scholarly journals Opportunistic interactions on Fe0 between methanogens and acetogens from a climate lake

2019 ◽  
Author(s):  
Paola Andrea Palacios ◽  
Amelia-Elena Rotaru
Keyword(s):  
Energy Source ◽  
Microbial Community ◽  
Common Good ◽  
Microbial Interactions ◽  
Microbial Interaction ◽  
Interspecies Interaction ◽  
Uptake Mechanism ◽  
Physiological Group ◽  
Pure Cultures ◽  
Sole Energy

AbstractMicrobial-induced corrosion has been extensively studied in pure cultures. However, Fe0 corrosion by complex environmental communities, and especially the interplay between microbial physiological groups, is still poorly understood. In this study, we combined experimental physiology and metagenomics to explore Fe0-dependent microbial interactions between physiological groups enriched from anoxic climate lake sediments. Then, we investigated how each physiological group interacts with Fe0. We offer evidence for a new interspecies interaction during Fe0 corrosion. We showed that acetogens enhanced methanogenesis but were negatively impacted by methanogens (opportunistic microbial interaction). Methanogens were positively impacted by acetogens. In the metagenome of the corrosive community, the acetogens were mostly represented by Clostridium and Eubacterium, the methanogens by Methanosarcinales, Methanothermobacter and Methanobrevibacter. Within the corrosive community, acetogens and methanogens produced acetate and methane concurrently, however at rates that cannot be explained by abiotic H2-buildup at the Fe0 surface. Thus, microbial-induced corrosion might have occurred via a direct or enzymatically mediated electron uptake from Fe0. The shotgun metagenome of Clostridium within the corrosive community contained several H2-releasing enzymes including [FeFe]-hydrogenases, which could boost Fe0-dependent H2-formation as previously shown for pure culture acetogens. Outside the cell, acetogenic hydrogenases could become a common good for any H2/CO2-consuming member in the microbial community including methanogens that rely on Fe0 as a sole energy source. However, the exact electron uptake mechanism from Fe0 remains to be unraveled.

scholarly journals Lanthanide-dependent cross-feeding of methane-derived carbon is linked by microbial community interactions

2016 ◽  
Vol 114 (2) ◽  
pp. 358-363 ◽  
Author(s):  
Sascha M. B. Krause ◽  
Timothy Johnson ◽  
Yasodara Samadhi Karunaratne ◽  
Yanfen Fu ◽  
David A. C. Beck ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microbial Community ◽  
Expression Profiles ◽  
Carbon Sources ◽  
Gene Expression Profiles ◽  
Microbial Interactions ◽  
Community Interactions ◽  
Carbon Cycles ◽  
Calcium Dependent ◽  
Pure Cultures

The utilization of methane, a potent greenhouse gas, is an important component of local and global carbon cycles that is characterized by tight linkages between methane-utilizing (methanotrophic) and nonmethanotrophic bacteria. It has been suggested that the methanotroph sustains these nonmethanotrophs by cross-feeding, because subsequent products of the methane oxidation pathway, such as methanol, represent alternative carbon sources. We established cocultures in a microcosm model system to determine the mechanism and substrate that underlay the observed cross-feeding in the environment. Lanthanum, a rare earth element, was applied because of its increasing importance in methylotrophy. We used co-occurring strains isolated from Lake Washington sediment that are involved in methane utilization: a methanotroph and two nonmethanotrophic methylotrophs. Gene-expression profiles and mutant analyses suggest that methanol is the dominant carbon and energy source the methanotroph provides to support growth of the nonmethanotrophs. However, in the presence of the nonmethanotroph, gene expression of the dominant methanol dehydrogenase (MDH) shifts from the lanthanide-dependent MDH (XoxF)-type, to the calcium-dependent MDH (MxaF)-type. Correspondingly, methanol is released into the medium only when the methanotroph expresses the MxaF-type MDH. These results suggest a cross-feeding mechanism in which the nonmethanotrophic partner induces a change in expression of methanotroph MDHs, resulting in release of methanol for its growth. This partner-induced change in gene expression that benefits the partner is a paradigm for microbial interactions that cannot be observed in studies of pure cultures, underscoring the importance of synthetic microbial community approaches to understand environmental microbiomes.

scholarly journals In Vitro Kinetic Analysis of Oligofructose Consumption by Bacteroides and Bifidobacterium spp. Indicates Different Degradation Mechanisms

2006 ◽  
Vol 72 (2) ◽  
pp. 1006-1012 ◽  
Author(s):  
Roel Van der Meulen ◽  
Lefteris Makras ◽  
Kristof Verbrugghe ◽  
Tom Adriany ◽  
Luc De Vuyst
Keyword(s):  
Energy Source ◽  
Lactic Acid ◽  
Kinetic Analysis ◽  
Fermentation Process ◽  
Bifidobacterium Longum ◽  
Degradation Mechanisms ◽  
Pure Cultures ◽  
The Cost ◽  
Sole Energy

ABSTRACT The growth of pure cultures of Bacteroides thetaiotaomicron LMG 11262 and Bacteroides fragilis LMG 10263 on fructose and oligofructose was examined and compared to that of Bifidobacterium longum BB536 through in vitro laboratory fermentations. Gas chromatography (GC) analysis was used to determine the different fractions of oligofructose and their degradation during the fermentation process. Both B. thetaiotaomicron LMG 11262 and B. fragilis LMG 10263 were able to grow on oligofructose as fast as on fructose, succinic acid being the major metabolite produced by both strains. B. longum BB536 grew slower on oligofructose than on fructose. Acetic acid and lactic acid were the main metabolites produced when fructose was used as the sole energy source. Increased amounts of formic acid and ethanol were produced when oligofructose was used as an energy source at the cost of lactic acid. Detailed kinetic analysis revealed a preferential metabolism of the short oligofructose fractions (e.g., F2 and F3) for B. longum BB536. After depletion of the short fractions, the larger oligofructose fractions (e.g., F4, GF4, F5, GF5, and F6) were metabolized, too. Both Bacteroides strains did not display such a preferential metabolism and degraded all oligofructose fractions simultaneously, transiently increasing the fructose concentration in the medium. This suggests a different mechanism for oligofructose breakdown between the strain of Bifidobacterium and both strains of Bacteroides, which helps to explain the bifidogenic nature of inulin-type fructans.

A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Environmental Remediation ◽  
Real Life ◽  
Design Principles ◽  
Microbial Interactions ◽  
Potential Applications ◽  
New Gene ◽  
Global Biogeochemical Cycles ◽  
Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

Deciphering bacterial interactions via DSF-regulated public goods in an anammox community

2019 ◽  
Author(s):  
Yongzhao Guo ◽  
Yunpeng Zhao ◽  
Xi Tang ◽  
Tianxing Na ◽  
Juejun Pan ◽  
...  
Keyword(s):  
Amino Acids ◽  
Microbial Community ◽  
Public Goods ◽  
Extracellular Polymeric Substances ◽  
Microbial Interactions ◽  
Anammox Bacteria ◽  
Signal Molecules ◽  
Bacteria Growth ◽  
Bacterial Interactions ◽  
Social Traits

Abstract Background: Bacterial interaction and communication via quorum sensing (QS) received extensively attention, as it can coordinate bacterial behavior and activity through the QS signal molecules in microbial community. Though the exchange of public goods regulated by QS have been explored in pure culture, how signal sense, transmit, and affect the social traits through regulating public goods in complex communities remains unclear. Results: The levels of public goods (e.g. extracellular polymeric substances (EPS) and amino acids) changed significantly when exogenous diffusion signal factor (DSF), a kind of QS molecules, was added. Approaches involving meta-omics and hierarchical signalling network construction give insight into that anammox species ( Jettenia caeni , AMX1) and Proteobacteria -affiliated bacterium (PRO1) can sense and transit DSF signals, thus directly regulating the production and exchange of public goods via the secondary messenger c-di-GMP regulator, Clp. In detail, these two kinds of species can supply more costly amino acids for DSF-Secretor species (like AMX2, CFX1, CFX3, and PRO4) after sensing DSF. Meanwhile, DSF-Secretor species encoded diverse genes involved in hydrolysis of extracellular protein and carbohydrate and genes involved in transportation of peptides and sugars. The exogenous DSF-inducement also leads to the high expression of these genes, which indicated DSF-Secretor species helped anammox bacteria scavenge extracellular detritus. This process can be considered as a feedback of public goods supply by anammox bacteria, as this process contributed to create a suitable environment for anammox bacteria growth. Namely, DSF can bridge bacterial interactions through regulating public goods. Furthermore, the trade-off induces discrepant metabolic loads of different microbial clusters and community succession. It illustrated the potential to artificially alleviate metabolic loads and thus increase proliferation rate for certain bacteria through QS. Conclusions: DSF can bridge interactions of anammox bacteria and DSF-Secretor species through regulating production and exchange of public goods using Clp regulator. Deciphering microbial interactions via QS provides insights for understanding the molecular evolution of QS in microbial community.

scholarly journals Age-Related Colonic Mucosal Microbiome Community Shifts in Monkeys

2020 ◽  
Author(s):  
Ravichandra Vemuri ◽  
Chrissy Sherrill ◽  
Matthew A Davis ◽  
Kylie Kavanagh
Keyword(s):  
Microbial Community ◽  
Systemic Inflammation ◽  
16S Rrna Gene Sequencing ◽  
Microbial Interactions ◽  
Rrna Gene ◽  
Vervet Monkeys ◽  
Fecal Samples ◽  
Age Related ◽  
Rrna Gene Sequencing ◽  
The Stability

Abstract Age-related changes in gut microbiome impact host health. The interactive relationship between the microbiome and physiological systems in an aged body system remains to be clearly defined, particularly in the context of inflammation. Therefore, we aimed to evaluate systemic inflammation, microbial translocation (MT), and differences between fecal and mucosal microbiomes. Ascending colon mucosal biopsies, fecal samples, and blood samples from healthy young and old female vervet monkeys were collected for 16S rRNA gene sequencing, MT, and cytokine analyses, respectively. To demonstrate microbial co-occurrence patterns, we used Kendall’s tau correlation measure of interactions between microbes. We found elevated levels of plasma LBP-1, MCP-1, and CRP in old monkeys, indicative of higher MT and systemic inflammation. Microbiome analysis revealed significant differences specific to age. At the phylum level, abundances of pathobionts such as Proteobacteria were increased in the mucosa of old monkeys. At the family level, Helicobacteriaceae was highly abundant in mucosal samples (old); in contrast, Ruminococcaceae were higher in the fecal samples of old monkeys. We found significantly lower Firmicutes:Bacteroidetes ratio and lower abundance of butyrate-producing microbes in old monkeys, consistent with less healthy profiles. Microbial community co-occurrence analysis on mucosal samples revealed 13 nodes and 41 associations in the young monkeys, but only 12 nodes and 21 associations in the old monkeys. Our findings provide novel insights into systemic inflammation and gut microbial interactions, highlight the importance of the mucosal niche, and facilitate further understanding of the decline in the stability of the microbial community with aging.

MARINE THIOBACILLI: II. CULTURE AND ULTRASTRUCTURE

1967 ◽  
Vol 13 (11) ◽  
pp. 1529-1534 ◽  
Author(s):  
R. C. Tilton ◽  
G. J. Stewart ◽  
G. E. Jones
Keyword(s):  
Energy Source ◽  
Amino Acids ◽  
Atlantic Ocean ◽  
Elemental Sulfur ◽  
Cell Envelope ◽  
Nuclear Material ◽  
Gram Negative ◽  
Mineral Sulfides ◽  
Sulfur Containing ◽  
Sole Energy

Gram-negative, polar-flagellated bacteria isolated from the Atlantic Ocean using thiosulfate or elemental sulfur as the sole energy source are considered members of the genus Thiobacillus. These cultures require seawater in the medium although they grow optimally when the salinity is reduced to a range of 6.4 to 25.8 p.p.t. There is no growth at 0 salinity and a 25–30% reduction of thiosulfate oxidation in 3 weeks is observed at 18 °C in a salinity of 32.3 p.p.t. The pH of the medium decreased from 7.2 or 5.6 to a final pH of 2–3. One culture decreased the pH to only 5.0 while oxidizing 80% of the thiosulfate. One representative culture, WH-2, was able to oxidize only thiosulfate and elemental sulfur from a series of substrates including tetrathionate, sulfite, sulfur-containing amino acids, and mineral sulfides. This culture is a strict aerobe and did not grow in the presence of 0.01% yeast extract, 2216E, or nutrient broth.The ultrastructure of culture WH-2 indicates that it is very similar to that of Thiobacillus thioosidans. The cells indicate a substantial cell envelope, cytomembranes, electron-dense fibrillar nuclear material, unknown granules, and distinct polyphosphate granules.

scholarly journals Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model

2021 ◽  
Author(s):  
Shion Hosoda ◽  
Tsukasa Fukunaga ◽  
Michiaki Hamada
Keyword(s):  
Gut Microbiota ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Continuous Time ◽  
Hidden Markov ◽  
Hidden Variables ◽  
Microbial Interactions ◽  
Interaction Networks ◽  
Time Varying ◽  
Microbial Interaction

AbstractMotivationAccumulating evidence has highlighted the importance of microbial interaction networks. Methods have been developed for estimating microbial interaction networks, of which the generalized Lotka-Volterra equation (gLVE)-based method can estimate a directed interaction network. The previous gLVE-based method for estimating microbial interaction networks did not consider time-varying interactions.ResultsIn this study, we developed unsupervised learning based microbial interaction inference method using Bayesian estimation (Umibato), a method for estimating time-varying microbial interactions. The Umibato algorithm comprises Gaussian process regression (GPR) and a new Bayesian probabilistic model, the continuous-time regression hidden Markov model (CTRHMM). Growth rates are estimated by GPR, and interaction networks are estimated by CTRHMM. CTRHMM can estimate time-varying interaction networks using interaction states, which are defined as hidden variables. Umibato outperformed the existing methods on synthetic datasets. In addition, it yielded reasonable estimations in experiments on a mouse gut microbiota dataset, thus providing novel insights into the relationship between consumed diets and the gut microbiota.AvailabilityThe C++ and python source codes of the Umibato software are available at http://github.com/shion-h/[email protected], [email protected]

scholarly journals Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data

2021 ◽  
Author(s):  
Jie Zhou ◽  
Jiang Gui ◽  
Weston D Viles ◽  
Anne G Hoen
Keyword(s):  
16S Rrna ◽  
Permutation Test ◽  
Sequence Data ◽  
Interaction Network ◽  
Microbial Interactions ◽  
Microbial Interaction ◽  
Rrna Sequence ◽  
16S Rrna Sequence ◽  
Data Set ◽  
Graphical Lasso

Though being vital for human health, microbial interactions with their host and with each other are still largely obscure for researchers. To deepen the understanding, the analyses based on longitudinal data are a better choice than the cross-sectional data since the information provided by the former is usually more stable. To this end, in this paper, we first propose an EM-type algorithm to identify microbial interaction network for the irregularly spaced longitudinal measurements. Correlation functions are employed to account for the correlation across the temporal measurements for a given subject. The algorithms take advantage of the efficiency of the popular graphical lasso algorithm and can be implemented straightforwardly. Simulation studies show that the proposed algorithms can significantly outperform the conventional algorithms such as graphical lasso or neighborhood method when the correlation between measurements grows larger. In second part of the paper, based on a 16S rRNA sequence data set of gut microbiome, module-preserving permutation test is proposed to test the independence of the estimated network and the phylogeny of the microbe species. The results demonstrate evidences of strong association between the interaction network and the phylogenetic tree which indicates that the taxa closer in their genomes tend to have more/stronger interactions in their functions. The proposed algorithms can be implemented through R package lglasso at \url{https://github.com/jiezhou-2/lglasso

Enzymes of agmatine degradation and the control of their synthesis in Streptococcus faecalis

1982 ◽  
Vol 152 (2) ◽  
pp. 676-681
Author(s):  
J P Simon ◽  
V Stalon
Keyword(s):  
Energy Source ◽  
Catabolite Repression ◽  
Type Strain ◽  
Wild Type Strain ◽  
Arginine Deiminase ◽  
The Other ◽  
Wild Type ◽  
Streptococcus Faecalis ◽  
Agmatine Deiminase ◽  
Sole Energy

Streptococcus faecalis ATCC 11700 uses agmatine as its sole energy source for growth. Agmatine deiminase and putrescine carbamoyltransferase are coinduced by growth on agmatine. Glucose and arginine were found to exert catabolite repression on the agmatine deiminase pathway. Four mutants unable to utilize agmatine as an energy source, isolated from the wild-type strain, exhibited three distinct phenotypes. Two of these strains showed essentially no agmatine deiminase, one mutant showed negligible activity of putrescine carbamoyltransferase, and one mutant was defective in both activities. Two carbamate kinases are present in S. faecalis, one belonging to the arginine deiminase pathway, the other being induced by growth on agmatine. These two enzymes have the same molecular weight, 82,000, and seem quite different in size from the kinases isolated from other streptococci.

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