Archives of microbiology & immunology最新文献

Long Covid is one of the most prevalent and puzzling conditions that arose with the Covid pandemic. Covid-19 infection generally resolves within several weeks but some experience new or lingering symptoms. Though there is no formal definition for such lingering symptoms the CDC boadly describes long Covid as persons having a wide range of new, recurring or sustained health issues four or more weeks after first being infected with SARS-CoV2. The WHO defines long Covid as the manifestation of symptoms from a "probable or confirmed" Covid-19 infection that start approximately 3 months after the onset of the acute infection and last for more than 2 months. Numerous studies have looked at the implications of long Covid on various organs. Many specific mechanisms have been proposed for such changes. In this article, we provide an overview of some of the main mechanisms by which long Covid induces end-organ damage proposed in recent research studies. We also review various treatment options, current clinical trials, and other potential therapeutic avenues to control long Covid followed by the information about the effect of vaccination on long Covid. Lastly, we discuss some of the questions and knowledge gaps in the present understanding of long Covid. We believe more studies of the effects long Covid has on quality of life, future health and life expectancy are required to better understand and eventually prevent or treat the disease. We acknowledge the effects of long Covid are not limited to those in this article but as it may affect the health of future offspring and therefore, we deem it important to identify more prognostic and therapeutic targets to control this condition.

There is increasing evidence that the T-cell protein, Lck, is involved in the pathogenesis of chronic lymphocytic leukemia (CLL) as well as other leukemias and lymphomas. We previously discovered that Lck binds to domain 5 of inositol 1,4,5-trisphosphate receptors (IP₃R) to regulate Ca²⁺ homeostasis. Using bioinformatics, we targeted a region within domain 5 of IP₃R-1 predicted to facilitate protein-protein interactions (PPIs). We generated a synthetic 21 amino acid peptide, KKRMDLVLELKNNASKLLLAI, which constitutes a domain 5 sub-domain (D5SD) of IP₃R-1 that specifically binds Lck via its SH2 domain. With the addition of an HIV-TAT sequence to enable cell permeability of D5SD peptide, we observed wide-spread, Ca²⁺-dependent, cell killing of hematological cancer cells when the Lck-IP₃R PPI was disrupted by TAT-D5SD. All cell lines and primary cells were sensitive to D5SD peptide, but malignant T-cells were less sensitive compared with B-cell or myeloid malignancies. Mining of RNA-seq data showed that LCK was expressed in primary diffuse large B-cell lymphoma (DLBCL) as well as acute myeloid leukemia (AML). In fact, LCK shows a similar pattern of expression as many well-characterized AML oncogenes and is part of a protein interactome that includes FLT3-ITD, Notch-1, and Kit. Consistent with these findings, our data suggest that the Lck-IP₃R PPI may protect malignant hematopoietic cells from death. Importantly, TAT-D5SD showed no cytotoxicity in three different non-hematopoietic cell lines; thus its ability to induce cell death appears specific to hematopoietic cells. Together, these data show that a peptide designed to disrupt the Lck-IP₃R PPI has a wide range of pre-clinical activity in leukemia and lymphoma.

GATA3 and Mammaglobin are often used in the clinic to identify metastases of mammary origin due to their robust and diffuse expression in mammary tissue. However, the expression of these markers has not been well characterized in tumors from African American women. The goal of this study was to characterize and evaluate the expression of GATA3 and mammaglobin in breast tumors from African American women and determine their association with clinicopathological outcomes including breast cancer subtypes. Tissue microarrays (TMAs) were constructed from well preserved, morphologically representative tumors in archived formalin-fixed, paraffin-embedded (FFPE) surgical blocks from 202 patients with primary invasive ductal carcinoma. Mammaglobin and GATA3 expression was assessed using immunohistochemistry (IHC). Univariate analysis was carried out to determine the association between expression of GATA3, mammaglobin and clinicopathological characteristics. Kaplan-Meier estimates of overall survival and disease-free survival were also plotted and a log-rank test performed to compare estimates among groups. GATA3 expression showed statistically significant association with lower grade (p<0.001), ER-positivity (p<0.001), PR-positivity (p<0.001), and the luminal subtype (p<0.001). Mammaglobin expression was also significantly associated with lower grade (p=0.031), ER-positivity (p=0.007), and PR-positivity (p=0.022). There was no association with recurrence-free or overall survival. Our results confirm that GATA3 and mammaglobin demonstrate expression predominantly in luminal breast cancers from African American women. Additional markers with improved specificity and sensitivity are warranted for triple negative breast tumors given the high prevalence in women of African descent.

Muscular dystrophies are inherited disorders that are characterized by progressive muscle degeneration. These disorders are caused by mutations in the genes encoding structural elements within the muscle, which leads to increased vulnerability to mechanical stress and sarcolemma damage. Although myofibers have the capacity to regenerate, the newly formed myofibers still harbor genetic mutation, which induces continuous cycles of muscle fiber death and regeneration. This repeated cycling is accompanied by an inflammatory response which eventually provokes excessive fibrotic deposition. The histopathological changes in skeletal muscle tissue are central to the disease pathogenesis. Analysis of muscle histopathology is the gold standard for monitoring muscle health and disease progression. However, manual, or semi-manual quantification methods, are not only immensely tedious but can be subjective. Here, we present four image analysis pipelines built in CellProfiler which enable users without a background in computer vision or programming to quantitatively analyze biological images. These image analysis pipelines are designed to quantify skeletal muscle histopathological staining for membrane damage, the abundance and size distribution of regenerating muscle fibers, inflammation via quantification of CD68+ M1 macrophages, and collagen deposition. Additionally, we discuss methods to address common errors associated with the quantification of microscopy images. These automated tools can not only improve workflow efficiency but can provide a better understanding of the histopathological progression of muscular dystrophy.