Recovering low molecular weight extractives from degraded straw by oyster mushroom at the farm scale for high value use

The cultivation of mushrooms on wheat straw can be considered a solid state fermentation, yet following harvest the residual, partially degraded straw is discarded. During cultivation, the degradation of lignocellulose in the straw takes place by the fungus under the action of enzymes releasing degradation products with small molecular weight, some of which are potentially valuable. These compounds may be extracted from straw after mushroom cultivation in two stages: an aqueous extraction followed by a solvent extraction. The present work is focused on the first stage of the process. The aqueous extraction releases water soluble compounds, such as sugars and phenolics with lower molecular weight, which are easily obtained. The partially degraded straw may then be treated with organic solvents to release water insoluble lignin breakdown products, such as fatty acids, phenolics and other aromatics. It is important to conduct scale-up experiments at a scale that would reflect the amount of waste straw generated by a mushroom farm. A study was performed using a vessel of 300 L capacity with mixing impeller, by observing the influence of the temperature (20oC, 25oC, 40oC, 60oC and 80oC) and water-to-dry straw ratio (from 40:1 to 90:1) on the total extracted matter and especially on sugar and phenolic compounds yields. A microbial study of the aqueous extract was also performed at 20oC and 25oC to explain the high concentration of organic carbon in the extract under certain circumstances. The optimum extraction conditions were determined by taking into account the yield and the energy consumption of the process. The conclusion was that the extraction temperature can be conducted between 20oC and 25oC with good results for obtaining liquor which can be used in a biogas installation. The extraction should be conducted at 80oC to obtain greater yields of sugars and phenolics

Statistical modelling of transcript profiles of differentially regulated genes

Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes

New approaches to investigating the function of mycelial networks

Fungi play a key role in ecosystem nutrient cycles by scavenging, concentrating, translocating and redistributing nitrogen. To quantify and predict fungal nitrogen redistribution, and assess the importance of the integrity of fungal networks in soil for ecosystem function, we need better understanding of the structures and processes involved. Until recently nitrogen translocation has been experimentally intractable owing to the lack of a suitable radioisotope tracer for nitrogen, and the impossibility of observing nitrogen translocation in real time under realistic conditions. We have developed an imaging method for recording the magnitude and direction of amino acid flow through the whole mycelial network as it captures, assimilates and channels its carbon and nitrogen resources, while growing in realistically heterogeneous soil microcosms. Computer analysis and modeling, based on these digitized video records, can reveal patterns in transport that suggest experimentally testable hypotheses. Experimental approaches that we are developing include genomics and stable isotope NMR to investigate where in the system nitrogen compounds are being acquired and stored, and where they are mobilized for transport or broken down. The results are elucidating the interplay between environment, metabolism, and the development and function of transport networks as mycelium forages in soil. The highly adapted and selected foraging networks of fungi may illuminate fundamental principles applicable to other supply networks

Incorporating alternative interaction modes, forbidden links and trait‐based mechanisms increases the minimum trait dimensionality of ecological networks

1. Individual-level traits mediate interaction outcomes and community structure. It is important, therefore, to identify the minimum number of traits that characterise ecological networks, that is, their ‘minimum dimensionality’. Existing methods for estimating minimum dimensionality often lack three features associated with in- creased trait numbers: alternative interaction modes (e.g. feeding strategies such as active vs. sit-and-wait feeding), trait-mediated ‘forbidden links’ and a mechanistic description of interactions. Omitting these features can underestimate the trait numbers involved, and therefore, minimum dimensionality. We develop a ‘mini- mum mechanistic dimensionality’ measure, accounting for these three features.2. The only input our method requires is the network of interaction outcomes. We assume how traits are mechanistically involved in alternative interaction modes. These unidentified traits are contrasted using pairwise performance inequalities between interacting species. For example, if a predator feeds upon a prey spe- cies via a typical predation mode, in each step of the predation sequence, the predator's performance must be greater than the prey's. We construct a system of inequalities from all observed outcomes, which we attempt to solve with mixed integer linear programming. The number of traits required for a feasible system of inequalities provides our minimum dimensionality estimate.3. We applied our method to 658 published empirical ecological networks includ- ing primary consumption, predator–prey, parasitism, pollination, seed dispersal and animal dominance networks, to compare with minimum dimensionality estimates when the three focal features are missing. Minimum dimensionality was typically higher when including alternative interaction modes (54% of empirical networks), ‘forbidden interactions’ as trait-mediated interaction outcomes (92%) or a mechanistic perspective (81%), compared to estimates missing these features. Additionally, we tested minimum dimensionality estimates on simulated networks with known dimensionality. Our method typically estimated a higher minimum dimensionality, closer to the actual dimensionality, while avoiding the overestimation associated with a previous method.4. Our method can reduce the risk of omitting traits involved in different interaction modes, in failure outcomes or mechanistically. More accurate estimates will allow us to parameterise models of theoretical networks with more realistic structure at the interaction outcome level. Thus, we hope our method can improve predictions of community structure and structure-dependent dynamics

A comparison of ergosterol and PLFA methods for monitoring the growth of ligninolytic fungi during wheat straw solid state cultivation

Ergosterol, total phospholipid fatty acid (PLFA) and linoleic acid (18:2n-6) have all been used to determine fungal growth. This paper compares these methods to assess the growth of four different saprotrophic fungal species during solid state cultivation using a wheat straw substrate that have not been compared or measured previously. Ergosterol production appeared to track the mycelia growth well but its production differed considerably between fungi. This means that a specific conversion factor needs to be determined and applied for any given fungus. In comparison, measurements of total PLFA and linoleic acid only showed promise for determining the growth of Postia placenta due to the positive correlation with ergosterol measurements. In contrast, the other fungi tested (Phanerochaete chrysosporium, Serpula lacrymans and Schizophyllum commune) showed either no correlation or in some cases a negative correlation using this assay. The novel findings highlight the variation in fungal fatty acid between species, culture conditions and durations of incubation; suggesting that measurement of linoleic acid is only usable in specific cases. These findings provide important consideration for the study of fungi growing in solid substrates and suggest that the use of PLFA might bias diversity indices

Biochemical characterization of Serpula lacrymans iron-reductase enzymes in lignocellulose breakdown

Putative iron-reductase (IR) genes from Serpula lacrymans with similarity to the conserved iron-binding domains of cellobiose dehydrogenase (CDH) enzymes have been identified. These genes were cloned and expressed to functionally characterize their activity and role in the decomposition of lignocellulose. The results show that IR1 and IR2 recombinant enzymes have the ability to depolymerize both lignin and cellulose, are capable of the reduction of ferric iron to the ferrous form, and are capable of the degradation of nitrated lignin. Expression of these genes during wheat straw solid-state fermentation was shown to correlate with the release of compounds associated with lignin decomposition. The results suggest that both IR enzymes mediate a non-enzymatic depolymerisation of lignocellulose and highlight the potential of chelator-mediated Fenton systems in the industrial pre-treatment of biomass

Space and patchiness affects diversity–function relationships in fungal decay communities

The space in which organisms live determines health and physicality, shaping the way in which they interact with their peers. Space, therefore, is critically important for species diversity and the function performed by individuals within mixed communities. The biotic and abiotic factors defined by the space that organisms occupy are ecologically significant and the difficulty in quantifying space-defined parameters within complex systems limits the study of ecological processes. Here, we overcome this problem using a tractable system whereby spatial heterogeneity in interacting fungal wood decay communities demonstrates that scale and patchiness of territory directly influence coexistence dynamics. Spatial arrangement in 2- and 3-dimensions resulted in measurable metabolic differences that provide evidence of a clear biological response to changing landscape architecture. This is of vital importance to microbial systems in all ecosystems globally, as our results demonstrate that community function is driven by the effects of spatial dynamics

Contrasting demographic histories revealed in two invasive populations of the dry rot fungus Serpula lacrymans

Globalization and international trade have impacted organisms around the world leading to a considerable number of species establishing in new geographic areas. Many organisms have taken advantage of human-made environments, including buildings. One such species is the dry rot fungus Serpula lacrymans, which is the most aggressive wood-decay fungus in indoor environments in temperate regions. Using population genomic analyses of 36 full genome sequenced isolates, we demonstrated that European and Japanese isolates are highly divergent and the populations split 3000–19,000 generations ago, probably predating human influence. Approximately 250 generations ago, the European population went through a tight bottleneck, probably corresponding to the fungus colonization of the built environment in Europe. The demographic history of these populations, probably lead to low adaptive potential. Only two loci under selection were identified using a Fst outlier approach, and selective sweep analyses identified three loci with extended haplotype homozygosity. The selective sweep analyses found signals in genes possibly related to decay of various substrates in Japan and in genes involved DNA replication and protein modification in Europe. Our results suggest that the dry rot fungus independently established in indoor environments in Europe and Japan and that invasive species can potentially establish large populations in new habitats based on a few colonizing individuals

Proliferating particle surface area via microbial decay has profound consequences for remineralisation rate: a new approach to modelling the degradation of sinking detritus in the ocean

Sinking detritus particles in the ocean help to regulate global climate by transporting organic carbon into deep waters where it is sequestered from the atmosphere. The rate at which bacteria remineralise detritus influences how deep particles sink and the length-scale of carbon sequestration. Conventional marine biogeochemical models typically represent particles as smooth spheres where remineralisation causes surface area (SA) to progressively shrink over time. In contrast, we propose that particle SA increases during degradation as microbial ectoenzymes cause a roughening of surfaces in a process similar to acid etching on previously smooth glass or metal surfaces. This concept is investigated using a novel model, SAMURAI (Surface Area Modelling Using Rubik As Inspiration), in which the biomass of individual particles is represented as a 3D matrix of cubical sub-units that degrades by progressive removal of sub-units that have faces in contact with the external environment. The model rapidly generates microscale rugosity (roughness) that profoundly increases total SA, giving rise to biomass-specific remineralisation rates that are approximately double those of conventional models. Faster remineralisation means less carbon penetrates the ocean’s interior, diminishing carbon sequestration in deep waters. Results indicate that both SA and microbial remineralisation are highly dynamic, as well as exhibiting large variability associated with particles of different porosities. Our work highlights the need for further studies, both observational and modelling, to investigate particle SA and related microbial dynamics in order to reliably represent the role of ocean biology in global biogeochemical models

The need to promote sleep health in public health agendas across the globe.

Healthy sleep is essential for physical and mental health, and social wellbeing; however, across the globe, and particularly in developing countries, national public health agendas rarely consider sleep health. Sleep should be promoted as an essential pillar of health, equivalent to nutrition and physical activity. To improve sleep health across the globe, a focus on education and awareness, research, and targeted public health policies are needed. We recommend developing sleep health educational programmes and awareness campaigns; increasing, standardising, and centralising data on sleep quantity and quality in every country across the globe; and developing and implementing sleep health policies across sectors of society. Efforts are needed to ensure equity and inclusivity for all people, particularly those who are most socially and economically vulnerable, and historically excluded