This work presents a benchmark of bioreactor instrumentation and describe its relationship to critical biotic variables, exploring technologies of sensors, control loops, and the integration of 4.0 technologies, such as artificial intelligence (AI) and Internet of Things (IoT). A review of literature through scientific database was conducted with accurate methodology. Out of 28,200 papers retrieved in the bibliographic search, the most relevant ones were extracted and classified, arriving at a working database of 89 articles from which 130 instruments were analysed and referenced. This benchmark highlighted significant advancements in Bioindustry 4.0, particularly trends surrounding in-situ and ex-situ sensors. Six major trends were identified, including the adoption of Process Analytical Technology (PAT) nomenclature, the growing use of optical and integrative instruments for real-time data, the vital role of soft sensors that estimate unmeasured variables, and the integration of AI into bioprocess monitoring and control. While these developments indicate a shift toward a more automated and adaptable biotechnology landscape, challenges such as data processing and scaling of sensor technologies remain. In summary, this research provides a comprehensive perspective on the evolution of instrumentation into bioprocess and highlights the importance of emerging technologies in the move towards a faster, easier, more sustainable, integrated, smarter and more efficient bioindustry.

Phasing biological and physiological processes to periodic light-dark cycles is crucial for the life of most organisms. Marine diatoms, as many phytoplanktonic species, exhibit biological rhythms, yet their molecular timekeepers remain largely uncharacterized. Recently, the bHLH-PAS protein RITMO1 has been proposed to act as a regulator of diatom circadian rhythms. In this study, we first determined the physiological conditions to monitor circadian clock activity and its perturbation in the diatom model species Phaeodactylum tricornutum by using cell fluorescence as a circadian output. Employing ectopic overexpression, targeted gene mutagenesis, and functional complementation, we then investigated the role of RITMO1 in various circadian processes. Our data reveal that RITMO1 significantly influences the P. tricornutum circadian rhythms not only of cellular fluorescence, but also of photosynthesis and of the expression of clock-controlled genes, including transcription factors and putative clock input/output components. RITMO1 effects on rhythmicity are unambiguously detectable under free-running conditions. By uncovering the complex regulation of biological rhythms in P. tricornutum, these findings advance our understanding of the endogenous factors controlling diatom physiological responses to environmental changes. They also offer initial insights into the mechanistic principles of oscillator functions in a major group of phytoplankton, which remain largely unexplored in chronobiology.

Real-time predictions in fermentation processes are crucial because they enable continuous monitoring and control of bioprocessing. However, the availability of online measurements is limited by the availability and feasibility of sensing technology. Soft sensors- or software sensors that convert available measurements into measurements of interest (product yield, quality, etc.)- have the potential to improve efficiency and product quality. Machine learning (ML) based soft sensors have gained increased popularity over the years since they can incorporate variables that are measured in real-time, and exploit the intricate patterns embedded in such voluminous datasets. However, ML-based soft sensor requires more than just a classical ML learner with an unseen test set to evaluate the quality prediction of the model. When a ML model is deployed in production, its performance can deteriorate rapidly leading to an unanticipated decline in the quality of the output and predictions. Here a proof concept of Machine Learning Operations (MLOps) to automate the end-to-end soft sensor lifecycle in industrial scale fed-batch fermentation, from development and deployment to maintenance and monitoring is proposed. Using the industrial-scale penicillin fermentation ( IndPenSim) dataset that includes 100 fermentation batches, to build a soft sensor based on Long Short Term Memory (LSTM) for penicillin concentration prediction. The batches containing deviations in the processes (91-100) were used to assess concept drift of the LSTM soft sensor. The evaluation of concept drift is evidenced by the soft sensor performance falling below the set threshold based on the Population Stability Index (PSI), which automatically triggers an alert to run the retraining pipeline.

Diatoms (Bacillariophyceae) accumulate neutral storage lipids in lipid droplets during stress conditions, which can be rapidly degraded and recycled when optimal conditions resume. Since nutrient and light availability fluctuate in marine environments, storage lipid turnover is essential for diatom dominance of marine ecosystems. Diatoms have garnered attention for their potential to provide a sustainable source of omega-3 fatty acids. Several independent proteomic studies of lipid droplets isolated from the model oleaginous pennate diatom Phaeodactylum tricornutum have identified a previously uncharacterized protein with an acyl-CoA binding (ACB) domain, Phatrdraft_48778, here referred to as Phaeodactylum tricornutum acyl-CoA binding protein (PtACBP). We report the phenotypic effects of CRISPR-Cas9 targeted genome editing of PtACBP. ptacbp mutants were defective in lipid droplet and triacylglycerol degradation, as well as lipid and eicosapentaenoic acid synthesis, during recovery from nitrogen starvation. Transcription of genes responsible for peroxisomal β-oxidation, triacylglycerol lipolysis, and eicosapentaenoic acid synthesis was inhibited. A lipid-binding assay using a synthetic ACB domain from PtACBP indicated preferential binding specificity toward certain polar lipids. PtACBP fused to eGFP displayed an endomembrane-like pattern, which surrounded the periphery of lipid droplets. PtACBP is likely responsible for intracellular acyl transport, affecting cell division, development, photosynthesis, and stress response. A deeper understanding of the molecular mechanisms governing storage lipid turnover will be crucial for developing diatoms and other microalgae as biotechnological cell factories.

Monitoring bioprocesses is a challenging task where most of the variables of interest can only be measured offline. Soft sensors have emerged as a solution to provide online estimations. This work compares interpretable learners such as CART, M5, CUBIST, and Random Forest as soft sensors for industrial-scale fed-batch fermentation of penicillin production. A structured model of industrial-scale penicillin fermentation is implemented to generate the dataset and train the interpretable learners. Variables such as substrate feed rate, agitation, temperature, pH, dissolved oxygen, vessel volume, CO2, and O2 percent in off-gas are considered as independent (predictors). The CUBIST model has achieved the best results with values of 0.908, 9.916, 3.149, and 1.920 for the coefficient of determination, Mean Squared Error, Root Mean Squared Error, and Mean Absolute Error, respectively. These results demonstrate the feasibility of developing soft sensors based on interpretable models to predict penicillin concentration at an industrial scale.

BACKGROUND:Physarum polycephalum is an unusual macroscopic myxomycete expressing a large range of glycosyl hydrolases. Among them, enzymes from the GH18 family can hydrolyze chitin, an important structural component of the cell walls in fungi and in the exoskeleton of insects and crustaceans.METHODS:Low stringency sequence signature search in transcriptomes was used to identify GH18 sequences related to chitinases. Identified sequences were expressed in E. coli and corresponding structures modelled. Synthetic substrates and in some cases colloidal chitin were used to characterize activities.RESULTS:Catalytically functional hits were sorted and their predicted structures compared. All share the TIM barrel structure of the GH18 chitinase catalytic domain, optionally fused to binding motifs, such as CBM50, CBM18, and CBM14, involved in sugar recognition. Assessment of the enzymatic activities following deletion of the C-terminal CBM14 domain of the most active clone evidenced a significant contribution of this extension to the chitinase activity. A classification based on module organization, functional and structural criteria of characterized enzymes was proposed.CONCLUSIONS:Physarum polycephalum sequences encompassing a chitinase like GH18 signature share a modular structure involving a structurally conserved catalytic TIM barrels decorated or not by a chitin insertion domain and optionally surrounded by additional sugar binding domains. One of them plays a clear role in enhancing activities toward natural chitin.GENERAL SIGNIFICANCE:Myxomycete enzymes are currently poorly characterized and constitute a potential source for new catalysts. Among them glycosyl hydrolases have a strong potential for valorization of industrial waste as well as in therapeutic field.

Metabolic engineering has evolved towards creating cell factories with increasingly complex pathways as economic criteria push biotechnology to higher value products to provide a sustainable source of speciality chemicals. Optimization of such pathways often requires high combinatory exploration of best pathway balance, and this has led to increasing use of high-throughput automated strain construction platforms or novel optimization techniques. In addition, the low catalytic efficiency of such pathways has shifted emphasis from gene expression strategies towards novel protein engineering to increase specific activity of the enzymes involved so as to limit the metabolic burden associated with excessively high pressure on ribosomal machinery when using massive overexpression systems. Metabolic burden is now generally recognized as a major hurdle to be overcome with consequences on genetic stability but also on the intensified performance needed industrially to attain the economic targets for successful product launch. Increasing awareness of the need to integrate novel genetic information into specific sites within the genome which not only enhance genetic stability (safe harbors) but also enable maximum expression profiles has led to genome-wide assessment of best integration sites, and bioinformatics will facilitate the identification of most probable landing pads within the genome.To facilitate the transfer of novel biotechnological potential to industrial-scale production, more attention, however, has to be paid to engineering metabolic fitness adapted to the specific stress conditions inherent to large-scale fermentation and the inevitable heterogeneity that will occur due to mass transfer limitations and the resulting deviation away from ideal conditions as seen in laboratory-scale validation of the engineered cells. To ensure smooth and rapid transfer of novel cell lines to industry with an accelerated passage through scale-up, better coordination is required form the onset between the biochemical engineers involved in process technology and the genetic engineers building the new strain so as to have an overall strategy able to maximize innovation at all levels. This should be one of our key objectives when building fermentation-friendly chassis organisms.

Diatoms, an evolutionarily successful group of microalgae, display high levels of intraspecific genetic variability in natural populations. However, the contribution of various mechanisms generating such diversity is unknown. Here we estimated the genetic micro-diversity within a natural diatom population and mapped the genomic changes arising within clonally propagated diatom cell cultures. Through quantification of haplotype diversity by next-generation sequencing and amplicon re-sequencing of selected loci, we documented a rapid accumulation of multiple haplotypes accompanied by the appearance of novel protein variants in cell cultures initiated from a single founder cell. Comparison of the genomic changes between mother and daughter cells revealed copy number variation and copy-neutral loss of heterozygosity leading to the fixation of alleles within individual daughter cells. The loss of heterozygosity can be accomplished by recombination between homologous chromosomes. To test this hypothesis, we established an endogenous readout system and estimated that the frequency of interhomolog mitotic recombination was under standard growth conditions 4.2 events per 100 cell divisions. This frequency is increased under environmental stress conditions, including treatment with hydrogen peroxide and cadmium. These data demonstrate that copy number variation and mitotic recombination between homologous chromosomes underlie clonal variability in diatom populations. We discuss the potential adaptive evolutionary benefits of the plastic response in the interhomolog mitotic recombination rate, and we propose that this may have contributed to the ecological success of diatoms.

TALENs (Transcription Activator-Like EndoNuclease) are molecular scissors designed to recognize and introduce a double-strand break at a specific genome locus. They represent tools of interest in the frame of genome edition. Upon cleavage, two different pathways lead to DNA repair: Non-homologous End Joining (NHEJ) repair, leading to efficient introduction of short insertion/deletion mutations which can disrupt translational reading frame and Homology Recombination (HR)-directed repair that occurs when exogenous DNA is supplied. Here we introduce how to use TALENs in the oleaginous yeast Yarrowia lipolytica by presenting a step-by-step method allowing to knock out or to introduce in vivo a point mutation in a gene of Yarrowia lipolytica. This chapter describes the material required, the transformation procedure, and the screening process.

Efficient and reliable genome engineering technologies have yet to be developed for diatoms. The delivery of DNA in diatoms results in the random integration of multiple copies, quite often leading to heterogeneous gene activity, as well as host instability. Transgenic diatoms are generally selected on the basis of transgene expression or high enzyme activity, without consideration of the copy number or the integration locus. Here, we propose an integrated pipeline for the diatom, Phaeodactylum tricornutum , that accurately quantifies transgene activity using a β-glucuronidase assay and the number of transgene copies integrated into the genome through Droplet Digital PCR (ddPCR). An exhaustive and systematic analysis performed on 93 strains indicated that 42% of them exhibited high β-glucuronidase activity. Though most were attributed to high transgene copy numbers, we succeeded in isolating single-copy clones, as well as sequencing the integration loci. In addition to demonstrating the impact of the genomic integration site on gene activity, this study identifies integration sites for stable transgene expression in Phaeodactylum tricornutum .

CRISPR/Cas9 is a powerful tool to edit the genome of the yeast Yarrowia lipolytica. Here, we design a simple and robust method to knockout multiple gene families based on the construction of plasmids enabling the simultaneous expression of several sgRNAs. We exemplify the potency of this approach by targeting the well-characterized acyl-CoA oxidase family (POX) and the uncharacterized SPS19 family. We establish a correlation between the high lethality observed upon editing multiple loci and chromosomal translocations resulting from the simultaneous generation of several double-strand breaks (DSBs) and develop multiplex gene editing strategies. Using homologous directed recombination to reduce chromosomal translocations, we demonstrated that simultaneous editing of four genes can be achieved and constructed a strain carrying a sextuple deletion of POX genes. We explore an "excision approach" by simultaneously performing two DSBs in genes and reached 73 to 100% editing efficiency in double disruptions and 41.7% in a triple disruption. This work led to identifying SPS193 as a gene encoding a 2-4 dienoyl-CoA reductase, demonstrating the potential of this method to accelerate knowledge on gene function in expanded gene families.

EDITORIAL article Front. Bioeng. Biotechnol., 06 May 2020Sec. Synthetic Biology Volume 8 - 2020 | https://doi.org/10.3389/fbioe.2020.00431

Diatoms, an evolutionarily successful group of microalgae, display high levels of intraspecific variability in natural populations. However, the process generating such diversity is unknown. Here we estimated the variability within a natural diatom population and subsequently mapped the genomic changes arising within cultures clonally propagated from single diatom cells. We demonstrate that genome rearrangements and mitotic recombination between homologous chromosomes underlie clonal variability, resulting in haplotype diversity accompanied by the appearance of novel protein variants and loss of heterozygosity resulting in the fixation of alleles. The frequency of interhomolog mitotic recombination exceeds 4 out of 100 cell divisions and increases under environmental stress. We propose that this plastic response in the interhomolog mitotic recombination rate increases the evolutionary potential of diatoms, contributing to their ecological success. One Sentence Summary Recombination between homologous chromosomes in diatom vegetative cells leads to extensive genomic diversity in clonal populations.

L’ingenierie metabolique est un levier incontournable pour ameliorer la capacite de production des microalgues et les rendre economiquement competitives. Elle requiert des outils d’ingenierie des genomes qui ont connu un developpement tardif compare aux châssis industriels conventionnels (levures, bacteries). Cet article decrit les avancees recentes dans les domaines de l'ingenierie genetique et l’edition du genome des microalgues, qui ouvrent la voie a une meilleure comprehension de la biologie de ces organismes fascinants ainsi qu'a la manipulation de leur metabolisme pour des applications biotechnologiques.

Recently developed transgenic techniques to explore and exploit the metabolic potential of microalgae present several drawbacks associated with the delivery of exogenous DNA into the cells and its subsequent integration at random sites within the genome. Here, we report a highly efficient multiplex genome-editing method in the diatom Phaeodactylum tricornutum, relying on the biolistic delivery of CRISPR-Cas9 ribonucleoproteins coupled with the identification of two endogenous counter-selectable markers, PtUMPS and PtAPT. First, we demonstrate the functionality of RNP delivery by positively selecting the disruption of each of these genes. Then, we illustrate the potential of the approach for multiplexing by generating double-gene knock-out strains, with 65% to 100% efficiency, using RNPs targeting one of these markers and PtAureo1a, a photoreceptor-encoding gene. Finally, we created triple knock-out strains in one step by delivering six RNP complexes into Phaeodactylum cells. This approach could readily be applied to other hard-to-transfect organisms of biotechnological interest.

Diatoms are major components of phytoplankton and play a key role in the ecology of aquatic ecosystems. These algae are of great scientific importance for a wide variety of research areas, ranging from marine ecology and oceanography to biotechnology. During the last 20 years, the availability of genomic information on selected diatom species and a substantial progress in genetic manipulation, strongly contributed to establishing diatoms as molecular model organisms for marine biology research. Recently, tailored TALEN endonucleases and the CRISPR/Cas9 system were utilized in diatoms, allowing targeted genetic modifications and the generation of knockout strains. These approaches are extremely valuable for diatom research because breeding, forward genetic screens by random insertion, and chemical mutagenesis are not applicable to the available model species Phaeodactylum tricornutum and Thalassiosira pseudonana, which do not cross sexually in the lab. Here, we provide an overview of the genetic toolbox that is currently available for performing stable genetic modifications in diatoms. We also discuss novel challenges that need to be addressed to fully exploit the potential of these technologies for the characterization of diatom biology and for metabolic engineering.