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Abstract Microbial activity is the driving force of the carbon cycle, including the digestion of biomass in the soil, oceans, and oil deposits. This natural diversity of microbial carbon sources poses challenges for humans. Contamination monitoring can be difficult in oil tanks and similar settings. To assess microbial activity in such industrial settings, off‐gas analysis can be employed by considering growth and non‐growth‐associated metabolic activity. In this work, we describe the monitoring of CO2 as a method for measuring microbial activity. We revealed that the CO2 signal corresponds to classical growth curves, exemplified by Pseudomonas fluorescens, Yarrowia lipolytica, and Penicillium chrysogenum. Deviations of the CO2 signal from the growth curves occurred when the yield of biomass on the substrate changed (i.e., the non‐growth‐associated metabolic activities). We monitored CO2 to track the onset of microbial contamination in an oil tank. This experimental setup was applied to determine the susceptibility of heating oil and biodiesel to microbial contamination long before the formation of problematic biofilms. In summary, the measurement of CO2 production by bacteria, yeasts, and molds allowed the permanent monitoring of microbial activity under oil storage conditions without invasive sampling.

While working on an identification guide to the sawflies of Fennoscandia, we encountered numerous taxonomic problems, for some of which we present solutions. Dicrostema Benson, 1952 is a new synonym of Phymatoceropsis Rohwer, 1916, and not congeneric with Paracharactus MacGillivray, 1908. Two species occurring in Europe are transferred to Phymatoceropsis. Dolerus aericepsellus Heidemaa and Mutanen sp. nov. and Heptamelus viitasaarii Liston, Mutanen and Prous sp. nov. are described from Finland. Abia brevicornis Leach, 1817 nom. rev. is the valid name of Abia nitens auct. nec Linnaeus, and Abia nitens (Linnaeus, 1758) is the valid name for what has recently been called Abia sericea (Linnaeus, 1767). Tenthredo haemorrhoidalis Fabricius, 1781 is treated as an unplaced species of Hymenoptera, possibly Ichneumonoidea. Calameuta variabilis (Mocsáry, 1886) is the valid name of the species recently generally called C. haemorrhoidalis. Claremontia confusa (Konow, 1886) sp. rev. and Claremontia brevicornis (Brischke, 1883) are distinct species. Dolerus coracinus (Klug, 1818) is the valid name for D. anthracinus auct. Dolerus anthracinus (Klug, 1818) is a valid species similar to D. nitens Zaddach, 1859. Dolerus coruscans Konow, 1890 sp. rev. is a valid species. Dolerus junci (Stephens, 1835) is the valid name for Dolerus cothurnatus auct. Dolerus timidus (Klug, 1818) sp. rev. is distinguished from the similar D. pratensis (Linnaeus, 1758). A neotype is designated for Astatus punctatus Klug, 1803. Lectotypes are designated for 39 nominal species. 29 species group names are new junior synonyms. We present data on some species recently collected for the first time in Finland, including first records for the Palaearctic and West Palaearctic.

Dascillidae are a species-poor beetle group with a scarce fossil record. Here, we describe Baltodascillus serraticornis gen. et sp. nov. based on a well-preserved specimen from Eocene Baltic amber. It differs from all known Dascillidae by its reduced mandibles. After studying the specimen using light microscopy and X-ray microtomography, we tentatively place this genus in the poorly defined subfamily Karumiinae based on the large eyes, serrate antennae, and lack of prosternal process. This is the first representative of the Dascillidae formally described from Baltic amber and the first described fossil member of the subfamily Karumiinae. We briefly discuss the problematic higher classification of Dascillidae, along with the morphology and biogeography of the group.

Abstract Background Ogataea polymorpha is a thermotolerant, methylotrophic yeast with significant industrial applications. While previously mainly used for protein synthesis, it also holds promise for producing platform chemicals. O. polymorpha has the distinct advantage of using methanol as a substrate, which could be potentially derived from carbon capture and utilization streams. Full development of the organism into a production strain and estimation of the metabolic capabilities require additional strain design, guided by metabolic modeling with a genome-scale metabolic model. However, to date, no genome-scale metabolic model is available for O. polymorpha. Results To overcome this limitation, we used a published reconstruction of the closely related yeast Komagataella phaffii as a reference and corrected reactions based on KEGG and MGOB annotation. Additionally, we conducted phenotype microarray experiments to test the suitability of 190 substrates as carbon sources. Over three-quarter of the substrate use was correctly reproduced by the model and 27 new substrates were added, that were not present in the K. phaffii reference model. Conclusion The developed genome-scale metabolic model of O. polymorpha will support the engineering of synthetic metabolic capabilities and enable the optimization of production processes, thereby supporting a sustainable future methanol economy.

Abstract Background Itaconic acid is a bio-derived platform chemical with uses ranging from polymer synthesis to biofuel production. The efficient conversion of cellulosic waste streams into itaconic acid could thus enable the sustainable production of a variety of substitutes for fossil oil based products. However, the realization of such a process is currently hindered by an expensive conversion of cellulose into fermentable sugars. Here, we present the stepwise development of a fully consolidated bioprocess (CBP), which is capable of directly converting recalcitrant cellulose into itaconic acid without the need for separate cellulose hydrolysis including the application of commercial cellulases. The process is based on a synthetic microbial consortium of the cellulase producer Trichoderma reesei and the itaconic acid producing yeast Ustilago maydis. A method for process monitoring was developed to estimate cellulose consumption, itaconic acid formation as well as the actual itaconic acid production yield online during co-cultivation. Results The efficiency of the process was compared to a simultaneous saccharification and fermentation setup (SSF). Because of the additional substrate consumption of T. reesei in the CBP, the itaconic acid yield was significantly lower in the CBP than in the SSF. In order to increase yield and productivity of itaconic acid in the CBP, the population dynamics was manipulated by varying the inoculation delay between T. reesei and U. maydis. Surprisingly, neither inoculation delay nor inoculation density significantly affected the population development or the CBP performance. Instead, the substrate availability was the most important parameter. U. maydis was only able to grow and to produce itaconic acid when the cellulose concentration and thus, the sugar supply rate, was high. Finally, the metabolic processes during fed-batch CBP were analyzed in depth by online respiration measurements. Thereby, substrate availability was again identified as key factor also controlling itaconic acid yield. In summary, an itaconic acid titer of 34 g/L with a total productivity of up to 0.07 g/L/h and a yield of 0.16 g/g could be reached during fed-batch cultivation. Conclusion This study demonstrates the feasibility of consortium-based CBP for itaconic acid production and also lays the fundamentals for the development and improvement of similar microbial consortia for cellulose-based organic acid production.

With their ability of CO2 fixation using sunlight as an energy source, algae and especially microalgae are moving into the focus for the production of proteins and other valuable compounds. However, the valorization of algal biomass depends on the effective disruption of the recalcitrant microalgal cell wall. Especially cell walls of Chlorella species proved to be very robust. The wall structures that are responsible for this robustness have been studied less so far. Here, we evaluate different common methods to break up the algal cell wall effectively and measure the success by protein and carbohydrate release. Subsequently, we investigate algal cell wall features playing a role in the wall’s recalcitrance towards disruption. Using different mechanical and chemical technologies, alkali catalyzed hydrolysis of the Chlorella vulgaris cells proved to be especially effective in solubilizing up to 56 wt% protein and 14 wt% carbohydrates of the total biomass. The stepwise degradation of C. vulgaris cell walls using a series of chemicals with increasingly strong conditions revealed that each fraction released different ratios of proteins and carbohydrates. A detailed analysis of the monosaccharide composition of the cell wall extracted in each step identified possible factors for the robustness of the cell wall. In particular, the presence of chitin or chitin-like polymers was indicated by glucosamine found in strong alkali extracts. The presence of highly ordered starch or cellulose was indicated by glucose detected in strong acidic extracts. Our results might help to tailor more specific efforts to disrupt Chlorella cell walls and help to valorize microalgae biomass.

Microbial co-cultures have been used in several biotechnological applications. Within these co-cultures, the microorganisms tend to interact with each other and perform complex actions. Investigating metabolic interactions in microbial co-cultures is crucial in designing microbial consortia. Here, we present a pipeline integrating modelling and experimental approaches to understand metabolic interactions between organisms in a community. We define a new index named “Metabolic Support Index (MSI)”, which quantifies the benefits derived by each organism in the presence of the other when grown as a co-culture. We computed MSI for several experimentally demonstrated co-cultures and showed that MSI, as a metric, accurately identifies the organism that derives the maximum benefit. We also computed MSI for a commonly used yeast co-culture consisting of Saccharomyces cerevisiae and Pichia stipitis and observed that the latter derives higher benefit from the interaction. Further, we designed two-stage experiments to study mutual interactions and showed that P. stipitis indeed derives the maximum benefit from the interaction, as shown from our computational predictions. Also, using our previously developed computational tool MetQuest, we identified all the metabolic exchanges happening between these organisms by analysing the pathways spanning the two organisms. By analysing the HPLC profiles and studying the isotope labelling, we show that P. stipitis consumes the ethanol produced by S. cerevisiae when grown on glucose-rich medium under aerobic conditions, as also indicated by our in silico pathway analyses. Our approach represents an important step in understanding metabolic interactions in microbial communities through an integrated computational and experimental workflow.

Abstract Background Ustilago cynodontis ranks among the relatively unknown itaconate production organisms. In comparison to the well-known and established organisms like Aspergillus terreus and Ustilago maydis, genetic engineering and first optimizations for itaconate production were only recently developed for U. cynodontis, enabling metabolic and morphological engineering of this acid-tolerant organism for efficient itaconate production. These engineered strains were so far mostly characterized in small scale shaken cultures. Results In pH-controlled fed-batch experiments an optimum pH of 3.6 could be determined for itaconate production in the morphology-engineered U. cynodontis Δfuz7. With U. cynodontis ∆fuz7 r ∆cyp3 r P etef mttA P ria1 ria1, optimized for itaconate production through the deletion of an itaconate oxidase and overexpression of rate-limiting production steps, titers up to 82.9 ± 0.8 g L−1 were reached in a high-density pulsed fed-batch fermentation at this pH. The use of a constant glucose feed controlled by in-line glucose analysis increased the yield in the production phase to 0.61 gITA gGLC−1, which is 84% of the maximum theoretical pathway yield. Productivity could be improved to a maximum of 1.44 g L−1 h−1 and cell recycling was achieved by repeated-batch application. Conclusions Here, we characterize engineered U. cynodontis strains in controlled bioreactors and optimize the fermentation process for itaconate production. The results obtained are discussed in a biotechnological context and show the great potential of U. cynodontis as an itaconate producing host.

Abstract Background Itaconic acid is an unsaturated, dicarboxylic acid which finds a wide range of applications in the polymer industry and as a building block for fuels, solvents and pharmaceuticals. Currently, Aspergillus terreus is used for industrial production, with titers above 100 g L−1 depending on the conditions. Besides A. terreus, Ustilago maydis is also a promising itaconic acid production host due to its yeast-like morphology. Recent strain engineering efforts significantly increased the yield, titer and rate of production. Results In this study, itaconate production by U. maydis was further increased by integrated strain- and process engineering. Next-generation itaconate hyper-producing strains were generated using CRISPR/Cas9 and FLP/FRT genome editing tools for gene deletion, promoter replacement, and overexpression of genes. The handling and morphology of this engineered strain were improved by deletion of fuz7, which is part of a regulatory cascade that governs morphology and pathogenicity. These strain modifications enabled the development of an efficient fermentation process with in situ product crystallization with CaCO3. This integrated approach resulted in a maximum itaconate titer of 220 g L−1, with a total acid titer of 248 g L−1, which is a significant improvement compared to best published itaconate titers reached with U. maydis and with A. terreus. Conclusion In this study, itaconic acid production could be enhanced significantly by morphological- and metabolic engineering in combination with process development, yielding the highest titer reported with any microorganism.

Metabolic engineering relies on modifying gene expression to regulate protein concentrations and reaction activities. The gene expression is controlled by the promoter sequence, and sequence libraries are used to scan expression activities and to identify correlations between sequence and activity. We introduce a computational workflow called Exp2Ipynb to analyze promoter libraries maximizing information retrieval and promoter design with desired activity. We applied Exp2Ipynb to seven prokaryotic expression libraries to identify optimal experimental design principles. The workflow is open source, available as Jupyter Notebooks and covers the steps to 1) generate a statistical overview to sequence and activity, 2) train machine-learning algorithms, such as random forest, gradient boosting trees and support vector machines, for prediction and extraction of feature importance, 3) evaluate the performance of the estimator, and 4) to design new sequences with a desired activity using numerical optimization. The workflow can perform regression or classification on multiple promoter libraries, across species or reporter proteins. The most accurate predictions in the sample libraries were achieved when the promoters in the library were recognized by a single sigma factor and a unique reporter system. The prediction confidence mostly depends on sample size and sequence diversity, and we present a relationship to estimate their respective effects. The workflow can be adapted to process sequence libraries from other expression-related problems and increase insight to the growing application of high-throughput experiments, providing support for efficient strain engineering.

ABSTRACT It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes. IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today’s whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli. Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.

Abstract Background Thermotolerance is a highly desirable trait of microbial cell factories and has been the focus of extensive research. Yeast usually tolerate only a narrow temperature range and just two species, Kluyveromyces marxianus and Ogataea polymorpha have been described to grow at reasonable rates above 40 °C. However, the complex mechanisms of thermotolerance in yeast impede its full comprehension and the rare physiological data at elevated temperatures has so far not been matched with corresponding metabolic analyses. Results To elaborate on the metabolic network response to increased fermentation temperatures of up to 49 °C, comprehensive physiological datasets of several Kluyveromyces and Ogataea strains were generated and used for 13C-metabolic flux analyses. While the maximum growth temperature was very similar in all investigated strains, the metabolic network response to elevated temperatures was not conserved among the different species. In fact, metabolic flux distributions were remarkably irresponsive to increasing temperatures in O. polymorpha, while the K. marxianus strains exhibited extensive flux rerouting at elevated temperatures. Conclusions While a clear mechanism of thermotolerance is not deducible from the fluxome level alone, the generated data can be valued as a knowledge repository for using temperature to modulate the metabolic activity towards engineering goals.

The question of what determines whether cells are big or small has been the focus of many studies because it is thought that such determinants underpin the coupling of cell growth with cell division. In contrast, what determines the overall pattern of how cell size is distributed within a population of wild type or mutant cells has received little attention. Knowing how cell size varies around a characteristic pattern could shed light on the processes that generate such a pattern and provide a criterion to identify its genetic basis. Here, we show that cell size values of wild type Saccharomyces cerevisiae cells fit a gamma distribution, in haploid and diploid cells, and under different growth conditions. To identify genes that influence this pattern, we analyzed the cell size distributions of all single-gene deletion strains in Saccharomyces cerevisiae. We found that yeast strains which deviate the most from the gamma distribution are enriched for those lacking gene products functioning in gene expression, especially those in transcription or transcription-linked processes. We also show that cell size is increased in mutants carrying altered activity substitutions in Rpo21p/Rpb1, the largest subunit of RNA polymerase II (Pol II). Lastly, the size distribution of cells carrying extreme altered activity Pol II substitutions deviated from the expected gamma distribution. Our results are consistent with the idea that genetic defects in widely acting transcription factors or Pol II itself compromise both cell size homeostasis and how the size of individual cells is distributed in a population.

Understanding the composability of genetic elements is central to synthetic biology. Even for seemingly well-known elements such as a sigma 70 promoter the genetic context-dependent variability of promoter activity remains poorly understood. The lack of understanding of sequence to function results in highly limited de novo design of novel genetic element combinations. To address this issue, we characterized in detail concatenated “stacked” synthetic promoters including varying spacer sequence lengths and compared the transcription strength to the output of the individual promoters. The proxy for promoter activity, the msfGFP synthesis from stacked promoters was consistently lower than expected from the sum of the activities of the single promoters. While the spacer sequence itself had no activity, it drastically affected promoter activities when placed up- or downstream of a promoter. Single promoter-spacer combinations revealed a bivalent effect on msfGFP synthesis. By systematic analysis of promoter and spacer combinations, a semi-empirical correlation was developed to determine the combined activity of stacked promoters.

High gene expression of enzymes partaking in recombinant production pathways is a desirable trait among cell factories belonging to all different kingdoms of life. High enzyme abundance is generally aimed for by utilizing strong promoters, which ramp up gene transcription and mRNA levels. Increased protein abundance can alternatively be achieved by optimizing the expression on the post-transcriptional level. Here, we evaluated protein synthesis with a previously proposed optimized gene expression architecture, in which mRNA stability and translation initiation are modulated by genetic parts such as self-cleaving ribozymes and a bicistronic design, which have initially been described to support the standardization of gene expression. The optimized gene expression architecture was tested in Pseudomonas taiwanensis VLB120, a promising, novel microbial cell factory. The expression cassette was employed on a plasmid basis and after single genomic integration. We used three constitutive and two inducible promoters to drive the expression of two fluorescent reporter proteins and a short acetoin biosynthesis pathway. The performance was confronted with that of a traditional expression cassette harboring the same promoter and gene of interest but lacking the genetic parts for increased expression efficiency. The optimized expression cassette granted higher protein abundance independently of the expression basis or promoter used proving its value for applications requiring high protein abundance.

Microbial biocatalysis represents a promising alternative for the production of a variety of aromatic chemicals, where microorganisms are engineered to convert a renewable feedstock under mild production conditions into a valuable chemical building block. This study describes the rational engineering of the solvent-tolerant bacterium Pseudomonas taiwanensis VLB120 toward accumulation of L-phenylalanine and its conversion into the chemical building block t-cinnamate. We recently reported rational engineering of Pseudomonas toward L-tyrosine accumulation by the insertion of genetic modifications that allow both enhanced flux and prevent aromatics degradation. Building on this knowledge, three genes encoding for enzymes involved in the degradation of L-phenylalanine were deleted to allow accumulation of 2.6 mM of L-phenylalanine from 20 mM glucose. The amino acid was subsequently converted into the aromatic model compound t-cinnamate by the expression of a phenylalanine ammonia-lyase (PAL) from Arabidopsis thaliana. The engineered strains produced t-cinnamate with yields of 23 and 39% Cmol Cmol−1 from glucose and glycerol, respectively. Yields were improved up to 48% Cmol Cmol−1 from glycerol when two enzymes involved in the shikimate pathway were additionally overexpressed, however with negative impact on strain performance and reproducibility. Production titers were increased in fed-batch fermentations, in which 33.5 mM t-cinnamate were produced solely from glycerol, in a mineral medium without additional complex supplements. The aspect of product toxicity was targeted by the utilization of a streamlined, genome-reduced strain, which improves upon the already high tolerance of P. taiwanensis VLB120 toward t-cinnamate.

Microsatellites are widely used as powerful markers in population genetics because of their ability to access recent genetic variation and to resolve subtle population genetic structures. However, their development, especially for non-model organisms with no available genome-wide sequence data has been difficult and time-consuming. Here, a commercial high-throughput sequencing approach (HTS) was used for the very first identification of microsatellite motifs in the genome of Xyela concava and the design of primer pairs flanking those motifs. Sixteen of those primer pairs were selected and implemented successfully to answer questions on the phylogeography and population genetics of X. concava. The markers were characterized in three geographically distinct populations of X. concava and tested for cross-species amplification in two additional Xyela and one Pleroneura species (Xyelidae). All markers showed substantial polymorphism as well as revealing subtle genetic structures among the three genotyped populations. We also analyzed a fragment of the nuclear gene region of sodium/potassium-transporting ATPase subunit alpha (NaK) and a partial mitochondrial gene region coding for cytochrome oxidase subunit I (COI) to demonstrate different genetic resolutions and sex-biased patterns of these markers, and their potential for combined use in future studies on the phylogeography and population genetics of X. concava. Although a limited number of populations was analyzed, we nevertheless obtained new insights on the latter two topics. The microsatellites revealed a generally high gene flow between the populations, but also suggested a deep historical segregation into two genetic lineages. This deep genetic segregation was confirmed by NaK. While the high gene flow was unexpected, because of assumed restricted dispersal ability of X. concava and the discontinuous distribution of the host trees between the populations, the segregation of two lineages is comprehensible and could be explained by different refuge areas of the hosts during glacial times. The COI results showed a discordant strong genetic structure between all populations, which might be explained by the smaller effective population size of the mitochondrial genome. However, given the frequent evidence of a similar nature in recent studies on sawflies, we also consider and discuss mitochondrial introgression on population level as an alternative explanation.

Non-alcoholic fatty liver disease (NAFLD) is a serious metabolic condition affecting millions of people worldwide. A “Western-style diet” has been shown to induce pediatric NAFLD with the potential disruption of skeletal muscle composition and metabolism. To determine the in vivo effect of a “Western-style diet” on pediatric skeletal muscle fiber type and fuel utilization, 28 juvenile Iberian pigs were fed either a control diet (CON) or a high-fructose, high-fat diet (HFF), with or without probiotic supplementation, for 10 weeks. The HFF diets increased the total triacylglycerol content of muscle tissue but decreased intramyocellular lipid (IMCL) content and the number of type I (slow oxidative) muscle fibers. HFF diets induced autophagy as assessed by LC3I and LC3II, and inflammation, as assessed by IL-1α. No differences in body composition were observed, and there was no change in insulin sensitivity, but HFF diets increased several plasma acylcarnitines and decreased expression of lipid oxidation regulators PGC1α and CPT1, suggesting disruption of skeletal muscle metabolism. Our results show that an HFF diet fed to juvenile Iberian pigs produces a less oxidative skeletal muscle phenotype, similar to a detraining effect, and reduces the capacity to use lipid as fuel, even in the absence of insulin resistance and obesity.

The beetle family Ptilodactylidae contains more than 500 extant species; however, its fossil record is scarce and remains understudied. In this study, we describe a new species of Ptilodactylidae, Ptilodactyla eocenica Kundrata, Bukejs and Blank, sp. nov., based on a relatively well-preserved specimen from Baltic amber. We use X-ray microcomputed tomography to reconstruct its morphology since some of the principal diagnostic characters have been obscured by opaque bubbles. It is the third ptilodactylid species described from Baltic amber, and the first one belonging to the subfamily Ptilodactylinae. Additionally, we summarize the classification, diversity, and distribution of both extinct and extant Ptilodactylidae.