Evolving embodied intelligence from materials to machines

International audienceNatural lifeforms specialise to their environmental niches across many levels; from low-level features such as DNA and proteins, through to higher-level artefacts including eyes, limbs, and overarching body plans. We propose Multi-Level Evolution (MLE), a bottom-up automatic process that designs robots across multiple levels and niches them to tasks and environmental conditions. MLE concurrently explores constituent molecular and material 'building blocks', as well as their possible assemblies into specialised morphological and sensorimotor configurations. MLE provides a route to fully harness a recent explosion in available candidate materials and ongoing advances in rapid manufacturing processes. We outline a feasible MLE architecture that realises this vision, highlight the main roadblocks and how they may be overcome, and show robotic applications to which MLE is particularly suited. By forming a research agenda to stimulate discussion between researchers in related fields, we hope to inspire the pursuit of multi-level robotic design all the way from material to machin

Evolution and gene regulation of the genomic imprinting mechanism

Genomic imprinting describes an epigenetic mechanism by which genes are active or silent depending on their parental origin. Imprinting exists in plants and mammals, but how this monoallelic expression mechanism has evolved is not understood at the molecular level. Here I describe the mapping, sequencing and analysis of vertebrate orthologous imprinted regions spanning 11.5 Mb of genomic sequence from species with and without genomic imprinting. In eutherian (placental) mammals, imprinting can be regulated by differential DNA methylation, non-coding RNAs, enhancers and insulator elements. The systematic sequence comparison of the IGF2-H19 imprinting cluster, in eutherians and marsupials (tammar wallaby and opossum), has revealed the presence of the enigmatic non-coding RNA H19 in marsupials. Furthermore, we have characterised the marsupial H19 expression status and identified key regulatory elements required for the germline imprinting of the neighbouring IGF2 gene. All the major hallmarks of the imprinting mechanism of the IGF2-H19 locus were found to be conserved in therian mammals. In mammals, this imprinting system is therefore the most conserved germline derived epigenetic mechanism discovered so far. The high-quality genomic sequences have provided early glimpses of the genomic landscapes for species such as the monotreme platypus and marsupial tammar wallaby for which little was previously known. Comparative sequence analysis was used to identify candidate regulatory elements in the neighbouring imprinting centre 1 and 2 regions of human chromosome 11p15.5. Nine novel enhancer elements were identified following in vitro gene-reporter assays and correlation of conserved sequences with recent ENCODE data revealed probable functions for a further 24 elements. This project has led to the formation of the Sequence Analysis of Vertebrate Orthologous Imprinted Regions (SAVOIR) consortium and resources developed here are being used by the imprinting community to further our knowledge of the evolution of the genomic imprinting mechanism

TDiscovery and Development of Novel Therapeutic Agents for Advanced Melanoma

Malignant melanoma is the most dangerous form of skin cancer and accounts for about 75% of skin cancer deaths. Once diagnosed at the metastatic stage, it has a very poor prognosis with a median survival rate of 6 months and a 5-year survival rate of less than 5%. In addition, melanoma has become an important public health hazard owing to its rising incidence, which has been well documented over the past 50 years. Currently there is no effective way to treat melanoma. It is highly resistant to existing chemotherapy, radiotherapy, and immunotherapy. Over the past 30 years, only two drugs have been approved by the Food and Drug Administration (FDA) for metastatic melanoma: dacarbazine (DTIC) and interleukin-2 (IL-2). But even with these two drugs, fewer than 15% of patients have a favorable response and fewer than 5% of patients reach complete remission. On the other hand, the toxicity associated with DTIC and IL-2 is often significant, resulting in serious or life threatening side effects in many patients. In recent years, great efforts have been made in fighting metastatic melanoma. But neither combinations of DTIC with other chemotherapy drugs (e.g., cisplatin, vinblastine, and carmustine) nor adding interferon-α2b to DTIC have shown a survival advantage over DTIC treatment alone. Extensive clinical trials with a lot of antibodies and vaccines to treat metastatic melanoma have also failed to demonstrate satisfactory efficacy. Therefore, developing more effective drugs for melanoma is urgently needed. We started our efforts in finding new drugs for melanoma by screening a large compound library. The in vitro cytotoxicity data on several melanoma cell lines led us to the discovery of three active structure scaffolds: serine amides, serine amino alcohols, and arylthiazolidine-4-carboxylic acid amides (ATCAAs). Because ATCAAs showed better selectivity between cancer cells and normal fibroblast cells, the chemists in our group focused on this scaffold and performed extensive structure modifications for structure-activity-relationship (SAR) studies. The SAR results were then used to guide further synthesis in an effort to maximize activity and selectivity. Two active compounds identified during the process were sent to the U.S. National Cancer Institute for anticancer screening using 60 human tumor cell lines. Results showed that these two compounds have extensive cytotoxic activity against all nine types of cancer cells with IC50values ranging from 120 nM (leukemia, CCRF-CEM cell line) to 11 μM (colon cancer, HCC-15 cell line). One compound showed particularly good activity against melanoma cells (IC50=130 nM~1 mM against all eight melanoma cell lines). I then evaluated ATCAAs inhibitory effect on melanoma colony formation and in vivo melanoma tumor growth. The in vivo data were very encouraging. One tested compound significantly inhibited melanoma tumor growth at a dose of 10 mg/kg and showed higher efficacy than did DTIC at a dose of 60 mg/kg. These findings built up a strong basis for the development of novel chemotherapeutic drugs for advanced melanoma. Furthermore, the chemists in our group also synthesized some new imidazole and imidazoline analogs by focusing on the SAR studies of the central five-member ring. Although the current compounds displayed lower potency when compared with our lead thiazolidine analogs, they may have the distinct advantage of being more stable in vivo with the reduced necessity of chiral separations. Some of these new compounds have activity similar to Sorafenib, an FDA-approved drug that has been tested clinically in melanoma patients. To further expand our understanding of SARs and to potentially identify new platforms for active compounds, Dr. Li and Dr. Seibel explored a compound library from the University of Cincinnati’s Drug Discovery Center. This library contains 342,910 small molecules. Based on the structure of our lead molecule, two ligand-based virtual screening approaches were used: 1) similarity search based on atom connectivity by using Scitegic Pipeline Pilot software and 2) similarity search based on molecular shape by using Schrodinger software. Results showed that these two approaches are highly complementary and lead to different active molecular structures. These structures are quite suitable for further structural modification and provide new platforms for our anticancer drug discovery efforts. Subsequently, further lead structure optimization led to the discovery of substituted methoxylbenzoyl-aryl-thiazole (SMART) compounds. To improve solubility and to circumvent the metabolic instability brought by the thiazole ring, our team designed and synthesized a new series of analogs: 2-aryl-4-benzoyl-imidazoles (ABIs). These two classes of compounds showed great in vitro cytotoxicity against melanoma, and the IC50 of the most active compound was below 10 nM. They also showed equal potency against multi-drug resistant melanoma cells and the sensitive parent cells, indicating that these compounds can effectively overcome multi-drug resistance, which is a major cause of cancer chemotherapy failure. In vivo testing on C57BL/6 mice bearing B16-F1 melanoma allograft and on double homozygous SCID (severe combined immunodeficiency) hairless outbred (SHO) mice or athymic nude mice bearing A375 human melanoma xenograft showed these two classes of compounds significantly inhibited melanoma tumor growth. Some compounds even showed substantially better activity than did DTIC, the gold standard anti-melanoma drug. Meanwhile, preliminary toxicity studies suggested that mice can tolerate tested compounds well at effective dose levels. No sign of acute toxicity was observed from the experiments. More importantly, I identified the cellular target for ABI and SMART compounds through a series of biotechniques and molecular modeling studies. Strong experimental evidence has shown that these compounds bind to tubulin at the colchicine binding site in the α/β-tubulin heterodimers to disrupt functional microtubule formation. In the meantime, I also tested the pharmacokinetic properties of some active compounds in mice together with Mr. Chien-ming Li. With their good in vivo anti-melanoma activity and their ability to overcome multi-drug resistance, these new classes of compounds have great potential for melanoma therapy

Virus discovery using current and novel methods

Next Generation Sequencing (NGS) technology allows researchers to sequence genetic material from a wide range of sources, including patient and environmental samples, and ancient remains. The recovery of viruses from such datasets can provide insights into the diversity and evolution of both novel and already known viruses. This thesis focuses on two aspects of virus discovery in NGS datasets. In the first part of this thesis, I present ancient viral sequences from hepatitis B virus, human parvovirus B19, and variola virus. The sequences were recovered from NGS datasets from individuals living in Eurasia between ∼150 to ∼31,630 years ago, using standard sequence matching tools. The data show the past existence of viruses similar to variants circulating today. The sequences reveal a complexity of virus evolution that is not evident when considering modern sequences alone, including revised substitution rates and most recent common ancestor dates, as well as geographic movement and extinction of strains. The identification of viral sequences in NGS datasets relies heavily on sequence-based matching of unknown sequences to a database of known sequences. Comparisons are usually done at the nucleotide or amino acid level. However, those methods only work well on sequences closely related to those already present in the database. With the aim of identifying more diverged viral sequences, in the second part of this thesis, I present an algorithm to compare sequences based on predicted structural features, such as secondary structures and conserved amino acids. The algorithm is modelled after the music-matching algorithm ‘Shazam’. While initial results of the algorithm are somewhat encouraging, problems remain, in particular with the identification of adequate structural features. Identifying highly diverged viral sequences is thus still a challenging problem, hopefully to be solved in the future

A grid and cloud-based framework for high throughput bioinformatics

Recent advances in genome sequencing technologies have unleashed a flood of new data. As a result, the computational analysis of bioinformatics data sets has been rapidly moving from a labbased desktop computer environment to exhaustive analyses performed by large dedicated computing resources. Traditionally, large computational problems have been performed on dedicated clusters of high performance machines that are typically local to, and owned by, a particular institution. The current trend in Grid computing has seen institutions pooling their computational resources in order to offload excess computational work to remote locations during busy periods. In the last year or so, commercial Cloud computing initiatives have matured enough to offer a viable remote source of reliable computational power. Collections of idle desktop computers have also been used as a source of computational power in the form of ‘volunteer Grids’. The field of bioinformatics is highly dynamic, with new or updated versions of software tools and databases continually being developed. Several different tools and datasets must often be combined into a coherent, automated workflow or pipeline. While existing solutions are available for constructing workflows, there is a clear need for long-lived analyses consisting of many interconnected steps to be able to migrate among Grid and cloud computational resources dynamically. This project involved research into the principles underlying the design and architecture of flexible, high-throughput bioinformatics processes. Following extensive research into requirements gathering, a novel Grid-based platform, Microbase, has been implemented that is based on service-oriented architectures and peer-to-peer data transfer technology. This platform has been shown to be amenable to utilising a wide range of hardware from commodity desktop computers, to high-performance cloud infrastructure. The system has been shown to drastically reduce the bandwidth requirements of bioinformatics data distribution, and therefore reduces both the financial and computational costs associated with cloud computing. The system is inherently modular in nature, comprising a service based notification system, a data storage system scheduler and a job manager. In keeping with e-Science principles, each module can operate in physical isolation from each other, distributed within an intranet or Internet. Moreover, since each module is loosely coupled via Web services, modules have the potential to be used in combination with external service oriented components or in isolation as part of another system. In order to demonstrate the utility of such an open source system to the bioinformatics community, a pipeline of inter-connected bioinformatics applications was developed using the Microbase system to form a high throughput application for the comparative and visual analysis of microbial genomes. This application, Automated Genome Analyser (AGA) has been developed to operate without user interaction. AGA exposes its results via Web-services which can be used by further analytical stages within Microbase, by external computational resources via a Web service interface or which can be queried by users via an interactive genome browser. In addition to providing the necessary infrastructure for scalable Grid applications, a modular development framework has been provided, which simplifies the process of writing Grid applications. Microbase has been adopted by a number of projects ranging from comparative genomics to synthetic biology simulations.EThOS - Electronic Theses Online ServiceGBUnited Kingdo