a broad substrate range. This work demonstrated that a combinatory omic approach is a suitable strategy identifying unique thermoactive enzymes from environmental samples.

Indicators for assessment of soil quality: a mini-review

Soil quality is the competence of soil to perform necessary functions that are able to maintain animal and plant productivity of the soil. Soil consists of various physical, chemical, and biological parameters, and all these parameters are involved in the critical functioning of soil. There is a need for continuous assessment of soil quality as soil is a complex and dynamic constituent of Earth's biosphere that is continuously changing by natural and anthropogenic disturbances. Any perturbations in the soil cause disturbances in the physical (soil texture, bulk density, etc.), chemical (pH, salinity, organic carbon, etc.), and biological (microbes and enzymes) parameters. These physical, chemical, and biological parameters can serve as indicators for soil quality assessment. However, soil quality assessment cannot be possible by evaluating only one parameter out of physical, chemical, or biological. So, there is an emergent need to establish a minimum dataset (MDS) which shall include physical, chemical, and biological parameters to assess the quality of the given soil. This review attempts to describe various physical, chemical, and biological parameters, combinations of which can be used in the establishment of MDS.

Sub-Lethal Effects of Pesticides on the DNA of Soil Organisms as Early Ecotoxicological Biomarkers

This review describes the researches performed in the last years to assess the impact of pesticide sub-lethal doses on soil microorganisms and non-target organisms in agricultural soil ecosystems. The overview was developed through the careful description and a critical analysis of three methodologies based on culture-independent approaches involving DNA extraction and sequencing (denaturing gradient gel electrophoresis, DGGE; next-generation sequencing, NGS) to characterize the microbial population and DNA damage assessment (comet assay) to determine the effect on soil invertebrates. The examination of the related published articles showed a continuous improvement of the possibility to detect the detrimental effect of the pesticides on soil microorganisms and non-target organisms at sub-lethal doses, i.e., doses which have no lethal effect on the organisms. Considering the overall critical discussion on microbial soil monitoring in the function of pesticide treatments, we can confirm the usefulness of PCR-DGGE as a screening technique to assess the genetic diversity of microbial communities. Nowadays, DGGE remains a preliminary technique to highlight rapidly the main differences in microbial community composition, which is able to give further information if coupled with culture-dependent microbiological approaches, while thorough assessments must be gained by high-throughput techniques such as NGS. The comet assay represents an elective technique for assessing genotoxicity in environmental biomonitoring, being mature after decades of implementation and widely used worldwide for its direct, simple, and affordable implementation. Nonetheless, in order to promote the consistency and reliability of results, regulatory bodies should provide guidelines on the optimal use of this tool, strongly indicating the most reliable indicators of DNA damage. This review may help the European Regulation Authority in deriving new ecotoxicological endpoints to be included in the Registration Procedure of new pesticides.

Metaproteomics insights into traditional fermented foods and beverages

Traditional fermented foods and beverages (TFFB) are important dietary components. Multi-omics techniques have been applied to all aspects of TFFB research to clarify the composition and nutritional value of TFFB, and to reveal the microbial community, microbial interactions, fermentative kinetics, and metabolic profiles during the fermentation process of TFFB. Because of the advantages of metaproteomics in providing functional information, this technology has increasingly been used in research to assess the functional diversity of microbial communities. Metaproteomics is gradually gaining attention in the field of TFFB research because it can reveal the nature of microorganism function at the protein level. This paper reviews the common methods of metaproteomics applied in TFFB research; systematically summarizes the results of metaproteomics research on TFFB, such as sauces, wines, fermented tea, cheese, and fermented fish; and compares the differences in conclusions reached through metaproteomics versus other omics methods. Metaproteomics has great advantages in revealing the microbial functions in TFFB and the interaction between the materials and microbial community. In the future, metaproteomics should be further applied to the study of functional protein markers and protein interaction in TFFB; multi-omics technology requires further integration to reveal the molecular nature of TFFB fermentation.

Digitalization in microbiology - Paving the path to sustainable circular bioeconomy

The transition to a sustainable bio-based circular economy requires cutting edge technologies that ensure economic growth with environmentally responsible action. This transition will only be feasible when the opportunities of digitalization are also exploited. Digital methods and big data handling have already found their way into life sciences and generally offer huge potential in various research areas. While computational analyses of microbial metagenome data have become state of the art, the true potential of bioinformatics remains mostly untapped so far. In this article we present challenges and opportunities of digitalization including multi-omics approaches in discovering and exploiting the microbial diversity of the planet with the aim to identify robust biocatalysts for application in sustainable bioprocesses as part of the transition from a fossil-based to a bio-based circular economy. This will contribute to solving global challenges, including utilization of natural resources, food supply, health, energy and the environment.

Who Is Metabolizing What? Discovering Novel Biomolecules in the Microbiome and the Organisms Who Make Them

Even as the field of microbiome research has made huge strides in mapping microbial community composition in a variety of environments and organisms, explaining the phenotypic influences on the host by microbial taxa-both known and unknown-and their specific functions still remain major challenges. A pressing need is the ability to assign specific functions in terms of enzymes and small molecules to specific taxa or groups of taxa in the community. This knowledge will be crucial for advancing personalized therapies based on the targeted modulation of microbes or metabolites that have predictable outcomes to benefit the human host. This perspective article advocates for the combined use of standards-free metabolomics and activity-based protein profiling strategies to address this gap in functional knowledge in microbiome research via the identification of novel biomolecules and the attribution of their production to specific microbial taxa.

Art-omics: multi-omics meet archaeology and art conservation

Multi-omics can informally be described as the combined use of high-throughput techniques allowing the characterization of complete microbial communities by the sequencing/identification of total pools of biomolecules including DNA, proteins or metabolites. These techniques have allowed an unprecedented level of knowledge on complex microbial ecosystems, which is having key implications in land and marine ecology, industrial biotechnology or biomedicine. Multi-omics have recently been applied to artistic or archaeological objects, with the goal of either contributing to shedding light on the original context of the pieces and/or to inform conservation approaches. In this minireview, we discuss the application of -omic techniques to the study of prehistoric artworks and ancient man-made objects in three main technical blocks: metagenomics, proteomics and metabolomics. In particular, we will focus on how proteomics and metabolomics can provide paradigm-breaking results by unambiguously identifying peptides associated with a given, palaeo-cultural context; and we will discuss how metagenomics can be central for the identification of the microbial keyplayers on artworks surfaces, whose conservation can then be approached by a range of techniques, including using selected microorganisms as 'probiotics' because of their direct or indirect effect in the stabilization and preservation of valuable art objects.

Enterotype identification and its influence on regulating the duodenum metabolism in chickens

Enterotypes are used to describe clusters of specific gut microbial community structures, but few reports exist on the identification of enterotypes in poultry. In addition, there is incomplete understanding on the role of the foregut microbiota in the digestion and absorption of nutrients in poultry. Thus, this study aimed to identify the duodenal enterotypes by examining microbial communities from 206 broilers using 16S rRNA high-throughput sequencing and explore the effects of enterotypes on phenotypic performance and nutrient metabolism with metabolomics. The duodenal microbial communities of the broiler population were partitioned into 3 enterotypes (ET1, ET2, and ET3), and significant differences were observed in α-diversity among the enterotypes (P < 0.01). At the genus level, the ET1 group was over-represented by Bacteroides (9.8%) and Escherichia–Shigella (8.9%), the ET2 group was over-represented by Ochrobactrum (19.4%) and Rhodococcus (14.7%), and the ET3 group was over-represented by Bacillus (23.4%) and Akkermansia (16.2%). The relative abundance of the dominant taxa of each enterotype was significantly higher than that in the other 2 enterotypes (P < 0.01). The results showed that Ochrobactrum and Rhodococcus were positively correlated with cellobiose, alpha-D-glucose, D-mannose, and D-allose (r = 0.429, 0.435, 0.482, and 0.562, respectively; all P < 0.05). Rhodococcus was also positively correlated with tridecanoic acid and glycerol 1-myristate (r = 0.655 and 0.489, respectively; all P < 0.01). In terms of phenotype, the triglyceride level in the ET2 group was significantly higher than that in the ET1 group (P < 0.05), and the subcutaneous fat thickness and abdominal fat weight in the ET2 group were the highest (P > 0.05). Taken together, these results confirmed the presence of enterotypes in broilers and found that the dominant microbes in broilers of the ET2 group might play a major role in the degradation and utilization of plant polysaccharides, which may have an impact on the serum triglyceride level and fat deposition in broilers. These findings lay a foundation for further studies on the gut microbial interactions with the metabolism in broilers and the regulation of the gut microbiota to promote growth and well-being in broilers.