COVID-19 disease and malignant cancers: The impact for the furin gene expression in susceptibility to SARS-CoV-2.

Furin is a proprotein convertase that activates different kinds of regulatory proteins, including SARS-CoV-2 spike protein which contains an additional furin-specific cleavage site. It is essential in predicting cancer patients' susceptibility to SARS-CoV-2 and the disease outcomes due to varying furin expressions in tumor tissues. In this study, we analyzed furin's expression, methylation, mutation rate, functional enrichment, survival rate and COVID-19 outcomes in normal and cancer tissues using online databases, and our IHC. As a result, furin presented with biased expression profiles in normal tissues, showing 12.25-fold higher than ACE2 in the lungs. The furin expression in tumors were significantly increased in ESCA and TGCT, and decreased in DLBC and THYM, indicating furin may play critical mechanistic functions in COVID-19 viral entry into cells in these cancer patients. Line with furin over/downexpression, furin promoter hypo-/hyper-methylation may be the regulatory cause of disease and lead to pathogenesis of ESCA and THYM. Furthermore, presence of FURIN-201 isoform with functional domains (P_proprotein, Peptidase_S8 and S8_pro-domain) is highest in all cancer types in comparison to other isoforms, demonstrating its use in tumorigenesis and SARS-Cov-2 entry into tumor tissues. Furin mutation frequency was highest in UCES, and its mutation might elevate ACE2 expression in LUAD and UCEC, reduce ACE2 expression in COAD, elevate HSPA5 expression in PAAD, and elevate TMPRSS2 expression in BRCA. These results showed that furin mutations mostly increased expression of ACE2, HSPA5, and TMPRSS2 in certain cancers, indicating furin mutations might facilitate COVID-19 cell entry in cancer patients. In addition, high expression of furin was significantly inversely correlated with long overall survival (OS) in LGG and correlated with long OS in COAD and KIRC, indicating that it could be used as a favorable prognostic marker for cancer patients' survival. GO and KEGG demonstrated that furin was mostly enriched in genes for metabolic and biosynthetic processes, retinal dehydrogenase activity, tRNA methyltransferase activity, and genes involving COVID-19, further supporting its role in COVID-19 and cancer metabolism. Moreover, Cordycepin (CD) inhibited furin expression in a dosage dependent manner. Altogether, furin's high expression might not only implies increased susceptibility to SARS-CoV-2 and higher severity of COVID-19 symptoms in cancer patients, but also it highlights the need for cancer treatment and therapy during the COVID-19 pandemic. CD might have a potential to develop an anti-SARS-CoV-2 drug through inhibiting furin expression.

Quantifying Light Response of Leaf-Scale Water-Use Efficiency and Its Interrelationships With Photosynthesis and Stomatal Conductance in C3 and C4 Species.

Light intensity (I) is the most dynamic and significant environmental variable affecting photosynthesis (A n), stomatal conductance (g s), transpiration (T r), and water-use efficiency (WUE). Currently, studies characterizing leaf-scale WUE-I responses are rare and key questions have not been answered. In particular, (1) What shape does the response function take? (2) Are there maximum intrinsic (WUEi; WUEi-max) and instantaneous WUE (WUEinst; WUEinst-max) at the corresponding saturation irradiances (I i-sat and I inst-sat)? This study developed WUEi-I and WUEinst-I models sharing the same non-asymptotic function with previously published A n-I and g s-I models. Observation-modeling intercomparison was conducted for field-grown plants of soybean (C3) and grain amaranth (C4) to assess the robustness of our models versus the non-rectangular hyperbola models (NH models). Both types of models can reproduce WUE-I curves well over light-limited range. However, at light-saturated range, NH models overestimated WUEi-max and WUEinst-max and cannot return I i-sat and I inst-sat due to its asymptotic function. Moreover, NH models cannot describe the down-regulation of WUE induced by high light, on which our models described well. The results showed that WUEi and WUEinst increased rapidly within low range of I, driven by uncoupled photosynthesis and stomatal responsiveness. Initial response rapidity of WUEi was higher than WUEinst because the greatest increase of A n and T r occurred at low g s. C4 species showed higher WUEi-max and WUEinst-max than C3 species-at similar I i-sat and I inst-sat. Our intercomparison highlighted larger discrepancy between WUEi-I and WUEinst-I responses in C3 than C4 species, quantitatively characterizing an important advantage of C4 photosynthetic pathway-higher A n gain but lower T r cost per unit of g s change. Our models can accurately return the wealth of key quantities defining species-specific WUE-I responses-besides A n-I and g s-I responses. The key advantage is its robustness in characterizing these entangled responses over a wide I range from light-limited to light-inhibitory light intensities, through adopting the same analytical framework and the explicit and consistent definitions on these responses. Our models are of significance for physiologists and modelers-and also for breeders screening for genotypes concurrently achieving maximized photosynthesis and optimized WUE.

Comparing two measures of leaf photorespiration rate across a wide range of light intensities.

Suppression of photorespiration by low O2 concentrations (Method 1) and simultaneous measurements of gas exchange and chlorophyll fluorescence (Method 2) are often used to estimate leaf photorespiration rate (Rp) of C3 plants. However, it is largely unknown whether Method 1 and Method 2 can be used equivalently in estimating Rp. Using a field experiment on two wheat cultivars (T. aestivum JM22 and T. aestivum Z39-118) whose leaf gas exchange and chlorophyll fluorescence at low and normal O2 concentrations (2% versus 21% O2) were simultaneously measured across a wide range of light intensities (I), this study assessed the impacts of the two measures on Rp and its response under changing irradiance conditions. All the above quantities increased with the increasing I until reaching the cultivar-specific maximum values and the corresponding saturation light intensities. However, there were significant differences between Rp estimated by Method 1 and Method 2 at the I range from 150 to 2000 µmol m-2 s-1 for T. aestivum JM22 and from 150 to 1000 µmol m-2 s-1 for T. aestivum Z39-118. These findings demonstrated that the two methods cannot be used equivalently under changing irradiance conditions.