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Biofoundries provide an integrated infrastructure to enable the rapid design, construction, and testing of genetically reprogrammed organisms for biotechnology applications and research. Many biofoundries are being built and a Global Biofoundry Alliance has recently been established to coordinate activities worldwide.

The original version of this Comment contained errors in the legend of Figure 2, in which the locations of the fifteenth and sixteenth GBA members were incorrectly given as ‘(15) Australian Genome Foundry, Macquarie University; (16) Australian Foundry for Advanced Biomanufacturing, University of Queensland.’. The correct version replaces this with ‘(15) Australian Foundry for Advanced Biomanufacturing (AusFAB), University of Queensland and (16) Australian Genome Foundry, Macquarie University’. This has been corrected in both the PDF and HTML versions of the Comment.

The main objective of the research project is to design and develop a web-based visualization interface for the assessment of osteoarthritis. This involves the development of semi-automatic segmentation method, cartilage measurement technique, and 2D/3D visualization techniques/interfaces for the knee joint (e.g. bones and cartilage). The project focused on analyzing the articular cartilage thickness of the knee joint using MR images. The following were carried out in the project. 1. A web-based 3D visualization interface has been developed. Using this interface, it is possible to visualize the knee joint in 3D and perform quantitative measurement of anatomical structures. The interface also enables the visibility of 3D structures to be interactively changed. This enables clinician to view structures that would otherwise be obstructed. This interface was subsequently developed using Java to make it web-based. A new 3D trackback function was developed to facilitate the studying of 3D model and 2D images by allowing clinician to click on the 3D model to retrieve corresponding image and highlight the point of interest on the image. 2. A program to visualise both anatomical and quantitative MR images was developed to facilitate the examining of quantitative MR images during diagnosis. 3. A MR noise removal technique which utilized differential evolution for parameters selection has been developed. 4. A semi-automatic segmentation method for the cartilage has been developed to delineate articular cartilage using MR images. 5. A cartilage thickness measurement and visualization program has been developed which measures the articular cartilage thickness using segmented images derived from the semi-automatic segmentation program. An interface that aids segmentation process has been developed. This interface allows clinician to use prior region of interest to initiate the segmentation of bone and cartilage. SUG 9/07

Clinical decision making is a ubiquitous and frequent task physicians make in their daily clinical practice. Conventionally, physicians adopt a cognitive predictive modelling process (i.e. knowledge and experience learnt from past lecture, research, literature, patients, etc.) for anticipating or ascertaining clinical problems based on clinical risk factors that they deemed to be most salient. However, with the inundation of health data and the confounding characteristics of diseases, more effective clinical prediction approaches are required to address these challenges. Approximately a few century ago, the first major transformation of medical practice took place as science-based approaches emerged with compelling results. Now, in the 21st century, new advances in science will once again transform healthcare. Data science has been postulated as an important component in this healthcare reform and has received escalating interests for its potential for ‘personalizing’ medicine. The key advantages of having personalized medicine include, but not limited to, (1) more effective methods for disease prevention, management and treatment, (2) improved accuracy for clinical diagnosis and prognosis, (3) provide patient-oriented personal health plan, and (4) cost containment. In view of the paramount importance of personalized predictive models, this thesis proposes 2 novel learning algorithms (i.e. an immune-inspired algorithm called the Evolutionary Data-Conscious Artificial Immune Recognition System, and a neural-inspired algorithm called the Artificial Neural Cell System for classification) and 3 continuum-based paradigms (i.e. biological, time and age continuum) for enhancing clinical prediction. Cardiovascular disease has been selected as the disease under investigation as it is an epidemic and major health concern in today’s world. We believe that our work has a meaningful and significant impact to the development of future healthcare system and we look forward to the wide adoption of advanced medical technologies by all care centres in the near future. BIOENGINEERING

Knee joint is the largest joint within the human body and is most prone to injuries. This thesis presents the works that were carried out as part of a major research to develop an integrated system for knee joint related clinical diagnosis, pre-surgical planning and post-operative monitoring. The research is divided into three phases. Phase one involves in the creation of image segmentation modules for specific tissues at the joint, while phase two focuses on reconstruction of three-dimensional models from segmented images. Phase three dwells in the development of clinical based application modules. This project focuses on phase one of the development of the proposed integrated system. The specific aims of the project are to develop semi-automated segmentation techniques for anterior cruciate ligament (ACL) and menisci of the knee joint in magnetic resonance (MR) images, because these two tissues are most prone to damages when a knee joint is injured. Achieving these aims will set the foundation for future developments of this integrated system. The first presented work is the profile studies of knee joint related MR images. This study revealed a reproducible landmark in the vertical intensity profile which can aid computer based systems in locating the menisci automatically in MR images. In the second and third works, methodologies to the innovated semi-automated segmentation programs of ACL and meniscus are presented respectively. Both programs relied on morphological operations to locate the anatomical structures and active contour to perform the segmentation. Proton density weighted isotropic MR images were acquired and used to test the programs developed. Validation studies were conducted and the methodologies developed were proven to be feasible in achieving the segmentation tasks. MASTER OF ENGINEERING (SCBE)

Quantitative understanding of complex biological systems has been a major challenge. The synthetic biology toolkit helps in engineering genetic circuits to design such complex systems. To develop effective precisely-controlled circuits, rapidly regulate-able gene expression systems are necessary. Opto-genetic modules offer unprecedented ways to control cellular functions in precise spatial and temporal resolution. However, current opto-genetic systems have been limited to low dynamic expression and switchable control. Henceforth, the design of synthetic circuits for coordinated cell-cell communication has been difficult. A novel blue light-regulated genetic system is characterised in this work that demonstrates precise and stable switchable gene expression control with light intensity and pulse-width percentages. The system provides effective means of coordinated functions and thus, is applied to optically synchronize cells to perform different control functions. With such precise control, the system serves as a basis for underlying biological patterns and new developments in Systems biology and Biotechnology. MASTER OF ENGINEERING (EEE)

Superbug infection is one of the greatest public health threat with grave implications across all levels of society. Towards a new solution to combat infection by multi-drug resistant bacteria, this thesis presents an engineering framework and genetic tools applied to repurpose commensal bacteria into "micro-robots" for the treatment of superbug infection. Specifically, a prototype of designer probiotic was developed using the human commensal bacteria Escherichia coli. The engineered commensal was reprogrammed with user-specified functions to sense superbug, produced pathogen-specific killing molecules and released the killing molecules via a lytic mechanism. The engineered commensal was effective in suppressing -99% of planktonic Pseudomonas and preventing - 90% of biofilm formation. To enhance the sensing capabilities of engineered commensal, genetic interfaces comprising orthogonal AND & OR logic devices were developed to mediate the integration and interpretation of binary input signals. Finally, AND, OR and NOT logic gates were networked to generate a myriad of cellular logic operations including half adder and half subtracter. The creation of half adder logic represents a significant advancement of engineering human commensal to be biological equivalent of microprocessor Chips in programmable computer with the ability to process input signals into diversified actions. Importantly. this thesis provides exemplary case studies to the attenuation of cellular and genetic context dependent effects through principles elucidated herein, thereby advancing our capability to engineer commensal bacteria. DOCTOR OF PHILOSOPHY (SCBE)

Cholera disease is still a major global threat according to WHO. This notion is reinforced by the fact that the antibiotic resistance of Vibrio cholerae, the causative agent of the disease, is increasing in the epidemic strains. In year 2016 alone numerous occurrences of cholera outbreaks were reported, e.g. in Haiti and Sudan. The currently available methods of detection, treatment and prevention of cholera lack the required characteristics. Detection is slow or costly, treatment is mostly aimed at the symptoms and prevention in forms of vaccines is ineffective. To mitigate some of these problems, the goal of this research project is to engineer novel beneficial probiotic microbes to fight V. cholerae infections. To this end, a set of synthetic genetic circuits were created using the tools of synthetic biology. These circuits aim was to create a genetically modified Escherichia coli able to sense and kill V. cholerae. First, a whole cell E. coli based biosensor for V. cholerae detection has been designed, constructed and characterized. Second, this sensor circuit was redesigned to create sense and kill mechanism. Artilysin, a recently developed antimicrobial agent that can be directly expressed by cells was shown to be effective against V. cholerae cells. This work is first both to show a working V. cholerae biosensor in E. coli and an E. coli strain that is able to destroy V. cholerae upon its detection. Main advantage of this approach is that it should be possible not only to mitigate the cholera symptoms, but also to eliminate the cause of the disease, which was not possible before. This study is also a showcase of design principles for synthetic biology with examples of novel circuits with new, previously unknown applications and combinations. Finally, this integrated system forms a basis for a further development of viable detection and therapy option for V. cholerae infection. Doctor of Philosophy (SCBE)

Magnetic Resonance Imaging (MRI) is a versatile modality which is widely used for anatomical and physiological imaging in applications including oncology, neuroimaging, and cardiac angiography - to name a few. However, due to patient motion, hardware limitations and constraints on acquisition time, anisotropic images are acquired, sacrificing detail in through-plane. Multiplane super-resolution is a post-processing technique that uses data from multiplane anisotropic acquisition and reconstructs higher resolution MR images. However, certain gaps exist in the application of super-resolution in the context of MRI and research presented in this thesis attempts to address some of the unexplored areas in terms of clinical applications as well as applicability of current state-of-art super-resolution frameworks. The focus of this thesis is on the application of super-resolution for resolution improvement of MR images and development of a novel super-resolution framework that broadens its applicability to other MR applications. For this, three main studies were performed. In the first study, super-resolution was employed to enhance DWI resolution in the context of prostate cancer assessment. In this study, MRI data of 25 patients were acquired, isotropically reconstructed using super-resolution and analysed. Since it is unclear how through plane affects prostate cancer assessment, impact of through plane resolution improvement on prostate cancer diagnosis has been investigated. From the study, super-resolution reconstructions have been found to have increased SNR, sharpness and reduced volumetric error compared to anisotropic acquisitions. These isotropic super-resolution reconstructions have been also found to have increased accuracy for detection of clinically significant cancers and improved visualization in through-plane. In the second study, super-resolution reconstructions of DWI and super-resolution reconstructions of T2WI were fused to improve delineation of tumor and visualization. In this study, it was found out that fusion of super-resolution reconstructions of DWI and T2WI improved tumor coverage and visualization in through and oblique planes, which could potentially benefit targeted biopsy. In the third study, a novel SR framework, DIRSR, was designed and developed in which deformable registration is added to registration framework, along with rigid registration. Most super-resolution implementations use rigid registration, making the SR framework prone to artifacts in applications with non-rigid deformation/motion including lungs and heart. Using DIRSR, isotropic volumes were reconstructed from lung data and were evaluated. Results show significant improvement in alignment of images compared to Rigid-Registration SR frameworks. Reconstructions from DIRSR were also found to have increased sharpness and reduced error compared to Rigid-Registration SR framework and super-resolution using pre-registered inputs. In summary, the studies presented in the thesis indicate that SR techniques can be beneficial for clinical assessment and diagnosis, including MR guided biopsy. Doctor of Philosophy (SCBE)

Genetic transcription is the first step for gene expression. Without transcription, it is impossible for organism to transfer the genetic information to translation and eventually realize its normal function via proteins. The regulation of transcription is very important to ensure the accurate heredity of genetic information. Growth rate is a crucial characteristic for exponentially growing bacteria and thus lots of macromolecules including gene expression production is usually growth-dependent. Lots of studies have been focused on global growthdependence of gene expression while not so much researches and reviews focused on transcription’s growth-dependence. Promoters, sigma factors and RNA polymerase are important regulatory factors in transcription initiation, elongation and termination. However normal transcription involves not only regulatory factors but also need sufficient free and available raw materials like RNA polymerase, and growth rate will also impact the promoter activity and strength. Moreover, what is the relationship between sigma factors and bacterial global growth? This report reviews recent studies and investigates the detailed functions of promoters, sigma factors and RNA polymerase and their growth-dependence in bacteria. More importantly, we discuss how growth rate can affect promoter activity and strength, relationship between RNA polymerase and growth rate, how sigma factors involve in bacterial growth. It concludes that some transcription elements are growth-rate dependent like RNAP, alternative sigma factors like σ38, the strength of constitutive promoters; some are irrelevant with growth-rate, like total RNAP, core RNAP and housekeeping sigma factors such as σ70. ​Master of Science (Biomedical Engineering)