Coupling engineering of Saccharomyces cerevisiae with medium optimization for the production of ergothioneine

Ergothioneine (ERG) is a naturally occurring, exogenous antioxidant that is nonetheless abundant in the human body. It has been shown both to reduce oxidative damage and to be involved in several diseases in vivo1,2. Therefore, ergothioneine is poised to take a place in the dietary supplement industry. Here we describe the engineering of the yeast Saccharomyces cerevisiae and subsequent medium optimization to produce ergothioneine by fermentation. After integrating combinations of biosynthetic pathways from different organisms, we screened yeast strains for their production of ERG. Next, the highest producing strain was engineered with ergothioneine transporters, and its amino acid metabolism was altered by knock-out of Tor1 or Yih1. The bottleneck for ergothioneine production was determined by integration of a second copy of the pathway enzymes. We also optimized the media composition for production of ergothioneine using yeast S. cerevisiae. Following these manipulations, we obtained a titer of 630 mg/l in fed-batch cultivation in bioreactors. This work shows that with further engineering of the strain, current chemical synthesis of ergothioneine could be replaced with a sustainable alternative. 1. Cheah, I. K. & Halliwell, B. Ergothioneine; antioxidant potential, physiological function and role in disease. Biochim. Biophys. Acta - Mol. Basis Dis. 1822, 784–793 (2012). 2. Halliwell, B., Cheah, I. K. & Tang, R. M. Y. Ergothioneine - a diet-derived antioxidant with therapeutic potential. FEBS Lett. (2018). doi:10.1002/1873-3468.1312

Prevalence of symptoms, comorbidities, fibrin amyloid microclots and platelet pathology in individuals with Long COVID/Post-Acute Sequelae of COVID-19 (PASC)

BackgroundFibrin(ogen) amyloid microclots and platelet hyperactivation previously reported as a novel finding in South African patients with the coronavirus 2019 disease (COVID-19) and Long COVID/Post-Acute Sequelae of COVID-19 (PASC), might form a suitable set of foci for the clinical treatment of the symptoms of Long COVID/PASC. A Long COVID/PASC Registry was subsequently established as an online platform where patients can report Long COVID/PASC symptoms and previous comorbidities.MethodsIn this study, we report on the comorbidities and persistent symptoms, using data obtained from 845 South African Long COVID/PASC patients. By using a previously published scoring system for fibrin amyloid microclots and platelet pathology, we also analysed blood samples from 80 patients, and report the presence of significant fibrin amyloid microclots and platelet pathology in all cases.ResultsHypertension, high cholesterol levels (dyslipidaemia), cardiovascular disease and type 2 diabetes mellitus (T2DM) were found to be the most important comorbidities. The gender balance (70% female) and the most commonly reported Long COVID/PASC symptoms (fatigue, brain fog, loss of concentration and forgetfulness, shortness of breath, as well as joint and muscle pains) were comparable to those reported elsewhere. These findings confirmed that our sample was not atypical. Microclot and platelet pathologies were associated with Long COVID/PASC symptoms that persisted after the recovery from acute COVID-19.ConclusionsFibrin amyloid microclots that block capillaries and inhibit the transport of O2 to tissues, accompanied by platelet hyperactivation, provide a ready explanation for the symptoms of Long COVID/PASC. Removal and reversal of these underlying endotheliopathies provide an important treatment option that urgently warrants controlled clinical studies to determine efficacy in patients with a diversity of comorbidities impacting on SARS-CoV-2 infection and COVID-19 severity. We suggest that our platelet and clotting grading system provides a simple and cost-effective diagnostic method for early detection of Long COVID/PASC as a major determinant of effective treatment, including those focusing on reducing clot burden and platelet hyperactivation

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

Protet_PCT model of ETP

A review of the deficiencies of the textbook explanation of electron transport-linked phosphorylation, and a proposed alternative that covers the fact

Lactoferrin biology

A review of lactoferrin, with a focus on its use as an immune booster and antivira

A dormant microbial component in the development of pre-eclampsia

Pre-eclampsia (PE) is a complex, multi-system disorder that remains a leading cause of morbidity and mortality in pregnancy. Four main classes of dysregulation accompany PE, and are widely considered to contribute to its severity. These are abnormal trophoblast invasion of the placenta, anti-angiogenic responses, oxidative stress, and inflammation. What is lacking, however, is an explanation of how these themselves are caused.We here develop the unifying idea, and the considerable evidence for it, that the originating cause of PE (and of the four classes of dysregulation) is in fact microbial infection, that most such microbes are dormant and hence resist detection by conventional (replication-dependent) microbiology, and that by occasional resuscitation and growth it is they that are responsible for all the observable sequelae, including the continuing, chronic inflammation. In particular, bacterial products such as lipopolysaccharide (LPS), also known as endotoxin, are well known as highly inflammagenic and stimulate an innate (and possibly trained) immune response that exacerbates the inflammation further. The known need of microbes for free iron can explain the iron dysregulation that accompanies PE. We describe the main routes of infection (gut, oral, urinary tract infection) and the regularly observed presence of microbes in placental and other tissues in PE. Every known proteomic biomarker of pre-eclampsia that we assessed has in fact also been shown to be raised in response to infection. An infectious component to PE fulfils the Bradford Hill criteria for ascribing a disease to an environmental cause, and suggests a number of treatments, some of which have in fact been shown to be successful.PE was classically referred to as endotoxaemia or toxaemia of pregnancy, and it is ironic that it seems that LPS and other microbial endotoxins really are involved. Overall, the recognition of an infectious component in the aetiology of PE mirrors that for ulcers and other diseases that were previously considered to lack one

Data sharing:A Long COVID perspective, challenges, and road map for the future

‘Long COVID’ is the term used to describe the phenomenon in which patients who have survived a COVID-19 infection continue to experience prolonged SARS-CoV-2 symptoms. Millions of people across the globe are affected by Long COVID. Solving the Long COVID conundrum will require drawing upon the lessons of the COVID-19 pandemic, during which thousands of experts across diverse disciplines such as epidemiology, genomics, medicine, data science, and computer science collaborated, sharing data and pooling resources to attack the problem from multiple angles. Thus far, there has been no global consensus on the definition, diagnosis, and most effective treatment of Long COVID. In this work, we examine the possible applications of data sharing and data science in general with a view to, ultimately, understand Long COVID in greater detail and hasten relief for the millions of people experiencing it. We examine the literature and investigate the current state, challenges, and opportunities of data sharing in Long COVID research

Data sharing: A Long COVID perspective, challenges, and road map for the future

‘Long COVID’ is the term used to describe the phenomenon in which patients who have survived a COVID-19 infection continue to experience prolonged SARS-CoV-2 symptoms. Millions of people across the globe are affected by Long COVID. Solving the Long COVID conundrum will require drawing upon the lessons of the COVID-19 pandemic, during which thousands of experts across diverse disciplines such as epidemiology, genomics, medicine, data science, and computer science collaborated, sharing data and pooling resources to attack the problem from multiple angles. Thus far, there has been no global consensus on the definition, diagnosis, and most effective treatment of Long COVID. In this work, we examine the possible applications of data sharing and data science in general with a view to, ultimately, understand Long COVID in greater detail and hasten relief for the millions of people experiencing it. We examine the literature and investigate the current state, challenges, and opportunities of data sharing in Long COVID research.</jats:p