Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient's body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research. Lay Summary Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient's body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

The rapid and global spread of a new human coronavirus (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of COVID-19. Drug repositioning is an attractive approach that can facilitate the drug discovery process by repurposing existing pharmaceuticals to treat illnesses other than their primary indications. Here, we review current information concerning the global health issue of COVID-19 including promising approved drugs and ongoing clinical trials for prospective treatment options. In addition, we describe computational approaches to be used in drug repurposing and highlight examples of in silico studies of drug development efforts against SARS-CoV-2.

The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

Recent advancements in the use of microbial cells for scalable production of industrial enzymes encourage exploring new environments for efficient microbial cell factories (MCFs). Here, through a comparison study, ten newly sequenced Bacillus species, isolated from the Rabigh Harbor Lagoon on the Red Sea shoreline, were evaluated for their potential use as MCFs. Phylogenetic analysis of 40 representative genomes with phylogenetic relevance, including the ten Red Sea species, showed that the Red Sea species come from several colonization events and are not the result of a single colonization followed by speciation. Moreover, clustering reactions in reconstruct metabolic networks of these Bacillus species revealed that three metabolic clades do not fit the phylogenetic tree, a sign of convergent evolution of the metabolism of these species in response to special environmental adaptation. We further showed Red Sea strains Bacillus paralicheniformis (Bac48) and B. halosaccharovorans (Bac94) had twice as much secreted proteins than the model strain B. subtilis 168. Also, Bac94 was enriched with genes associated with the Tat and Sec protein secretion system and Bac48 has a hybrid PKS/NRPS cluster that is part of a horizontally transferred genomic region. These properties collectively hint towards the potential use of Red Sea Bacillus as efficient protein secreting microbial hosts, and that this characteristic of these strains may be a consequence of the unique ecological features of the isolation environment.

The yeast Saccharomyces cerevisiae is an attractive host for industrial scale production of biofuels including fatty alcohols due to its robustness and tolerance towards harsh fermentation conditions. Many metabolic engineering strategies have been applied to generate high fatty alcohol production strains. However, impaired growth caused by fatty alcohol accumulation and high cost of extraction are factors limiting large-scale production. Here, we demonstrate that the use of heterologous transporters is a promising strategy to increase fatty alcohol production. Among several plant and mammalian transporters tested, human FATP1 was shown to mediate fatty alcohol export in a high fatty alcohol production yeast strain. An approximately five-fold increase of fatty alcohol secretion was achieved. The results indicate that the overall cell fitness benefited from fatty alcohol secretion and that the acyl-CoA synthase activity of FATP1 contributed to increased cell growth as well. This is the first study that enabled an increased cell fitness for fatty alcohol production by heterologous transporter expression in yeast, and this investigation indicates a new potential function of FATP1, which has been known as a free fatty acid importer to date. We furthermore successfully identified the functional domain of FATP1 involved in fatty alcohol export through domain exchange between FATP1 and another transporter, FATP4. This study may facilitate a successful commercialization of fatty alcohol production in yeast and inspire the design of novel cell factories.

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

Altered metabolism has long been recognized as a defining property of cancer physiology, but is experiencing renewed interest as the importance of such alterations are becoming fully realized. Once regarded merely as a side effect of a damaging mutation or a general increase in proliferation rate, metabolic network rewiring is now viewed as an intentional process to optimize tumor growth and maintenance, and can even drive cancer transformation. This has motivated the search for anticancer targets among enzymes in the metabolic network of cancer cells. Genome-scale metabolic models (GEMs) provide the necessary framework to systematically interrogate this network, and many recent studies have successfully employed GEMs to predict anticancer drug targets in the metabolic networks of various cancer types.

The incentive for developing microbial cell factories for production of fuels and chemicals comes from the ability of microbes to deliver these valuable compounds at a reduced cost and with a smaller environmental impact compared to the analogous chemical synthesis. Another crucial advantage of microbes is their great biological diversity, which offers a much larger "catalog" of molecules than the one obtainable by chemical synthesis. Adaptation to different environments is one of the important drives behind microbial diversity. We argue that the Red Sea, which is a rather unique marine niche, represents a remarkable source of biodiversity that can be geared towards economical and sustainable bioproduction processes in the local area and can be competitive in the international bio-based economy. Recent bioprospecting studies, conducted by the King Abdullah University of Science and Technology, have established important leads on the Red Sea biological potential, with newly isolated strains of Bacilli and Cyanobacteria. We argue that these two groups of local organisms are currently most promising in terms of developing cell factories, due to their ability to operate in saline conditions, thus reducing the cost of desalination and sterilization. The ability of Cyanobacteria to perform photosynthesis can be fully exploited in this particular environment with one of the highest levels of irradiation on the planet. We highlight the importance of new experimental and in silico methodologies needed to overcome the hurdles of developing efficient cell factories from the Red Sea isolates.

The biotech industry relies on cell factories for production of pharmaceutical proteins, of which several are among the top-selling medicines. There is, therefore, considerable interest in improving the efficiency of protein production by cell factories. Protein secretion involves numerous intracellular processes with many underlying mechanisms still remaining unclear. Here, we use RNA-seq to study the genome-wide transcriptional response to protein secretion in mutant yeast strains. We find that many cellular processes have to be attuned to support efficient protein secretion. In particular, altered energy metabolism resulting in reduced respiration and increased fermentation, as well as balancing of amino-acid biosynthesis and reduced thiamine biosynthesis seem to be particularly important. We confirm our findings by inverse engineering and physiological characterization and show that by tuning metabolism cells are able to efficiently secrete recombinant proteins. Our findings provide increased understanding of which cellular regulations and pathways are associated with efficient protein secretion.

Microbial synthesis of medium chain aliphatic hydrocarbons, attractive drop-in molecules to gasoline and jet fuels, is a promising way to reduce our reliance on petroleum-based fuels. In this study, we enabled the synthesis of straight chain hydrocarbons (C7–C13) by yeast Saccharomyces cerevisiae through engineering fatty acid synthases to control the chain length of fatty acids and introducing heterologous pathways for alkane or 1-alkene synthesis. We carried out enzyme engineering/screening of the fatty aldehyde deformylating oxygenase (ADO), and compartmentalization of the alkane biosynthesis pathway into peroxisomes to improve alkane production. The two-step synthesis of alkanes was found to be inefficient due to the formation of alcohols derived from aldehyde intermediates. Alternatively, the drain of aldehyde intermediates could be circumvented by introducing a one-step decarboxylation of fatty acids to 1-alkenes, which could be synthesized at a level of 3 mg/L, 25-fold higher than that of alkanes produced via aldehydes.