Understanding and Predicting Foam in Anaerobic Digester

As a result of the ambiguity and complexity surrounding anaerobic digester foaming, efforts have been made by various researchers to understand the process of anaerobic digester foaming so as to proffer a solution that can be universally applied rather than site specific. All attempts ranging from experimental analysis to comparative review of other process has not fully explained the conditions and process of foaming in anaerobic digester. Studying the current available knowledge on foam formation and relating it to anaerobic digester process and operating condition, this piece of work presents a succinct and enhanced understanding of foaming in anaerobic digesters as well as introducing a simple method to identify the onset of anaerobic digester foaming based on analysis of historical data from a field scale system

Systems biology approach to elucidation of contaminants biodegradation in complex samples- integration of high-resolution analytical and molecular tools

We present here a data-driven systems biology framework to the rational design of biotechnological solutions for contaminated environments with the aim of understanding the interactions and mechanisms underpinning the role of microbial communities in the biodegradation of contaminated soils. We have considered a multi-omics approach which employs novel in silico tools to combine high-throughput sequencing data (16S rRNA amplicons) with the chemical data including high-resolution analytical data generated by comprehensive two-dimensional gas chromatography (GCxGC). To assess this approach, we have considered a matching dataset with both microbiological and chemical signatures available for samples from two former manufactured gas plant sites. On this dataset, we applied the numerical procedures informed by ecological principles (predominantly diversity measures) as well as recently published statistical approaches that give discriminatory features and their correlations by maximizing the covariances between multiple datasets on the same sample space. In particular, we have utilized sparse projection to latent discriminant analysis and its derivative to multiple datasets, an N-integration algorithm called DIABLO. Our results indicate microbial community structure dependent on the contaminated environment and unravel promising interactions of some of the microbial species with the biodegradation potential. To the best of our knowledge, this is the first study that incorporates with microbiome an unprecedented high-level distribution of hydrocarbons obtained through GC x GC

Spatial patterns in soil organic matter dynamics are shaped by mycorrhizosphere interactions in a treeline forest

Aims In the Swedish sub-Arctic, mountain birch (Betula pubescens ssp. czerepanovii) forests mediate rapid soil C cycling relative to adjacent tundra heaths, but little is known about the role of individual trees within forests. Here we investigate the spatial extent over which trees influence soil processes. Methods We measured respiration, soil C stocks, root and mycorrhizal productivity and fungi:bacteria ratios at fine spatial scales along 3 m transects extending radially from mountain birch trees in a sub-Arctic ecotone forest. Root and mycorrhizal productivity was quantified using in-growth techniques and fungi:bacteria ratios were determined by qPCR. Results Neither respiration, nor root and mycorrhizal production, varied along transects. Fungi:bacteria ratios, soil organic C stocks and standing litter declined with increasing distance from trees. Conclusions As 3 m is half the average size of forest gaps, these findings suggest that forest soil environments are efficiently explored by roots and associated mycorrhizal networks of B. pubescens. Individual trees exert influence substantially away from their base, creating more uniform distributions of root, mycorrhizal and bacterial activity than expected. However, overall rates of soil C accumulation do vary with distance from trees, with potential implications for spatio-temporal soil organic matter dynamics and net ecosystem C sequestration

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

8 páginas, 4 figuras. -- The first publication is available at https://www.nature.comThe temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.We gratefully acknowledge financial support from the National Research Foundation of South Africa (grant no.81779 and TTK2008052000003), the Research Council of Norway (grant No. 180352) and the University of the Western Cape. Partial support was also provided under the Laboratory Directed Research and Development Program at PNNL, a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy under contract DE-AC05-76RL01830.Peer reviewe

Biodegradation of the herbicide mecoprop-p with soil depth and its relationship with class III tfdA genes

Mecoprop-p [(R)-2-(4-chloro-2-methylphenoxy) propanoic acid) is widely used 37 in agriculture and poses an environmental concern because of its susceptibility to leach 38 from soil to water. We investigated the effect of soil depth on mecoprop-p 39 biodegradation and its relationship with the number and diversity of tfdA related genes, 40 which are the most widely known genes involved in degradation of the 41 phenoxyalkanoic acid group of herbicides by bacteria. Mecoprop-p half-life (DT50) was 42 approximately 12 days in soil sampled from <30 cm depth, and increased progressively 43 with soil depth, reaching over 84 days at 70-80 cm. In sub-soil there was a lag period of 44 between 23 and 34 days prior to a phase of rapid degradation. No lag phase occurred in 45 top-soil samples prior to the onset of degradation. The maximum degradation rate was 46 the same in top-soil and sub-soil samples. Although diverse tfdAα and tfdA genes were 47 present prior to mecoprop-p degradation, real time PCR revealed that degradation was 48 associated with proliferation of tfdA genes. The number of tfdA genes and the most 49 probable number of mecoprop-p degrading organisms in soil prior to mecoprop-p 50 addition were below the limit of quantification and detection respectively. Melting 51 curves from the real time PCR analysis showed that prior to mecoprop-p degradation 52 both class I and class III tfdA genes were present in top- and sub-soil samples. However 53 at all soil depths only tfdA class III genes proliferated during degradation. Denaturing 54 gradient gel electrophoresis confirmed that class III tfdA genes were associated with 55 mecoprop-p degradation. Degradation was not associated with the induction of novel 56 tfdA genes in top- or sub-soil samples, and there were no apparent differences in tfdA 57 gene diversity with soil depth prior to or following degradation