Population Dynamics is a Cancer Driver.

Most tissues are continuously renovated through the division of stem cells and the death of old or damaged cells, which is known as cell turnover rate (CTOR). Despite being in steady state, tissues have different population dynamics and leading to diverse clonality levels. Here, we propose and test that cell population dynamics can be a cancer driver. We employed the evolutionary software esiCancer to show that CTOR, within a range comparable to what is observed in human tissues, can amplify the risk of a mutation due to ancestral selection (ANSEL). In a high CTOR tissue, a mutated ancestral cell is likely to be selected and persist over generations, which leads to a scenario of elevated ANSEL profile, characterized by few niches of large clones, which does not occur in low CTOR. We found that CTOR is significantly associated with the risk of developing cancer, even when correcting for mutation load, indicating that population dynamics per se is a cancer driver. This concept is central to understanding cancer risk and for the design of new therapeutic interventions that minimize the contribution of ANSEL in cancer growth.

Graphene and Natural Products: A Review of Antioxidant Properties in Graphene Oxide Reduction.

This review article addresses the antioxidant properties of different natural products, including ascorbic acid, gallic acid, oxalic acid, L-glutathione (GSH), bacteriorhodopsin, green tea polyphenols, glucose, hydroxycinnamic acid, ethanoic acid, betanin, and L-glutathione, in the reduction of graphene oxide (rGO). rGO can cause damage to cells, including oxidative stress and inflammation, limiting its application in different sectors that use graphene, such as technologies used in medicine and dentistry. The natural substances reviewed have properties that help reduce this damage, neutralizing free radicals and maintaining cellular integrity. This survey demonstrates that the combination of these antioxidant compounds can be an effective strategy to minimize the harmful effects of rGO and promote cellular health.

Three-dimensional nuclear architecture distinguishes thyroid cancer histotypes.

Molecular markers can serve as diagnostic tools to support pathological analysis in thyroid neoplasms. However, because the same markers can be observed in some benign thyroid lesions, additional approaches are necessary to differentiate thyroid tumor subtypes, prevent overtreatment and tailor specific clinical management. This applies particularly to the recently described variant of thyroid cancer referred to as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). This variant has an estimated prevalence of 4.4% to 9.1% of all papillary thyroid carcinomas worldwide. We studied 60 thyroid lesions: 20 classical papillary thyroid carcinoma (CPTC), 20 follicular variant of PTC (FVPTC) and 20 NIFTP. We examined morphological and molecular features to identify parameters that can differentiate NIFTP from the other PTC subtypes. When blindly investigating the nuclear architecture of thyroid neoplasms, we observed that NIFTP has significantly longer telomeres than CPTC and FVPTC. Super-resolved 3D-structured illumination microscopy demonstrated that NIFTP is heterogeneous and that its nuclei contain more densely packed DNA and smaller interchromatin spaces than CPTC and FVPTC, a pattern that resembles normal thyroid tissue. These data are consistent with the observed indolent biological behavior and favorable prognosis associated with NIFTP, which lacks BRAFV600E mutations. Of note, next-generation thyroid oncopanel sequencing was unable to distinguish the thyroid cancer histotypes in our study cohort. In summary, our data suggest that 3D nuclear architecture can be a powerful analytical tool to diagnose and guide clinical management of NIFTP.

An Alternative Exploitation of Synechocystis sp. PCC6803: A Cascade Approach for the Recovery of High Added-Value Products.

Microalgal biomass represents a very interesting biological feedstock to be converted into several high-value products in a biorefinery approach. In this study, the cyanobacterium Synechocystis sp. PCC6803 was used to obtain different classes of molecules: proteins, carotenoids and lipids by using a cascade approach. In particular, the protein extract showed a selective cytotoxicity towards cancer cells, whereas carotenoids were found to be active as antioxidants both in vitro and on a cell-based model. Finally, for the first time, lipids were recovered from Synechocystis biomass as the last class of molecules and were successfully used as an alternative substrate for the production of polyhydroxyalkanoate (PHA) by the native PHA producer Pseudomonas resinovorans. Taken together, our results lead to a significant increase in the valorization of Synechocystis sp. PCC6803 biomass, thus allowing a possible offsetting of the process costs.

Cycling between growth and production phases increases cyanobacteria bioproduction of lactate.

Decoupling growth from product synthesis is a promising strategy to increase carbon partitioning and maximize productivity in cell factories. However, reduction in both substrate uptake rate and metabolic activity in the production phase are an underlying problem for upscaling. Here, we used CRISPR interference to repress growth in lactate-producing Synechocystis sp. PCC 6803. Carbon partitioning to lactate in the production phase exceeded 90%, but CO2 uptake was severely reduced compared to uptake during the growth phase. We characterized strains during the onset of growth arrest using transcriptomics and proteomics. Multiple genes involved in ATP homeostasis were regulated once growth was inhibited, which suggests an alteration of energy charge that may lead to reduced substrate uptake. In order to overcome the reduced metabolic activity and take advantage of increased carbon partitioning, we tested a novel production strategy that involved alternating growth arrest and recovery by periodic addition of an inducer molecule to activate CRISPRi. Using this strategy, we maintained lactate biosynthesis in Synechocystis for 30 days in a constant light turbidostat cultivation. Cumulative lactate titers were also increased by 100% compared to a constant growth-arrest regime, and reached 1 g/L. Further, the cultivation produced lactate for 30 days, compared to 20 days for the non-growth arrest cultivation. Periodic growth arrest could be applicable for other products, and in cyanobacteria, could be linked to internal circadian rhythms that persist in constant light.

Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse.

The development of robotic solutions for agriculture requires advanced perception capabilities that can work reliably in any crop stage. For example, to automatise the tomato harvesting process in greenhouses, the visual perception system needs to detect the tomato in any life cycle stage (flower to the ripe tomato). The state-of-the-art for visual tomato detection focuses mainly on ripe tomato, which has a distinctive colour from the background. This paper contributes with an annotated visual dataset of green and reddish tomatoes. This kind of dataset is uncommon and not available for research purposes. This will enable further developments in edge artificial intelligence for in situ and in real-time visual tomato detection required for the development of harvesting robots. Considering this dataset, five deep learning models were selected, trained and benchmarked to detect green and reddish tomatoes grown in greenhouses. Considering our robotic platform specifications, only the Single-Shot MultiBox Detector (SSD) and YOLO architectures were considered. The results proved that the system can detect green and reddish tomatoes, even those occluded by leaves. SSD MobileNet v2 had the best performance when compared against SSD Inception v2, SSD ResNet 50, SSD ResNet 101 and YOLOv4 Tiny, reaching an F1-score of 66.15%, an mAP of 51.46% and an inference time of 16.44ms with the NVIDIA Turing Architecture platform, an NVIDIA Tesla T4, with 12 GB. YOLOv4 Tiny also had impressive results, mainly concerning inferring times of about 5 ms.

Adaption to glucose limitation is modulated by the pleotropic regulator CcpA, independent of selection pressure strength.

BACKGROUND: A central theme in (micro)biology is understanding the molecular basis of fitness i.e. which strategies are successful under which conditions; how do organisms implement such strategies at the molecular level; and which constraints shape the trade-offs between alternative strategies. Highly standardized microbial laboratory evolution experiments are ideally suited to approach these questions. For example, prolonged chemostats provide a constant environment in which the growth rate can be set, and the adaptive process of the organism to such environment can be subsequently characterized. RESULTS: We performed parallel laboratory evolution of Lactococcus lactis in chemostats varying the quantitative value of the selective pressure by imposing two different growth rates. A mutation in one specific amino acid residue of the global transcriptional regulator of carbon metabolism, CcpA, was selected in all of the evolution experiments performed. We subsequently showed that this mutation confers predictable fitness improvements at other glucose-limited growth rates as well. In silico protein structural analysis of wild type and evolved CcpA, as well as biochemical and phenotypic assays, provided the underpinning molecular mechanisms that resulted in the specific reprogramming favored in constant environments. CONCLUSION: This study provides a comprehensive understanding of a case of microbial evolution and hints at the wide dynamic range that a single fitness-enhancing mutation may display. It demonstrates how the modulation of a pleiotropic regulator can be used by cells to improve one trait while simultaneously work around other limiting constraints, by fine-tuning the expression of a wide range of cellular processes.

Training for translation between disciplines: a philosophy for life and data sciences curricula.

Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters' programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula. Supplementary information: Supplementary data are available at Bioinformatics online.

Combining retinal-based and chlorophyll-based (oxygenic) photosynthesis: Proteorhodopsin expression increases growth rate and fitness of a ∆PSI strain of Synechocystis sp. PCC6803.

To fill the "green absorption gap", a green absorbing proteorhodopsin was expressed in a PSI-deletion strain (ΔPSI) of Synechocystis sp. PCC6803. Growth-rate measurements, competition experiments and physiological characterization of the proteorhodopsin-expressing strains, relative to the ΔPSI control strain, allow us to conclude that proteorhodopsin can enhance the rate of photoheterotrophic growth of ΔPSI Synechocystis strain. The physiological characterization included measurement of the amount of residual glucose in the spent medium and analysis of oxygen uptake- and production rates. To explore the use of solar radiation beyond the PAR region, a red-shifted variant Proteorhodopsin-D212N/F234S was expressed in a retinal-deficient PSI-deletion strain (ΔPSI/ΔSynACO). Via exogenous addition of retinal analogue an infrared absorbing pigment (maximally at 740 nm) was reconstituted in vivo. However, upon illumination with 746 nm light, it did not significantly stimulate the growth (rate) of this mutant. The inability of the proteorhodopsin-expressing ΔPSI strain to grow photoautotrophically is most likely due to a kinetic rather than a thermodynamic limitation of its NADPH-dehydrogenase in NADP+-reduction.

A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory.

BACKGROUND: Lactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data. RESULTS: A genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden-Meyerhof-Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden-Meyerhof-Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies. CONCLUSION: We have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

On the use of oxygenic photosynthesis for the sustainable production of commodity chemicals.

A sustainable society will have to largely refrain from the use of fossil carbon deposits. In such a regime, renewable electricity can be harvested as a primary source of energy. However, as for the synthesis of carbon-based materials from bulk chemicals, an alternative is required. A sustainable approach towards this is the synthesis of commodity chemicals from CO2 , water and sunlight. Multiple paths to achieve this have been designed and tested in the domains of chemistry and biology. In the latter, the use of both chemotrophic and phototrophic organisms has been advocated. 'Direct conversion' of CO2 and H2 O, catalyzed by an oxyphototroph, has excellent prospects to become the most economically competitive of these transformations, because of the relative ease of scale-up of this process. Significantly, for a wide range of energy and commodity products, a proof of principle via engineering of the corresponding production organism has been provided. In the optimization of a cyanobacterial production organism, a wide range of aspects has to be addressed. Of these, here we will put our focus on: (1) optimizing the (carbon) flux to the desired product; (2) increasing the genetic stability of the producing organism and (3) maximizing its energy conversion efficiency. Significant advances have been made on all these three aspects during the past 2 years and these will be discussed: (1) increasing the carbon partitioning to >50%; (2) aligning product formation with the growth of the cells and (3) expanding the photosynthetically active radiation region for oxygenic photosynthesis.

Spectrally decomposed dark-to-light transitions in a PSI-deficient mutant of Synechocystis sp. PCC 6803.

Cyanobacterial thylakoid membranes are known to host photosynthetic and respiratory complexes. This hampers a straight forward interpretation of the highly dynamic fluorescence originating from photosynthetic units. The present study focuses on dark-to-light transitions in whole cells of a PSI-deficient mutant of the cyanobacterium Synechocystis sp. PCC 6803. The time-dependent cellular fluorescence spectrum has been measured, while having previously exposed the cells to different conditions that affect respiratory activity. The analysis method used allows the detected signal to be decomposed in a few components that are then assigned to functional emitting species. Additionally, we have worked out a minimal mathematical model consisting of sensible postulated species to interpret the recorded data. We conclude that the following two functional complexes play a major role: a phycobilisome antenna complex coupled to a PSII dimer with either two or no closed reaction centers. Crucially, we present evidence for an additional species capable of strongly quenching fluorescence, whose formation requires the presence of oxygen.

Spectrally decomposed dark-to-light transitions in Synechocystis sp. PCC 6803.

Photosynthetic activity and respiration share the thylakoid membrane in cyanobacteria. We present a series of spectrally resolved fluorescence experiments where whole cells of the cyanobacterium Synechocystis sp. PCC 6803 and mutants thereof underwent a dark-to-light transition after different dark-adaptation (DA) periods. Two mutants were used: (i) a PSI-lacking mutant (ΔPSI) and (ii) M55, a mutant without NAD(P)H dehydrogenase type-1 (NDH-1). For comparison, measurements of the wild-type were also carried out. We recorded spectrally resolved fluorescence traces over several minutes with 100 ms time resolution. The excitation light was at 590 nm so as to specifically excite the phycobilisomes. In ΔPSI, DA time has no influence, and in dichlorophenyl-dimethylurea (DCMU)-treated samples we identify three main fluorescent components: PB-PSII complexes with closed (saturated) RCs, a quenched or open PB-PSII complex, and a PB-PSII 'not fully closed.' For the PSI-containing organisms without DCMU, we conclude that mainly three species contribute to the signal: a PB-PSII-PSI megacomplex with closed PSII RCs and (i) slow PB → PSI energy transfer, or (ii) fast PB → PSI energy transfer and (iii) complexes with open (photochemically quenched) PSII RCs. Furthermore, their time profiles reveal an adaptive response that we identify as a state transition. Our results suggest that deceleration of the PB → PSI energy transfer rate is the molecular mechanism underlying a state 2 to state 1 transition.

Challenges in the Application of Synthetic Biology Toward Synthesis of Commodity Products by Cyanobacteria via "Direct Conversion".

Cyanobacterial direct conversion of CO2 to several commodity chemicals has been recognized as a potential contributor to support the much-needed sustainable development of human societies. However, the feasibility of this "green conversion" hinders on our ability to overcome the hurdles presented by the natural evolvability of microbes. The latter may result in the genetic instability of engineered cyanobacterial strains leading to impaired productivity. This challenge is general to any "cell factory" approach in which the cells grow for multiple generations, and based on several studies carried out in different microbial hosts, we could identify that three distinct strategies have been proposed to tackle it. These are (1) to reduce microbial evolvability by decreasing the native mutation rate, (2) to align product formation with cell growth/fitness, and, paradoxically, (3) to efficiently reallocate cellular resources to product formation by uncoupling it from growth. The implementation of either of these strategies requires an advanced synthetic biology toolkit. Here, we review the existing methods available for cyanobacteria and identify areas of focus in which specific developments are still needed. Furthermore, we discuss how potentially stabilizing strategies may be used in combination leading to further increases of productivity while ensuring the stability of the cyanobacterial-based direct conversion process.

Probing the Genome-Scale Metabolic Landscape of Bordetella pertussis, the Causative Agent of Whooping Cough.

Whooping cough is a highly contagious respiratory disease caused by Bordetella pertussis Despite widespread vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm, and experimental data to probe the full metabolic potential of this pathogen, using B. pertussis strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine, using inorganic sulfur sources, such as thiosulfate, and it can grow on organic acids, such as citrate or lactate, as sole carbon sources, providing in vivo demonstration that its tricarboxylic acid (TCA) cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three strains were shown to grow on substrate combinations requiring a functional TCA cycle, but only one strain could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with >2-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology and highlights the potential, but also the limitations, of models based solely on metabolic gene content.IMPORTANCE The metabolic capabilities of Bordetella pertussis, the causative agent of whooping cough, were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis and challenged its predictions experimentally. This systems approach shed light on new potential host-microbe interactions and allowed us to rationally design novel growth media with >2-fold improvements in pertussis toxin production. Most importantly, we also uncovered the potential for metabolic flexibility of B. pertussis (significantly larger range of substrates than previously alleged; novel active pathways allowing growth in minimal, nearly mineral nutrient combinations where only the carbon source must be organic), although our results also highlight the importance of strain-specific regulatory determinants in shaping metabolic capabilities. Deciphering the underlying regulatory mechanisms appears to be crucial for a comprehensive understanding of B. pertussis's lifestyle and the epidemiology of whooping cough. The contribution of metabolic models in this context will require the extension of the genome-scale metabolic model to integrate this regulatory dimension.

Protein costs do not explain evolution of metabolic strategies and regulation of ribosomal content: does protein investment explain an anaerobic bacterial Crabtree effect?

Protein investment costs are considered a major driver for the choice of alternative metabolic strategies. We tested this premise in Lactococcus lactis, a bacterium that exhibits a distinct, anaerobic version of the bacterial Crabtree/Warburg effect; with increasing growth rates it shifts from a high yield metabolic mode [mixed-acid fermentation; 3 adenosine triphosphate (ATP) per glucose] to a low yield metabolic mode (homolactic fermentation; 2 ATP per glucose). We studied growth rate-dependent relative transcription and protein ratios, enzyme activities, and fluxes of L. lactis in glucose-limited chemostats, providing a high-quality and comprehensive data set. A three- to fourfold higher growth rate rerouted metabolism from acetate to lactate as the main fermentation product. However, we observed hardly any changes in transcription, protein levels and enzyme activities. Even levels of ribosomal proteins, constituting a major investment in cellular machinery, changed only slightly. Thus, contrary to the original hypothesis, central metabolism in this organism appears to be hardly regulated at the level of gene expression, but rather at the metabolic level. We conclude that L. lactis is either poorly adapted to growth at low and constant glucose concentrations, or that protein costs play a less important role in fitness than hitherto assumed.

Availability of public goods shapes the evolution of competing metabolic strategies.

Tradeoffs provide a rationale for the outcome of natural selection. A prominent example is the negative correlation between the growth rate and the biomass yield in unicellular organisms. This tradeoff leads to a dilemma, where the optimization of growth rate is advantageous for an individual, whereas the optimization of the biomass yield would be advantageous for a population. High-rate strategies are observed in a broad variety of organisms such as Escherichia coli, yeast, and cancer cells. Growth in suspension cultures favors fast-growing organisms, whereas spatial structure is of importance for the evolution of high-yield strategies. Despite this realization, experimental methods to directly select for increased yield are lacking. We here show that the serial propagation of a microbial population in a water-in-oil emulsion allows selection of strains with increased biomass yield. The propagation in emulsion creates a spatially structured environment where the growth-limiting substrate is privatized for populations founded by individual cells. Experimental evolution of several isogenic Lactococcus lactis strains demonstrated the existence of a tradeoff between growth rate and biomass yield as an apparent Pareto front. The underlying mutations altered glucose transport and led to major shifts between homofermentative and heterofermentative metabolism, accounting for the changes in metabolic efficiency. The results demonstrated the impact of privatizing a public good on the evolutionary outcome between competing metabolic strategies. The presented approach allows the investigation of fundamental questions in biology such as the evolution of cooperation, cell-cell interactions, and the relationships between environmental and metabolic constraints.

Assessing and reducing phenotypic instability in cyanobacteria.

Cyanobacteria have promising potential as sustainable cell factories. However, one challenge that is still largely unreported in scaling-up cyanobacteria bioproduction is phenotypic instability, where the emergence and selection of nonproducing cells leading to loss in production has longer evolutionary timescales to take place in industrial-scale bioreactors. Quantifying phenotypic instability early on in strain development allows researchers to make informed decisions on whether to proceed with scalable designs, or if present, devise countermeasures to reduce instability. One particularly effective strategy to mitigate instability is the use of genome-scale metabolic models to design growth-coupled production strains. In silico studies have predicted that creating certain cofactor imbalances or removing recycling reactions in cyanobacteria can be exploited to stably produce a wide variety of metabolites.

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling.

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant disease diagnosis. This study aimed to investigate the potential of HS point-of-measurement (POM) data for in-situ, non-destructive diagnosis of tomato bacterial speck caused by Pseudomonas syringae pv. tomato (Pst), and bacterial spot, caused by Xanthomonas euvesicatoria (Xeu), on leaves (cv. cherry). Bacterial artificial infection was performed on tomato plants at the same phenological stage. A sensing system composed by a hyperspectral spectrometer, a transmission optical fiber bundle with a slitted probe and a white light source were used for spectral data acquisition, allowing the assessment of 3478 spectral points. An applied predictive classification model was developed, consisting of a normalizing pre-processing strategy allied with a Linear Discriminant Analysis (LDA) for reducing data dimensionality and a supervised machine learning algorithm (Support Vector Machine - SVM) for the classification task. The predicted model achieved classification accuracies of 100% and 74% for Pst and Xeu test set assessments, respectively, before symptom appearance. Model predictions were coherent with host-pathogen interactions mentioned in the literature (e.g., changes in photosynthetic pigment levels, production of bacterial-specific molecules, and activation of plants' defense mechanisms). Furthermore, these results were coherent with visual phenotyping inspection and PCR results. The reported outcomes support the application of spectral point measurements acquired in-vivo for plant disease diagnosis, aiming for more precise and eco-friendly phytosanitary approaches.

Interlaboratory Reproducibility in Growth and Reporter Expression in the Cyanobacterium Synechocystis sp. PCC 6803.

In recent years, a plethora of new synthetic biology tools for use in cyanobacteria have been published; however, their reported characterizations often cannot be reproduced, greatly limiting the comparability of results and hindering their applicability. In this interlaboratory study, the reproducibility of a standard microbiological experiment for the cyanobacterial model organism Synechocystis sp. PCC 6803 was assessed. Participants from eight different laboratories quantified the fluorescence intensity of mVENUS as a proxy for the transcription activity of the three promoters PJ23100, PrhaBAD, and PpetE over time. In addition, growth rates were measured to compare growth conditions between laboratories. By establishing strict and standardized laboratory protocols, reflecting frequently reported methods, we aimed to identify issues with state-of-the-art procedures and assess their effect on reproducibility. Significant differences in spectrophotometer measurements across laboratories from identical samples were found, suggesting that commonly used reporting practices of optical density values need to be supplemented by cell count or biomass measurements. Further, despite standardized light intensity in the incubators, significantly different growth rates between incubators used in this study were observed, highlighting the need for additional reporting requirements of growth conditions for phototrophic organisms beyond the light intensity and CO2 supply. Despite the use of a regulatory system orthogonal to Synechocystis sp. PCC 6803, PrhaBAD, and a high level of protocol standardization, ∼32% variation in promoter activity under induced conditions was found across laboratories, suggesting that the reproducibility of other data in the field of cyanobacteria might be affected similarly.