EGCG Disrupts the LIN28B/Let-7 Interaction and Reduces Neuroblastoma Aggressiveness.

Neuroblastoma (NB) is the most commonly diagnosed extracranial solid tumor in children, accounting for 15% of all childhood cancer deaths. Although the 5-year survival rate of patients with a high-risk disease has increased in recent decades, NB remains a challenge in pediatric oncology, and the identification of novel potential therapeutic targets and agents is an urgent clinical need. The RNA-binding protein LIN28B has been identified as an oncogene in NB and is associated with a poor prognosis. Given that LIN28B acts by negatively regulating the biogenesis of the tumor suppressor let-7 miRNAs, we reasoned that selective interference with the LIN28B/let-7 miRNA interaction would increase let-7 miRNA levels, ultimately leading to reduced NB aggressiveness. Here, we selected (-)-epigallocatechin 3-gallate (EGCG) out of 4959 molecules screened as the molecule with the best inhibitory activity on LIN28B/let-7 miRNA interaction and showed that treatment with PLC/PLGA-PEG nanoparticles containing EGCG (EGCG-NPs) led to an increase in mature let-7 miRNAs and a consequent inhibition of NB cell growth. In addition, EGCG-NP pretreatment reduced the tumorigenic potential of NB cells in vivo. These experiments suggest that the LIN28B/let-7 miRNA axis is a good therapeutic target in NB and that EGCG, which can interfere with this interaction, deserves further preclinical evaluation.

Thylakoid proteome modulation in pea plants grown at different irradiances: quantitative proteomic profiling in a non-model organism aided by transcriptomic data integration.

Plant thylakoid membranes contain hundreds of proteins that closely interact to cope with ever-changing environmental conditions. We investigated how Pisum sativum L. (pea) grown at different irradiances optimizes light-use efficiency through the differential accumulation of thylakoid proteins. Thylakoid membranes from plants grown under low (LL), moderate (ML) and high (HL) light intensity were characterized by combining chlorophyll fluorescence measurements with quantitative label-free proteomic analysis. Protein sequences retrieved from available transcriptomic data considerably improved thylakoid proteome profiling, increasing the quantifiable proteins from 63 to 194. The experimental approach used also demonstrates that this integrative omics strategy is powerful for unravelling protein isoforms and functions that are still unknown in non-model organisms. We found that the different growth irradiances affect the electron transport kinetics but not the relative abundance of photosystems (PS) I and II. Two acclimation strategies were evident. The behaviour of plants acclimated to LL was compared at higher irradiances: (i) in ML, plants turn on photoprotective responses mostly modulating the PSII light-harvesting capacity, either accumulating Lhcb4.3 or favouring the xanthophyll cycle; (ii) in HL, plants reduce the pool of light-harvesting complex II and enhance the PSII repair cycle. When growing at ML and HL, plants accumulate ATP synthase, boosting both cyclic and linear electron transport by finely tuning the ΔpH across the membrane and optimizing protein trafficking by adjusting the thylakoid architecture. Our results provide a quantitative snapshot of how plants coordinate light harvesting, electron transport and protein synthesis by adjusting the thylakoid membrane proteome in a light-dependent manner.

Public data and open source tools for multi-assay genomic investigation of disease.

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods.

Molecular portraits: the evolution of the concept of transcriptome-based cancer signatures.

Cancer results from dysregulation of multiple steps of gene expression programs. We review how transcriptome profiling has been widely explored for cancer classification and biomarker discovery but resulted in limited clinical impact. Therefore, we discuss alternative and complementary omics approaches.

MicroRNA-mediated regulatory circuits: outlook and perspectives.

MicroRNAs have been found to be necessary for regulating genes implicated in almost all signaling pathways, and consequently their dysfunction influences many diseases, including cancer. Understanding of the complexity of the microRNA-mediated regulatory network has grown in terms of size, connectivity and dynamics with the development of computational and, more recently, experimental high-throughput approaches for microRNA target identification. Newly developed studies on recurrent microRNA-mediated circuits in regulatory networks, also known as network motifs, have substantially contributed to addressing this complexity, and therefore to helping understand the ways by which microRNAs achieve their regulatory role. This review provides a summarizing view of the state-of-the-art, and perspectives of research efforts on microRNA-mediated regulatory motifs. In this review, we discuss the topological properties characterizing different types of circuits, and the regulatory features theoretically enabled by such properties, with a special emphasis on examples of circuits typifying their biological significance in experimentally validated contexts. Finally, we will consider possible future developments, in particular regarding microRNA-mediated circuits involving long non-coding RNAs and epigenetic regulators.

Control of Gene Expression by RNA Binding Protein Action on Alternative Translation Initiation Sites.

Transcript levels do not faithfully predict protein levels, due to post-transcriptional regulation of gene expression mediated by RNA binding proteins (RBPs) and non-coding RNAs. We developed a multivariate linear regression model integrating RBP levels and predicted RBP-mRNA regulatory interactions from matched transcript and protein datasets. RBPs significantly improved the accuracy in predicting protein abundance of a portion of the total modeled mRNAs in three panels of tissues and cells and for different methods employed in the detection of mRNA and protein. The presence of upstream translation initiation sites (uTISs) at the mRNA 5' untranslated regions was strongly associated with improvement in predictive accuracy. On the basis of these observations, we propose that the recently discovered widespread uTISs in the human genome can be a previously unappreciated substrate of translational control mediated by RBPs.

TrkA is amplified in malignant melanoma patients and induces an anti-proliferative response in cell lines.

BACKGROUND: The nerve growth factor (NGF) receptor tyrosine-kinase TrkA is a well-known determinant of the melanocytic lineage, through modulation of the MAPK and AKT cascades. While TrkA gene is frequently rearranged in cancers, its involvement in malignant melanoma (MM) development is still unclear. METHODS: We analyzed a dataset of primary cutaneous MM (n = 31) by array comparative genomic hybridization (aCGH), to identify genomic amplifications associated with tumor progression. The analysis was validated by genomic quantitative PCR (qPCR) on an extended set of cases (n = 64) and the results were correlated with the clinical outcome. To investigate TrkA molecular pathways and cellular function, we generated inducible activation of the NGF-TrkA signaling in human MM cell lines. RESULTS: We identified amplification of 1q23.1, where the TrkA locus resides, as a candidate hotspot implicated in the progression of MM. Across 40 amplicons detected, segmental amplification of 1q23.1 showed the strongest association with tumor thickness. By validation of the analysis, TrkA gene amplification emerged as a frequent event in primary melanomas (50 % of patients), and correlated with worse clinical outcome. However, experiments in cell lines revealed that induction of the NGF-TrkA signaling produced a phenotype of dramatic suppression of cell proliferation through inhibition of cell division and pronounced intracellular vacuolization, in a way straightly dependent on NGF activation of TrkA. These events were triggered via MAPK activity but not via AKT, and involved p21(cip1) protein increase, compatibly with a mechanism of oncogene-induced growth arrest. CONCLUSIONS: Taken together, our findings point to TrkA as a candidate oncogene in MM and support a model in which the NGF-TrkA-MAPK pathway may mediate a trade-off between neoplastic transformation and adaptive anti-proliferative response.

Increased frequency of minimal homozygous deletions is associated with poor prognosis in primary malignant melanoma patients.

Identification of prognostic melanoma-associated copy number alterations (CNAs) is still an area of active research. Here, we investigated by high-resolution array comparative genomic hybridization (aCGH) a cohort of 31 paraffin-preserved primary malignant melanomas (MMs), whose prognosis was not predictable on the basis of conventional histopathological parameters. Although we identified a variety of highly recurrent sites of genomic lesions, the total number of CNAs per patient was not a discriminator of MM outcome. Furthermore, validation of aCGH by quantitative PCR on an extended population of 65 MM samples confirmed the absence of predictive value for the most recurrent CNA loci. Instead, our analysis revealed specific prognostic potential of the frequency of homozygous deletions (representing less than 3% of the total CNAs on average per sample), which was strongly associated with sentinel lymph node (SLN) invasion (P = 0.003), and distant metastasis (P = 0.003). Increased number of homozygous deletions was also indicative of poor patient survival (P = 0.01), both in our samples and in an independent validation of public dataset of primary and metastatic MMs. Moreover, we identified 77 hotspots of minimal common homozygous deletions, enriched in genes involved in cell adhesion processes and cell-communication functions, which preferentially accumulated in primary MMs showing the most severe outcome. Therefore, specific loss of gene loci in regions of minimal homozygous deletion may represent a pivotal type of genomic alteration accumulating during MM progression with potential prognostic implication.

Coupling dairy wastewaters for nutritional balancing and water recycling: sustainable heterologous 2-phenylethanol production by engineered cyanobacteria.

Microalgae biotechnology is hampered by the high production costs and the massive usage of water during large-volume cultivations. These drawbacks can be softened by the production of high-value compounds and by adopting metabolic engineering strategies to improve their performances and productivity. Today, the most sustainable approach is the exploitation of industrial wastewaters for microalgae cultivation, which couples valuable biomass production with water resource recovery. Among the food processing sectors, the dairy industry generates the largest volume of wastewaters through the manufacturing process. These effluents are typically rich in dissolved organic matter and nutrients, which make it a challenging and expensive waste stream for companies to manage. Nevertheless, these rich wastewaters represent an appealing resource for microalgal biotechnology. In this study, we propose a sustainable approach for high-value compound production from dairy wastewaters through cyanobacteria. This strategy is based on a metabolically engineered strain of the model cyanobacterium Synechococcus elongatus PCC 7942 (already published elsewhere) for 2-phenylethanol (2-PE). 2-PE is a high-value aromatic compound that is widely employed as a fragrance in the food and cosmetics industry thanks to its pleasant floral scent. First, we qualitatively assessed the impact of four dairy effluents on cyanobacterial growth to identify the most promising substrates. Both tank-washing water and the liquid effluent of exhausted sludge resulted as suitable nutrient sources. Thus, we created an ideal buffer system by combining the two wastewaters while simultaneously providing balanced nutrition and completely avoiding the need for fresh water. The combination of 75% liquid effluent of exhausted sludge and 25% tank-washing water with a fine-tuning ammonium supplementation yielded 180 mg L-1 of 2-PE and a biomass concentration of 0.6 gDW L-1 within 10 days. The mixture of 90% exhausted sludge and 10% washing water produced the highest yield of 2-PE (205 mg L-1) and biomass accumulation (0.7 gDW L-1), although in 16 days. Through these treatments, the phosphates were completely consumed, and nitrogen was removed in a range of 74%-77%. Overall, our approach significantly valorized water recycling and the exploitation of valuable wastewaters to circularly produce marketable compounds via microalgae biotechnology, laying a promising groundwork for subsequent implementation and scale-up.

Segmental chromosome aberrations converge on overexpression of mitotic spindle regulatory genes in high-risk neuroblastoma.

Integration of genome-wide profiles of DNA copy number alterations (CNAs) and gene expression variations (GEVs) could provide combined power to the identification of driver genes and gene networks in tumors. Here we merge matched genome and transcriptome microarray analyses from neuroblastoma samples to derive correlation patterns of CNAs and GEVs, irrespective of their genomic location. Neuroblastoma correlation patterns are strongly asymmetrical, being on average 10 CNAs linked to 1 GEV, and show the widespread prevalence of long range covariance. Functional enrichment and network analysis of the genes covarying with CNAs consistently point to a major cell function, the regulation of mitotic spindle assembly. Moreover, elevated expression of 14 key genes promoting this function is strongly associated to high-risk neuroblastomas with 1p loss and MYCN amplification in a set of 410 tumor samples (P < 0.00001). Independent CNA/GEV profiling on neuroblastoma cell lines shows that increased levels of expression of these genes are linked to 1p loss. By this approach, we reveal a convergence of clustered neuroblastoma CNAs toward increased expression of a group of prognostic and functionally cooperating genes. We therefore propose gain of function of the spindle assembly machinery as a lesion potentially offering new targets for therapy of high-risk neuroblastoma.

Translational efficiency in gas-fermenting bacteria: Adding a new layer of regulation to gene expression in acetogens.

Major advances in mastering metabolism of single carbon (C1) gaseous feedstocks in acetogenic microorganisms are primed to fuel the transition toward environmentally sustainable and cost-efficient production schemes of biofuels and value-added biochemicals. Since acetogens grow under autotrophic energy-limited conditions, protein synthesis is expected to be controlled. This survey integrated publicly available RNA sequencing and ribosome profiling studies of several acetogens, providing data on genome-scale transcriptional and translational responses of A. woodii, E. limosum, C. drakei, and C. ljungdahlii to autotrophic and heterotrophic growth conditions. The extent of translational efficiency turned out to vary across key functional modules in acetogens' metabolism. Translational control was confirmed to support stoichiometric protein production in multimeric complexes. Comparing the autotrophic to the heterotrophic growth condition revealed growth-dependent regulation of translational efficiency, pointing at translational buffering as a widespread phenomenon shared by acetogens.

Current progress on engineering microbial strains and consortia for production of cellulosic butanol through consolidated bioprocessing.

In the last decades, fermentative production of n-butanol has regained substantial interest mainly owing to its use as drop-in-fuel. The use of lignocellulose as an alternative to traditional acetone-butanol-ethanol fermentation feedstocks (starchy biomass and molasses) can significantly increase the economic competitiveness of biobutanol over production from non-renewable sources (petroleum). However, the low cost of lignocellulose is offset by its high recalcitrance to biodegradation which generally requires chemical-physical pre-treatment and multiple bioreactor-based processes. The development of consolidated processing (i.e., single-pot fermentation) can dramatically reduce lignocellulose fermentation costs and promote its industrial application. Here, strategies for developing microbial strains and consortia that feature both efficient (hemi)cellulose depolymerization and butanol production will be depicted, that is, rational metabolic engineering of native (hemi)cellulolytic or native butanol-producing or other suitable microorganisms; protoplast fusion of (hemi)cellulolytic and butanol-producing strains; and co-culture of (hemi)cellulolytic and butanol-producing microbes. Irrespective of the fermentation feedstock, biobutanol production is inherently limited by the severe toxicity of this solvent that challenges process economic viability. Hence, an overview of strategies for developing butanol hypertolerant strains will be provided.

Leveraging substrate flexibility and product selectivity of acetogens in two-stage systems for chemical production.

Carbon dioxide (CO2 ) stands out as sustainable feedstock for developing a circular carbon economy whose energy supply could be obtained by boosting the production of clean hydrogen from renewable electricity. H2 -dependent CO2 gas fermentation using acetogenic microorganisms offers a viable solution of increasingly demonstrated value. While gas fermentation advances to achieve commercial process scalability, which is currently limited to a few products such as acetate and ethanol, it is worth taking the best of the current state-of-the-art technology by its integration within innovative bioconversion schemes. This review presents multiple scenarios where gas fermentation by acetogens integrate into double-stage biotechnological production processes that use CO2 as sole carbon feedstock and H2 as energy carrier for products' synthesis. In the integration schemes here reviewed, the first stage can be biotic or abiotic while the second stage is biotic. When the first stage is biotic, acetogens act as a biological platform to generate chemical intermediates such as acetate, formate and ethanol that become substrates for a second fermentation stage. This approach holds the potential to enhance process titre/rate/yield metrics and products' spectrum. Alternatively, when the first stage is abiotic, the integrated two-stage scheme foresees, in the first stage, the catalytic transformation of CO2 into C1 products that, in the second stage, can be metabolized by acetogens. This latter scheme leverages the metabolic flexibility of acetogens in efficient utilization of the products of CO2 abiotic hydrogenation, namely formate and methanol, to synthesize multicarbon compounds but also to act as flexible catalysts for hydrogen storage or production.

Widespread uncoupling between transcriptome and translatome variations after a stimulus in mammalian cells.

BACKGROUND: The classical view on eukaryotic gene expression proposes the scheme of a forward flow for which fluctuations in mRNA levels upon a stimulus contribute to determine variations in mRNA availability for translation. Here we address this issue by simultaneously profiling with microarrays the total mRNAs (the transcriptome) and the polysome-associated mRNAs (the translatome) after EGF treatment of human cells, and extending the analysis to other 19 different transcriptome/translatome comparisons in mammalian cells following different stimuli or undergoing cell programs. RESULTS: Triggering of the EGF pathway results in an early induction of transcriptome and translatome changes, but 90% of the significant variation is limited to the translatome and the degree of concordant changes is less than 5%. The survey of other 19 different transcriptome/translatome comparisons shows that extensive uncoupling is a general rule, in terms of both RNA movements and inferred cell activities, with a strong tendency of translation-related genes to be controlled purely at the translational level. By different statistical approaches, we finally provide evidence of the lack of dependence between changes at the transcriptome and translatome levels. CONCLUSIONS: We propose a model of diffused independency between variation in transcript abundances and variation in their engagement on polysomes, which implies the existence of specific mechanisms to couple these two ways of regulating gene expression.

Genome-Scale Mining of Acetogens of the Genus Clostridium Unveils Distinctive Traits in [FeFe]- and [NiFe]-Hydrogenase Content and Maturation.

Knowledge of the organizational and functional properties of hydrogen metabolism is pivotal to the construction of a framework supportive of a hydrogen-fueled low-carbon economy. Hydrogen metabolism relies on the mechanism of action of hydrogenases. In this study, we investigated the genomes of several industrially relevant acetogens of the genus Clostridium (C. autoethanogenum, C. ljungdahlii, C. carboxidivorans, C. drakei, C. scatologenes, C. coskatii, C. ragsdalei, C. sp. AWRP) to systematically identify their intriguingly diversified hydrogenases' repertoire. An entirely computational annotation pipeline unveiled common and strain-specific traits in the functional content of [NiFe]- and [FeFe]-hydrogenases. Hydrogenases were identified and categorized into functionally distinct classes by the combination of sequence homology, with respect to a database of curated nonredundant hydrogenases, with the analysis of sequence patterns characteristic of the mode of action of [FeFe]- and [NiFe]-hydrogenases. The inspection of the genes in the neighborhood of the catalytic subunits unveiled a wide agreement between their genomic arrangement and the gene organization templates previously developed for the predicted hydrogenase classes. Subunits' characterization of the identified hydrogenases allowed us to glean some insights on the redox cofactor-binding determinants in the diaphorase subunits of the electron-bifurcating [FeFe]-hydrogenases. Finally, the reliability of the inferred hydrogenases was corroborated by the punctual analysis of the maturation proteins necessary for the biosynthesis of [NiFe]- and [FeFe]-hydrogenases. IMPORTANCE Mastering hydrogen metabolism can support a sustainable carbon-neutral economy. Of the many microorganisms metabolizing hydrogen, acetogens of the genus Clostridium are appealing, with some of them already in usage as industrial workhorses. Having provided detailed information on the hydrogenase content of an unprecedented number of clostridial acetogens at the gene level, our study represents a valuable knowledge base to deepen our understanding of hydrogenases' functional specificity and/or redundancy and to develop a large array of biotechnological processes. We also believe our study could serve as a basis for future strain-engineering approaches, acting at the hydrogenases' level or at the level of their maturation proteins. On the other side, the wealth of functional elements discussed in relation to the identified hydrogenases is worthy of further investigation by biochemical and structural studies to ultimately lead to the usage of these enzymes as valuable catalysts.

Metabolic Engineering Interventions for Sustainable 2,3-Butanediol Production in Gas-Fermenting Clostridium autoethanogenum.

Gas fermentation provides a promising platform to turn low-cost and readily available single-carbon waste gases into commodity chemicals, such as 2,3-butanediol. Clostridium autoethanogenum is usually used as a robust and flexible chassis for gas fermentation. Here, we leveraged constraint-based stoichiometric modeling and kinetic ensemble modeling of the C. autoethanogenum metabolic network to provide a systematic in silico analysis of metabolic engineering interventions for 2,3-butanediol overproduction and low carbon substrate loss in dissipated CO2. Our analysis allowed us to identify and to assess comparatively the expected performances for a wide range of single, double, and triple interventions. Our analysis managed to individuate bottleneck reactions in relevant metabolic pathways when suggesting intervening strategies. Besides recapitulating intuitive and/or previously attempted genetic modifications, our analysis neatly outlined that interventions-at least partially-impinging on by-products branching from acetyl coenzyme A (acetyl-CoA) and pyruvate (acetate, ethanol, amino acids) offer valuable alternatives to the interventions focusing directly on the specific branch from pyruvate to 2,3-butanediol. IMPORTANCE Envisioning value chains inspired by environmental sustainability and circularity in economic models is essential to counteract the alterations in the global natural carbon cycle induced by humans. Recycling carbon-based waste gas streams into chemicals by devising gas fermentation bioprocesses mediated by acetogens of the genus Clostridium is one component of the solution. Carbon monoxide originates from multiple biogenic and abiogenic sources and bears a significant environmental impact. This study aims at identifying metabolic engineering interventions for increasing 2,3-butanediol production and avoiding carbon loss in CO2 dissipation via C. autoethanogenum fermenting a substrate comprising CO and H2. 2,3-Butanediol is a valuable biochemical by-product since, due to its versatility, can be transformed quite easily into chemical compounds such as butadiene, diacetyl, acetoin, and methyl ethyl ketone. These compounds are usable as building blocks to manufacture a vast range of industrially produced chemicals.

Combining metabolite doping and metabolic engineering to improve 2-phenylethanol production by engineered cyanobacteria.

2-Phenylethanol (2-PE) is a rose-scented aromatic compound, with broad application in cosmetic, pharmaceutical, food and beverage industries. Many plants naturally synthesize 2-PE via Shikimate Pathway, but its extraction is expensive and low-yielding. Consequently, most 2-PE derives from chemical synthesis, which employs petroleum as feedstock and generates unwanted by products and health issues. The need for "green" processes and the increasing public demand for natural products are pushing biotechnological production systems as promising alternatives. So far, several microorganisms have been investigated and engineered for 2-PE biosynthesis, but a few studies have focused on autotrophic microorganisms. Among them, the prokaryotic cyanobacteria can represent ideal microbial factories thanks to their ability to photosynthetically convert CO2 into valuable compounds, their minimal nutritional requirements, high photosynthetic rate and the availability of genetic and bioinformatics tools. An engineered strain of Synechococcus elongatus PCC 7942 for 2-PE production, i.e., p120, was previously published elsewhere. The strain p120 expresses four heterologous genes for the complete 2-PE synthesis pathway. Here, we developed a combined approach of metabolite doping and metabolic engineering to improve the 2-PE production kinetics of the Synechococcus elongatus PCC 7942 p120 strain. Firstly, the growth and 2-PE productivity performances of the p120 recombinant strain were analyzed to highlight potential metabolic constraints. By implementing a BG11 medium doped with L-phenylalanine, we covered the metabolic burden to which the p120 strain is strongly subjected, when the 2-PE pathway expression is induced. Additionally, we further boosted the carbon flow into the Shikimate Pathway by overexpressing the native Shikimate Kinase in the Synechococcus elongatus PCC 7942 p120 strain (i.e., 2PE_aroK). The combination of these different approaches led to a 2-PE yield of 300 mg/gDW and a maximum 2-PE titer of 285 mg/L, 2.4-fold higher than that reported in literature for the p120 recombinant strain and, to our knowledge, the highest recorded for photosynthetic microorganisms, in photoautotrophic growth condition. Finally, this work provides the basis for further optimization of the process aimed at increasing 2-PE productivity and concentration, and could offer new insights about the use of cyanobacteria as appealing microbial cell factories for the synthesis of aromatic compounds.

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development.

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Channeling Anabolic Side Products toward the Production of Nonessential Metabolites: Stable Malate Production in Synechocystis sp. PCC6803.

Powered by (sun)light to oxidize water, cyanobacteria can directly convert atmospheric CO2 into valuable carbon-based compounds and meanwhile release O2 to the atmosphere. As such, cyanobacteria are promising candidates to be developed as microbial cell factories for the production of chemicals. Nevertheless, similar to other microbial cell factories, engineered cyanobacteria may suffer from production instability. The alignment of product formation with microbial fitness is a valid strategy to tackle this issue. We have described previously the "FRUITS" algorithm for the identification of metabolites suitable to be coupled to growth (i.e., side products in anabolic reactions) in the model cyanobacterium Synechocystis. sp PCC6803. However, the list of candidate metabolites identified using this algorithm can be somewhat limiting, due to the inherent structure of metabolic networks. Here, we aim at broadening the spectrum of candidate compounds beyond the ones predicted by FRUITS, through the conversion of a growth-coupled metabolite to downstream metabolites via thermodynamically favored conversions. We showcase the feasibility of this approach for malate production using fumarate as the growth-coupled substrate in Synechocystis mutants. A final titer of ∼1.2 mM was achieved for malate during photoautotrophic batch cultivations. Under prolonged continuous cultivation, the most efficient malate-producing strain can maintain its productivity for at least 45 generations, sharply contrasting with other producing Synechocystis strains engineered with classical approaches. Our study also opens a new possibility for extending the stable production concept to derivatives of growth-coupled metabolites, increasing the list of suitable target compounds.

Clostridium cellulovorans Proteomic Responses to Butanol Stress.

Combination of butanol-hyperproducing and hypertolerant phenotypes is essential for developing microbial strains suitable for industrial production of bio-butanol, one of the most promising liquid biofuels. Clostridium cellulovorans is among the microbial strains with the highest potential for direct production of n-butanol from lignocellulosic wastes, a process that would significantly reduce the cost of bio-butanol. However, butanol exhibits higher toxicity compared to ethanol and C. cellulovorans tolerance to this solvent is low. In the present investigation, comparative gel-free proteomics was used to study the response of C. cellulovorans to butanol challenge and understand the tolerance mechanisms activated in this condition. Sequential Window Acquisition of all Theoretical fragment ion spectra Mass Spectrometry (SWATH-MS) analysis allowed identification and quantification of differentially expressed soluble proteins. The study data are available via ProteomeXchange with the identifier PXD024183. The most important response concerned modulation of protein biosynthesis, folding and degradation. Coherent with previous studies on other bacteria, several heat shock proteins (HSPs), involved in protein quality control, were up-regulated such as the chaperones GroES (Cpn10), Hsp90, and DnaJ. Globally, our data indicate that protein biosynthesis is reduced, likely not to overload HSPs. Several additional metabolic adaptations were triggered by butanol exposure such as the up-regulation of V- and F-type ATPases (involved in ATP synthesis/generation of proton motive force), enzymes involved in amino acid (e.g., arginine, lysine, methionine, and branched chain amino acids) biosynthesis and proteins involved in cell envelope re-arrangement (e.g., the products of Clocel_4136, Clocel_4137, Clocel_4144, Clocel_4162 and Clocel_4352, involved in the biosynthesis of saturated fatty acids) and a redistribution of carbon flux through fermentative pathways (acetate and formate yields were increased and decreased, respectively). Based on these experimental findings, several potential gene targets for metabolic engineering strategies aimed at improving butanol tolerance in C. cellulovorans are suggested. This includes overexpression of HSPs (e.g., GroES, Hsp90, DnaJ, ClpC), RNA chaperone Hfq, V- and F-type ATPases and a number of genes whose function in C. cellulovorans is currently unknown.