Cross-Feedings, Competition, and Positive and Negative Synergies in a Four-Species Synthetic Community for Anaerobic Degradation of Cellulose to Methane

Absence of biofilm adhesin proteins changes surface attachment and cell strategy for Desulfovibrio vulgaris Hildenborough

Ubiquitous in nature, biofilms provide stability in a fluctuating environment and provide protection from stressors. Biofilms formed in industrial processes are exceedingly problematic and costly. While biofilms of sulfate-reducing bacteria in the environment are often beneficial because of their capacity to remove toxic metals from water, in industrial pipelines, these biofilms cause a major economic impact due to their involvement in metal and concrete corrosion. The mechanisms by which biofilms of sulfate-reducing bacteria form, however, are not well understood. Our previous work identified two proteins, named by their gene loci DVU1012 and DVU1545, as adhesins in the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough. Both proteins are localized to the cell surface and the presence of at least one of the proteins, with either being sufficient, is necessary for biofilm formation to occur. In this study, differences in cell attachment and early biofilm formation in single deletion mutants of these adhesins were identified. Cells lacking DVU1012 had a different attachment strategy from wild-type (WT) and ΔDVU1545 cells, more often attaching as single cells than aggregates, which indicated that DVU1012 was more important for cell-to-cell attachment. ΔDVU1545 cells had increased cell attachment compared to WT cells when grown in static cultures. To date, comparisons of the D. vulgaris Hildenborough have been made to the large adhesion protein system in environmental pseudomonads. Yet, we and others have shown distinct mechanistic differences in the systems. We propose to name these proteins in D. vulgaris Hildenborough biofilm formation system to facilitate comparisons.

IMPORTANCE

Biofilms of sulfate-reducing bacteria contribute to biocorrosion, costing the United States hundreds of millions of dollars annually. In contrast, these biofilms can be used to bioremediate toxic heavy metals and to generate bioelectricity. As one of the most abundant groups of organisms on Earth, it is pertinent to better understand mechanistically how the biofilms of sulfate-reducing bacteria form so we may use this knowledge to help in efforts to mitigate biocorrosion, to promote bioremediation, and to produce clean energy. This study shows that the absence of either one of two biofilm adhesins impacts surface colonization by a sulfate-reducing bacterium, and that these two biofilm adhesins differ in their effect on cell attachment compared to other well-documented bacteria such as Pseudomonas species.

Modeling bacterial interactions uncovers the importance of outliers in the coastal lignin-degrading consortium

Lignin, as the abundant carbon polymer, is essential for carbon cycle and biorefinery. Microorganisms interact to form communities for lignin biodegradation, yet it is a challenge to understand such complex interactions. Here, we develop a coastal lignin-degrading bacterial consortium (LD), through "top-down" enrichment. Sequencing and physiological analyses reveal that LD is dominated by the lignin degrader Pluralibacter gergoviae (>98%), with additional rare non-degraders. Interestingly, LD, cultured in lignin-MB medium, significantly enhances cell growth and lignin degradation as compared to P. gergoviae alone, implying a role of additional outliers. Using genome-scale metabolic models, metabolic profiling and culture experiments, modeling of inter-species interactions between P. gergoviae, Vibrio alginolyticus, Aeromonas hydrophila and Shewanella putrefaciens, unravels cross-feeding of amino acids, organic acids and alcohols between the degrader and non-degraders. Furthermore, the sub-population ratio is essential to enforce the synergy. Our study highlights the unrecognized role of outliers in lignin degradation.

Creation of Cellulolytic Communities of Soil Microorganisms-A Search for Optimal Approaches

For the targeted selection of microbial communities that provide cellulose degradation, soil samples containing cellulolytic microorganisms and specific plant residues as a substrate can be used. The details of this process have not been studied: in particular, whether the use of different soils determines the varying efficiency of communities; whether these established cellulolytic communities will have substrate specificity, and other factors. To answer these questions, four soil microbial communities with different cellulolytic activity (Podzol and the soil of Chernevaya taiga) and substrates (oat straw and hemp shives) with different levels of cellulose availability were used, followed by trained communities that were tested on botrooth substrates (in all possible combinations). Based on the analysis of the taxonomic structure of all communities and their efficiency across all substrates (decomposition level, carbon, and nitrogen content), it was shown that the most important taxa of all trained microbial cellulolytic communities are recruited from secondary soil taxa. The original soil does not affect the efficiency of cellulose decomposition: both soils produce equally active communities. Unexpectedly, the resulting communities trained on oats were more effective on hemp than the communities trained on hemp. In general, the usage of pre-trained microbial communities increases the efficiency of decomposition.

Unraveling interspecies cross-feeding during anaerobic lignin degradation for bioenergy applications

Lignin, a major component of plant biomass, remains underutilized for renewable biofuels due to its complex and heterogeneous structure. Although investigations into depolymerizing lignin using fungi are well-established, studies of microbial pathways that enable anaerobic lignin breakdown linked with methanogenesis are limited. Through an enrichment cultivation approach with inoculation of freshwater sediment, we enriched a microbial community capable of producing methane during anaerobic lignin degradation. We reconstructed the near-complete population genomes of key lignin degraders and methanogens using metagenome-assembled genomes finally selected in this study (MAGs; 92 bacterial and 4 archaeal MAGs affiliated into 45 and 2 taxonomic groups, respectively). This study provides genetic evidence of microbial interdependence in conversion of lignin to methane in a syntrophic community. Metagenomic analysis revealed metabolic linkages, with lignin-hydrolyzing and/or fermentative bacteria such as the genera Alkalibaculum and Propionispora transforming lignin breakdown products into compounds such as acetate to feed methanogens (two archaeal MAGs classified into the genus Methanosarcina or UBA6 of the family Methanomassiliicoccaceae). Understanding the synergistic relationships between microbes that convert lignin could inform strategies for producing renewable bioenergy and treating aromatic-contaminated environments through anaerobic biodegradation processes. Overall, this study offers fundamental insights into complex community-level anaerobic lignin metabolism, highlighting hitherto unknown players, interactions, and pathways in this biotechnologically valuable process.

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure

Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O2) during droughts, or to sulfate (SO42-) as a result of sea level rise. How these stressors - separately and together - impact microbial food webs driving carbon cycling in the wetlands is still not understood. To investigate this, we integrated geochemical analysis, proteogenomics, and stoichiometric modeling to characterize the impact of elevated SO42- and O2 levels on microbial methane (CH4) and carbon dioxide (CO2) emissions. The results uncovered the adaptive responses of this community to changes in SO42- and O2 availability and identified altered microbial guilds and metabolic processes driving CH4 and CO2 emissions. Elevated SO42- reduced CH4 emissions, with hydrogenotrophic methanogenesis more suppressed than acetoclastic. Elevated O2 shifted the greenhouse gas emissions from CH4 to CO2. The metabolic effects of combined SO42- and O2 exposures on CH4 and CO2 emissions were similar to those of O2 exposure alone. The reduction in CH4 emission by increased SO42- and O2 was much greater than the concomitant increase in CO2 emission. Thus, greater SO42- and O2 exposure in wetlands is expected to reduce the aggregate warming effect of CH4 and CO2. Metaproteomics and stoichiometric modeling revealed a unique subnetwork involving carbon metabolism that converts lactate and SO42- to produce acetate, H2S, and CO2 when SO42- is elevated under oxic conditions. This study provides greater quantitative resolution of key metabolic processes necessary for the prediction of CH4 and CO2 emissions from wetlands under future climate scenarios.

SEMQuant: Extending Sipros-Ensemble with Match-Between-Runs for Comprehensive Quantitative Metaproteomics

Metaproteomics, utilizing high-throughput LC-MS, offers a profound understanding of microbial communities. Quantitative metaproteomics further enriches this understanding by measuring relative protein abundance and revealing dynamic changes under different conditions. However, the challenge of missing peptide quantification persists in metaproteomics analysis, particularly in data-dependent acquisition mode, where high-intensity precursors for MS2 scans are selected. To tackle this issue, the match-between-runs (MBR) technique is used to transfer peptides between LC-MS runs. Inspired by the benefits of MBR and the need for streamlined metaproteomics data analysis, we developed SEMQuant, an end-to-end software integrating Sipros-Ensemble's robust peptide identifications with IonQuant's MBR function. The experiments show that SEMQuant consistently obtains the highest or second highest number of quantified proteins with notable precision and accuracy. This demonstrates SEMQuant's effectiveness in conducting comprehensive and accurate quantitative metaproteomics analyses across diverse datasets and highlights its potential to propel advancements in microbial community studies. SEMQuant is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/SEMQuant.

Combining metabolic flux analysis with proteomics to shed light on the metabolic flexibility: the case of Desulfovibrio vulgaris Hildenborough

Introduction

Desulfovibrio vulgaris Hildenborough is a gram-negative anaerobic bacterium belonging to the sulfate-reducing bacteria that exhibits highly versatile metabolism. By switching from one energy mode to another depending on nutrients availability in the environments" it plays a central role in shaping ecosystems. Despite intensive efforts to study D. vulgaris energy metabolism at the genomic, biochemical and ecological level, bioenergetics in this microorganism remain far from being fully understood. Alternatively, metabolic modeling is a powerful tool to understand bioenergetics. However, all the current models for D. vulgaris appeared to be not easily adaptable to various environmental conditions.

Methods

To lift off these limitations, here we constructed a novel transparent and robust metabolic model to explain D. vulgaris bioenergetics by combining whole-cell proteomic analysis with modeling approaches (Flux Balance Analysis).

Results

The iDvu71 model showed over 0.95 correlation with experimental data. Further simulations allowed a detailed description of D. vulgaris metabolism in various conditions of growth. Altogether, the simulations run in this study highlighted the sulfate-to-lactate consumption ratio as a pivotal factor in D. vulgaris energy metabolism.

Discussion

In particular, the impact on the hydrogen/formate balance and biomass synthesis is discussed. Overall, this study provides a novel insight into D. vulgaris metabolic flexibility.

Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass

Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach. The top-down approach is a classical method that uses environmental variables to selectively steer an existing microbial consortium to achieve a target function. While high-throughput sequencing has enabled microbial community characterization, the major challenge is to disentangle complex microbial interactions and manipulate the structure and function accordingly. The bottom-up approach uses prior knowledge of the metabolic pathway and possible interactions among consortium partners to design and engineer synthetic microbial consortia. This strategy offers some control over the composition and function of the consortium for targeted bioprocesses, but challenges remain in optimal assembly methods and long-term stability. In this review, we present the recent advancements, challenges, and opportunities for further improvement using top-down and bottom-up approaches for microbiome engineering. As the bottom-up approach is relatively a new concept for waste valorization, this review explores the assembly and design of synthetic microbial consortia, ecological engineering principles to optimize microbial consortia, and metabolic engineering approaches for efficient conversion. Integration of top-down and bottom-up approaches along with developments in metabolic modeling to predict and optimize consortia function are also highlighted.

ONE-SENTENCE SUMMARY

This review highlights the microbial consortia-driven waste valorization for biomanufacturing through top-down and bottom-up design approaches and describes strategies, tools, and unexplored opportunities to optimize the design and stability of such consortia.

Microbe-cellulose hydrogels as a model system for particulate carbon degradation in soil aggregates

Particulate carbon (C) degradation in soils is a critical process in the global C cycle governing greenhouse gas fluxes and C storage. Millimeter-scale soil aggregates impose strong controls on particulate C degradation by inducing chemical gradients of e.g. oxygen, as well as limiting microbial mobility in pore structures. To date, experimental models of soil aggregates have incorporated porosity and chemical gradients but not particulate C. Here, we demonstrate a proof-of-concept encapsulating microbial cells and particulate C substrates in hydrogel matrices as a novel experimental model for soil aggregates. Ruminiclostridium cellulolyticum was co-encapsulated with cellulose in millimeter-scale polyethyleneglycol-dimethacrylate (PEGDMA) hydrogel beads. Microbial activity was delayed in hydrogel-encapsulated conditions, with cellulose degradation and fermentation activity being observed after 13 days of incubation. Unexpectedly, hydrogel encapsulation shifted product formation of R. cellulolyticum from an ethanol-lactate-acetate mixture to an acetate-dominated product profile. Fluorescence microscopy enabled simultaneous visualization of the PEGDMA matrix, cellulose particles, and individual cells in the matrix, demonstrating growth on cellulose particles during incubation. Together, these microbe-cellulose-PEGDMA hydrogels present a novel, reproducible experimental soil surrogate to connect single cells to process outcomes at the scale of soil aggregates and ecosystems.

Up-flow anaerobic sludge blanket treatment of swine wastewater: Effect of heterologous and homologous inocula on anaerobic digestion performance and the microbial community

The effects of heterogenous (anaerobic sludge from treating distillery sewage, ASDS) and homologous (anaerobic sludge from treating swine wastewater, ASSW) inocula on anaerobic digestion and the microbial community in an up-flow anaerobic sludge blanket treating swine wastewater were compared. The highest chemical oxygen demand removal efficiencies with ASDS (84.8%) and ASSW (83.1%) were obtained with an organic loading rate of 15 kg COD/m3/d. For ASSW compared with ASDS, methane production efficiency was 15.3% higher and excess sludge production was 73.0% lower. The abundance of the cellulose hydrolyzing bacterium Clostridium sensu stricto_1 with ASDS (36.1%) was 1.5 times that with ASSW, while that of Methanosarcina with ASSW (22.9%) was > 100 times that with ASDS. ASDS reduced the content of pathogenic bacteria by 88.0%, while ASSW maintained a low level of pathogenic bacteria. ASSW greatly improved the methane production efficiency of wastewater and is more suitable for treating swine wastewater.