Some Aspects of Mast Cells Carboxypeptidase A3 Participation in the Pathogenesis of COVID-19

Background: This study aimed to determine the involvement of carboxypeptidase A3 (CPA3) in developing lung damage in patients with COVID-19. Methods and Results: The study included samples of autopsy material from the lungs of patients who died as a result of severe COVID-19 (the main group [MG] and persons who died from external causes (the control group [CG]). Immunohistochemical staining for CPA3 was carried out. A quantitative study of CPA3-positive mast cells (MCs) and the degree of their degranulation was carried out using a ×40 objective lens with an analysis of ≥50 fields of view with further conversion to 1 mm². Significant representation of CPA3-positive MCs per 1 mm2 of CPA3-positive MCs, CPA3-positive MCs with signs of degranulation (SD), and co-adjacent MCs was found in the MG compared to the CG (P=0.01 in all cases). In the main group, positive correlations were identified between the total number of CPA3-positive MCs, CPA3-positive MCs with SD and the blood hemoglobin level shortly before death (r=0.491 [P=0.008] and r=0.521 [P=0.004], respectively). Co-adjacent CPA3-positive MCs were negatively correlated with blood eosinophils at the beginning of hospitalization (r=-0.420 [P=0.023]). Also, the number of separately lying, CPA3-positive MCs negatively correlated with the blood monocyte shortly before death (r=-0.384 [P=0.044]). A positive correlation was established between the total number of CPA3-positive MCs, CPA3-positive MCs with SD, and adjacent CPA3-positive MCs with total blood protein in patients at the beginning of hospitalization (r=0.431 [P=0.020], r=0.449 [P=0.015] and r=0.456 [P=0.013], respectively). In addition, the study demonstrated a positive correlation between CPA3-positive MCs with SD and the total number of CPA3-positive MCs with blood aPTT levels (r=0.304 [P=0.045] and r=0.375 [P=0.045], respectively). A negative correlation was also found between the total number of CPA3-positive MCs and the blood INR level (r=-0.812 [P=0.050]). Finally, in patients at the beginning of hospitalization, a negative correlation was found between CPA3-positive MCs with SD, CPA3-positive MCs without SD, separately located CPA3-positive MCs, adjacent CPA3-positive MCs, and the total number of CPA3-positive MCs with blood amylase (r=-0.550 [P=0.002], r=-0.452 [P=0.045], r=-0.485 [P=0.030], r=-0.622 [P=0.008], and r=-0.590 [P=0.006], respectively). Conclusion: Our study identifies the potential involvement of CPA3 in the pathogenesis of severe COVID-19. However, many aspects of its participation remain unclear and require further study

Exploring the Interplay between Drug Release and Targeting of Lipid-Like Polymer Nanoparticles Loaded with Doxorubicin

Targeted delivery of doxorubicin still poses a challenge with regards to the quantities reaching the target site as well as the specificity of the uptake. In the present approach, two colloidal nanocarrier systems, NanoCore-6.4 and NanoCore-7.4, loaded with doxorubicin and characterized by different drug release behaviors were evaluated in vitro and in vivo. The nanoparticles utilize a specific surface design to modulate the lipid corona by attracting blood-borne apolipoproteins involved in the endogenous transport of chylomicrons across the blood–brain barrier. When applying this strategy, the fine balance between drug release and carrier accumulation is responsible for targeted delivery. Drug release experiments in an aqueous medium resulted in a difference in drug release of approximately 20%, while a 10% difference was found in human serum. This difference affected the partitioning of doxorubicin in human blood and was reflected by the outcome of the pharmacokinetic study in rats. For the fast-releasing formulation NanoCore-6.4, the AUC0→1h was significantly lower (2999.1 ng × h/mL) than the one of NanoCore-7.4 (3589.5 ng × h/mL). A compartmental analysis using the physiologically-based nanocarrier biopharmaceutics model indicated a significant difference in the release behavior and targeting capability. A fraction of approximately 7.310–7.615% of NanoCore-7.4 was available for drug targeting, while for NanoCore-6.4 only 5.740–6.057% of the injected doxorubicin was accumulated. Although the targeting capabilities indicate bioequivalent behavior, they provide evidence for the quality-by-design approach followed in formulation development

The type II TA systems of mycobacteria were investigated. Schematic diagram of the toxin-antitoxin system.

<p>(A) TA systems are annotated according to the GenBank database, excluding VapBC50 (rv3750c-rv3749c), VapBC49 (rv3180c-rv3181c), HigBA3 (rv3182-rv3183), HigBA2 (rv2022c-rv2021c), MazEF10 (rv0298-rv0299) and VapBC45 (rv2018-rv2019) systems; these systems are annotated according to Sala et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]. The system RelBE3 (rv3358-rv3357, GenBank database, NCBI) is called the YefM/YoeB system by Sala. All of the TA systems depicted here are type II (systems marked with an asterisk are novel TA systems that are not classified to any family, but for which functional activity has been shown [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]). The 13 genes, our proposed set for genotyping, are highlighted in bold. (B) Type II TA systems are encoded by two genes, a toxin and an antitoxin, that form one operon with a promoter located upstream of the first antitoxin gene. PIN domain is the functional part of the toxin gene, the four conserved acidic residues marked at the picture: the three well-conserved acidic residues, at positions 4[D], 40[E] and 93[D], and with fourth acidic residue is less well conserved at position 112[D].</p

<i>Mycobacterium tuberculosis</i> Type II Toxin-Antitoxin Systems: Genetic Polymorphisms and Functional Properties and the Possibility of Their Use for Genotyping

<div><p>Various genetic markers such as IS-elements, DR-elements, variable number tandem repeats (VNTR), single nucleotide polymorphisms (SNPs) in housekeeping genes and other groups of genes are being used for genotyping. We propose a different approach. We suggest the type II toxin-antitoxin (TA) systems, which play a significant role in the formation of pathogenicity, tolerance and persistence phenotypes, and thus in the survival of <i>Mycobacterium tuberculosis</i> in the host organism at various developmental stages (colonization, infection of macrophages, etc.), as the marker genes. Most genes of TA systems function together, forming a single network: an antitoxin from one pair may interact with toxins from other pairs and even from other families. In this work a bioinformatics analysis of genes of the type II TA systems from 173 sequenced genomes of <i>M</i>. <i>tuberculosis</i> was performed. A number of genes of type II TA systems were found to carry SNPs that correlate with specific genotypes. We propose a minimally sufficient set of genes of TA systems for separation of <i>M</i>. <i>tuberculosis</i> strains at nine basic genotype and for further division into subtypes. Using this set of genes, we genotyped a collection consisting of 62 clinical isolates of <i>M</i>. <i>tuberculosis</i>. The possibility of using our set of genes for genotyping using PCR is also demonstrated.</p></div

Scheme of typing of <i>M</i>. <i>tuberculosis</i> strains using 13 genes of type II TA systems.

<p>The algorithm for determining the genotype is presented. The scheme shows that, after the first iteration to determine the genotype, the number of genes for the analysis is decreased twofold. Each gene in the brackets is given its position that is replaced, and the appropriate nucleotide is indicated. All replacements are calculated relative to the reference strain H37Rv.</p

Phylogenetic relationship between different genotypes of the <i>M</i>. <i>tuberculosis</i>.

<p>(A) Phylogenetic tree constructed on the basis of polymorphisms (SNP) in all of the considered genes of type II TA systems. An unrooted phylogenetic tree for the 173 strains from this study was constructed based on the presence/absence of SNPs in the nucleotide sequences of 71 TA systems (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.s003" target="_blank">S3 Table</a>); (B) Phylogenetic tree constructed on the basis of SNP in a minimum set of genes of type II TA systems. An unrooted phylogenetic tree for 173 strains constructed based on SNPs in the nucleotide sequences of 13 genes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.t002" target="_blank">Table 2</a>). In both of cases strains included in the one cluster belong to the same genotype (various genotypes highlighted by color). The trees was constructed by the neighbor-joining approach. The TA systems sequences were retrieved from different databases (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#sec002" target="_blank">Materials and Methods</a>). Sequences were multiply aligned by using ClustalW ver. 2.1 software. The trees was calculated using MEGA ver. 6. Bootstrap support > 60% is indicated for the trees.</p

Detection of the Ural genotype by qPCR.

<p>Fluorescence in the FAM channel (blue): (1)13_2978, (2) 13–3114, (3) 13–3086, (4) 13_3158, (5) 13_4178, (6) 13_3539, (7) 13_2566, (8) 13_3632, (9) 13_3599, (10) 13_3896, (11) 13_3582, (12) 13_4189, (13) 13_3535, (15) 13_3147; Fluorescence in the HEX channel (green): (14) 13_3147, (16) 13_2978. Fluorescence of the channel FAM (blue) indicates the accumulation of the PCR product containing cytosine (C); the fluorescence of the channel HEX (green) indicates the accumulation of the PCR product containing thymine (T, the variable nucleotide) and indicates the SNP in the <i>vapC10</i> gene (C394→T394) characteristic of the Ural genotype. Line 14 (13_3147) and 16 (13_2978) belong to the Ural genotype. For isolate 13_2978 fluorescence is detected on the two channels (FAM and HEX), this can indicate the presence of impurities (coinfection). qPCR fluorescence in RFU (relative fluorescence units) vs. PCR cycles. Intensity of fluorescence depending on the number of qPCR cycles for strains belonging to the Euro-American lineage.</p