scholarly journals Cellulolytic and Xylanolytic Microbial Communities Associated With Lignocellulose-Rich Wheat Straw Degradation in Anaerobic Digestion

2021 ◽  
Vol 12 ◽  
Author(s):  
Mads Borgbjerg Jensen ◽  
Nadieh de Jonge ◽  
Maja Duus Dolriis ◽  
Caroline Kragelund ◽  
Christian Holst Fischer ◽  
...  

The enzymatic hydrolysis of lignocellulosic polymers is generally considered the rate-limiting step to methane production in anaerobic digestion of lignocellulosic biomass. The present study aimed to investigate how the hydrolytic microbial communities of three different types of anaerobic digesters adapted to lignocellulose-rich wheat straw in continuous stirred tank reactors operated for 134 days. Cellulase and xylanase activities were monitored weekly using fluorescently-labeled model substrates and the enzymatic profiles were correlated with changes in microbial community compositions based on 16S rRNA gene amplicon sequencing to identify key species involved in lignocellulose degradation. The enzymatic activity profiles and microbial community changes revealed reactor-specific adaption of phylogenetically different hydrolytic communities. The enzymatic activities correlated significantly with changes in specific taxonomic groups, including representatives of Ruminiclostridium, Caldicoprobacter, Ruminofilibacter, Ruminococcaceae, Treponema, and Clostridia order MBA03, all of which have been linked to cellulolytic and xylanolytic activity in the literature. By identifying microorganisms with similar development as the cellulase and xylanase activities, the proposed correlation method constitutes a promising approach for deciphering essential cellulolytic and xylanolytic microbial groups for anaerobic digestion of lignocellulosic biomass.

2017 ◽  
Author(s):  
Rasmus H. Kirkegaard ◽  
Simon J. McIlroy ◽  
Jannie M. Kristensen ◽  
Marta Nierychlo ◽  
Søren M. Karst ◽  
...  

AbstractAnaerobic digestion is widely applied to treat organic waste at wastewater treatment plants. Characterisation of the underlying microbiology represents a source of information to develop strategies for improved operation. To this end, we investigated the microbial community composition of thirty-two full-scale digesters over a six-year period using 16S rRNA gene amplicon sequencing. Sampling of the sludge fed into these systems revealed that several of the most abundant populations were likely inactive and immigrating with the influent. This observation indicates that a failure to consider immigration will interfere with correlation analysis and give an inaccurate picture of the active microbial community. Furthermore, several abundant OTUs could not be classified to genus level with commonly applied taxonomies, making inference of their function unreliable. As such, the existing MiDAS taxonomy was updated to include these abundant phylotypes. The communities of individual plants surveyed were remarkably similar – with only 300 OTUs representing 80% of the total reads across all plants, and 15% of these identified as likely inactive immigrating microbes. By identifying the abundant and active taxa in anaerobic digestion, this study paves the way for targeted characterisation of the process important organisms towards an in-depth understanding of the microbial ecology of these biotechnologically important systems.


2021 ◽  
Vol 232 (1) ◽  
Author(s):  
Yazeed Abdelmageed ◽  
Carrie Miller ◽  
Carrie Sanders ◽  
Timothy Egbo ◽  
Alexander Johs ◽  
...  

AbstractIn nature, the bioaccumulative potent neurotoxin methylmercury (MeHg) is produced from inorganic mercury (Hg) predominantly by anaerobic microorganisms. Hg-contaminated soils are a potential source of MeHg due to microbial activity. We examine streambank soils collected from the contaminated East Fork Poplar Creek (EFPC) in Tennessee, USA, where seasonal variations in MeHg levels have been observed throughout the year, suggesting active microbial Hg methylation. In this study, we characterized the microbial community in contaminated bank soil samples collected from two locations over a period of one year and compared the results to soil samples from an uncontaminated reference site with similar geochemistry (n = 12). Microbial community composition and diversity were assessed by 16S rRNA gene amplicon sequencing. Furthermore, to isolate potential methylators from soils, enrichment cultures were prepared using selective media. A set of three clade-specific primers targeting the gene hgcA were used to detect Hg methylators among the δ-Proteobacteria in EFPC bank soils across all seasons. Two families among the δ-Proteobacteria that have been previously associated with Hg methylation, Geobacteraceae and Syntrophobacteraceae, were found to be predominant with relative abundances of 0.13% and 4.0%, respectively. However, in soil enrichment cultures, Firmicutes were predominant among families associated with Hg methylation. Specifically, Clostridiaceae and Peptococcaceae and their genera Clostridium and Desulfosporosinus were among the ten most abundant genera with relative abundances of 2.6% and 1.7%, respectively. These results offer insights into the role of microbial communities on Hg transformation processes in contaminated bank soils in EFPC. Identifying the biogeochemical drivers of MeHg production is critical for future remediation efforts.


2021 ◽  
Vol 12 ◽  
Author(s):  
René Janßen ◽  
Aaron J. Beck ◽  
Johannes Werner ◽  
Olaf Dellwig ◽  
Johannes Alneberg ◽  
...  

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a given environmental state. As proof of the principle, our goal was to assess the opportunities and limitations of machine learning to detect microbial fingerprints indicating the presence of the munition compound 2,4,6-trinitrotoluene (TNT) in southwestern Baltic Sea sediments. Over 40 environmental variables including grain size distribution, elemental composition, and concentration of munition compounds (mostly at pmol⋅g–1 levels) from 150 sediments collected at the near-to-shore munition dumpsite Kolberger Heide by the German city of Kiel were combined with 16S rRNA gene amplicon sequencing libraries. Prediction was achieved using Random Forests (RFs); the robustness of predictions was validated using Artificial Neural Networks (ANN). To facilitate machine learning with microbiome data we developed the R package phyloseq2ML. Using the most classification-relevant 25 bacterial genera exclusively, potentially representing a TNT-indicative fingerprint, TNT was predicted correctly with up to 81.5% balanced accuracy. False positive classifications indicated that this approach also has the potential to identify samples where the original TNT contamination was no longer detectable. The fact that TNT presence was not among the main drivers of the microbial community composition demonstrates the sensitivity of the approach. Moreover, environmental variables resulted in poorer prediction rates than using microbial fingerprints. Our results suggest that microbial communities can predict even minor influencing factors in complex environments, demonstrating the potential of this approach for the discovery of contamination events over an integrated period of time. Proven for a distinct environment future studies should assess the ability of this approach for environmental monitoring in general.


2021 ◽  
Vol 12 ◽  
Author(s):  
Viola Krukenberg ◽  
Nicholas J. Reichart ◽  
Rachel L. Spietz ◽  
Roland Hatzenpichler

Organic-rich, hydrothermal sediments of the Guaymas Basin are inhabited by diverse microbial communities including many uncultured lineages with unknown metabolic potential. Here we investigated the short-term effect of polysaccharide amendment on a sediment microbial community to identify taxa involved in the initial stage of macromolecule degradation. We incubated anoxic sediment with cellulose, chitin, laminarin, and starch and analyzed the total and active microbial communities using bioorthogonal non-canonical amino acid tagging (BONCAT) combined with fluorescence-activated cell sorting (FACS) and 16S rRNA gene amplicon sequencing. Our results show a response of an initially minor but diverse population of Clostridia particularly after amendment with the lower molecular weight polymers starch and laminarin. Thus, Clostridia may readily become key contributors to the heterotrophic community in Guaymas Basin sediments when substrate availability and temperature range permit their metabolic activity and growth, which expands our appreciation of the potential diversity and niche differentiation of heterotrophs in hydrothermally influenced sediments. BONCAT-FACS, although challenging in its application to complex samples, detected metabolic responses prior to growth and thus can provide complementary insight into a microbial community’s metabolic potential and succession pattern. As a primary application of BONCAT-FACS on a diverse deep-sea sediment community, our study highlights important considerations and demonstrates inherent limitations associated with this experimental approach.


2017 ◽  
Author(s):  
Manuel Kleiner ◽  
Erin Thorson ◽  
Christine E. Sharp ◽  
Xiaoli Dong ◽  
Dan Liu ◽  
...  

AbstractAssessment of microbial community composition is the cornerstone of microbial ecology. Microbial community composition can be analyzed by quantifying cell numbers or by quantifying biomass for individual populations. However, as cell volumes can differ by orders of magnitude, these two approaches yield vastly different results. Methods for quantifying cell numbers are already available (e.g. fluorescence in situ hybridization, 16S rRNA gene amplicon sequencing), yet methods for assessing community composition in terms of biomass are lacking.We developed metaproteomics based methods for assessing microbial community composition using protein abundance as a measure for biomass contributions of individual populations. We optimized the accuracy and sensitivity of the method using artificially assembled microbial communities and found that it is less prone to some of the biases found in sequencing-based methods. We applied the method using communities from two different environments, microbial mats from two alkaline soda lakes and saliva from multiple individuals.


2021 ◽  
Vol 11 (3) ◽  
pp. 1293
Author(s):  
Ana Eusébio ◽  
André Neves ◽  
Isabel Paula Marques

Olive oil and pig productions are important industries in Portugal that generate large volumes of wastewater with high organic load and toxicity, raising environmental concerns. The principal objective of this study is to energetically valorize these organic effluents—piggery effluent and olive mill wastewater—through the anaerobic digestion to the biogas/methane production, by means of the effluent complementarity concept. Several mixtures of piggery effluent were tested, with an increasing percentage of olive mill wastewater. The best performance was obtained for samples of piggery effluent alone and in admixture with 30% of OMW, which provided the same volume of biogas (0.8 L, 70% CH4), 63/75% COD removal, and 434/489 L CH4/kg SVin, respectively. The validation of the process was assessed by molecular evaluation through Next Generation Sequencing (NGS) of the 16S rRNA gene. The structure of the microbial communities for both samples, throughout the anaerobic process, was characterized by the predominance of bacterial populations belonging to the phylum Firmicutes, mainly Clostridiales, with Bacteroidetes being the subdominant populations. Archaea populations belonging to the genus Methanosarcina became predominant throughout anaerobic digestion, confirming the formation of methane mainly from acetate, in line with the greatest removal of volatile fatty acids (VFAs) in these samples.


Author(s):  
Tamara J. H. M. van Bergen ◽  
Ana B. Rios-Miguel ◽  
Tom M. Nolte ◽  
Ad M. J. Ragas ◽  
Rosalie van Zelm ◽  
...  

Abstract Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC–MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. Key points • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change. Graphical abstract


Data ◽  
2021 ◽  
Vol 6 (5) ◽  
pp. 44
Author(s):  
Jae-Hyun Lim ◽  
Il-Nam Kim

Marine bacteria are known to play significant roles in marine biogeochemical cycles regarding the decomposition of organic matter. Despite the increasing attention paid to the study of marine bacteria, research has been too limited to fully elucidate the complex interaction between marine bacterial communities and environmental variables. Jinhae Bay, the study area in this work, is the most anthropogenically eutrophied coastal bay in South Korea, and while its physical and biogeochemical characteristics are well described, less is known about the associated changes in microbial communities. In the present study, we reconstructed a metagenomics data based on the 16S rRNA gene to investigate temporal and vertical changes in microbial communities at three depths (surface, middle, and bottom) during a seven-month period from June to December 2016 at one sampling site (J1) in Jinhae Bay. Of all the bacterial data, Proteobacteria, Bacteroidetes, and Cyanobacteria were predominant from June to November, whereas Firmicutes were predominant in December, especially at the middle and bottom depths. These results show that the composition of the microbial community is strongly associated with temporal changes. Furthermore, the community compositions were markedly different between the surface, middle, and bottom depths in summer, when water column stratification and bottom water hypoxia (low dissolved oxygen level) were strongly developed. Metagenomics data contribute to improving our understanding of important relationships between environmental characteristics and microbial community change in eutrophication-induced and deoxygenated coastal areas.


2013 ◽  
Vol 80 (1) ◽  
pp. 177-183 ◽  
Author(s):  
Lavane Kim ◽  
Eulyn Pagaling ◽  
Yi Y. Zuo ◽  
Tao Yan

ABSTRACTThe impact of substratum surface property change on biofilm community structure was investigated using laboratory biological aerated filter (BAF) reactors and molecular microbial community analysis. Two substratum surfaces that differed in surface properties were created via surface coating and used to develop biofilms in test (modified surface) and control (original surface) BAF reactors. Microbial community analysis by 16S rRNA gene-based PCR-denaturing gradient gel electrophoresis (DGGE) showed that the surface property change consistently resulted in distinct profiles of microbial populations during replicate reactor start-ups. Pyrosequencing of the bar-coded 16S rRNA gene amplicons surveyed more than 90% of the microbial diversity in the microbial communities and identified 72 unique bacterial species within 19 bacterial orders. Among the 19 orders of bacteria detected,BurkholderialesandRhodocyclalesof theBetaproteobacteriaclass were numerically dominant and accounted for 90.5 to 97.4% of the sequence reads, and their relative abundances in the test and control BAF reactors were different in consistent patterns during the two reactor start-ups. Three of the five dominant bacterial species also showed consistent relative abundance changes between the test and control BAF reactors. The different biofilm microbial communities led to different treatment efficiencies, with consistently higher total organic carbon (TOC) removal in the test reactor than in the control reactor. Further understanding of how surface properties affect biofilm microbial communities and functional performance would enable the rational design of new generations of substrata for the improvement of biofilm-based biological treatment processes.


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