Developing semantic pathway comparison methods for systems biology

Systems biology is an emerging multi-disciplinary field in which the behaviour of complex biological systems is studied by considering the interaction of many cellular and molecular constituents rather than using a “traditional” reductionist approach where constituents are studied individually. Systems are often studied over time with the ultimate goal of developing models which can be used to understand and predict complex biological processes, such as human diseases. To support systems biology, a large number of biological pathways are being derived for many different organisms, and these are stored in various databases. This pathway collection presents an opportunity to compare and contrast pathways, and to utilise the knowledge they represent. This thesis presents some of the first algorithms that are designed to explore this opportunity. It is argued that the methods will be useful to biologists in order to assess the biological plausibility of derived pathways, compare different biological pathways for semantic similarities, and to derive putative pathways that are semantically similar to documented biological pathways. The methods will therefore extend the systems biology toolbox that biologists can use to make new biological discoveries.Knowledge Foundation. Grant No. 2003/0215Information Fusion Research Program (University of Skovde, Sweden) Grant No 2003/010

Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems

Genetic Algorithms (GAs) are known for their efficiency in solving combinatorial optimization problems, thanks to their ability to explore diverse solution spaces, handle various representations, exploit parallelism, preserve good solutions, adapt to changing dynamics, handle combinatorial diversity, and provide heuristic search. However, limitations such as premature convergence, lack of problem-specific knowledge, and randomness of crossover and mutation operators make GAs generally inefficient in finding an optimal solution. To address these limitations, this paper proposes a new metaheuristic algorithm called the Genetic Engineering Algorithm (GEA) that draws inspiration from genetic engineering concepts. GEA redesigns the traditional GA while incorporating new search methods to isolate, purify, insert, and express new genes based on existing ones, leading to the emergence of desired traits and the production of specific chromosomes based on the selected genes. Comparative evaluations against state-of-the-art algorithms on benchmark instances demonstrate the superior performance of GEA, showcasing its potential as an innovative and efficient solution for combinatorial optimization problems.Comment: Accepted in Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2023

When the path is never shortest: a reality check on shortest path biocomputation

Shortest path problems are a touchstone for evaluating the computing performance and functional range of novel computing substrates. Much has been published in recent years regarding the use of biocomputers to solve minimal path problems such as route optimisation and labyrinth navigation, but their outputs are typically difficult to reproduce and somewhat abstract in nature, suggesting that both experimental design and analysis in the field require standardising. This chapter details laboratory experimental data which probe the path finding process in two single-celled protistic model organisms, Physarum polycephalum and Paramecium caudatum, comprising a shortest path problem and labyrinth navigation, respectively. The results presented illustrate several of the key difficulties that are encountered in categorising biological behaviours in the language of computing, including biological variability, non-halting operations and adverse reactions to experimental stimuli. It is concluded that neither organism examined are able to efficiently or reproducibly solve shortest path problems in the specific experimental conditions that were tested. Data presented are contextualised with biological theory and design principles for maximising the usefulness of experimental biocomputer prototypes.Comment: To appear in: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

A C35 Carotenoid Biosynthetic Pathway

Upon coexpression with Erwinia geranylgeranyldiphosphate (GGDP) synthase in Escherichia coli, C30 carotenoid synthase CrtM from Staphylococcus aureus produces novel carotenoids with the asymmetrical C35 backbone. The products of condensation of farnesyldiphosphate and GDP, C35 structures comprise 40 to 60% of total carotenoid accumulated. Carotene desaturases and carotene cyclases from C40 or C30 pathways accepted and converted the C35 substrate, thus creating a C35 carotenoid biosynthetic pathway in E. coli. Directed evolution to modulate desaturase step number, together with combinatorial expression of the desaturase variants with lycopene cyclases, allowed us to produce at least 10 compounds not previously described. This result highlights the plastic and expansible nature of carotenoid pathways and illustrates how combinatorial biosynthesis coupled with directed evolution can rapidly access diverse chemical structures

Characterization of Sirt2 using conditional RNAi in mice

Within the past eight years, RNA interference (RNAi) has emerged as a powerful experimental tool for gene function analysis in mice. Reversible control of shRNA mediated RNAi has been achieved by using a tetracycline (tet)-inducible promoter. In the presence of the inductor doxycycline (dox), shRNA mediated gene silencing is initiated, whereas RNAi mechanism is blocked in the absence of dox. To achieve spatially and temporally regulated RNAi, the tet inducible system was combined with a Cre/loxP based strategy for tissue specific activation of shRNA constructs. To this end, a loxP-flanked "promoter inhibitory element" (PIE) was placed between the proximal (PSE) and distal sequence element (DSE) of a dox inducible promoter such that promoter function is completely blocked. Re-activation can be achieved through Cre mediated excision of PIE. To allow for gene silencing in a selected tissue, Cre expression can be regulated by a tissue-specific promoter. In mouse ES cells, the system mediated tight regulation of shRNA expression upon Cre mediated activation and dox administration, reaching knockdown efficiencies of >80%. Unexpectedly, the system showed a limited activity in transgenic mice when applied for conditional silencing of two different targets, LacZ and Sirt2. Sirt2 is a member of the sirtuin family which has considerably gained attention in vitro for its possible role in many physiological processes, including adipogenesis and neurodegenerative diseases. To investigate the function of Sirt2 in vivo, the unmodified dox-responsive and tet-inducible promoter was further used for conditional RNAi in transgenic mice. Inducible shRNA expression resulted in efficient silencing of Sirt2 (>90%) in all tissues which have been analyzed. Suppression of Sirt2 during embryogenesis resulted in offspring consisting of equal ratios of wild type and transgenic pups, indicating that Sirt2 is not indispensable for development. In adult animals, glucose metabolism, insulin sensitivity and energy balance appeared to be unaffected by Sirt2 deficiency. Likewise, expression of PPARγ, a downstream target of Sirt2, was not found to be altered upon Sirt2 inhibition. Finally, Sirt2 silencing was induced in an experimental model of Parkinson disease (PD). Data from Rotarod performances to study motor behaviour did not provide any evidence for a role of Sirt2 in PD pathogenesis as suggested by previous in vitro studies. Taken together, conditional Sirt2 silencing in vivo does not support speculation concerning a central role of Sirt2 in physiological processes, embryogenesis and in a mouse model of Parkinson disease

linc-mipep and linc-wrb encode micropeptides that regulate chromatin accessibility in vertebrate-specific neural cells

Thousands of long intergenic non-coding RNAs (lincRNAs) are transcribed throughout the vertebrate genome. A subset of lincRNAs enriched in developing brains have recently been found to contain cryptic open-reading frames and are speculated to encode micropeptides. However, systematic identification and functional assessment of these transcripts have been hindered by technical challenges caused by their small size. Here, we show that two putative lincRNAs (linc-mipep, also called lnc-rps25, and linc-wrb) encode micropeptides with homology to the vertebrate-specific chromatin architectural protein, Hmgn1, and demonstrate that they are required for development of vertebrate-specific brain cell types. Specifically, we show that NMDA receptor-mediated pathways are dysregulated in zebrafish lacking these micropeptides and that their loss preferentially alters the gene regulatory networks that establish cerebellar cells and oligodendrocytes - evolutionarily newer cell types that develop postnatally in humans. These findings reveal a key missing link in the evolution of vertebrate brain cell development and illustrate a genetic basis for how some neural cell types are more susceptible to chromatin disruptions, with implications for neurodevelopmental disorders and disease

Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate

International audienceABSTRACT: BACKGROUND: Nitrate, acting as both a nitrogen source and a signaling molecule, controls many aspects of plant development. However, gene networks involved in plant adaptation to fluctuating nitrate environments have not yet been identified. RESULTS: Here we use time-series transcriptome data to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to nitrate provision. The experimental approach has been to monitor genome-wide responses to nitrate at 3, 6, 9, 12, 15 and 20 minutes, using Affymetrix ATH1 gene chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by a very fast gene expression modulation, involving genes and functions needed to prepare plants to use or reduce nitrate. A state-space model inferred from this microarray time-series data successfully predicts gene behavior in unlearnt conditions. CONCLUSIONS: The experiments and methods allow us to propose a temporal working model for nitrate-driven gene networks. This network model is tested both in silico and experimentally. For example, the over-expression of a predicted gene hub encoding a transcription factor induced early in the cascade indeed leads to the modification of the kinetic nitrate response of sentinel genes such as NIR, NIA2, and NRT1.1, and several other transcription factors. The potential nitrate /hormone connections implicated by this time-series data is also evaluated

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210