Development of a System for Directed Evolution of \u3cem\u3eArabidopsis\u3c/em\u3e Formate Dehydrogenase to Utilize NADP as a Cofactor

Formate dehydrogenase (FDH) is a NAD-dependent enzyme found in methylotrophic bacteria, yeast and plants. This enzyme catalyzes the reversible oxidation of formate to carbon dioxide. The goal of this research was to determine the feasibility of using a directed evolution approach to generate an altered Arabidopsis FDH with a high affinity for NADP as a cofactor. A PCR procedure that induced approximately 1.5 mutations in the wild-type Arabidopsis FDH sequence per thousand base pairs was developed and the amplified products were transformed into E. coli cells. Approximately 1300 cell lines were assayed in 96-well microplates for activity with NADP+ and 100 putative mutants were selected for further study. One particular mutant line, pFDH-18, possessed reproducible NADP+-FDH activity. Sequence analysis showed that a single T in the wild-type DNA sequence had been changed to a G. The result of this mutation was that an isoleucine (Ile) residue at position 188 in the wild-type enzyme was converted to a methionine. This particular Ile residue is conserved in the known FDH sequences from higher plants and is located in the region of the enzyme that contains the binding domain for the NAD cofactor

A versatile polyacrylamide gel electrophoresis based sulfotransferase assay

<p>Abstract</p> <p>Background</p> <p>Sulfotransferases are a large group of enzymes that regulate the biological activity or availability of a wide spectrum of substrates through sulfation with the sulfur donor 3'-phosphoadenosine-5'-phosphosulfate (PAPS). These enzymes are known to be difficult to assay. A convenient assay is needed in order to better understand these enzymes.</p> <p>Results</p> <p>A universal sulfotransferase assay method based on sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) is described. This assay has been successfully applied to substrates as small as α-naphthol and as big as proteoglycans. As examples, we present the assays for recombinant human CHST4, TPST1, CHST3 and HS6ST1. In order to assess whether a small molecule can be applicable to this type of assay, a method to estimate the relative mobility of a molecule to PAPS is also presented. The estimated relative mobilities of various sulfated small molecules generated by SULT1A1, SULT1E1, SULT2A1 and CHST4 are in the range of ± 0.2 of the actual relative mobilities.</p> <p>Conclusion</p> <p>The versatility of the current method comes from the ability that SDS-PAGE can separate proteins and small molecules according to different parameters. While mobilities of proteins during SDS-PAGE are inversely related to their sizes, mobilities of small molecules are positively related to their charge/mass ratios. The predicted relative mobility of a product to PAPS is a good indicator of whether a sulfotransferase can be assayed with SDS-PAGE. Because phosphorylation is most similar to sulfation in chemistry, the method is likely to be applicable to kinases as well.</p

Exposures to structural racism and racial discrimination among pregnant and early post‐partum Black women living in Oakland, California

Research supports that exposure to stressors (e.g., perceived stress and racism) during pregnancy can negatively impact the immune system, which may lead to infection and ultimately increases the risk for having a preterm or low-birthweight infant. It is well known that Black women report higher levels of stressors at multiple timepoints across pregnancy compared with women of all other racial and ethnic groups. This study addresses gaps in the literature by describing pregnant and early post-partum Black women's exposures to structural racism and self-reported experiences of racial discrimination, and the extent to which these factors are related. We used a cross-sectional study design to collect data related to exposures to racism from pregnant and early post-partum Black women residing in Oakland, California, from January 2016 to December 2017. Comparative analysis revealed that living in highly deprived race + income neighborhoods was associated with experiencing racial discrimination in three or more situational domains (p = .01). Findings show that Black women are exposed to high levels of racism that may have negative impacts on maternal health outcomes

Exposures to structural racism and racial discrimination among pregnant and early post-partum Black women living in Oakland, California.

Research supports that exposure to stressors (e.g., perceived stress and racism) during pregnancy can negatively impact the immune system, which may lead to infection and ultimately increases the risk for having a preterm or low-birthweight infant. It is well known that Black women report higher levels of stressors at multiple timepoints across pregnancy compared with women of all other racial and ethnic groups. This study addresses gaps in the literature by describing pregnant and early post-partum Black women's exposures to structural racism and self-reported experiences of racial discrimination, and the extent to which these factors are related. We used a cross-sectional study design to collect data related to exposures to racism from pregnant and early post-partum Black women residing in Oakland, California, from January 2016 to December 2017. Comparative analysis revealed that living in highly deprived race + income neighborhoods was associated with experiencing racial discrimination in three or more situational domains (p = .01). Findings show that Black women are exposed to high levels of racism that may have negative impacts on maternal health outcomes

Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75&nbsp;days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The&nbsp;receiving operating characteristic&nbsp;(ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants.&nbsp;Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables