Integration of absolute multi-omics reveals dynamic protein-to-RNA ratios and metabolic interplay within mixed-domain microbiomes

Critical steps in an environmental metaproteomics workflow

Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.

Comparison of anaerobic digestion of starch- and petro-based bioplastic under hydrogen-rich conditions

To identify an economically viable waste management system for bioplastics, thermoplastic starch (TPS) and poly(butylene adipate-co-terephthalate) (PBAT) were anaerobically digested under hydrogen (H2)/carbon dioxide (CO2) and nitrogen (N2) gas-purged conditions to compare methane (CH4) production and biodegradation. Regardless of the type of bioplastics, CH4 production was consistently higher with H2/CO2 than with N2. The highest amount of CH4 was produced at 307.74 mL CH4/g volatile solids when TPS digested with H2/CO2. A stepwise increased in CH4 yield was observed, with a nominal initial increment followed by accelerated methanogenesis conversion as H2 was depleted. This may be attributed to a substantial shift in the microbial structure from hydrogenotrophic methanogen (Methanobacteriales and Methanomicrobiales) to heterotrophs (Spirochaetia). In contrast, no significant change was observed with PBAT, regardless of the type of purged gas. TPS was broken down into numerous derivatives, including volatile fatty acids. TPS produced more byproducts with H2/CO2 (i.e., 430) than with N2 (i.e., 320). In contrast, differential scanning calorimetry analysis on PBAT revealed an increase in crystallinity from 10.20 % to 12.31 % and 11.36 % in the H2/CO2- and N2-purged conditions, respectively, after 65 days of testing. PBAT surface modifications were characterized via Fourier transform infrared spectroscopy and scanning electron microscopy. The results suggest that the addition of H2/CO2 can enhance the CH4 yield and increase the breakdown rate of TPS more than that of PBAT. This study provides novel insights into the CH4 production potential of two bioplastics with different biodegradabilities in H2/CO2-mediated anaerobic digestion systems.

Diverse electron carriers drive syntrophic interactions in an enriched anaerobic acetate-oxidizing consortium

In many anoxic environments, syntrophic acetate oxidation (SAO) is a key pathway mediating the conversion of acetate into methane through obligate cross-feeding interactions between SAO bacteria (SAOB) and methanogenic archaea. The SAO pathway is particularly important in engineered environments such as anaerobic digestion (AD) systems operating at thermophilic temperatures and/or with high ammonia. Despite the widespread importance of SAOB to the stability of the AD process, little is known about their in situ physiologies due to typically low biomass yields and resistance to isolation. Here, we performed a long-term (300-day) continuous enrichment of a thermophilic (55 °C) SAO community from a municipal AD system using acetate as the sole carbon source. Over 80% of the enriched bioreactor metagenome belonged to a three-member consortium, including an acetate-oxidizing bacterium affiliated with DTU068 encoding for carbon dioxide, hydrogen, and formate production, along with two methanogenic archaea affiliated with Methanothermobacter_A. Stable isotope probing was coupled with metaproteogenomics to quantify carbon flux into each community member during acetate conversion and inform metabolic reconstruction and genome-scale modeling. This effort revealed that the two Methanothermobacter_A species differed in their preferred electron donors, with one possessing the ability to grow on formate and the other only consuming hydrogen. A thermodynamic analysis suggested that the presence of the formate-consuming methanogen broadened the environmental conditions where ATP production from SAO was favorable. Collectively, these results highlight how flexibility in electron partitioning during SAO likely governs community structure and fitness through thermodynamic-driven mutualism, shedding valuable insights into the metabolic underpinnings of this key functional group within methanogenic ecosystems.

Microbial interactions within beneficial consortia promote soil health

By ecologically interacting with various biotic and abiotic agents acting in soil ecosystems, highly diverse soil microorganisms establish complex and stable assemblages and survive in a community context in natural settings. Besides facilitating soil microbiome to maintain great levels of population homeostasis, such microbial interactions drive soil microbes to function as the major engine of terrestrial biogeochemical cycling. It is verified that the regulative effect of microbe-microbe interplay plays an instrumental role in microbial-mediated promotion of soil health, including bioremediation of soil pollutants and biocontrol of soil-borne phytopathogens, which is considered an environmentally friendly strategy for ensuring the healthy condition of soils. Specifically, in microbial consortia, it has been proven that microorganism-microorganism interactions are involved in enhancing the soil health-promoting effectiveness (i.e., efficacies of pollution reduction and disease inhibition) of the beneficial microbes, here defined as soil health-promoting agents. These microbial interactions can positively regulate the soil health-enhancing effect by supporting those soil health-promoting agents utilized in combination, as multi-strain soil health-promoting agents, to overcome three main obstacles: inadequate soil colonization, insufficient soil contaminant eradication and inefficient soil-borne pathogen suppression, all of which can restrict their probiotic functionality. Yet the mechanisms underlying such beneficial interaction-related adjustments and how to efficiently assemble soil health-enhancing consortia with the guidance of microbe-microbe communications remain incompletely understood. In this review, we focus on bacterial and fungal soil health-promoting agents to summarize current research progress on the utilization of multi-strain soil health-promoting agents in the control of soil pollution and soil-borne plant diseases. We discuss potential microbial interaction-relevant mechanisms deployed by the probiotic microorganisms to upgrade their functions in managing soil health. We emphasize the interplay-related factors that should be taken into account when building soil health-promoting consortia, and propose a workflow for assembling them by employing a reductionist synthetic community approach.

Proteomic and Transcriptomic Analyses to Decipher the Chitinolytic Response of Jeongeupia spp

In nature, chitin, the most abundant marine biopolymer, does not accumulate due to the action of chitinolytic organisms, whose saccharification systems provide instructional blueprints for effective chitin conversion. Therefore, discovery and deconstruction of chitinolytic machineries and associated enzyme systems are essential for the advancement of biotechnological chitin valorization. Through combined investigation of the chitin-induced secretome with differential proteomic and transcriptomic analyses, a holistic system biology approach has been applied to unravel the chitin response mechanisms in the Gram-negative Jeongeupia wiesaeckerbachi. Hereby, the majority of the genome-encoded chitinolytic machinery, consisting of various glycoside hydrolases and a lytic polysaccharide monooxygenase, could be detected extracellularly. Intracellular proteomics revealed a distinct translation pattern with significant upregulation of glucosamine transport, metabolism, and chemotaxis-associated proteins. While the differential transcriptomic results suggested the overall recruitment of more genes during chitin metabolism compared to that of glucose, the detected protein-mRNA correlation was low. As one of the first studies of its kind, the involvement of over 350 unique enzymes and 570 unique genes in the catabolic chitin response of a Gram-negative bacterium could be identified through a three-way systems biology approach. Based on the cumulative data, a holistic model for the chitinolytic machinery of Jeongeupia spp. is proposed.

Integrative meta-omics in Galaxy and beyond

BACKGROUND

'Omics methods have empowered scientists to tackle the complexity of microbial communities on a scale not attainable before. Individually, omics analyses can provide great insight; while combined as "meta-omics", they enhance the understanding of which organisms occupy specific metabolic niches, how they interact, and how they utilize environmental nutrients. Here we present three integrative meta-omics workflows, developed in Galaxy, for enhanced analysis and integration of metagenomics, metatranscriptomics, and metaproteomics, combined with our newly developed web-application, ViMO (Visualizer for Meta-Omics) to analyse metabolisms in complex microbial communities.

RESULTS

In this study, we applied the workflows on a highly efficient cellulose-degrading minimal consortium enriched from a biogas reactor to analyse the key roles of uncultured microorganisms in complex biomass degradation processes. Metagenomic analysis recovered metagenome-assembled genomes (MAGs) for several constituent populations including Hungateiclostridium thermocellum, Thermoclostridium stercorarium and multiple heterogenic strains affiliated to Coprothermobacter proteolyticus. The metagenomics workflow was developed as two modules, one standard, and one optimized for improving the MAG quality in complex samples by implementing a combination of single- and co-assembly, and dereplication after binning. The exploration of the active pathways within the recovered MAGs can be visualized in ViMO, which also provides an overview of the MAG taxonomy and quality (contamination and completeness), and information about carbohydrate-active enzymes (CAZymes), as well as KEGG annotations and pathways, with counts and abundances at both mRNA and protein level. To achieve this, the metatranscriptomic reads and metaproteomic mass-spectrometry spectra are mapped onto predicted genes from the metagenome to analyse the functional potential of MAGs, as well as the actual expressed proteins and functions of the microbiome, all visualized in ViMO.

CONCLUSION

Our three workflows for integrative meta-omics in combination with ViMO presents a progression in the analysis of 'omics data, particularly within Galaxy, but also beyond. The optimized metagenomics workflow allows for detailed reconstruction of microbial community consisting of MAGs with high quality, and thus improves analyses of the metabolism of the microbiome, using the metatranscriptomics and metaproteomics workflows.

'Multi-omics' data integration: applications in probiotics studies

The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and the modulation of host immunity through the strengthening of the gut barrier and stimulation of antibodies. These benefits, combined with the need for improved nutraceuticals, have resulted in the extensive characterization of probiotics leading to an outburst of data generated using several 'omics' technologies. The recent development in system biology approaches to microbial science is paving the way for integrating data generated from different omics techniques for understanding the flow of molecular information from one 'omics' level to the other with clear information on regulatory features and phenotypes. The limitations and tendencies of a 'single omics' application to ignore the influence of other molecular processes justify the need for 'multi-omics' application in probiotics selections and understanding its action on the host. Different omics techniques, including genomics, transcriptomics, proteomics, metabolomics and lipidomics, used for studying probiotics and their influence on the host and the microbiome are discussed in this review. Furthermore, the rationale for 'multi-omics' and multi-omics data integration platforms supporting probiotics and microbiome analyses was also elucidated. This review showed that multi-omics application is useful in selecting probiotics and understanding their functions on the host microbiome. Hence, recommend a multi-omics approach for holistically understanding probiotics and the microbiome.

Meta-omics elucidates key degraders in a bacterial tris(2-butoxyethyl) phosphate (TBOEP)-degrading enrichment culture

Organophosphate esters (OPEs) are emerging contaminants of growing concern, and there is limited information about the bacterial transformation of OPEs. In this study, we investigated the biotransformation of tris(2-butoxyethyl) phosphate (TBOEP), a frequently detected alkyl-OPE by a bacterial enrichment culture under aerobic conditions. The enrichment culture degraded 5 mg/L TBOEP following the first-order kinetics with a reaction rate constant of 0.314 h^-1. TBOEP was mainly degraded via ether bond cleavage, evidenced by the production of bis(2-butoxyethyl) hydroxyethyl phosphate, 2-butoxyethyl bis(2-hydroxyethyl) phosphate, and 2-butoxyethyl (2-hydroxyethyl) hydrogen phosphate. Other transformation pathways include terminal oxidation of the butoxyethyl group and phosphoester bond hydrolysis. Metagenomic sequencing generated 14 metagenome-assembled genomes (MAGs), showing that the enrichment culture primarily consisted of Gammaproteobacteria, Bacteroidota, Myxococcota, and Actinobacteriota. One MAG assigned to Rhodocuccus ruber strain C1 was the most active in the community, showing upregulation of various monooxygenase, dehydrogenase, and phosphoesterase genes throughout the degradation process, and thus was identified as the key degrader of TBOEP and the metabolites. Another MAG affiliated with Ottowia mainly contributed to TBOEP hydroxylation. Our results provided a comprehensive understanding of the bacterial TBOEP degradation at community level.

Virome diversity of ticks feeding on domestic mammals in China

Ticks are considered the second most common pathogen vectors transmitting a broad range of vital human and veterinary viruses. From 2017 to 2018, 640 ticks were collected in eight different provinces in central and western China. Six species were detected, including H.longicornis, De.everestianus, Rh.microplus, Rh.turanicus, Rh.sanguineous, and Hy.asiaticum. Sixty-four viral metagenomic libraries were constructed on the MiSeq Illumina platform, resulting in 13.44 ​G (5.88 ​× ​10⁷) of 250-bp-end reads, in which 2,437,941 are viral reads. We found 27 nearly complete genome sequences, including 16 genome sequences encoding entire protein-coding regions (lack of 3' or 5' end non-coding regions) and complete viral genomes, distributed in the arboviral family (Chuviridae, Rhabdoviridae, Nairoviridae, Phenuiviridae, Flaviviridae, Iflaviridae) as well as Parvoviridae and Polyomaviridae that cause disease in mammals and even humans. In addition, 13 virus sequences found in Chuviridae, Nairoviridae, Flaviviridae, Iflaviridae, Hepeviridae, Parvoviridae, and Polyomaviridae were identified as belonging to a new virus species in the identified viral genera. Besides, an epidemiological survey shows a high prevalence (9.38% and 15.63%) of two viruses (Ovine Copiparvovirus and Bovine parvovirus 2) in the tick cohort.

Impacts of organic loading rate and hydraulic retention time on organics degradation, interspecies interactions and functional traits in thermophilic anaerobic co-digestion of food waste and sewage sludge

This study provided novel insights into the effects of organic loading rate (OLR) and hydraulic retention time (HRT) on thermophilic anaerobic co-digestion of food waste and sewage sludge. The obtained maximum methane (CH₄) yield of 328 ± 4 mL CH₄/g COD_fed at HRT of 15 days (OLR = 5.8 g VS/L/d) was partly attributable to the enhanced acidogenesis, acetogenesis, and methanogenesis phases. The increased key enzyme activities, particularly acetate kinase (improved by 5.2-fold), providing substantial methanogenic substrates for efficient CH₄ production. The functional syntrophs that were related to syntrophic decarboxylation, novel acetate oxidation & reductive acetyl-CoA, and β-oxidation pathways could drive trophic interactions with methanogens. This markedly stimulated hydrogenotrophic Methanoculleus thermophilus metabolism and concomitantly enriched mixotrophic Methanosarcina thermophila. The distinctive cross-feeding interspecies interactions significantly affected the assembly and dynamics of thermophilic consortia. These findings shed light on the physicochemical and microbial mechanisms of HRT- and OLR-dependent enhancement of methanogenesis.

Long-Read Metagenomics and CAZyme Discovery

Microorganisms play a primary role in regulating biogeochemical cycles and are a valuable source of enzymes that have biotechnological applications, such as carbohydrate-active enzymes (CAZymes). However, the inability to culture the majority of microorganisms that exist in natural ecosystems restricts access to potentially novel bacteria and beneficial CAZymes. While commonplace molecular-based culture-independent methods such as metagenomics enable researchers to study microbial communities directly from environmental samples, recent progress in long-read sequencing technologies are advancing the field. We outline key methodological stages that are required as well as describe specific protocols that are currently used for long-read metagenomic projects dedicated to CAZyme discovery.

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

Untargeted Metabolomics Approach of Cross-Adaptation in Salmonella Enterica Induced by Major Compounds of Essential Oils

Cross-adaptation phenomena in bacterial populations, induced by sublethal doses of antibacterial solutions, are a major problem in the field of food safety. In this regard, essential oils and their major compounds appear as an effective alternative to common sanitizers in food industry environments. The present study aimed to evaluate the untargeted metabolomics perturbations of Salmonella enterica serovar Enteritidis that has been previously exposed to the sublethal doses of the major components of essential oils: cinnamaldehyde, citral, and linalool (CIN, CIT, and LIN, respectively). Cinnamaldehyde appeared to be the most efficient compound in the assays evaluating the inhibitory effects [0.06% (v/v) as MBC]. Also, preliminary tests exhibited a phenotype of adaptation in planktonic and sessile cells of S. Enteritidis when exposed to sublethal doses of linalool, resulting in tolerance to previously lethal concentrations of citral. A metabolomics approach on S. Enteritidis provided an important insight into the phenomenon of cross-adaptation induced by sublethal doses of major compounds of some essential oils. In addition, according to the results obtained, when single molecules were used, many pathways may be involved in bacterial tolerance, which could be different from the findings revealed in previous studies regarding the use of phytocomplex of essential oils. Orthogonal projection to latent structures (OPLS) proved to be an interesting predictive model to demonstrate the adaptation events in pathogenic bacteria because of the global engagement to prevent and control foodborne outbreaks.

Metaproteomic profiling of fungal gut colonization in gnotobiotic mice

Background

Eukaryotic microbes can modulate mammalian host health and disease states, yet the molecular contribution of gut fungi remains nascent. We previously showed that mice exclusively colonised with fungi displayed increased sensitivity to allergic airway inflammation and had fecal metabolite profiles similar to germ-free mice. This marginal effect on the host metabolome suggested that fungi do not primarily use metabolites to modulate the host immune system.

Methods

To describe functional changes attributed to fungal colonisation, we performed mass spectrometry-based analyses of feces (Label-Free Quantitative; LFQ) and the small intestine (labeling with Tandem Mass Tag; TMT) of gnotobiotic mice colonised with defined consortia of twelve bacterial species, five fungal species, or both. We also evaluated the effect of microbiome perturbances on the metaproteome by analysing feces from mouse pups treated with an antibiotic or antifungal.

Results

We detected 6675 proteins in the mice feces, of which 3845 had determined LFQ levels. Analysis of variance showed changes in the different gnotobiotic mouse groups; specifically, 46% of 2860 bacterial, 15% of 580 fungal, and 76% of 405 mouse quantified proteins displayed differential levels. The antimicrobial treatments resulted in lasting changes in the bacterial and fungal proteomes, suggesting that the antimicrobials impacted the entire community. Fungal colonisation resulted in changes in host proteins functional in innate immunity as well as metabolism, predicting specific roles of gut fungi on host systems during early developmental stages. Several of the detected fungal proteins (3% of 1492) have been previously reported as part of extracellular vesicles and having immunomodulating properties. Using an isobaric labelling TMT approach for profiling low abundant proteins of the jejunal tissue, we confirmed that the five fungal species differentially impacted the host intestinal proteome compared to the bacterial consortium. The detected changes in mouse jejunal proteins (4% of 1514) were mainly driven by metabolic proteins.

Conclusions

We used quantitative proteomic profiling of gnotobiotic conditions to show how colonisation with selected fungal species impacts the host gut proteome. Our results suggest that an increased abundance of certain gut fungal species in early life may affect the developing intracellular attributes of epithelial and immune cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00163-2.

Current understanding and perspectives in anaerobic digestion based on genome-resolved metagenomic approaches

Anaerobic digestion (AD) is a technique that can be used to treat high concentrations of various organic wastes using a consortium of functionally diverse microorganisms under anaerobic conditions. Methane gas, a beneficial by-product of the AD process, is a renewable energy source that can replace fossil fuels following purification. However, detailed functional roles and metabolic interactions between microbial populations involved in organic waste removal and methanogenesis are yet to be known. Recent metagenomic approaches based on advanced high-throughput sequencing techniques have enabled the exploration of holistic microbial taxonomy and functionality of complex microbial populations involved in the AD process. Gene-centric and genome-centric analyses based on metagenome-assembled genomes are a platform that can be used to study the composition of microbial communities and their roles during AD. This review looks at how these up-to-date metagenomic analyses can be applied to promote our understanding and improved the development of the AD process.

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.

Silica-coated magnetic nanoparticles activate microglia and induce neurotoxic D-serine secretion

BACKGROUND

Nanoparticles have been studied for brain imaging, diagnosis, and drug delivery owing to their versatile properties due to their small sizes. However, there are growing concerns that nanoparticles may exert toxic effects in the brain. In this study, we assessed direct nanotoxicity on microglia, the resident macrophages of the central nervous system, and indirect toxicity on neuronal cells exerted by silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)].

METHODS

We investigated MNPs@SiO2(RITC)-induced biological changes in BV2 murine microglial cells via RNA-sequencing-based transcriptome analysis and gas chromatography-mass spectrometry-based intracellular and extracellular amino acid profiling. Morphological changes were analyzed by transmission electron microscopy. Indirect effects of MNPs@SiO2(RITC) on neuronal cells were assessed by Transwell-based coculture with MNPs@SiO2(RITC)-treated microglia. MNPs@SiO2(RITC)-induced biological changes in the mouse brain in vivo were examined by immunohistochemical analysis.

RESULTS

BV2 murine microglial cells were morphologically activated and the expression of Iba1, an activation marker protein, was increased after MNPs@SiO2(RITC) treatment. Transmission electron microscopy analysis revealed lysosomal accumulation of MNPs@SiO2(RITC) and the formation of vesicle-like structures in MNPs@SiO2(RITC)-treated BV2 cells. The expression of several genes related to metabolism and inflammation were altered in 100 µg/ml MNPs@SiO2(RITC)-treated microglia when compared with that in non-treated (control) and 10 µg/ml MNPs@SiO2(RITC)-treated microglia. Combined transcriptome and amino acid profiling analyses revealed that the transport of serine family amino acids, including glycine, cysteine, and serine, was enhanced. However, only serine was increased in the growth medium of activated microglia; especially, excitotoxic D-serine secretion from primary rat microglia was the most strongly enhanced. Activated primary microglia reduced intracellular ATP levels and proteasome activity in cocultured neuronal cells, especially in primary cortical neurons, via D-serine secretion. Moreover, ubiquitinated proteins accumulated and inclusion bodies were increased in primary dopaminergic and cortical neurons cocultured with activated primary microglia. In vivo, MNPs@SiO2(RITC), D-serine, and ubiquitin aggresomes were distributed in the MNPs@SiO2(RITC)-treated mouse brain.

CONCLUSIONS

MNPs@SiO2(RITC)-induced activation of microglia triggers excitotoxicity in neurons via D-serine secretion, highlighting the importance of neurotoxicity mechanisms incurred by nanoparticle-induced microglial activation.

Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies

In recent years, multi-omic studies have enabled resolving community structure and interrogating community function of microbial communities. Simultaneous generation of metagenomic, metatranscriptomic, metaproteomic, and (meta) metabolomic data is more feasible than ever before, thus enabling in-depth assessment of community structure, function, and phenotype, thus resulting in a multitude of multi-omic microbiome datasets and the development of innovative methods to integrate and interrogate those multi-omic datasets. Specifically, the application of reference-independent approaches provides opportunities in identifying novel organisms and functions. At present, most of these large-scale multi-omic datasets stem from spatial sampling (e.g., water/soil microbiomes at several depths, microbiomes in/on different parts of the human anatomy) or case-control studies (e.g., cohorts of human microbiomes). We believe that longitudinal multi-omic microbiome datasets are the logical next step in microbiome studies due to their characteristic advantages in providing a better understanding of community dynamics, including: observation of trends, inference of causality, and ultimately, prediction of community behavior. Furthermore, the acquisition of complementary host-derived omics, environmental measurements, and suitable metadata will further enhance the aforementioned advantages of longitudinal data, which will serve as the basis to resolve drivers of community structure and function to understand the biotic and abiotic factors governing communities and specific populations. Carefully setup future experiments hold great potential to further unveil ecological mechanisms to evolution, microbe-microbe interactions, or microbe-host interactions. In this article, we discuss the challenges, emerging strategies, and best-practices applicable to longitudinal microbiome studies ranging from sampling, biomolecular extraction, systematic multi-omic measurements, reference-independent data integration, modeling, and validation.

Mantis: flexible and consensus-driven genome annotation

Background

The rapid development of the (meta-)omics fields has produced an unprecedented amount of high-resolution and high-fidelity data. Through the use of these datasets we can infer the role of previously functionally unannotated proteins from single organisms and consortia. In this context, protein function annotation can be described as the identification of regions of interest (i.e., domains) in protein sequences and the assignment of biological functions. Despite the existence of numerous tools, challenges remain in terms of speed, flexibility, and reproducibility. In the big data era, it is also increasingly important to cease limiting our findings to a single reference, coalescing knowledge from different data sources, and thus overcoming some limitations in overly relying on computationally generated data from single sources.

Results

We implemented a protein annotation tool, Mantis, which uses database identifiers intersection and text mining to integrate knowledge from multiple reference data sources into a single consensus-driven output. Mantis is flexible, allowing for the customization of reference data and execution parameters, and is reproducible across different research goals and user environments. We implemented a depth-first search algorithm for domain-specific annotation, which significantly improved annotation performance compared to sequence-wide annotation. The parallelized implementation of Mantis results in short runtimes while also outputting high coverage and high-quality protein function annotations.

Conclusions

Mantis is a protein function annotation tool that produces high-quality consensus-driven protein annotations. It is easy to set up, customize, and use, scaling from single genomes to large metagenomes. Mantis is available under the MIT license at https://github.com/PedroMTQ/mantis.

Updates on metaQuantome Software for Quantitative Metaproteomics

metaQuantome is a software suite that enables the quantitative analysis, statistical evaluation. and visualization of mass-spectrometry-based metaproteomics data. In the latest update of this software, we have provided several extensions, including a step-by-step training guide, the ability to perform statistical analysis on samples from multiple conditions, and a comparative analysis of metatranscriptomics data. The training module, accessed via the Galaxy Training Network, will help users to use the suite effectively both for functional as well as for taxonomic analysis. We extend the ability of metaQuantome to now perform multi-data-point quantitative and statistical analyses so that studies with measurements across multiple conditions, such as time-course studies, can be analyzed. With an eye on the multiomics analysis of microbial communities, we have also initiated the use of metaQuantome statistical and visualization tools on outputs from metatranscriptomics data, which complements the metagenomic and metaproteomic analyses already available. For this, we have developed a tool named MT2MQ ("metatranscriptomics to metaQuantome"), which takes in outputs from the ASaiM metatranscriptomics workflow and transforms them so that the data can be used as an input for comparative statistical analysis and visualization via metaQuantome. We believe that these improvements to metaQuantome will facilitate the use of the software for quantitative metaproteomics and metatranscriptomics and will enable multipoint data analysis. These improvements will take us a step toward integrative multiomic microbiome analysis so as to understand dynamic taxonomic and functional responses of these complex systems in a variety of biological contexts. The updated metaQuantome and MT2MQ are open-source software and are available via the Galaxy Toolshed and GitHub.

Metagenomic tools in microbial ecology research

Ability to directly sequence DNA from the environment permanently changed microbial ecology. Here, we review the new insights to microbial life gleaned from the applications of metagenomics, as well as the extensive set of analytical tools that facilitate exploration of diversity and function of complex microbial communities. While metagenomics is shaping our understanding of microbial functions in ecosystems via gene-centric and genome-centric methods, annotating functions, metagenome assembly and binning in heterogeneous samples remains challenging. Development of new analysis and sequencing platforms generating high-throughput long-read sequences and functional screening opportunities will aid in harnessing metagenomes to increase our understanding of microbial taxonomy, function, ecology, and evolution in the environment.