T7-CYANO - Production and development of a Synechocystis strain useful for inducible membrane protein expression and controlled antisense RNA synthesis

Cyanobacteria are supposed to have been the first organisms able to evolve oxygen by photosynthesis, the process that uses solar light as energy source to fix CO2 into carbohydrate molecules. Historically, they have been and are a model system for studying fundamental processes including and relating to photosynthesis. In more recent years cyanobacteria acquired interest also in biotechnology, in particular as an alternative energy resource, for instance in ethanol or hydrogen production, and as a source for the production of molecules useful in the pharmaceutical industry. Moreover cyanobacteria are interesting host organisms for proteins expression, in particular for membrane proteins. Indeed, the abundant internal membrane system (the thylakoids) typical of cyanobacteria would provide the proper compartment to harbour these kind of proteins, permitting higher production of these proteins. Synechocystis sp. PCC 6803 is nowadays one of the most extensively studied species among all cyanobacteria and is considered a model organism for the study of photosynthesis. Some of the main reason are that it is spontaneously transformable, it can easily incorporate exogenous DNA into its genome by homologous recombination and it is able to grow both photoautotrophically and heterotrophycally. However, the lack of handy episomal elements for cloning and the presence of 10-12 copies of the chromosome per cell have hampered its use so far. The aim of the present study is to develop a Synechocystis strain suitable for a simplified use of DNA recombinant techniques within this organism and for the inducible expression of proteins. The genetic tool consists in a two component system: i) a new Synechocystis strain, called âT7-cyanoâ, hosting the highly processive RNA polymerase from the bacteriophage T7 under the control of different inducible promoters; ii) vectors, called pSEV (Synechocystis Expression Vectors), for stable introduction of a DNA fragment of interest under the control of the T7 promoter. The system resembles therefore the BL21 strain of Escherichia coli: induction of the T7 RNA polymerase will lead to transcription of the heterologous sequence in a controlled manner. The present work describes the design and the early development of the T7-cyano system. After a brief introduction on cyanobacteria (chapter one), the second chapter describes the design of the new cyanobacterial tool and the construction of a vector, called Transformation Vector, for the stable integration of the T7 RNA polymerase gene in the genome of Synechocystis sp. PCC 6803. In this same chapter, the construction of the second component of the system is also illustrated. This is represented by three different expression vectors having different applications: pSEV1, for Strep-tagged fusion proteins expression; pSEV2, for recombinant expression of endogenous or heterologous proteins; pSAS, for the synthesis of RNA molecules in antisense. The development of the T7-cyano strain is reported in the third chapter. Three different inducible promoters are chosen to control the expression of the T7 RNA polymerase gene: Pzia, a zinc-inducible endogenous promoter, Pnrs, an endogenous nickel-inducible one and variant of the E. coli promoter Plac. By the developed Transformation Vector the T7 RNA polymerase gene is homoplasmically inserted in the genome of the cyanobacterium. The production of the bacteriophage polymerase in the T7-cyano strain is successfully confirmed by immunoblotting upon induction of the Pzia and Pnrs promoters. The system is tested in the expression of three different heterologous proteins (chapter four): the eGFP fluorescence protein; HydA, a [FeFe]-hydrogenase from Chlamydomonas reinhardtii previously expressed in Synechocystis sp. PCC 6803; and a Baeyer-Villiger monooxygenase, BVMO, from the algae Cyanidioschyzon merolae, previously expressed in Escherichia coli. The sequences of the chosen protein coding genes are cloned in one of the expression vectors developed, pSEV1 and pSEV2, and the obtained vectors are used to transform the T7-cyano strains. In preliminary induction experiments transcript analysis confirms transcription of the heterologous genes by the T7 RNA polymerase. Moreover by western blot, the BVMO enzyme is successfully confirmed expressed in T7-cyano. However the promoters Pzia and Pnrs are found both leaky and the low amount of the BVMO enzyme produced suggests translation inefficiency. In the last chapter the system is proposed for the inducible synthesis of antisense RNAs. Synechocystis sp. PCC 6803, in fact, possesses a significant number of regulatory RNAs transcribed in a wide range of environmental changes and stress conditions. To date, however, only few of them have been characterized and new genetic tools are required for the study and identification of these small RNA molecules. In addition, an interesting application would be the controlled knockdown of endogenous genes. To test the T7-cyano system in the synthesis of antisense RNAs, the characterized IsrR, known to down-regulate the iron-starvation responding gene isiA, is chosen. In addition an antisense is designed against the 5â UTR of the same isiA gene. The experiments were performed at the Department of Biochemistry of the University of Turku (Finland) at the Molecular Plant Biology group headed by Prof. Eva-Mari Aro, one of the main experts in the study of photosynthetic organisms. Preliminary experiments shows a knockdown phenotype in induced cells, however more experiments are necessary to confirm the silencing of the gene by the synthesis of antisense RNAs in T7-cyano. The present work gives a general view of the new system showing, for the first time, the capability of Synechocystis sp. PCC 6803 to produce the T7 RNA polymerase that in turn is able to transcribe the sequence downstream the T7 promoter. The work also pointed out the two major problematic issues found within the system that are the leakiness of the promoters, Pzia and Pnrs, and a translational inefficiency in proteins expressio

Hearing impairment in MELAS: new prospective in clinical use of microRNA, a systematic review

Aim To evaluate the feasibility of microRNAs (miR) in clinical use to fill in the gap of current methodology commonly used to test hearing impairment in MELAS patients. Material and method A literature review was performed using the following keywords, i.e., MELAS, Hearing Loss, Hearing Impairment, Temporal Bone, Otoacustic Emission (OTOAE), Auditory Brain Response (ABR), and microRNA. We reviewed the literature and focused on the aspect of the temporal bone, the results of electrophysiological tests in human clinical studies, and the use of miR for detecting lesions in the cochlea in patients with MELAS. Results In patients with MELAS, Spiral Ganglions (SG), stria vascularis (SV), and hair cells are damaged, and these damages affect in different ways various structures of the temporal bone. The function of these cells is typically investigated using OTOAE and ABR, but in patients with MELAS these tests provide inconsistent results, since OTOAE response is absent and ABR is normal. The normal ABR responses are unexpected given the SG loss in the temporal bone. Recent studies in humans and animals have shown that miRs, and in particular miRs 34a, 29b, 76, 96, and 431, can detect damage in the cells of the cochlea with high sensitivity. Studies that focus on the temporal bone aspects have reported that miRs increase is correlated with the death of specific cells of the inner ear. MiR − 9/9* was identified as a biomarker of human brain damage, miRs levels increase might be related to damage in the central auditory pathways and these increased levels could identify the damage with higher sensitivity and several months before than electrophysiological testing. Conclusion We suggest that due to their accuracy and sensitivity, miRs might help monitor the progression of SNHL in patients with MELAS

X-SRAM: Enabling In-Memory Boolean Computations in CMOS Static Random Access Memories

Silicon-based Static Random Access Memories (SRAM) and digital Boolean logic have been the workhorse of the state-of-art computing platforms. Despite tremendous strides in scaling the ubiquitous metal-oxide-semiconductor transistor, the underlying \textit{von-Neumann} computing architecture has remained unchanged. The limited throughput and energy-efficiency of the state-of-art computing systems, to a large extent, results from the well-known \textit{von-Neumann bottleneck}. The energy and throughput inefficiency of the von-Neumann machines have been accentuated in recent times due to the present emphasis on data-intensive applications like artificial intelligence, machine learning \textit{etc}. A possible approach towards mitigating the overhead associated with the von-Neumann bottleneck is to enable \textit{in-memory} Boolean computations. In this manuscript, we present an augmented version of the conventional SRAM bit-cells, called \textit{the X-SRAM}, with the ability to perform in-memory, vector Boolean computations, in addition to the usual memory storage operations. We propose at least six different schemes for enabling in-memory vector computations including NAND, NOR, IMP (implication), XOR logic gates with respect to different bit-cell topologies $-$ the 8T cell and the 8$^+$T Differential cell. In addition, we also present a novel \textit{`read-compute-store'} scheme, wherein the computed Boolean function can be directly stored in the memory without the need of latching the data and carrying out a subsequent write operation. The feasibility of the proposed schemes has been verified using predictive transistor models and Monte-Carlo variation analysis.Comment: This article has been accepted in a future issue of IEEE Transactions on Circuits and Systems-I: Regular Paper

Short communication: Comparison of growth kinetics at different temperatures of Streptococcus macedonicus and Streptococcus thermophilus strains of dairy origin

Within the genus Streptococcus, S. thermophilus and S. macedonicus are the 2 known species related to foods. Streptococci are widely used as starter cultures to rapidly lower milk pH. As S. macedonicus has been introduced quite recently, much less information is available on its technological potential. Because temperature is an important factor in fermented food production, we compared the growth kinetics over 24 h of 8 S. thermophilus and 7 S. macedonicus strains isolated from various dairy environments in Italy, at 4 temperatures, 30\ub0C, 34\ub0C, 37\ub0C and 42\ub0C. We used the Gompertz model to estimate the 3 main growth parameters; namely, lag phase duration (\u3bb), maximum growth rate (\ub5max), and maximum cell number at the stationary phase (Nmax). Our results showed significant differences in average growth kinetics between the 2 species. Among the strains tested, 37\ub0C appeared to be the optimal temperature for the growth of both species, particularly for S. macedonicus strains, which showed mean shorter lag phases and higher cell numbers compared with S. thermophilus. Overall, the growth curves of S. macedonicus strains were more similar to each other whereas S. thermophilus strains grew very differently. These results help to better define and compare technological characteristics of the 2 species, in view of the potential use of S. macedonicus in place of S. thermophilus in selected technological applications

Temperature and humidity index (THI) affects salivary cortisol (HC) and dehydroepiandrosterone (DHEA) concentrations in growing bulls following stress generated by performance test procedures

The hypothalamus-pituitary–adrenal axis response to a challenge was proposed for genetic selection of robust and resilient animals. As ACTH (adrenocorticotropic hormone) test and hormone measurements in blood may result impractical, it may be useful to measure salivary hormones in response to natural stressors, after an accurate biological validation, to control factors that could contribute to the response. We evaluated whether animal handling during performance test affects salivary HC and DHEA secretion and could be used for selection. We tested the effects of habituation to repeated handling and THI as putative bias. Bull calves (N = 273) undergoing performance test were sampled at 8–9 and 11–13 months (N = 101), 8–9 months (N = 131), or 11–13 months (N = 41). On each test day (D0), calves were isolated, conducted to a squeeze chute and immobilized for 6 min. Saliva samples were collected in the morning after feed administration (T0), and after 6 min immobilization in the squeeze chute (T1) for HC and DHEA measurement. Environmental temperature and relative humidity were recorded every hour from 1:00 h to 24:00 h during the 6 days before the performance test and on D0. Salivary HC and DHEA concentrations were higher in T1 (p < 0.01), although a clear individual positive response to handling could be observed in less than 10% of subjects. The mixed model revealed: (i) HC and HC/DHEA were higher in Young bulls (p < 0.05). (ii) The time of T0 sample collection significantly affected DHEA (p < 0.01) and HC/DHEA (p < 0.05). (iii) THI affected both steroids (p < 0.001) but not HC/DHEA. Spearman correlations suggested that THI weakly affected salivary HC at T0 only (ρ = 0.150, p < 0.01), while moderate statistically significant correlations were found between DHEA and THI at T0 (ρ = 0.316, p < 0.001), and T1 (ρ = 0.353, p < 0.001). Salivary HC and DHEA in response to handling procedures might identify subpopulations of subjects with sensitive HPA axis. Habituation to repeated handling played a role, as the hormone response was lower in older animals. Chronic exposure to high THI had a minor effect on salivary HC visible at T0. A more intense THI effect was observed on salivary DHEA concentrations at both T0 and T1, which should be worth of further investigations

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense