ARC Centre of Excellence in Synthetic Biology

Antibiotic resistance genes (ARGs) have accelerated microbial threats to human health in the last decade. Many genes can confer resistance, but evaluating the relative health risks of ARGs is complex. Factors such as the abundance, propensity for lateral transmission and ability of ARGs to be expressed in pathogens are all important. Here, an analysis at the metagenomic level from various habitats (6 types of habitats, 4572 samples) detects 2561 ARGs that collectively conferred resistance to 24 classes of antibiotics. We quantitatively evaluate the health risk to humans, defined as the risk that ARGs will confound the clinical treatment for pathogens, of these 2561 ARGs by integrating human accessibility, mobility, pathogenicity and clinical availability. Our results demonstrate that 23.78% of the ARGs pose a health risk, especially those which confer multidrug resistance. We also calculate the antibiotic resistance risks of all samples in four main habitats, and with machine learning, successfully map the antibiotic resistance threats in global marine habitats with over 75% accuracy. Our novel method for quantitatively surveilling the health risk of ARGs will help to manage one of the most important threats to human and animal health.

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications. In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

Mankind has recognized the value of land plants as renewable sources of food, medicine, and materials for millennia. Throughout human history, agricultural methods were continuously modified and improved to meet the changing needs of civilization. Today, our rapidly growing population requires further innovation to address the practical limitations and serious environmental concerns associated with current industrial and agricultural practices. Microalgae are a diverse group of unicellular photosynthetic organisms that are emerging as next-generation resources with the potential to address urgent industrial and agricultural demands. The extensive biological diversity of algae can be leveraged to produce a wealth of valuable bioproducts, either naturally or via genetic manipulation. Microalgae additionally possess a set of intrinsic advantages, such as low production costs, no requirement for arable land, and the capacity to grow rapidly in both large-scale outdoor systems and scalable, fully contained photobioreactors. Here, we review technical advancements, novel fields of application, and products in the field of algal biotechnology to illustrate how algae could present high-tech, low-cost, and environmentally friendly solutions to many current and future needs of our society. We discuss how emerging technologies such as synthetic biology, high-throughput phenomics, and the application of internet of things (IoT) automation to algal manufacturing technology can advance the understanding of algal biology and, ultimately, drive the establishment of an algal-based bioeconomy.

Biofilms are organised heterogeneous assemblages of microbial cells that are encased within a self-produced matrix. Current estimates suggest that up to 80% of bacterial and archaeal cells reside in biofilms. Since biofilms are the main mode of microbial life, understanding their biology and functions is critical, especially as controlling biofilm growth is essential in industrial, infrastructure and medical contexts. Here we discuss biofilms both as collections of individual cells, and as multicellular biological individuals, and introduce the concept of biofilms as unique incubators of diversity for the microbial world.

Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need for methods that can overcome these challenges to model this complex data. At present there is no cure for dementia and no treatment that can successfully change the course of the disease. Machine learning models that can predict the time until a patient develops dementia are important tools in helping understand dementia risks and can give more accurate results than traditional statistical methods when modelling high-dimensional, heterogeneous, clinical data. This work compares the performance and stability of ten machine learning algorithms, combined with eight feature selection methods, capable of performing survival analysis of high-dimensional, heterogeneous, clinical data. We developed models that predict survival to dementia using baseline data from two different studies. The Sydney Memory and Ageing Study (MAS) is a longitudinal cohort study of 1037 participants, aged 70-90 years, that aims to determine the effects of ageing on cognition. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal study aimed at identifying biomarkers for the early detection and tracking of Alzheimer's disease. Using the concordance index as a measure of performance, our models achieve maximum performance values of 0.82 for MAS and 0.93 For ADNI.

Smart devices are gaining popularity in our homes with the promise to make our lives easier and more comfortable. However, the increased deployment of such smart devices brings an increase in potential security risks. In this work, we propose an intrusion detection and mitigation framework, called IoT-IDM, to provide a network-level protection for smart devices deployed in home environments. IoT-IDM monitors the network activities of intended smart devices within the home and investigates whether there is any suspicious or malicious activity. Once an intrusion is detected, it is also capable of blocking the intruder in accessing the victim device on the fly. The modular design of IoT-IDM gives its users the flexibility to employ customized machine learning techniques for detection based on learned signature patterns of known attacks. Software-defined networking technology and its enabling communication protocol, OpenFlow, are used to realise this framework. Finally, a prototype of IoT-IDM is developed and the applicability and efficiency of proposed framework demonstrated through a real IoT device: a smart light bulb.

Antibiotic-resistant pathogens pose a significant threat to human health. Several dispersal mechanisms have been described, but transport of both microbes and antibiotic resistance genes (ARGs) via atmospheric particles has received little attention as a pathway for global dissemination. These atmospheric particles can return to the Earth's surface via rain or snowfall, and thus promote long-distance spread of ARGs. However, the diversity and abundance of ARGs in fresh snow has not been studied and their potential correlation with particulate air pollution is not well explored. Here, we characterized ARGs in 44 samples of fresh snow from major cities in China, three in North America, and one in Europe, spanning a gradient from pristine to heavily anthropogenically influenced ecosystems. High-throughput qPCR analysis of ARGs and mobile genetic elements (MGEs) provided strong indications that dissemination of ARGs in fresh snow could be exacerbated by air pollution, severely increasing the health risks of both air pollution and ARGs. We showed that snowfall did effectively spread ARGs from point sources over the Earth surface. Together our findings urge for better pollution control to reduce the risk of global dissemination of antibiotic resistance genes.

UTEX 2973. The UTEX 2973 fast-growth phenotype was only evident under specific growth conditions; however, UTEX 2973 accumulated high levels of proteins with strong native or synthetic promoters. The system is publicly available and can be readily expanded to accommodate other standardized MoClo parts to accelerate the development of reliable synthetic biology tools for the cyanobacterial community.

Bacterial multidrug efflux pumps have come to prominence in human and veterinary pathogenesis because they help bacteria protect themselves against the antimicrobials used to overcome their infections. However, it is increasingly realized that many, probably most, such pumps have physiological roles that are distinct from protection of bacteria against antimicrobials administered by humans. Here we undertake a broad survey of the proteins involved, allied to detailed examples of their evolution, energetics, structures, chemical recognition, and molecular mechanisms, together with the experimental strategies that enable rapid and economical progress in understanding their true physiological roles. Once these roles are established, the knowledge can be harnessed to design more effective drugs, improve existing microbial production of drugs for clinical practice and of feedstocks for commercial exploitation, and even develop more sustainable biological processes that avoid, for example, utilization of petroleum.

The co-selective pressure of heavy metals is a contributor to the dissemination and persistence of antibiotic resistance genes in environmental reservoirs. The overlapping range of antibiotic and metal contamination and similarities in their resistance mechanisms point to an intertwined evolutionary history. Metal resistance genes are known to be genetically linked to antibiotic resistance genes, with plasmids, transposons, and integrons involved in the assembly and horizontal transfer of the resistance elements. Models of co-selection between metals and antibiotics have been proposed, however, the molecular aspects of these phenomena are in many cases not defined or quantified and the importance of specific metals, environments, bacterial taxa, mobile genetic elements, and other abiotic or biotic conditions are not clear. Co-resistance is often suggested as a dominant mechanism, but interpretations are beset with correlational bias. Proof of principle examples of cross-resistance and co-regulation has been described but more in-depth characterizations are needed, using methodologies that confirm the functional expression of resistance genes and that connect genes with specific bacterial hosts. Here, we comprehensively evaluate the recent evidence for different models of co-selection from pure culture and metagenomic studies in environmental contexts and we highlight outstanding questions.

Phosphorus-rich carbons (PCs) were prepared by phosphoric acid activation of waste coffee grounds in different impregnation ratios. PCs were characterized by nitrogen and carbon dioxide adsorption and X-ray photoelectron spectroscopy. The results indicate that the activation step not only creates a porous structure, but also introduces various phosphorus and oxygen functional groups to the surface of carbons. As evidenced by cyclic voltammetry, galvanostatic charge/discharge, and wide potential window tests, a supercapacitor constructed from PC-2 (impregnation ratio of 2), with the highest phosphorus content, can operate very stably in 1 M H2 SO4 at 1.5 V with only 18 % degradation after 10 000 cycles at a current density of 5 A g(-1) . Due to the wide electrochemical window, a supercapacitor assembled with PC-2 has a high energy density of 15 Wh kg(-1) at a power density of 75 W kg(-1) . The possibility of widening the potential window above the theoretical potential for the decomposition of water is attributed to reversible electrochemical hydrogen storage in narrow micropores and the positive effect of phosphorus-rich functional groups, particularly the polyphosphates on the carbon surface.

Over the years, seaweeds have been highlighted as valuable natural sources of bioactive polysaccharides. Fucoidan, a sulphated polysaccharide mainly from brown seaweeds composed of a fucopyranose backbone and several monosaccharides, have been reported to possess numerous biological activities such as anticancer, antioxidant, immunoregulatory, antiviral, antithrombic, and anti-inflammatory properties thus may confer health benefits to humans. However, the main mechanisms bridging the structural complexity of fucoidans and their biological activity are mostly ignored. This review provides an update on the current knowledge of green extraction methods, purification, and structural analysis of fucoidan. Factors influencing the biological activities of fucoidan are also discussed. Lastly, the review presents concise information about the current application of fucoidans in the food industry, its utilization as delivery systems for nutraceuticals and its prospects in designing functional foods, as well as the toxicological concerns associated with the use of fucoidans. The structural complexity of fucoidans is dependent on the species, source, harvesting time, among other factors. This in turn greatly influences the biological activity of fucoidans, with high degree of sulphation and low molecular weight particularly linked with increased biological activity. Due to the presence of sulphate moieties, fucoidans easily interact with other polymers with far-reaching applications.

Global habitat deterioration of marine ecosystems has led to a need for active interventions to halt or reverse the loss of ecological function. Restoration has historically been a key tool to reverse habitat loss and restore functions, but the extent to which this will be sufficient under future climates is uncertain. Emerging genetic technologies now provide the ability for restoration to proactively match adaptability of target species to predicted future environmental conditions, which opens up the possibility of boosting resistance to future stress in degraded and threatened habitats. As such, the choice of whether to restore to historical baselines or anticipate the future remains a key decision that will influence restoration success in the face of environmental and climate change. Here, we present an overview of the different motives for restoration – to recover or revive lost or degraded habitats to extant or historical states, or to reinforce or redefine for future conditions. We focus on the genetic and adaptive choices that underpin each option and subsequent consequences for restoration success. These options span a range of possible trajectories, technological advances and societal acceptability, and represent a framework for progressing restoration of marine habitat forming species into the future.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the "One-Health" framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.

Antimicrobial resistance is a major threat for public health. Plasmids play a critical role in the spread of antimicrobial resistance via horizontal gene transfer between bacterial species. However, it remains unclear how plasmids originally recruit and assemble various antibiotic resistance genes (ARGs). Here, we track ARG recruitment and assembly in clinically relevant plasmids by combining a systematic analysis of 2420 complete plasmid genomes and experimental validation. Results showed that ARG transfer across plasmids is prevalent, and 87% ARGs were observed to potentially transfer among various plasmids among 8229 plasmid-borne ARGs. Interestingly, recruitment and assembly of ARGs occur mostly among compatible plasmids within the same bacterial cell, with over 88% of ARG transfers occurring between compatible plasmids. Integron and insertion sequences drive the ongoing ARG acquisition by plasmids, especially in which IS26 facilitates 63.1% of ARG transfer events among plasmids. In vitro experiment validated the important role of IS26 involved in transferring gentamicin resistance gene aacC1 between compatible plasmids. Network analysis showed four beta-lactam genes (blaTEM-1, blaNDM-4, blaKPC-2, and blaSHV-1) shuffling among 1029 plasmids and 45 clinical pathogens, suggesting that clinically alarming ARGs transferred accelerate the propagation of antibiotic resistance in clinical pathogens. ARGs in plasmids are also able to transmit across clinical and environmental boundaries, in terms of the high-sequence similarities of plasmid-borne ARGs between clinical and environmental plasmids. This study demonstrated that inter-plasmid ARG transfer is a universal mechanism for plasmid to recruit various ARGs, thus advancing our understanding of the emergence of multidrug-resistant plasmids.

Plastids, the defining organelles of plant cells, undergo physiological and morphological changes to fulfill distinct biological functions. In particular, the differentiation of chloroplasts into chromoplasts results in an enhanced storage capacity for carotenoids with industrial and nutritional value such as beta-carotene (provitamin A). Here, we show that synthetically inducing a burst in the production of phytoene, the first committed intermediate of the carotenoid pathway, elicits an artificial chloroplast-to-chromoplast differentiation in leaves. Phytoene overproduction initially interferes with photosynthesis, acting as a metabolic threshold switch mechanism that weakens chloroplast identity. In a second stage, phytoene conversion into downstream carotenoids is required for the differentiation of chromoplasts, a process that involves a concurrent reprogramming of nuclear gene expression and plastid morphology for improved carotenoid storage. We hence demonstrate that loss of photosynthetic competence and enhanced production of carotenoids are not just consequences but requirements for chloroplasts to differentiate into chromoplasts.

Abstract Utilising one-carbon substrates such as carbon dioxide, methane, and methanol is vital to address the current climate crisis. Methylotrophic metabolism enables growth and energy generation from methanol, providing an alternative to sugar fermentation. Saccharomyces cerevisiae is an important industrial microorganism for which growth on one-carbon substrates would be relevant. However, its ability to metabolize methanol has been poorly characterised. Here, using adaptive laboratory evolution and 13 C-tracer analysis, we discover that S. cerevisiae has a native capacity for methylotrophy. A systems biology approach reveals that global rearrangements in central carbon metabolism fluxes, gene expression changes, and a truncation of the uncharacterized transcriptional regulator Ygr067cp supports improved methylotrophy in laboratory evolved S. cerevisiae . This research paves the way for further biotechnological development and fundamental understanding of methylotrophy in the preeminent eukaryotic model organism and industrial workhorse, S. cerevisiae .

Gram-negative bacteria are intrinsically resistant to many antibiotics, due in large part to the permeability barrier formed by their cell envelope. The complex and synergistic interplay of the two Gram-negative membranes and active efflux prevents the accumulation of a diverse range of compounds that are effective against Gram-positive bacteria. A lack of detailed information on how components of the cell envelope contribute to this has been identified as a key barrier to the rational development of new antibiotics with efficacy against Gram-negative species. This review describes the current understanding of the role of the different components of the Gram-negative cell envelope in preventing compound accumulation and the state of efforts to describe properties that allow compounds to overcome this barrier and apply them to the development of new broad-spectrum antibiotics.

Genome scale metabolic modeling has traditionally been used to explore metabolism of individual cells or tissues. In higher organisms, the metabolism of individual tissues and organs is coordinated for the overall growth and well-being of the organism. Understanding the dependencies and rationale for multicellular metabolism is far from trivial. Here, we have advanced the use of AraGEM (a genome-scale reconstruction of Arabidopsis metabolism) in a multi-tissue context to understand how plants grow utilizing their leaf, stem and root systems across the day-night (diurnal) cycle. Six tissue compartments were created, each with their own distinct set of metabolic capabilities, and hence a reliance on other compartments for support. We used the multi-tissue framework to explore differences in the "division-of-labor" between the sources and sink tissues in response to: (a) the energy demand for the translocation of C and N species in between tissues; and (b) the use of two distinct nitrogen sources (NO(-) 3 or NH(+) 4). The "division-of-labor" between compartments was investigated using a minimum energy (photon) objective function. Random sampling of the solution space was used to explore the flux distributions under different scenarios as well as to identify highly coupled reaction sets in different tissues and organelles. Efficient identification of these sets was achieved by casting this problem as a maximum clique enumeration problem. The framework also enabled assessing the impact of energetic constraints in resource (redox and ATP) allocation between leaf, stem, and root tissues required for efficient carbon and nitrogen assimilation, including the diurnal cycle constraint forcing the plant to set aside resources during the day and defer metabolic processes that are more efficiently performed at night. This study is a first step toward autonomous modeling of whole plant metabolism.

Plastic offers a new niche for microorganisms, the plastisphere. The ever-increasing emission of plastic waste makes it critical to understand the microbial ecology of the plastisphere and associated effects. Here, we present a global fingerprint of the plastisphere, analyzing samples collected from freshwater, seawater, and terrestrial ecosystems. The plastisphere assembles a distinct microbial community that has a clearly higher heterogeneity and a more deterministically dominated assembly compared to natural habitats. New coexistence patterns-loose and fragile networks with mostly specialist linkages among microorganisms that are rarely found in natural habitats-are seen in the plastisphere. Plastisphere microbiomes generally have a great potential to metabolize organic compounds, which could accelerate carbon turnover. Microorganisms involved in the nitrogen cycle are also altered in the plastisphere, especially in freshwater plastispheres, where a high abundance of denitrifiers may increase the release of nitrite (aquatic toxicant) and nitrous oxide (greenhouse gas). Enrichment of animal, plant, and human pathogens means that the plastisphere could become an increasingly mobile reservoir of harmful microorganisms. Our findings highlight that if the trajectory of plastic emissions is not reversed, the expanding plastisphere could pose critical planetary health challenges.