Background Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2–4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation. Methods We customized Illumina’s Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls. Results Epigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g.IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively. Conclusions In summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections.

Carbendazim (methyl 2-benzimidazolecarbamate) is widely used as a systemic fungicide in human food production and appears to act on fungal tubulin. However, it also inhibits proliferation of human cancer cells, including drug-and multidrug-resistant and p53-deficient cell lines. Because of its promising preclinical antitumor activity, it has undergone phase I clinical trials and is under further clinical development. Although it weakly inhibits polymerization of brain microtubules and induces G 2 /M arrest in tumor cells, its mechanism of action in human cells has not been fully elucidated. We examined its mechanism of action in MCF7 human breast cancer cells and found that it inhibits proliferation (IC 50 , 10 M) and half-maximally arrests mitosis at a similar concentration (8 M), in concert with suppression of microtubule dynamic instability without appreciable microtubule depolymerization. It induces mitotic spindle abnormalities and reduces the metaphase intercentromere distance of sister chromatids, indicating reduction of tension on kinetochores, thus leading to metaphase arrest. With microtubules assembled in vitro from pure tubulin, carbendazim also suppresses dynamic instability, reducing the dynamicity by 50% at 10 M, with only minimal (

Secondary resistance to hormonal therapy for breast cancer commonly develops after an initial response to tamoxifen or aromatase inhibitors. Agents to abrogate these adaptive changes would substantially enhance the long-term benefits of hormonal therapy. Our studies with a stilbene derivative called TMS (2,3 ¶,4,5 ¶-tetramethoxystilbene) identified unexpected effects with potential utility for treatment of breast tumors secondarily resistant to hormonal therapy. TMS was originally developed as an inhibitor of cytochrome P450 1B1 to block the conversion of estradiol to 4-OH-estradiol. While studying this agent in three models of hormone resistance, we detected direct antitumor effects not related to its role as an inhibitor of catecholestrogens. During examination of the mechanisms involved, we showed that treatment with 3 Mmol/L TMS for 24 h inhibited tubulin polymerization and microtubule formation, caused a cell cycle block at the G 2 -M phase, and induced apoptosis. TMS also inhibited activated focal adhesion kinase (FAK), Akt, and mammalian target of rapamycin (mTOR) and stimulated c-jun-NH 2 -kinase and p38 mitogen-activated protein kinase activity. With respect to antitumor effects, TMS at a concentrations of 0.2 to 0.3 Mmol/L inhibited the growth of long-term tamoxifen-treated MCF-7 cells by 80% and fulvestrant-treated MCF-7 cells by 70%. In vivo studies, involving 8 weeks of treatment with TMS via a 30-mg s.c. implant, reduced tumor volume of tamoxifen-resistant MCF-7 breast cancer xenografts by 53%. Our data suggest that TMS is a promising therapeutic agent because of its unique ability to block several pathways involved in the development of hormone resistance. [Cancer Res 2007;67(12):5717-26]

NAP (Asn-Ala-Pro-Val-Ser-Ile-Pro-Gln) is a neuroprotective peptide that shows cognitive protection in patients with amnestic mild cognitive impairment, a precursor to Alzheimer's disease. NAP exhibits potent neuroprotective properties in several in vivo and cellular models of neural injury. While it has been found in many studies to affect microtubule assembly and/or stability in neuronal and glial cells at fM concentrations, it has remained unclear whether it acts directly or indirectly on tubulin or microtubules. We analyzed the effects of NAP (1 fM-1 μM) on the assembly of reconstituted bovine brain microtubules in vitro and found that it did not significantly (p < 0.05) alter polymerization of either purified tubulin or of a mixture of tubulin and unfractionated microtubuleassociated proteins. NAP also had no significant effect (p < 0.05) on the growing and shortening dynamics of steady-state microtubules at their plus ends, nor did it alter the polymerization or dynamics of microtubules assembled in the presence of 3-repeat or 4-repeat tau. Thus, the neuroprotective activity of NAP does not appear to involve a direct action on the polymerization or dynamics of purified tubulin or microtubules.

Most common methods for inferring transposable element (TE) evolutionary relationships are based on dividing TEs into subfamilies using shared diagnostic nucleotides. Although originally justified based on the “master gene” model of TE evolution, computational and experimental work indicates that many of the subfamilies generated by these methods contain multiple source elements. This implies that subfamily-based methods give an incomplete picture of TE relationships. Studies on selection, functional exaptation, and predictions of horizontal transfer may all be affected. Here, we develop a Bayesian method for inferring TE ancestry that gives the probability that each sequence was replicative, its frequency of replication, and the probability that each extant TE sequence came from each possible ancestral sequence. Applying our method to 986 members of the newly-discovered LAVA family of TEs, we show that there were far more source elements in the history of LAVA expansion than subfamilies identified using the CoSeg subfamily-classification program. We also identify multiple replicative elements in the AluSc subfamily in humans. Our results strongly indicate that a reassessment of subfamily structures is necessary to obtain accurate estimates of mutation processes, phylogenetic relationships and historical times of activity.