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Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder affecting 50 million people globally. It is characterized by the presence of extracellular senile plaques and intracellular neurofibrillary tangles, consisting of amyloid-β and hyperphosphorylated tau proteins, respectively. Despite global research efforts, there is currently no cure available, due in part to an incomplete understanding of the disease pathogenesis. Numerous possible mechanisms, or hypotheses, explaining the origins of sporadic or late-onset AD have been proposed, including the amyloid-β, inflammatory, vascular, and infectious hypotheses. However, despite ample evidence, the failure of multiple trial drugs at the clinical stage illuminates the possible pitfalls of these hypotheses. Systems biology is a strategy which aims to elucidate the interactions between parts of a whole. Using this approach, the current paper shows how the four previously mentioned hypotheses of AD pathogenesis can be intricately connected. This approach allows for seemingly contradictory evidence to be unified in a system-focused explanation of sporadic AD development. Within this view, it is seen that infectious agents, such as P. gingivalis, may play a central role. The data presented here shows that when present, P. gingivalis or its virulence factors, such as gingipains, may induce or exacerbate pathologies underlying sporadic AD. This evidence supports the view that infectious agents, and specifically P. gingivalis, may be suitable treatment targets in AD.

‘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 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. Significance:Although millions of people across the globe have been diagnosed with Long COVID, there still exist many research gaps in our understanding of the condition and its underlying causes. This work aims to elevate the discussion surrounding data sharing and data science in the research community and to engage data sharing as an enabler to fast-track the process of finding effective treatment for Long COVID.

The prevailing hypotheses for the persistent symptoms of Long COVID have been narrowed down to immune dysregulation and autoantibodies, widespread organ damage, viral persistence, and fibrinaloid microclots (entrapping numerous inflammatory molecules) together with platelet hyperactivation. Here we demonstrate significantly increased concentrations of von Willebrand factor (VWF), platelet factor 4 (PF4), serum amyloid A (SAA), α-2 antiplasmin (α-2AP), endothelial-leukocyte adhesion molecule 1 (E-selectin), and platelet endothelial cell adhesion molecule (PECAM-1) in the soluble part of the blood. It was noteworthy that the mean level of α-2 antiplasmin exceeded the upper limit of the laboratory reference range in Long COVID patients, and the other 5 were significantly elevated in Long COVID patients as compared to the controls. This is alarming if we take into consideration that a significant amount of the total burden of these inflammatory molecules has previously been shown to be entrapped inside fibrinolysis-resistant microclots (thus decreasing the apparent level of the soluble molecules). We conclude that presence of microclotting, together with relatively high levels of six biomarkers known to be key drivers of endothelial and clotting pathology, points to thrombotic endothelialitis as a key pathological process in Long COVID.

Background: Fibrin(ogen) amyloid microclots and platelet hyperactivation are key pathological findings in patients with acute COVID-19 infection and also in those with Long COVID/Post-Acute Sequelae of COVID-19 (PASC). These pathologies may represent a suitable target for pharmacological treatment of Long COVID. Methods: Here we report on the symptoms displayed by a cohort of 91 South African Long COVID patients at baseline and after a clinician-initiated anticoagulant regime was completed. For laboratory analysis, patients provided a blood sample before and after treatment. Fibrinaloid microclot presence was studied by adding thioflavin T to platelet poor plasma (PPP), whilst platelet hyperactivation was studied using two platelet markers- PAC1 and CD62P (P-selectin). The anticoagulant regime included dual antiplatelet therapy (DAPT- Clopidogrel 75mg + Aspirin 75mg) once a day, and a direct oral anticoagulant (DOAC- Apixaban) 5mg twice a day. A proton pump inhibitor (PPI) pantoprazole 40 mg/day was also prescribed for gastric protection. Each of the treated cases reported their main Long COVID symptoms, and whether their symptoms resolved following treatment or not. Results: In our cohort a most participants did not report any comorbidities before acute COVID-19 infection. Hypertension and dyslipidaemia were the commonest underlying illnesses, whilst the most commonly reported Long COVID symptoms included fatigue, cognitive dysfunction, shortness of breath, and joint and muscle pains. Following completion of treatment, each of the different symptoms resolved in the majority of patients. This was also reflected in the laboratory analysis, where a decrease in the severity of fibrin amyloid microclotting and the degree of platelet pathology was noted. No serious adverse bleeding events were reported. Conclusions: Fibrin amyloid microclots, platelet hyperactivation/ aggregation, and widespread endothelialitis inhibit the transport of oxygen at a capillary/cellular level. This provides a ready explanation for the symptoms of Long COVID. By normalizing the failed clotting physiology and reversal of the endothelialitis, triple anticoagulant therapy represents a promising treatment option that appears to be highly efficacious, and warrants controlled clinical studies. We caution that such a regime must only be followed under expert medical supervision in view of the risk of bleeding.

INTRODUCTIONSince the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients.OBJECTIVESIn this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome.METHODSA targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3’,4’-didehydro-3’-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients’ levels.RESULTS & CONCLUSIONFinally, we demonstrate the added value of the kynurenic acid / tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.

Ergothioneine is a naturally occurring antioxidant that has shown potential in ameliorating neurodegenerative and cardiovascular diseases. In this study, we investigated the potential of the Crabtree-negative, oleaginous yeast Yarrowia lipolytica as an alternative host for ergothioneine production. We expressed the biosynthetic enzymes EGT1 from Neurospora crassa and EGT2 from Claviceps purpurea to obtain 158 mg/L of ergothioneine in small-scale cultivation, with an additional copy of each gene improving the titer to 205 mg/L. The effect of phosphate limitation on ergothioneine production was studied, and finally, a phosphate-limited fed-batch fermentation in 1 L bioreactors yielded 1.63 ± 0.04 g/L ergothioneine in 220 hours, corresponding to an overall volumetric productivity of 7.41 mg L-1 h-1 , showing that Yarrowia lipolytica is a promising host for ergothioneine production.

Long COVID has become a significant global health and economic burden, yet there are currently no established diagnostic tools to identify which patients might benefit from specific treatments. One of the major pathophysiological factors contributing to Long COVID is the presence of hypercoagulability; this results in insoluble amyloid microclots that are resistant to fibrinolysis. Our previous research using fluorescence microscopy has demonstrated a significant amyloid microclot load in Long COVID patients. However, this approach lacked statistical robustness, objectivity, and rapid throughput. In the current study, we have used imaging flow cytometry for the first time to show significantly increased concentration and size of these microclots. We identified notable variations in size and fluorescence between microclots in Long COVID and those of controls even using a 20x objective. By combining cell imaging and the high-event-rate nature of a conventional flow cytometer, imaging flow cytometry can eliminate erroneous results and increase accuracy in gating and analysis beyond what pure quantitative measurements from conventional flow cytometry can provide. Although imaging flow cytometry was used in our study, our results suggest that the signals indicating the presence of microclots should be easily detectable using a conventional flow cytometer. Flow cytometry is a more widely available technique which has been used in pathology laboratories for decades, rendering it a potentially more suitable and accessible method for detecting microclots in individuals suffering from both Long COVID and other conditions with similar pathology, such as myalgic encephalomyelitis.

Acute COVID-19 infection is followed by prolonged symptoms in approximately one in ten cases: known as Long COVID. The disease affects ~65 million individuals worldwide. Many pathophysiological processes appear to underlie Long COVID, including viral factors (persistence, reactivation, and bacteriophagic action of SARS CoV-2); host factors (chronic inflammation, metabolic and endocrine dysregulation, immune dysregulation, and autoimmunity); and downstream impacts (tissue damage from the initial infection, tissue hypoxia, host dysbiosis, and autonomic nervous system dysfunction). These mechanisms culminate in the long-term persistence of the disorder characterized by a thrombotic endothelialitis, endothelial inflammation, hyperactivated platelets, and fibrinaloid microclots. These abnormalities of blood vessels and coagulation affect every organ system and represent a unifying pathway for the various symptoms of Long COVID.

Ergothioneine, an antioxidant nutraceutical mainly at present derived from the dietary intake of mushrooms, has been suggested as a preventive for pre-eclampsia. We analysed early pregnancy samples for a cohort of 432 first time mothers as part of the Screening for Endpoints in Pregnancy (SCOPE, European branch) project to determine the concentration of ergothioneine in their plasma. There was a weak association between the ergothioneine levels and maternal age, but none for BMI. Of these 432 women, 97 went on to develop pre-term (23) or term (74) pre-eclampsia. If a threshold was set at the 90thpercentile of the reference range in the control population (≥ 462 ng/mL), only one of these 97 women (1%) developed pre-eclampsia, versus 97/432 (22.5%) whose ergothioneine level was below this threshold. One possible interpretation of these findings, consistent with previous experiments in a reduced uterine perfusion model in rats, is that ergothioneine may indeed prove protective against pre-eclampsia in humans. An intervention study of some kind now seems warranted.

Multidrug transporters (MDTs) are major contributors to microbial drug resistance and are further utilized for improving host phenotypes in biotechnological applications. Therefore, the identification of these MDTs and the understanding of their mechanisms of action in vivo are of great importance. However, their promiscuity and functional redundancy represent a major challenge towards their identification. Here, a multistep tolerance adaptive laboratory evolution (TALE) approach was leveraged to achieve this goal. Specifically, a wild-type E. coli K-12-MG1655 and its cognate knockout individual mutants ΔemrE, ΔtolC, and ΔacrB were evolved separately under increasing concentrations of two lipophilic cations, tetraphenylphosphonium (TPP+), and methyltriphenylphosphonium (MTPP+). The evolved strains showed a significant increase in MIC values of both cations and an apparent cross-cation resistance. Sequencing of all evolved mutants highlighted diverse mutational mechanisms that affect the activity of nine MDTs including acrB, mdtK, mdfA, acrE, emrD, tolC, acrA, mdtL, and mdtP. Besides regulatory mutations, several structural mutations were recognized in the proximal binding domain of acrB and the permeation pathways of both mdtK and mdfA. These details can aid in the rational design of MDT inhibitors to efficiently combat efflux-based drug resistance. Additionally, the TALE approach can be scaled to different microbes and molecules of medical and biotechnological relevance.

The prevailing hypotheses for the persistent symptoms of Long COVID have been narrowed down to immune dysregulation and autoantibodies, widespread organ damage, viral persistence, and fibrinaloid microclots (entrapping numerous inflammatory molecules) together with platelet hyperactivation. Here we demonstrate significantly increased concentrations of Von Willebrand Factor, platelet factor 4,serum amyloid A, α-2antiplasmin E-selectin, and platelet endothelial cell adhesion molecule-1, in the soluble part of the blood. It was noteworthy that the mean level of α-2-antiplasmin exceeded the upper limit of the laboratory reference range in Long COVID patients, and the other 5 were significantly elevated in Long COVID patients as compared to the controls. This is alarming if we take into consideration that a significant amount of the total burden of these inflammatory molecules has previously been shown to be entrapped inside fibrinolysis-resistant microclots (thus decreasing the apparent level of the soluble molecules). We also determined that by individually adding E-selectin and PECAM-1 to healthy blood, these molecules may indeed be involved in protein-protein interactions with plasma proteins (contributing to microclot formation) and platelet hyperactivation. This investigation was performed as a laboratory model investigation and the final exposure concentration of these molecules was chosen to mimic concentrations found in Long COVID. We conclude that presence of microclotting, together with relatively high levels of six inflammatory molecules known to be key drivers of endothelial and clotting pathology, points to thrombotic endotheliitis as a key pathological process in Long COVID. This has implications for the choice of appropriate therapeutic options in Long COVID.SENTENCE SUMMARYThe presence of fibrinaloid microclots and multiple inflammatory molecules in the soluble part of blood points to thrombotic endotheliitis as a key pathological process in Long COVID.

Earlier variants of SARS-CoV-2 have been associated with plasma hypercoagulability (as judged by thromboelastography) and an extensive formation of fibrin amyloid microclots, which are considered to contribute to the pathology of the coronavirus 2019 disease (COVID-19). The newer Omicron variants appear to be far more transmissible, but less virulent, even when taking immunity acquired from previous infections or vaccination into account. We here show that while the clotting parameters associated with Omicron variants are significantly raised over those of healthy, matched controls, they are only raised to levels significantly lower than those seen with more severe variants such as Beta and Delta. We also observed that individuals infected with Omicron variants manifested less extensive microclot formation in platelet poor plasma compared to those harbouring the more virulent variants. The measurement of clotting effects between the different variants acts as a kind of ‘internal control’ that demonstrates the relationship between the extent of coagulopathies and the virulence of the variant of interest. This adds to the evidence that microclots play an important role in determining the severity of symptoms observed in COVID-19.

BackgroundPost-acute sequelae of COVID-19 (PASC), also now known as long COVID, has become a major global health and economic burden. Previously, we provided evidence that there is a significant insoluble fibrin amyloid microclot load in the circulation of individuals with long COVID, and that these microclots entrap a substantial number of inflammatory molecules, including those that might prevent clot breakdown. Scientifically, the most challenging aspect of this debilitating condition is that traditional pathology tests such as a serum CRP (C-reactive protein) may not show any significant abnormal inflammatory markers, albeit these tests measure only the soluble inflammatory molecules. Elevated, or abnormal soluble biomarkers such as IL-6, D-Dimer or fibrinogen indicate an increased risk for thrombosis or a host immune response in COVID-19. The absence of biomarkers in standard pathology tests, result in a significant amount of confusion for patients and clinicians, as patients are extremely sick or even bed-ridden but with no regular identifiable reason for their disease. Biomarkers that are currently available cannot detect the molecules present in the microclots we identified and are therefore unable to confirm their presence or the mechanisms that drive their formation.MethodsHere we analysed the protein content of double-digested microclots of 99 long COVID patients and 29 healthy controls. The patients suffering from long COVID reported their symptoms through a questionnaire completed by themselves or their attending physician.ResultsOur long COVID cohort’s symptoms were found to be in line with global findings, where the most prevalent symptoms were constant fatigue (74%,) cognitive impairment (71%) and depression and anxiety (30%). Our most noteworthy findings were a reduced level of plasma Kallikrein compared to our controls, an increased level of platelet factor 4 (PF4) von Willebrand factor (VWF), and a marginally increased level of α-2 antiplasmin (α-2-AP). We also found a significant presence of antibodies entrapped inside these microclots.ConclusionOur results confirm the presence of pro-inflammatory molecules that may also contribute to a failed fibrinolysis phenomenon, which could possibly explain why individuals with long COVID suffer from chronic fatigue, dyspnoea, or cognitive impairment. In addition, significant platelet hyperactivation was noted. Hyperactivation will result in the granular content of platelets being shed into the circulation, including PF4. Overall, our results provide further evidence of both a failed fibrinolytic system in long COVID/PASC and the entrapment of many proteins whose presence might otherwise go unrecorded. These findings might have significant implications for individuals with pre-existing comorbidities, including cardiovascular disease and type 2 diabetes.

Antibiotic resistance is a major global healthcare issue. Antibiotic compounds cross the bacterial cell membrane via membrane transporters, and a major mechanism of antibiotic resistance is through modification of the membrane transporters to increase the efflux or reduce the influx of antibiotics. Targeting these transporters is a potential avenue to combat antibiotic resistance. In this study, we used an automated screening pipeline to evaluate the growth of a library of 447

Directed evolution of proteins is a highly effective strategy for tailoring biocatalysts to a particular application, and is capable of engineering improvements such as k

The number of ‘small’ molecules that may be of interest to chemical biologists — chemical space — is enormous, but the fraction that have ever been made is tiny. Most strategies are discriminative, i.e. have involved ‘forward’ problems (have molecule, establish properties). However, we normally wish to solve the much harder generative or inverse problem (describe desired properties, find molecule). ‘Deep’ (machine) learning based on large-scale neural networks underpins technologies such as computer vision, natural language processing, driverless cars, and world-leading performance in games such as Go; it can also be applied to the solution of inverse problems in chemical biology. In particular, recent developments in deep learning admit the in silico generation of candidate molecular structures and the prediction of their properties, thereby allowing one to navigate (bio)chemical space intelligently. These methods are revolutionary but require an understanding of both (bio)chemistry and computer science to be exploited to best advantage. We give a high-level (non-mathematical) background to the deep learning revolution, and set out the crucial issue for chemical biology and informatics as a two-way mapping from the discrete nature of individual molecules to the continuous but high-dimensional latent representation that may best reflect chemical space. A variety of architectures can do this; we focus on a particular type known as variational autoencoders. We then provide some examples of recent successes of these kinds of approach, and a look towards the future.

Tuberculosis (TB) claims nearly 1.5 million lives annually. Current TB treatment requires a combination of several drugs administered for at least 6 months.

Early in the coronavirus disease 2019 (COVID-19) pandemic, global governing bodies prioritized transmissibility-based precautions and hospital capacity as the foundation for delay of elective procedures. As elective surgical volumes increased, convalescent COVID-19 patients faced increased postoperative morbidity and mortality and clinicians had limited evidence for stratifying individual risk in this population. Clear evidence now demonstrates that those recovering from COVID-19 have increased postoperative morbidity and mortality. These data—in conjunction with the recent American Society of Anesthesiologists guidelines—offer the evidence necessary to expand the early pandemic guidelines and guide the surgeon’s preoperative risk assessment. Here, we argue elective surgeries should still be delayed on a personalized basis to maximize postoperative outcomes. We outline a framework for stratifying the individual COVID-19 patient’s fitness for surgery based on the symptoms and severity of acute or convalescent COVID-19 illness, coagulopathy assessment, and acuity of the surgical procedure. Although the most common manifestation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is COVID-19 pneumonitis, every system in the body is potentially afflicted by an endotheliitis. This endothelial derangement most often manifests as a hypercoagulable state on admission with associated occult and symptomatic venous and arterial thromboembolisms. The delicate balance between hyper and hypocoagulable states is defined by the local immune-thrombotic crosstalk that results commonly in a hemostatic derangement known as fibrinolytic shutdown. In tandem, the hemostatic derangements that occur during acute COVID-19 infection affect not only the timing of surgical procedures, but also the incidence of postoperative hemostatic complications related to COVID-19-associated coagulopathy (CAC). Traditional methods of thromboprophylaxis and treatment of thromboses after surgery require a tailored approach guided by an understanding of the pathophysiologic underpinnings of the COVID-19 patient. Likewise, a prolonged period of risk for developing hemostatic complications following hospitalization due to COVID-19 has resulted in guidelines from differing societies that recommend varying periods of delay following SARS-CoV-2 infection. In conclusion, we propose the perioperative, personalized assessment of COVID-19 patients’ CAC using viscoelastic hemostatic assays and fluorescent microclot analysis.