Metaproteomics of complex microbial communities in biogas plants

Microbiome modeling: a beginner's guide

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Biogas from lignocellulosic feedstock: current status and challenges

The organic wastes and residues generated from agricultural, industrial, and domestic activities have the potential to be converted to bioenergy. One such energy is biogas, which has already been included in rural areas as an alternative cooking energy source and agricultural activities. It is produced via anaerobic digestion of a wide range of organic nutrient sources and is an essential renewable energy source. The factors influencing biogas yield, i.e., the various substrate, their characteristics, pretreatment methods involved, different microbial types, sources, and inoculum properties, are analyzed. Furthermore, the optimization of these parameters, along with fermentation media optimization, such as optimum pH, temperature, and anaerobic digestion strategies, is discussed. Novel approaches of bioaugmentation, co-digestion, phase separation, co-supplementation, nanotechnology, and biorefinery approach have also been explored for biogas production. Finally, the current challenges and prospects of the process are discussed in the review.

Bioinformatic Workflows for Metaproteomics

The strong influence of microbiomes on areas such as ecology and human health has become widely recognized in the past years. Accordingly, various techniques for the investigation of the composition and function of microbial community samples have been developed. Metaproteomics, the comprehensive analysis of the proteins from microbial communities, allows for the investigation of not only the taxonomy but also the functional and quantitative composition of microbiome samples. Due to the complexity of the investigated communities, methods developed for single organism proteomics cannot be readily applied to metaproteomic samples. For this purpose, methods specifically tailored to metaproteomics are required. In this work, a detailed overview of current bioinformatic solutions and protocols in metaproteomics is given. After an introduction to the proteomic database search, the metaproteomic post-processing steps are explained in detail. Ten specific bioinformatic software solutions are focused on, covering various steps including database-driven identification and quantification as well as taxonomic and functional assignment.

Metaproteomic Analysis of Biogas Plants: A Complete Workflow from Lab to Bioinformatics

Metaproteomics represents a promising and fast method to analyze the taxonomic and functional composition of biogas plant microbiomes. However, metaproteomics sample preparation and bioinformatics analysis is still challenging due to the sample complexity and contaminants. In this chapter, a tailored workflow including sampling, phenol extraction in a ball mill, amido black protein quantification, FASP digestion, LC-MS/MS measurement as well as bioinformatics and biostatistical data evaluation are here described for the metaproteomics advancements applied to biogas plant samples.

Metaproteomics, metagenomics and 16S rRNA sequencing provide different perspectives on the aerobic granular sludge microbiome

The tremendous progress in sequencing technologies has made DNA sequencing routine for microbiome studies. Additionally, advances in mass spectrometric techniques have extended conventional proteomics into the field of microbial ecology. However, systematic studies that provide a better understanding of the complementary nature of these 'omics' approaches, particularly for complex environments such as wastewater treatment sludge, are urgently needed. Here, we describe a comparative metaomics study on aerobic granular sludge from three different wastewater treatment plants. For this, we employed metaproteomics, whole metagenome, and 16S rRNA amplicon sequencing to study the same granule material with uniform size. We furthermore compare the taxonomic profiles using the Genome Taxonomy Database (GTDB) to enhance the comparability between the different approaches. Though the major taxonomies were consistently identified in the different aerobic granular sludge samples, the taxonomic composition obtained by the different omics techniques varied significantly at the lower taxonomic levels, which impacts the interpretation of the nutrient removal processes. Nevertheless, as demonstrated by metaproteomics, the genera that were consistently identified in all techniques cover the majority of the protein biomass. The established metaomics data and the contig classification pipeline are publicly available, which provides a valuable resource for further studies on metabolic processes in aerobic granular sludge.

Proteomic analysis to unravel the biochemical mechanisms triggered by Bacillus toyonensis SFC 500-1E under chromium(VI) and phenol stress

Bacillus toyonensis SFC 500-1E is a member of the consortium SFC 500-1 able to remove Cr(VI) and simultaneously tolerate high phenol concentrations. In order to elucidate mechanisms utilized by this strain during the bioremediation process, the differential expression pattern of proteins was analyzed when it grew with or without Cr(VI) (10 mg/L) and Cr(VI) + phenol (10 and 300 mg/L), through two complementary proteomic approaches: gel-based (Gel-LC) and gel-free (shotgun) nanoUHPLC-ESI-MS/MS. A total of 400 differentially expressed proteins were identified, out of which 152 proteins were down-regulated under Cr(VI) and 205 up-regulated in the presence of Cr(VI) + phenol, suggesting the extra effort made by the strain to adapt itself and keep growing when phenol was also added. The major metabolic pathways affected include carbohydrate and energetic metabolism, followed by lipid and amino acid metabolism. Particularly interesting were also ABC transporters and the iron-siderophore transporter as well as transcriptional regulators that can bind metals. Stress-associated global response involving the expression of thioredoxins, SOS response, and chaperones appears to be crucial for the survival of this strain under treatment with both contaminants. This research not only provided a deeper understanding of B. toyonensis SFC 500-1E metabolic role in Cr(VI) and phenol bioremediation process but also allowed us to complete an overview of the consortium SFC 500-1 behavior. This may contribute to an improvement in its use as a bioremediation strategy and also provides a baseline for further research.

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics

The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters. Microbial communities were analyzed regarding their taxonomic composition, functional potential, as well as functions expressed on the proteome level. Different abundances of genes and enzymes related to the biogas process could be mostly attributed to different process parameters. Individual MAGs exhibiting different abundances in the digesters were studied in detail, and their roles in the hydrolysis, acidogenesis and acetogenesis steps of anaerobic digestion could be assigned. Methanoculleus thermohydrogenotrophicum was an active hydrogenotrophic methanogen in all three digesters, whereas Methanothermobacter wolfeii was more prevalent at higher process temperatures. Further analysis focused on MAGs, which were abundant in all digesters, indicating their potential to ensure biogas process stability. The most prevalent MAG belonged to the class Limnochordia; this MAG was ubiquitous in all three digesters and exhibited activity in numerous pathways related to different steps of AD.

Functional response of Acinetobacter guillouiae SFC 500-1A to tannery wastewater as revealed by a complementary proteomic approach

Acinetobacter guillouiae SFC 500-1 A is a promising candidate for the bioremediation of tannery wastewater. In this study, we applied shotgun proteomic technology in conjunction with a gel-based assay (Gel-LC) to explore the strain's intracellular protein profile when grown in tannery wastewater as opposed to normal culture conditions. A total of 1775 proteins were identified, 52 of which were unique to the tannery wastewater treatment. Many of them were connected to the degradation of aromatic compounds and siderophore biosynthesis. On the other hand, 1598 proteins overlapped both conditions but were differentially expressed in each. Those that were upregulated in wastewater (109) were involved in the processes mentioned above, as well as in oxidative stress mitigation and intracellular redox state regulation. Particularly interesting were the downregulated proteins under the same treatment (318), which were diverse but mainly linked to the regulation of basic cellular functions (replication, transcription, translation, cell cycle, and wall biogenesis); metabolism (amino acids, lipids, sulphate, energetic processes); and other more complex responses (cell motility, exopolysaccharide production, biofilm formation, and quorum sensing). The findings suggest that SFC 500-1 A engages in survival and stress management strategies to cope with the toxic effects of tannery wastewater, and that such strategies may be mostly oriented at keeping metabolic processes to a minimum. Altogether, the results might be useful in the near future to improve the strain's effectiveness if it will be applied for bioremediation.

Taxonomical composition and functional analysis of biofilms sampled from a nuclear storage pool

Sampling small amounts of biofilm from harsh environments such as the biofilm present on the walls of a radioactive material storage pool offers few analytical options if taxonomic characterization and estimation of the different biomass contributions are the objectives. Although 16S/18S rRNA amplification on extracted DNA and sequencing is the most widely applied method, its reliability in terms of quantitation has been questioned as yields can be species-dependent. Here, we propose a tandem-mass spectrometry proteotyping approach consisting of acquiring peptide data and interpreting then against a generalist database without any a priori. The peptide sequence information is transformed into useful taxonomical information that allows to obtain the different biomass contributions at different taxonomical ranks. This new methodology is applied for the first time to analyze the composition of biofilms from minute quantities of material collected from a pool used to store radioactive sources in a nuclear facility. For these biofilms, we report the identification of three genera, namely Sphingomonas, Caulobacter, and Acidovorax, and their functional characterization by metaproteomics which shows that these organisms are metabolic active. Differential expression of Gene Ontology GOslim terms between the two main microorganisms highlights their metabolic specialization.

In silico evaluation of a targeted metaproteomics strategy for broad screening of cellulolytic enzyme capacities in anaerobic microbiome bioreactors

Background

Microbial-driven solubilization of lignocellulosic material is a natural mechanism that is exploited in anaerobic digesters (ADs) to produce biogas and other valuable bioproducts. Glycoside hydrolases (GHs) are the main enzymes that bacterial and archaeal populations use to break down complex polysaccharides in these reactors. Methodologies for rapidly screening the physical presence and types of GHs can provide information about their functional activities as well as the taxonomical diversity within AD systems but are largely unavailable. Targeted proteomic methods could potentially be used to provide snapshots of the GHs expressed by microbial consortia in ADs, giving valuable insights into the functional lignocellulolytic degradation diversity of a community. Such observations would be essential to evaluate the hydrolytic performance of a reactor or potential issues with it.

Results

As a proof of concept, we performed an in silico selection and evaluation of groups of tryptic peptides from five important GH families derived from a dataset of 1401 metagenome-assembled genomes (MAGs) in anaerobic digesters. Following empirical rules of peptide-based targeted proteomics, we selected groups of shared peptides among proteins within a GH family while at the same time being unique compared to all other background proteins. In particular, we were able to identify a tractable unique set of peptides that were sufficient to monitor the range of GH families. While a few thousand peptides would be needed for comprehensive characterization of the main GH families, we found that at least 50% of the proteins in these families (such as the key families) could be tracked with only 200 peptides. The unique peptides selected for groups of GHs were found to be sufficient for distinguishing enzyme specificity or microbial taxonomy. These in silico results demonstrate the presence of specific unique GH peptides even in a highly diverse and complex microbiome and reveal the potential for development of targeted metaproteomic approaches in ADs or lignocellulolytic microbiomes. Such an approach could be valuable for estimating molecular-level enzymatic capabilities and responses of microbial communities to different substrates or conditions, which is a critical need in either building or utilizing constructed communities or defined cultures for bio-production.

Conclusions

This in silico study demonstrates the peptide selection strategy for quantifying relevant groups of GH proteins in a complex anaerobic microbiome and encourages the development of targeted metaproteomic approaches in fermenters. The results revealed that targeted metaproteomics could be a feasible approach for the screening of cellulolytic enzyme capacities for a range of anaerobic microbiome fermenters and thus could assist in bioreactor evaluation and optimization.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02125-x.

Anaeropeptidivorans aminofermentans gen. nov., sp. nov., a mesophilic proteolytic salt-tolerant bacterium isolated from a laboratory-scale biogas fermenter, and emended description of Clostridium colinum

An anaerobic bacterial strain, designated strain M3/9^T, was isolated from a laboratory-scale biogas fermenter fed with maize silage supplemented with 5 % wheat straw. Cells were straight, non-motile rods, which stained Gram-negative. Optimal growth occurred between 30 and 40°C, at pH 7.5-8.5, and up to 3.9 % (w/v) NaCl was tolerated. When grown on peptone from casein and soymeal, strain M3/9^T produced mainly acetic acid, ethanol, and isobutyric acid. The major cellular fatty acids of the novel strain were C_16 : 0 and C_16 : 0 DMA. The genome of strain M3/9^T is 3757  330 bp in size with a G+C content of 38.45 mol%. Phylogenetic analysis allocated strain M3/9^T within the family Lachnospiraceae with Clostridium colinum DSM 6011^T and Anaerotignum lactatifermentans DSM 14214^T being the most closely related species sharing 57.86 and 56.99% average amino acid identity and 16S rRNA gene sequence similarities of 91.58 and 91.26 %, respectively. Based on physiological, chemotaxonomic and genetic data, we propose the description of a novel species and genus Anaeropeptidivorans aminofermentans gen. nov., sp. nov., represented by the type strain M3/9^T (=DSM 100058^T=LMG 29527^T). In addition, an emended description of Clostridium colinum is provided.

Comparative Proteomic Analysis of an Ethyl Tert-Butyl Ether-Degrading Bacterial Consortium

A bacterial consortium capable of degrading ethyl tert-butyl ether (ETBE) as a sole carbon source was enriched and isolated from gasoline-contaminated water. Arthrobacter sp., Herbaspirillum sp., Pseudacidovorax sp., Pseudomonas sp., and Xanthomonas sp. were identified as the initial populations with the 16S rDNA analysis. The consortium aerobically degraded 49% of 50 mg/L of ETBE, in 6 days. The ETBE degrading efficiency of the consortium increased to 98% even with the higher concentrations of ETBE (1000 mg/L) in the subsequent subcultures, which accumulated tert-butyl alcohol (TBA). Xanthomonas sp. and Pseudomonas sp. were identified as the predominant ETBE degrading populations in the final subculture. The metaproteome of the ETBE-grown bacterial consortium was compared with the glucose-grown bacterial consortium, using 2D-DIGE. Proteins related to the ETBE metabolism, stress response, carbon metabolism and chaperones were found to be abundant in the presence of ETBE while proteins related to cell division were less abundant. The metaproteomic study revealed that the ETBE does have an effect on the metabolism of the bacterial consortium. It also enabled us to understand the responses of the complex bacterial consortium to ETBE, thus revealing interesting facts about the ETBE degrading bacterial community.

Impact of innovative nanoadditives on biodigesters microbiome

Nanoparticles (NPs) supplementation to biodigesters improves the digestibility of biowaste and the generation of biogas. This study investigates the impact of innovative nanoadditives on the microbiome of biodigesters. Fresh cow manure was anaerobically incubated in a water bath under mesophilic conditions for 30 days. Three different NPs (zinc ferrite, zinc ferrite with 10% carbon nanotubes and zinc ferrite with 10% C76 fullerene) were separately supplemented to the biodigesters at the beginning of the incubation period. Methane and hydrogen production were monitored daily. Manure samples were collected from the digesters at different time points and the microbial communities inside the biodigesters were investigated via real-time PCR and 16 S rRNA gene amplicon-sequencing. The results indicate that zinc ferrite NPs enhanced biogas production the most. The microbial community was significantly affected by NPs addition in terms of archaeal and bacterial 16 S rRNAgene copy numbers. The three ZF formulations NPs augmented the abundance of members within the hydrogenotrophic methanogenic phyla Methanobacteriaceae. While Methanomassiliicoccacaea were enriched in ZF/C76 supplemented biodigester due to a significant increase in hydrogen partial pressure, probably caused by the enrichment of Spirochaetaceae (genus Treponema). Overall, NPs supplementation significantly enriched acetate-producing members within Hungateiclostridiaceae in ZF/CNTs, Dysgonomonadaceae in ZF and Spirochaetaceae ZF/C76 biodigesters.

Adaptation of a microbial community to demand-oriented biological methanation

BACKGROUND

Biological conversion of the surplus of renewable electricity and carbon dioxide (CO₂) from biogas plants to biomethane (CH₄) could support energy storage and strengthen the power grid. Biological methanation (BM) is linked closely to the activity of biogas-producing Bacteria and methanogenic Archaea. During reactor operations, the microbiome is often subject to various changes, e.g., substrate limitation or pH-shifts, whereby the microorganisms are challenged to adapt to the new conditions. In this study, various process parameters including pH value, CH₄ production rate, conversion yields and final gas composition were monitored for a hydrogenotrophic-adapted microbial community cultivated in a laboratory-scale BM reactor. To investigate the robustness of the BM process regarding power oscillations, the biogas microbiome was exposed to five hydrogen (H₂)-feeding regimes lasting several days.

RESULTS

Applying various "on-off" H₂-feeding regimes, the CH₄ production rate recovered quickly, demonstrating a significant resilience of the microbial community. Analyses of the taxonomic composition of the microbiome revealed a high abundance of the bacterial phyla Firmicutes, Bacteroidota and Thermotogota followed by hydrogenotrophic Archaea of the phylum Methanobacteriota. Homo-acetogenic and heterotrophic fermenting Bacteria formed a complex food web with methanogens. The abundance of the methanogenic Archaea roughly doubled during discontinuous H₂-feeding, which was related mainly to an increase in acetoclastic Methanothrix species. Results also suggested that Bacteria feeding on methanogens could reduce overall CH₄ production. On the other hand, using inactive biomass as a substrate could support the growth of methanogenic Archaea. During the BM process, the additional production of H₂ by fermenting Bacteria seemed to support the maintenance of hydrogenotrophic methanogens at non-H₂-feeding phases. Besides the elusive role of Methanothrix during the H₂-feeding phases, acetate consumption and pH maintenance at the non-feeding phase can be assigned to this species.

CONCLUSIONS

Taken together, the high adaptive potential of microbial communities contributes to the robustness of BM processes during discontinuous H₂-feeding and supports the commercial use of BM processes for energy storage. Discontinuous feeding strategies could be used to enrich methanogenic Archaea during the establishment of a microbial community for BM. Both findings could contribute to design and improve BM processes from lab to pilot scale.

New opportunities in plant microbiome engineering for increasing agricultural sustainability under stressful conditions

Plant microbiome (or phytomicrobiome) engineering (PME) is an anticipated untapped alternative strategy that could be exploited for plant growth, health and productivity under different environmental conditions. It has been proven that the phytomicrobiome has crucial contributions to plant health, pathogen control and tolerance under drastic environmental (a)biotic constraints. Consistent with plant health and safety, in this article we address the fundamental role of plant microbiome and its insights in plant health and productivity. We also explore the potential of plant microbiome under environmental restrictions and the proposition of improving microbial functions that can be supportive for better plant growth and production. Understanding the crucial role of plant associated microbial communities, we propose how the associated microbial actions could be enhanced to improve plant growth-promoting mechanisms, with a particular emphasis on plant beneficial fungi. Additionally, we suggest the possible plant strategies to adapt to a harsh environment by manipulating plant microbiomes. However, our current understanding of the microbiome is still in its infancy, and the major perturbations, such as anthropocentric actions, are not fully understood. Therefore, this work highlights the importance of manipulating the beneficial plant microbiome to create more sustainable agriculture, particularly under different environmental stressors.

Identification of Extracellular Key Enzyme and Intracellular Metabolic Pathway in Alginate-Degrading Consortia via an Integrated Metaproteomic/Metagenomic Analysis

Uronic acid in extracellular polymeric substances is a primary but often ignored factor related to the difficult hydrolysis of waste-activated sludge (WAS), with alginate as a typical polymer. Previously, we enriched alginate-degrading consortia (ADC) in batch reactors that can enhance methane production from WAS, but the enzymes and metabolic pathway are not well documented. In this work, two chemostats in series were operated to enrich ADC, in which 10 g/L alginate was wholly consumed. Based on it, the extracellular alginate lyase (∼130 kD, EC 4.2.2.3) in the cultures was identified by metaproteomic analysis. This enzyme offers a high specificity to convert alginate to disaccharides over other mentioned hydrolases. Genus Bacteroides (>60%) was revealed as the key bacterium for alginate conversion. A new Entner-Doudoroff pathway of alginate via 5-dehydro-4-deoxy-d-glucuronate (DDG) and 3-deoxy-d-glycerol-2,5-hexdiulosonate (DGH) as the intermediates to 2-keto-3-deoxy-gluconate (KDG) was constructed based on the metagenomic and metaproteomic analysis. In summary, this work documented the core enzymes and metabolic pathway for alginate degradation, which provides a good paradigm when analyzing the degrading mechanism of unacquainted substrates. The outcome will further contribute to the application of Bacteroides-dominated ADC on WAS methanogenesis in the future.

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.

Integrated Metagenomic and Metaproteomic Analyses Unravel Ammonia Toxicity to Active Methanogens and Syntrophs, Enzyme Synthesis, and Key Enzymes in Anaerobic Digestion

During anaerobic digestion, the active microbiome synthesizes enzymes by transcription and translation, and then enzymes catalyze multistep bioconversions of substrates before methane being produced. However, little information is available on how ammonia affects truly active microbes containing the expressed enzymes, enzyme synthesis, and key enzymes. In this study, an integrated metagenomic and metaproteomic investigation showed that ammonia suppressed not only the obligate acetotrophic methanogens but also the syntrophic propionate and butyrate oxidation taxa and their assistant bacteria (genus Desulfovibrio), which declined the biotransformations of propionate and butyrate → acetate → methane. Although the total population of the hydrolyzing and acidifying bacteria was not affected by ammonia, the bacteria with ammonia resistance increased. Our study also revealed that ammonia restrained the enzyme synthesis process by inhibiting the RNA polymerase (subunits A' and D) during transcription and the ribosome (large (L3, L12, L13, L22, and L25) and small (S3, S3Ae, and S7) ribosomal subunits) and aminoacyl-tRNA synthesis (aspartate-tRNA synthetase) in translation. Further investigation suggested that methylmalonyl-CoA mutase, acetyl-CoA C-acetyltransferase, and CH₃-CoM reductase, which regulate propionate and butyrate oxidation and acetoclastic methanation, were significantly downregulated by ammonia. This study provides intrinsic insights into the fundamental mechanisms of how ammonia inhibits anaerobic digestion.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.

A review of mechanisms underlying the impacts of (nano)microplastics on anaerobic digestion

The presence of (nano)microplastics in domestic wastewater and their subsequent release to the aquatic environment via the discharge of treated sewage has raised significant concerns. Previous studies have also identified their excessive accumulation in sewage sludge. Anaerobic digestion is one of the most used sludge stabilization methods in wastewater treatment plants. Therefore, understanding the potential effects of (nano)microplastics on anaerobic digestion has been receiving increasing attention from researchers. This article provides a comprehensive review of mechanisms underlying the impacts of (nano)microplastics on anaerobic digestion. Notably, this review covers mechanisms of inhibition/enhancement of anaerobic digestion by (nano)microplastics and their potential impacts on biochemical pathways, key enzymes, functional genes, and microbial communities investigated to date. Moreover, potential environmental risks of biosolids contaminated with (nano)microplastics were highlighted. Finally, knowledge gaps and future research needs were outlined. This review will guide more standardized studies in the future, covering both fundamental and engineering aspects.

Molecular Microbial Community Analysis as an Analysis Tool for Optimal Biogas Production

The microbial diversity in anaerobic digestion (AD) is important because it affects process robustness. High-throughput sequencing offers high-resolution data regarding the microbial diversity and robustness of biological systems including AD; however, to understand the dynamics of microbial processes, knowing the microbial diversity is not adequate alone. Advanced meta-omic techniques have been established to determine the activity and interactions among organisms in biological processes like AD. Results of these methods can be used to identify biomarkers for AD states. This can aid a better understanding of system dynamics and be applied to producing comprehensive models for AD. The paper provides valuable knowledge regarding the possibility of integration of molecular methods in AD. Although meta-genomic methods are not suitable for on-line use due to long operating time and high costs, they provide extensive insight into the microbial phylogeny in AD. Meta-proteomics can also be explored in the demonstration projects for failure prediction. However, for these methods to be fully realised in AD, a biomarker database needs to be developed.

The Role of Petrimonas mucosa ING2-E5AT in Mesophilic Biogas Reactor Systems as Deduced from Multiomics Analyses

Members of the genera Proteiniphilum and Petrimonas were speculated to represent indicators reflecting process instability within anaerobic digestion (AD) microbiomes. Therefore, Petrimonas mucosa ING2-E5AT was isolated from a biogas reactor sample and sequenced on the PacBio RSII and Illumina MiSeq sequencers. Phylogenetic classification positioned the strain ING2-E5AT in close proximity to Fermentimonas and Proteiniphilum species (family Dysgonomonadaceae). ING2-E5AT encodes a number of genes for glycosyl-hydrolyses (GH) which are organized in Polysaccharide Utilization Loci (PUL) comprising tandem susCD-like genes for a TonB-dependent outer-membrane transporter and a cell surface glycan-binding protein. Different GHs encoded in PUL are involved in pectin degradation, reflecting a pronounced specialization of the ING2-E5AT PUL systems regarding the decomposition of this polysaccharide. Genes encoding enzymes participating in amino acids fermentation were also identified. Fragment recruitments with the ING2-E5AT genome as a template and publicly available metagenomes of AD microbiomes revealed that Petrimonas species are present in 146 out of 257 datasets supporting their importance in AD microbiomes. Metatranscriptome analyses of AD microbiomes uncovered active sugar and amino acid fermentation pathways for Petrimonas species. Likewise, screening of metaproteome datasets demonstrated expression of the Petrimonas PUL-specific component SusC providing further evidence that PUL play a central role for the lifestyle of Petrimonas species.

Impact of feeding and stirring regimes on the internal stratification of microbial communities in the fermenter of anaerobic digestion plants

In anaerobic digestion plants (ADs), homogenization of the feed, fermenter content and microbial communities is crucial for efficient and robust biogas production. However, mixing also requires a significant amount of energy. For an 850 m³ agricultural AD equipped with eight sampling ports, we investigated whether different feeding and stirring regimes enable a sufficient homogenization of the microbial community using metaproteomics and terminal restriction fragment length polymorphism (TRFLP) analysis. Systematic comparison of samples taken at the top and the bottom as well as at the rim and the center of the AD using scatter plots and students t-test revealed only a small number of differences in metaproteins, taxonomies and biological processes. Obviously, the applied stirring and feeding conditions were sufficient to largely homogenize the content of the AD.

Transition of microbial communities and degradation pathways in anaerobic digestion at decreasing retention time

Tuning of operational variables is a common practice to control the anaerobic digestion process and, in advanced applications, to promote the accumulation of fermentation products. However, process variables are interrelated. In this study, the hydraulic retention time (HRT) was decoupled from the organic loading rate (OLR) in order to isolate the effect of HRT as a selective pressure on: process performance, metabolic rates (hydrolytic, acetogenic, and methanogenic) and the microbial community. Four mesophilic anaerobic digesters were subjected to a sequential decrease in HRT from 15 to 8, 4 and 2 days while keeping the OLR constant at chemical oxygen demand of 1 gCOD L _r^-1 d^-1. The results showed that HRT alone was insufficient to washout methanogens from the digesters, which in turn prevented the accumulation of volatile fatty acids (VFA). Methanosaeta was the dominant genus in the four digesters at all HRTs. Metabolic rates showed that process performance was controlled by hydrolysis, with a clear shift in acetogenic rates, from butyrate and propionate degradation to ethanol degradation at 4 and 2d HRT. The change in acetogenic pathways was attributed to a shift in the fermentation pathways co-current with changes in fermentative bacteria. At 2d HRT, biofilm was formed on the walls and paddles of the digesters, probably as a survival strategy. Most of the taxa in the biofilm were also present in the digester media. Overall, it is the combination of HRT with other operational parameters which promotes the washout of methanogens and the accumulation of VFA.

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.

Function is what counts: how microbial community complexity affects species, proteome and pathway coverage in metaproteomics

Introduction: Metaproteomics is an established method to obtain a comprehensive taxonomic and functional view of microbial communities. After more than a decade, we are now able to describe the promise, reality, and perspectives of metaproteomics and provide useful information about the choice of method, applications, and potential improvement strategies.Areas covered: In this article, we will discuss current challenges of species and proteome coverage, and also highlight functional aspects of metaproteomics analysis of microbial communities with different levels of complexity. To do this, we re-analyzed data from microbial communities with low to high complexity (8, 72, 200 and >300 species). High species diversity leads to a reduced number of protein group identifications in a complex community, and thus the number of species resolved is underestimated. Ultimately, low abundance species remain undiscovered in complex communities. However, we observed that the main functional categories were better represented within complex microbiomes when compared to species coverage.Expert opinion: Our findings showed that even with low species coverage, metaproteomics has the potential to reveal habitat-specific functional features. Finally, we exploit this information to highlight future research avenues that are urgently needed to enhance our understanding of taxonomic composition and functions of complex microbiomes.

Impact of process temperature and organic loading rate on cellulolytic / hydrolytic biofilm microbiomes during biomethanation of ryegrass silage revealed by genome-centered metagenomics and metatranscriptomics

BACKGROUND

Anaerobic digestion (AD) of protein-rich grass silage was performed in experimental two-stage two-phase biogas reactor systems at low vs. increased organic loading rates (OLRs) under mesophilic (37 °C) and thermophilic (55 °C) temperatures. To follow the adaptive response of the biomass-attached cellulolytic/hydrolytic biofilms at increasing ammonium/ammonia contents, genome-centered metagenomics and transcriptional profiling based on metagenome assembled genomes (MAGs) were conducted.

RESULTS

In total, 78 bacterial and archaeal MAGs representing the most abundant members of the communities, and featuring defined quality criteria were selected and characterized in detail. Determination of MAG abundances under the tested conditions by mapping of the obtained metagenome sequence reads to the MAGs revealed that MAG abundance profiles were mainly shaped by the temperature but also by the OLR. However, the OLR effect was more pronounced for the mesophilic systems as compared to the thermophilic ones. In contrast, metatranscriptome mapping to MAGs subsequently normalized to MAG abundances showed that under thermophilic conditions, MAGs respond to increased OLRs by shifting their transcriptional activities mainly without adjusting their proliferation rates. This is a clear difference compared to the behavior of the microbiome under mesophilic conditions. Here, the response to increased OLRs involved adjusting of proliferation rates and corresponding transcriptional activities. The analysis led to the identification of MAGs positively responding to increased OLRs. The most outstanding MAGs in this regard, obviously well adapted to higher OLRs and/or associated conditions, were assigned to the order Clostridiales (Acetivibrio sp.) for the mesophilic biofilm and the orders Bacteroidales (Prevotella sp. and an unknown species), Lachnospirales (Herbinix sp. and Kineothrix sp.) and Clostridiales (Clostridium sp.) for the thermophilic biofilm. Genome-based metabolic reconstruction and transcriptional profiling revealed that positively responding MAGs mainly are involved in hydrolysis of grass silage, acidogenesis and / or acetogenesis.

CONCLUSIONS

An integrated -omics approach enabled the identification of new AD biofilm keystone species featuring outstanding performance under stress conditions such as increased OLRs. Genome-based knowledge on the metabolic potential and transcriptional activity of responsive microbiome members will contribute to the development of improved microbiological AD management strategies for biomethanation of renewable biomass.

Co-digestion of harvested microalgae and primary sludge in a mesophilic anaerobic membrane bioreactor (AnMBR): Methane potential and microbial diversity

Anaerobic co-digestion of primary sludge and raw microalgae (Scenedesmus and Chlorella) was performed in a lab-scale semi-continuous anaerobic membrane bioreactor to assess the biological performance and identify the microbial community involved in the co-digestion process. The reactor was operated at 35 °C for 440 days, working at a solids retention time of 100 days. The system achieved 73% biodegradability and showed high stability in terms of pH and volatile fatty acids. An enriched microbial community was observed. Of the several phyla, Chloroflexi and Proteobacteria were the most abundant. Cellulose-degraders phyla (Bacteroidetes, Chloroflexi and Thermotogae) were detected. Syntrophic microorganisms played an important role in intermediate degradation, enhancing methane production, mainly carried out by Methanosaeta. A nutrient-rich effluent (400 mg NH₄-N·L^-1 and 29 mg PO₄-P·L^-1) and digestate (860 mg N·L^-1 and 151 mg P·L^-1) were obtained. The bio-nutrients released from anaerobic co-digestion could be reused for microalgae cultivation or agricultural applications.

The microbiome driving anaerobic digestion and microbial analysis

The microbiome residing in anaerobic digesters drives the anaerobic digestion (AD) process to convert various feedstocks to biogas as a renewable source of energy. This microbiome has been investigated in numerous studies in the last century. The early studies used cultivation-based methods and analysis to identify the four guilds (or functional groups) of microorganisms. Molecular biology techniques overcame the limitations of cultivation-based methods and allowed the identification of unculturable microorganisms, revealing the high diversity of microorganisms involved in AD. In the past decade, omics technologies, including metataxonomics, metagenomics, metatranscriptomics, metaproteomics, and metametabolomics, have been or start to be used in comprehensive analysis and studies of biogas-producing microbiomes. In this chapter, we reviewed the utilities and limitations of these analysis methods, techniques, and technologies when they were used in studies of biogas-producing microbiomes, as well as the new information on diversity, composition, metabolism, and syntrophic interactions of biogas-producing microbiomes. We also discussed the current knowledge gaps and the research needed to further improve AD efficiency and stability.

Immediate Effects of Ammonia Shock on Transcription and Composition of a Biogas Reactor Microbiome

The biotechnological process of biogas production from organic material is carried out by a diverse microbial community under anaerobic conditions. However, the complex and sensitive microbial network present in anaerobic degradation of organic material can be disturbed by increased ammonia concentration introduced into the system by protein-rich substrates and imbalanced feeding. Here, we report on a simulated increase of ammonia concentration in a fed batch lab-scale biogas reactor experiment. Two treatment conditions were used simulating total ammonia nitrogen concentrations of 4.9 and 8.0 g/L with four replicate reactors. Each reactor was monitored concerning methane generation and microbial composition using 16S rRNA gene amplicon sequencing, while the transcriptional activity of the overall process was investigated by metatranscriptomic analysis. This allowed investigating the response of the microbial community in terms of species composition and transcriptional activity to a rapid upshift to high ammonia conditions. Clostridia and Methanomicrobiales dominated the microbial community throughout the entire experiment under both experimental conditions, while Methanosarcinales were only present in minor abundance. Transcription analysis demonstrated clostridial dominance with respect to genes encoding for enzymes of the hydrolysis step (cellulase, EC 3.2.1.4) as well as dominance of key genes for enzymes of the methanogenic pathway (methyl-CoM reductase, EC 2.8.4.1; heterodisulfide reductase, EC 1.8.98.1). Upon ammonia shock, the selected marker genes showed significant changes in transcriptional activity. Cellulose hydrolysis as well as methanogenesis were significantly reduced at high ammonia concentrations as indicated by reduced transcription levels of the corresponding genes. Based on these experiments we concluded that, apart from the methanogenic archaea, hydrolytic cellulose-degrading microorganisms are negatively affected by high ammonia concentrations. Further, Acholeplasma and Erysipelotrichia showed lower abundance under increased ammonia concentrations and thus might serve as indicator species for an earlier detection in order to counteract against ammonia crises.

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.

Challenges and promise at the interface of metaproteomics and genomics: an overview of recent progress in metaproteogenomic data analysis

INTRODUCTION

The study of microbial communities based on the combined analysis of genomic and proteomic data - called metaproteogenomics - has gained increased research attention in recent years. This relatively young field aims to elucidate the functional and taxonomic interplay of proteins in microbiomes and its implications on human health and the environment. Areas covered: This article reviews bioinformatics methods and software tools dedicated to the analysis of data from metaproteomics and metaproteogenomics experiments. In particular, it focuses on the creation of tailored protein sequence databases, on the optimal use of database search algorithms including methods of error rate estimation, and finally on taxonomic and functional annotation of peptide and protein identifications. Expert opinion: Recently, various promising strategies and software tools have been proposed for handling typical data analysis issues in metaproteomics. However, severe challenges remain that are highlighted and discussed in this article; these include: (i) robust false-positive assessment of peptide and protein identifications, (ii) complex protein inference against a background of highly redundant data, (iii) taxonomic and functional post-processing of identification data, and finally, (iv) the assessment and provision of metrics and tools for quantitative analysis.

Metaproteome analysis reveals that syntrophy, competition, and phage-host interaction shape microbial communities in biogas plants

BACKGROUND

In biogas plants, complex microbial communities produce methane and carbon dioxide by anaerobic digestion of biomass. For the characterization of the microbial functional networks, samples of 11 reactors were analyzed using a high-resolution metaproteomics pipeline.

RESULTS

Examined methanogenesis archaeal communities were either mixotrophic or strictly hydrogenotrophic in syntrophy with bacterial acetate oxidizers. Mapping of identified metaproteins with process steps described by the Anaerobic Digestion Model 1 confirmed its main assumptions and also proposed some extensions such as syntrophic acetate oxidation or fermentation of alcohols. Results indicate that the microbial communities were shaped by syntrophy as well as competition and phage-host interactions causing cell lysis. For the families Bacillaceae, Enterobacteriaceae, and Clostridiaceae, the number of phages exceeded up to 20-fold the number of host cells.

CONCLUSION

Phage-induced cell lysis might slow down the conversion of substrates to biogas, though, it could support the growth of auxotrophic microbes by cycling of nutrients.

A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures

The soil microbiome is inherently complex with high biological diversity, and spatial heterogeneity typically occurring on the submillimetre scale. To study the microbial ecology of soils, and other microbiomes, biomolecules, that is, nucleic acids and proteins, must be efficiently and reliably co-recovered from the same biological samples. Commercial kits are currently available for the co-extraction of DNA, RNA and proteins but none has been developed for soil samples. We present a new protocol drawing on existing phenol-chloroform-based methods for nucleic acids co-extraction but incorporating targeted precipitation of proteins from the phenol phase. The protocol is cost-effective and robust, and easily implemented using reagents commonly available in laboratories. The method is estimated to be eight times cheaper than using disparate commercial kits for the isolation of DNA and/or RNA, and proteins, from soil. The method is effective, providing good quality biomolecules from a diverse range of soil types, with clay contents varying from 9.5% to 35.1%, which we successfully used for downstream, high-throughput gene sequencing and metaproteomics. Additionally, we demonstrate that the protocol can also be easily implemented for biomolecule co-extraction from other complex microbiome samples, including cattle slurry and microbial communities recovered from anaerobic bioreactors, as well as from Gram-positive and Gram-negative pure cultures.

Long-term investigation of microbial community composition and transcription patterns in a biogas plant undergoing ammonia crisis

Ammonia caused disturbance of biogas production is one of the most frequent incidents in regular operation of biogas reactors. This study provides a detailed insight into the microbial community of a mesophilic, full-scale biogas reactor (477 kWh h-1 ) fed with maize silage, dried poultry manure and cow manure undergoing initial process disturbance by increased ammonia concentration. Over a time period of 587 days, the microbial community of the reactor was regularly monitored on a monthly basis by high-throughput amplicon sequencing of the archaeal and bacterial 16S rRNA genes. During this sampling period, the total ammonia concentrations varied between 2.7 and 5.8 g l-1 [NH4 + -N]. To gain further inside into the active metabolic pathways, for selected time points metatranscriptomic shotgun analysis was performed allowing the quantification of marker genes for methanogenesis, hydrolysis and syntrophic interactions. The results obtained demonstrated a microbial community typical for a mesophilic biogas plant. However in response to the observed changing process conditions (e.g. increasing NH4 + levels, changing feedstock composition), the microbial community reacted highly flexible by changing and adapting the community composition. The Methanosarcina-dominated archaeal community was shifted to a Methanomicrobiales-dominated archaeal community in the presence of increased ammonia conditions. A similar trend as in the phylogenetic composition was observed in the transcription activity of genes coding for enzymes involved in acetoclastic methanogenesis and syntrophic acetate oxidations (Codh/Acs and Fthfs). In accordance, Clostridia simultaneously increased under elevated ammonia concentrations in abundance and were identified as the primary syntrophic interaction partner with the now Methanomicrobiales-dominated archaeal community. In conclusion, overall stable process performance was maintained during increased ammonia concentration in the studied reactor based on the microbial communities' ability to flexibly respond by reorganizing the community composition while remaining functionally stable.

Development and characterization of stable anaerobic thermophilic methanogenic microbiomes fermenting switchgrass at decreasing residence times

BACKGROUND

Anaerobic fermentation of lignocellulose occurs in both natural and managed environments, and is an essential part of the carbon cycle as well as a promising route to sustainable production of fuels and chemicals. Lignocellulose solubilization by mixed microbiomes is important in these contexts.

RESULTS

Here, we report the development of stable switchgrass-fermenting enrichment cultures maintained at various residence times and moderately high (55 °C) temperatures. Anaerobic microbiomes derived from a digester inoculum were incubated at 55 °C and fed semi-continuously with medium containing 30 g/L mid-season harvested switchgrass to achieve residence times (RT) of 20, 10, 5, and 3.3 days. Stable, time-invariant cellulolytic methanogenic cultures with minimal accumulation of organic acids were achieved for all RTs. Fractional carbohydrate solubilization was 0.711, 0.654, 0.581 and 0.538 at RT = 20, 10, 5 and 3.3 days, respectively, and glucan solubilization was proportional to xylan solubilization at all RTs. The rate of solubilization was described well by the equation r = k(C - C₀f_r), where C represents the concentration of unutilized carbohydrate, C₀ is the concentration of carbohydrate (cellulose and hemicellulose) entering the bioreactor and f_r is the extrapolated fraction of entering carbohydrate that is recalcitrant at infinite residence time. The 3.3 day RT is among the shortest RT reported for stable thermophilic, methanogenic digestion of a lignocellulosic feedstock. 16S rDNA phylotyping and metagenomic analyses were conducted to characterize the effect of RT on community dynamics and to infer functional roles in the switchgrass to biogas conversion to the various microbial taxa. Firmicutes were the dominant phylum, increasing in relative abundance from 54 to 96% as RT decreased. A Clostridium clariflavum strain with genetic markers for xylose metabolism was the most abundant lignocellulose-solubilizing bacterium. A Thermotogae (Defluviitoga tunisiensis) was the most abundant bacterium in switchgrass digesters at RT = 20 days but decreased in abundance at lower RTs as did multiple Chloroflexi. Synergistetes and Euryarchaeota were present at roughly constant levels over the range of RTs examined.

CONCLUSIONS

A system was developed in which stable methanogenic steady-states were readily obtained with a particulate biomass feedstock, mid-season switchgrass, at laboratory (1 L) scale. Characterization of the extent and rate of carbohydrate solubilization in combination with 16S rDNA and metagenomic sequencing provides a multi-dimensional view of performance, species composition, glycoside hydrolases, and metabolic function with varying residence time. These results provide a point of reference and guidance for future studies and organism development efforts involving defined cultures.

SDS-PAGE fractionation to increase metaproteomic insight into the taxonomic and functional composition of microbial communities for biogas plant samples

Metaproteomics represent an important tool for the taxonomic and functional investigation of microbial communities in humans, environment, and technical applications. Due to the high complexity of the microbial communities, protein, and peptide fractionation is applied to improve the characterization of taxonomic and functional composition of microbial communities. In order to target scientific questions regarding taxonomic and functional composition adequately, a tradeoff between the number of fractions analyzed and the required depth of information has to be found. Two samples of a biogas plant were analyzed by either single LC-MS/MS measurement (1D) or LC-MS/MS measurements of fractions obtained after SDS-PAGE (2D) separation. Fractionation with SDS-PAGE increased the number of identified spectra by 273%, the number of peptides by 95%, and the number of metaproteins by 59%. Rarefaction plots of species and metaproteins against identified spectra showed that 2D separation was sufficient to identify most microbial families but not all metaproteins. More reliable quantitative comparison could be achieved with 2D. 1D separation enabled high-throughput analysis of samples, however, depth in functional descriptions and reliability of quantification were lost. Nevertheless, the proteotyping of multiple samples was still possible. 2D separations provided more reliable quantitative data combined with a deeper insight into the taxonomic and functional composition of the microbial communities. Regarding taxonomic and functional composition, metaproteomics based on 2D is just the tip of an iceberg.

Challenges and Approaches in Microbiome Research: From Fundamental to Applied

We face major agricultural challenges that remain a threat for global food security. Soil microbes harbor enormous potentials to provide sustainable and economically favorable solutions that could introduce novel approaches to improve agricultural practices and, hence, crop productivity. In this review we give an overview regarding the current state-of-the-art of microbiome research by discussing new technologies and approaches. We also provide insights into fundamental microbiome research that aim to provide a deeper understanding of the dynamics within microbial communities, as well as their interactions with different plant hosts and the environment. We aim to connect all these approaches with potential applications and reflect how we can use microbial communities in modern agricultural systems to realize a more customized and sustainable use of valuable resources (e.g., soil).

Characteristics of adapted hydrogenotrophic community during biomethanation

The results presented in this study were carried out as concomitant experiments during the start-up and operation of a biomethanation unit to evaluate the effect of process parameters on carbon conversion, product formation (methane and acetate) and community composition. For that, two different samples were withdrawn from a trickle-bed reactor with immobilized enrichment culture of hydrogenotrophic methanogens adapted from sewage sludge. One sample was taken from the recirculation liquid during start-up phase while the other was withdrawn directly from the carrier material in the reactor. Elevated acid levels especially during start-up were shown to affect the overall carbon conversion. This effect was also seen during the acid tolerance testing reported here. Final acid concentrations of 1.6±0.3g/L resulted in a reduced conversion ratio of only 46%. Without acid addition complete conversion of CO₂ in the headspace was achieved. However, maximum methane production of 0.55±0.02mmol after 4days of incubation was monitored at moderate initial acetate concentration of 0.4g/L. In both analyzed inoculation materials Methanobacterium species were by far the most dominant Archaea with 21.8% in the recirculation liquid during start-up and 84.8% in the enrichment culture immobilized on the carrier material. The microbial composition of the two analyzed samples is in accordance with the results obtained for the carbon conversion and product formation. With approximately 50% of Bacteroidetes and Firmicutes present during reactor start-up the acetic acid production significantly contributed to the overall carbon conversion. In contrast, methane was produced almost exclusively in trials representing continuous operation where acetogenic bacteria accounted only up to 17.5%. In summary, the acid accumulation monitored during reactor start-up of a biomethanation unit is most likely to result from the microbial composition present. Nevertheless, complete adaptation to hydrogenotrophic conditions was proven to alter the consortium and yield methane as main product alongside high carbon conversion of up to 70.5±1.8%.

Challenges and perspectives of metaproteomic data analysis

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.

Metaproteomics-guided selection of targeted enzymes for bioprospecting of mixed microbial communities

BACKGROUND

Hitherto, the main goal of metaproteomic analyses has been to characterize the functional role of particular microorganisms in the microbial ecology of various microbial communities. Recently, it has been suggested that metaproteomics could be used for bioprospecting microbial communities to query for the most active enzymes to improve the selection process of industrially relevant enzymes. In the present study, to reduce the complexity of metaproteomic samples for targeted bioprospecting of novel enzymes, a microbial community capable of producing cellulases was maintained on a chemically defined medium in an enzyme suppressed metabolic steady state. From this state, it was possible to specifically and distinctively induce the desired cellulolytic activity. The extracellular fraction of the protein complement of the induced sample could thereby be purified and compared to a non-induced sample of the same community by differential gel electrophoresis to discriminate between constitutively expressed proteins and proteins upregulated in response to the inducing substance.

RESULTS

Using the applied approach, downstream analysis by mass spectrometry could be limited to only proteins recognized as upregulated in the cellulase-induced sample. Of 39 selected proteins, the majority were found to be linked to the need to degrade, take up, and metabolize cellulose. In addition, 28 (72%) of the proteins were non-cytosolic and 17 (44%) were annotated as carbohydrate-active enzymes. The results demonstrated both the applicability of the proposed approach for identifying extracellular proteins and guiding the selection of proteins toward those specifically upregulated and targeted by the enzyme inducing substance. Further, because identification of interesting proteins was based on the regulation of enzyme expression in response to a need to hydrolyze and utilize a specific substance, other unexpected enzyme activities were able to be identified.

CONCLUSIONS

The described approach created the conditions necessary to be able to select relevant extracellular enzymes that were extracted from the enzyme-induced microbial community. However, for the purpose of bioprospecting for enzymes to clone, produce, and characterize for practical applications, it was concluded that identification against public databases was not sufficient to identify the correct gene or protein sequence for cloning of the identified novel enzymes.

Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type

BACKGROUND

Methane yield and biogas productivity of biogas plants (BGPs) depend on microbial community structure and function, substrate supply, and general biogas process parameters. So far, however, relatively little is known about correlations between microbial community function and process parameters. To close this knowledge gap, microbial communities of 40 samples from 35 different industrial biogas plants were evaluated by a metaproteomics approach in this study.

RESULTS

Liquid chromatography coupled to tandem mass spectrometry (Orbitrap Elite™ Hybrid Ion Trap-Orbitrap Mass Spectrometer) of all 40 samples as triplicate enabled the identification of 3138 different metaproteins belonging to 162 biological processes and 75 different taxonomic orders. The respective database searches were performed against UniProtKB/Swiss-Prot and seven metagenome databases. Subsequent clustering and principal component analysis of these data allowed for the identification of four main clusters associated with mesophile and thermophile process conditions, the use of upflow anaerobic sludge blanket reactors and BGP feeding with sewage sludge. Observations confirm a previous phylogenetic study of the same BGP samples that was based on 16S rRNA gene sequencing by De Vrieze et al. (Water Res 75:312-323, 2015). In particular, we identified similar microbial key players of biogas processes, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. For the elucidation of the main biomass degradation pathways, the most abundant 1 % of metaproteins was assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN), and (iv) sludge retention time (SRT) on these pathways was investigated. For example, high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation.

CONCLUSIONS

This is the first large-scale metaproteome study of BGPs. Proteotyping of BGPs reveals general correlations between the microbial community structure and its function with process parameters. The monitoring of changes on the level of microbial key functions or even of the microbial community represents a well-directed tool for the identification of process problems and disturbances.Graphical abstractCorrelation between the different orders and process parameter, as well as principle component analysis of all investigated biogas plants based on the identified metaproteins.

An integrated metagenome and -proteome analysis of the microbial community residing in a biogas production plant

To study the metaproteome of a biogas-producing microbial community, fermentation samples were taken from an agricultural biogas plant for microbial cell and protein extraction and corresponding metagenome analyses. Based on metagenome sequence data, taxonomic community profiling was performed to elucidate the composition of bacterial and archaeal sub-communities. The community's cytosolic metaproteome was represented in a 2D-PAGE approach. Metaproteome databases for protein identification were compiled based on the assembled metagenome sequence dataset for the biogas plant analyzed and non-corresponding biogas metagenomes. Protein identification results revealed that the corresponding biogas protein database facilitated the highest identification rate followed by other biogas-specific databases, whereas common public databases yielded insufficient identification rates. Proteins of the biogas microbiome identified as highly abundant were assigned to the pathways involved in methanogenesis, transport and carbon metabolism. Moreover, the integrated metagenome/-proteome approach enabled the examination of genetic-context information for genes encoding identified proteins by studying neighboring genes on the corresponding contig. Exemplarily, this approach led to the identification of a Methanoculleus sp. contig encoding 16 methanogenesis-related gene products, three of which were also detected as abundant proteins within the community's metaproteome. Thus, metagenome contigs provide additional information on the genetic environment of identified abundant proteins.