From lab to industry: Methods for biomass quantification in basidiomycetous fungi

Analysis of toxigenic fungi and their mycotoxins in biotic interactions

Evaluation of factors influencing dairy biofilm formation in filling hoses of food-processing equipment

Fusarium is a large and complex genus, comprises important pathogens most of which are able to produce mycotoxins. Maize is a host of several Fusarium species that cause ear rot, kernel rot, stalk rot and also seedling blight. Fusarium contamination of kernels and maize products had always been a serious concern. Owing to the positive correlation between fungal biomass and mycotoxin content, quantification of fungal DNA in plant materials would be considered as an initial fast and cost-effective mean to evaluate the risk of grain contamination. Several quantification methods are well-known of which real-time PCR (qPCR) has been used as an effective tool for species-specific quantification of fungal biomass in plant tissues. The method mostly relies on standard thermocyclers (96-well or 384-well blocks) with a separate run for each template and usually set in total reaction volume of 15 to 25 µl. In this investigation, we developed a multi-species qPCR assay for simultaneous quantification of genomic DNA of the nine Fusarium species with 384-well microplates in a total volume of 4 µl. The sensitivity of the method ranged from 0.05 - 1.52 pg DNA per reaction, and the repeatability ranged from 0.81% to 1.71% RSD. Developed low volume qPCR assay was successfully employed for the analysis of weed plants to the infection of nine Fusarium spp. The main objectives were determination the role of weeds in the survival of maize fusarium pathogens and assessment of their ability for producing of the main mycotoxins. The Real-time PCR detected eight Fusarium species in 201 weed samples representing 36 weed species, collected from maize fields. The highest frequency was observed for F. equiseti (49%) and F. avenaceum (34.7%). Similar diversity of Fusarium spp. was observed in both conventional and organic farming systems. Isolation of Fusarium strains from 12 common weed species were carried out, the strains were identified based on the morphological characters and then identification was confirmed by using the translation elongation factor 1-alpha (TEF-1α) gene sequence. The recovery rate was high for F. equiseti (32.7%) and F. avenaceum (21%). None of the field samples as well as weed plants tested in inoculation studies show obvious symptoms of Fusarium infection. Re-isolation of the strains from artificially inoculated plants confirmed the endophytic infection of weeds by Fusarium spp. The present study reports five new alternative hosts for Fusarium species in maize fields. High incidence rate of beauvericin and enniatins contamination was obtained in weed samples while trichothecenes, fumonisins and zearalenone were not detected in any of the weeds studied. Although toxicity of fumonisins to plants and field animals has been clearly demonstrated, the function of this toxin, however, in virulence of F. verticillioides toward maize plants is still unknown. In present study, virulence of two non-fumonisins producing strains (fum 1-3 and fum 1-4) and their progenitors (FUM 1-1) was assessed on different plants including maize, sorghum, rice and beetroot seedlings grown under greenhouse conditions. The quantity of fungal biomass in plant tissues was considered as an indicator of fungal aggressiveness and it was measured by the developed low volume qPCR protocol. There was no significant (P = 0.05) differences between each wild type and the relevant mutant for colonization of plant tissues. In inoculated maize, rice and beetroot seedlings, systemic fungal infection was observed from roots to the aboveground parts; but rate of systemic transmission was low in sorghum plants. Although our results are not enough to make a final conclusion of fumonisin function in virulence of F. verticillioides on rice and sorghum seedlings, however, the results show diseases incidence was independent of fumonisins production in maize seedlings. In our system, therefore, fumonisins had no role as a pathogenicity factor.

Comparison of three assays for the quantification of Candida biomass in suspension and CDC reactor grown biofilms

Production of lignocellulolytic enzymes by filamentous fungi have a great potential at industrial level due to their widespread applications. Mixed fungal cultures and particularly mixed fungal biofilms constitute a promising fermentation system for an enhanced enzyme production. However, it has not been addressed how much of this enhancement depends on the mixed biomass proportion. In this sense, the aim of this study was to develop a method to specifically and accurately quantify mixed fungal biomass. For this purpose, mixed biofilm cultures composed of Aspergillus niger and Trichoderma reesei, two filamentous fungi used industrially for cellulase production, were collected from 48 to 120 h of growth; mycelia were pulverized, and DNA was extracted for qPCR assays with specific primers for each fungus. Primers were designed from non-conserved regions of sequences of actin and β-tubulin genes of both A. niger and T. reesei. Specificity of these primers was tested in silico and experimentally. A statistically significant correlation was obtained between qPCR-calculated biomass and dry weight biomass data. By this method, it was possible to detect changes on mycelia proportions in biofilms over time, suggesting a competitive interaction between these two fungi. In conclusion, this method allows a specific and accurate quantification of mixed fungal biomass and could be also applied to different mixed culture systems for studying microbial interactions.

Bloom-forming toxic cyanobacterium Microcystis: Quantification and monitoring with a high-frequency echosounder

Roots support plant growth and resilience and are a major route for carbon sequestration. Thus, the study of roots in agricultural and natural systems is essential to develop strategies to mitigate and adjust to climate change. Methods to quantify root biomass in mono- and mixed crop systems are therefore in high demand. A promising approach is to exploit the correlation between root biomass and nuclear DNA. The use of qPCR for the quantitative analysis of root samples has been reported. Here, we show how digital PCR can be used to quantify root DNA from soil samples harboring single species or species mixtures. This molecular method has several advantages over more time-consuming methods, including enhanced sensitivity and absolute quantification of target DNA, increased accuracy and reliability, and the ability to quantify roots directly from soil in different species mixtures. We developed a DNA-based digital droplet PCR (ddPCR) method for root species profiling and biomass quantification directly from soil samples under semi-field conditions. Our findings suggest that implementing this ddPCR method can substantially simplify and improve root quantification of specific species, even in crop mixtures. This method offers a more time- and labor-efficient alternative to traditional techniques (e.g. root separation or C13 labeling). The complement of primer-probe sets presented here can be continuously expanded to include additional plant species, thus broadening the scope of this DNA-based ddPCR method.

Os objetivos deste trabalho foram quantificar a biomassa e a estocagem de carbono em uma Floresta Estacional Semidecidual,com área de 44,11 ha, localizado no Parque Tecnológico de Viçosa, MG e avaliar as diferenças entre as metodologias de quantificação de biomassa propostas pelo Painel Intergovernamental sobre Mudanças do Clima (IPCC) e utilizando equações regionais. Para a quantificação da biomassa e estocagem de carbono da área utilizou-se duas metodologias distintas, uma com equações regionais e outra sugerida pelo IPCC. Os estoques totais de biomassa e de carbono foram de 116,98 t ha-1 e 56,31 t ha-1,respectivamente, pela metodologia de equações regionais, considerando os valores acima e abaixo do solo, sub-bosque e serapilheira. E pela metodologia sugerida pelo IPCC, os estoques totais de biomassa e de carbono foram de 107,59 t ha-1 e 48,70 t ha-1, respectivamente. De acordo com os resultados a metodologia do IPCC subestimou a biomassa e o carbono em relação às equações regionais.

ABSTRACTThe development of a fully automated on-line monitoring and control system is very important in bioprocesses. One of the most important parameters in these processes is biomass. This review discusses different methods for biomass quantification. A general definition of biomass and biovolume are presented. Interesting concepts about active but not culturable cells considerations are included as well as concepts that must be taken into account when selecting biomass quantification technology. Chemical methods have had few applications in biomass measurement to date; however, bioluminescence can selectively enumerate viable cells. Photometric methods including fluorescence and scattered light measurements are presented. Reference methods including dry and wet weight, viable counts and direct counts are discussed, as well as the physical methods of flow cytometry, impedancimetric and dielectric techniques.

Various methods have been reported to quantify total biofilm or different components of biofilm; however, these methods are often confusedly used, leading to discrepancies and misleading results. In this study, different methods for quantification of biofilm, including those for total biomass, total amount of bacterial cells, viable cell number, and amount of extracellular polymeric substances, were systematically compared in microtiter plates. To evaluate which method is suitable for assessment of biofilm removal and for bacterial killing, biofilm samples were treated with various cleaners possessing removing and/or killing capacities. It was found that most of the methods tested in this study in general exhibited high reproducibility and repeatability. Crystal Violet staining was a simple but reliable method for total biomass quantification. Total bacteria cell numbers could be reliably quantified by the fluorescent DNA-binding dye Acridine Orange. Viable cells could be quantified by either an ATP-based assay or a proliferation assay. Both of these viability methods showed a broad detection range and led to precise measurement. For quantification of proteins in the biofilm, staining with fluorescein isothiocyanate was most suitable. Furthermore, it was revealed that a combination of different methods is required to determine if a cleaner kills or removes biofilm.Electronic supplementary materialThe online version of this article (doi:10.1007/s00253-016-7396-9) contains supplementary material, which is available to authorized users.

Chlorella vulgaris is of great importance in numerous exploratory or industrial applications (e.g., medicals, food, and feed additives). Rapid quantification of algal biomass is crucial in photobioreactors for the optimization of nutrient management and the estimation of production. The main goal of this study is to provide a simple, rapid, and not-resource-intensive estimation method for determining the algal density of C. vulgaris according to the measured parameters using UV-Vis spectrophotometry. Comparative assessment measurements were conducted with seven different methods (e.g., filtration, evaporation, chlorophyll a extraction, and detection of optical density and fluorescence) to determine algal biomass. By analyzing the entire spectra of diluted algae samples, optimal wavelengths were determined through a stepwise series of linear regression analyses by a novel correlation scanning method, facilitating accurate parameter estimation. Nonlinear formulas for spectrometry-based estimation processes were derived for each parameter. As a result, a general formula for biomass concentration estimation was developed, with recommendations for suitable measuring devices based on algae concentration levels. New values for magnesium content and the average single-cell weight of C. vulgaris were established, in addition to the development of a rapid, semiautomated cell counting method, improving efficiency and accuracy in algae quantification for cultivation and biotechnology applications.

New method for rapid identification and quantification of fungal biomass using ergosterol autofluorescence

Application of AC-Impedance in microbial cultivation system for in-situ biomass measurements

Lentinula edodes, commonly known as shiitake, is an edible mushroom that is cultivated and consumed around the globe, especially in Asia. Monitoring mycelial growth inside a woody substrate is difficult, but it is essential for effective management of mushroom cultivation. Mycelial biomass also affects the rate of wood decomposition under natural conditions and must be known to determine the metabolic quotient, an important ecophysiological parameter of fungal growth. Therefore, developing a method to measure it inside a substrate would be very useful. In this study, as the first step in understanding species-specific rates of fungal decomposition of wood, we developed species-specific primers and qPCR procedures for L. edodes. We tested primer specificity using strains of L. edodes from Japan and Southeast Asia, as well as related species of fungi and plant species for cultivation of L. edodes, and generated a calibration curve for quantification of mycelial biomass in wood dust inoculated with L. edodes. The qPCR procedure we developed can specifically detect L. edodes and allowed us to quantify the increase in L. edodes biomass in wood dust substrate and calculate the metabolic quotient based on the mycelial biomass and respiration rate. Development of a species-specific method for biomass quantification will be useful for both estimation of mycelial biomass and determining the kinetics of fungal growth in decomposition processes.

The timely and accurate quantification of grassland biomass is a prerequisite for sustainable grazing management. With advances in artificial intelligence, the launch of new satellites, and perceived efficiency gains in the time and cost of the quantification of remote methods, there has been growing interest in using satellite imagery and machine learning to quantify pastures at the field scale. Here, we systematically reviewed 214 journal articles published between 1991 to 2021 to determine how vegetation indices derived from satellite imagery impacted the type and quantification of pasture indicators. We reveal that previous studies have been limited by highly spatiotemporal satellite imagery and prognostic analytics. While the number of studies on pasture classification, degradation, productivity, and management has increased exponentially over the last five years, the majority of vegetation parameters have been derived from satellite imagery using simple linear regression approaches, which, as a corollary, often result in site-specific parameterization that become spurious when extrapolated to new sites or production systems. Few studies have successfully invoked machine learning as retrievals to understand the relationship between image patterns and accurately quantify the biophysical variables, although many studies have purported to do so. Satellite imagery has contributed to the ability to quantify pasture indicators but has faced the barrier of monitoring at the paddock/field scale (20 hectares or less) due to (1) low sensor (coarse pixel) resolution, (2) infrequent satellite passes, with visibility in many locations often constrained by cloud cover, and (3) the prohibitive cost of accessing fine-resolution imagery. These issues are perhaps a reflection of historical efforts, which have been directed at the continental or global scales, rather than at the field level. Indeed, we found less than 20 studies that quantified pasture biomass at pixel resolutions of less than 50 hectares. As such, the use of remote sensing technologies by agricultural practitioners has been relatively low compared with the adoption of physical agronomic interventions (such as ‘no-till’ practices). We contend that (1) considerable opportunity for advancement may lie in fusing optical and radar imagery or hybrid imagery through the combination of optical sensors, (2) there is a greater accessibility of satellite imagery for research, teaching, and education, and (3) developers who understand the value proposition of satellite imagery to end users will collectively fast track the advancement and uptake of remote sensing applications in agriculture.