The advent of the genomic era has made elucidating gene function on a large scale a pressing challenge. ORFeome collections, whereby almost all ORFs of a given species are cloned and can be subsequently leveraged in multiple functional genomic approaches, represent valuable resources toward this endeavor. Here we provide novel, genome-scale tools for the study of Candida albicans, a commensal yeast that is also responsible for frequent superficial and disseminated infections in humans. We have generated an ORFeome collection composed of 5099 ORFs cloned in a Gateway™ donor vector, representing 83% of the currently annotated coding sequences of C. albicans. Sequencing data of the cloned ORFs are available in the CandidaOrfDB database at http://candidaorfeome.eu. We also engineered 49 expression vectors with a choice of promoters, tags and selection markers and demonstrated their applicability to the study of target ORFs transferred from the C. albicans ORFeome. In addition, the use of the ORFeome in the detection of protein-protein interaction was demonstrated. Mating-compatible strains as well as Gateway™-compatible two-hybrid vectors were engineered, validated and used in a proof of concept experiment. These unique and valuable resources should greatly facilitate future functional studies in C. albicans and the elucidation of mechanisms that underlie its pathogenicity.

The increasing cultivation of microalgae in photobioreactors warrants efficient and non-invasive methods to quantify biomass density in real time. Nephelometric turbidity assessment, a method that measures light scatter by particles in suspension, was introduced already several decades ago but was only recently validated as a high-throughput tool to monitor microalgae biomass. The light scatter depends on the density of the suspended particles as well as on their physical properties, but so far there are hardly any accounts on how nephelometric assessment relates to classic methods such as dry weight and spectrophotometric measurement across a broad biomass density range for different microalgae species. Here, we monitored biomass density online and in real time during the semi-continuous cultivation of three commercial microalgae species Chloromonas typhlos, Microchloropsis gaditana and Porphyridium purpureum in pilot-scale photobioreactors, and relate nephelometric turbidity to dry weight and optical density. The results confirm a relatively strong (R2 = 0.87–0.93) and nonlinear relationship between turbidity and biomass density that differs among the three species. Overall, we demonstrate how nephelometry can be used to monitor microalgal biomass in photobioreactors, and provide the necessary means to estimate the biomass density of the studied species from turbidity data to facilitate automated biomass monitoring.

Microalgae can form renewable feedstock for many sectors. However, most microalgae commercially cultivated are difficult to grow in colder climates. To overcome this problem one could cultivate cold tolerant algae. One such alga is the red marine alga Porphyridium purpureum. It is currently often cultivated in bag systems in limited volumes. In this study we cultivated P. purpureum at pilot-scale in horizontal tubular reactors in a greenhouse. P. purpureum was grown in batch mode in a total volume of either 350, 500, 1000 or 1500 L. A total of 28 batches, spread over two years, were cultivated reaching a maximum dry weight of 1.94 g L⁻¹. The growth was continuously monitored to calculate the productivities and growth rates. The P and N concentrations were measured frequently during four batches to calculate the P and N usage per gram biomass. To calculate CO₂ fixation efficiencies the total CO₂ consumption was monitored during 6 of the 28 batches. A maximum productivity and growth rate of respectively 0.195 g L⁻¹ day⁻¹ and 0.233 day⁻¹ were achieved while the P and N usage varied from 3.2–6.19 and 14.5–36.6 mg g⁻¹ biomass for P and N, respectively. Growth was supported between 10 °C and 30 °C, while temperatures above 34—35 °C proved to be detrimental. The CO₂ efficiencies differed among the 6 tested periods with the highest utilization efficiency being 13.5% and the lowest a mere 1.5%. Further large-scale, continuous, tests would be needed to fully optimize the cultivation of P. purpureum in larger volumes.

To meet the increasing demands of the growing population and to cope with the challenges of global change, both the production of biological feedstock and the recovery of recyclable natural resources play a critical role. Microalgal biomass is a promising source of renewable multifunctional feedstock, but the production is costly and requires large amounts of water. Here, we explored the potential of using wastewater as culture medium to lower the economic and environmental costs of microalgae biomass production and evaluated its valorization opportunities for animal feed production. As a proof of principle, we show that Chlorella sorokiniana can be cultivated on poultry wastewater, with a 83 and 113% increase in productivity when wastewater was first 50% diluted with tap water or standard growth medium, respectively. Wastewater sterilization before use enhanced algal growth with 36–118%, but only when wastewater was 25–50% diluted with standard medium. In contrast, it offered no additional benefits when dilutions were made with tap water or when wastewater was not diluted. At the end of the 22-days experiment, a maximum biomass of 0.8–1.9 g L⁻¹ was reached for algae grown on wastewater. The produced biomass had a high macronutrient content, and the heavy metal content was below maximum limits for use in animal feed. Likewise, the tested pathogen groups were reduced until below safety norms for feed production after algal growth in unsterilized 50% wastewater (diluted with tap water). Overall, these findings add to our growing knowledge on the cultivation of microalgae on wastewater and its valorization opportunities, paving the way for a more sustainable use and reuse of resources.

Despite being one of the most important human fungal pathogens, Candida albicans has not been studied extensively at the level of protein-protein interactions (PPIs) and data on PPIs are not readily available in online databases. In January 2018, the database called "Biological General Repository for Interaction Datasets (BioGRID)" that contains the most PPIs for C. albicans, only documented 188 physical or direct PPIs (release 3.4.156) while several more can be found in the literature. Other databases such as the String database, the Molecular INTeraction Database (MINT), and the Database for Interacting Proteins (DIP) database contain even fewer interactions or do not even include C. albicans as a searchable term. Because of the non-canonical codon usage of C. albicans where CUG is translated as serine rather than leucine, it is often problematic to use the yeast two-hybrid system in Saccharomyces cerevisiae to study C. albicans PPIs. However, studying PPIs is crucial to gain a thorough understanding of the function of proteins, biological processes and pathways. PPIs can also be potential drug targets. To aid in creating PPI networks and updating the BioGRID, we performed an exhaustive literature search in order to provide, in an accessible format, a more extensive list of known PPIs in C. albicans.