Targeting TRIM26: Unveiling an Oncogene and Identification of Plant Metabolites as a Potential Therapeutics for Breast Cancer.

Breast cancer is the major cause of cancer-related mortality and frequent malignancies among women worldwide. The TRIM (Tripartite Motif) protein family is a broad and diverse set of proteins that contain a conserved structural motif known as the tripartite motif, which comprises of three different domains, B-box domain, Coiled-coil domain and RBR (Ring-finger, B-box, and coiled-coil) domain. TRIM proteins are involved in regulating cancer growth and metastasis. However, TRIM proteins are still unexplored in cancer cell regulation. In this study, by using a cancer database expression of all TRIM proteins was determined in breast cancer. Out of 77 TRIM genes, 16 genes were upregulated in breast cancer. Here, the upregulated TRIM26 gene's role is not yet explored in breast cancer. Indeed, TRIM26 is upregulated in 21 cancer types out of 33 cancer types. To investigate the role of TRIM26 in breast cancer, siRNA-mediated gene silencing was carried out in MCF-7 and MDA-MB 231 breast cancer cells. Reduced expression of TRIM 26 decreased cancer cell proliferation, migration and invasion with simultaneous reduction of various proliferative, cell cycle and mesenchymal markers and upregulation of epithelial markers. Further, docking studies found potential novel plant metabolites. Thus, targeting TRIM26 may provide a novel therapeutic approach for breast cancer treatment.

Metformin prevents osteoblast-like potential and calcification in lung cancer A549 cells.

In spite of recent advances made in understanding its progression, cancer is still a leading cause of death across the nations. Molecular pathophysiology of these cancer cells largely differs depending on cancer types and even within the same tumor. Pathological mineralization/calcification is seen in various tissues including breast, prostate, and lung cancer. Osteoblast-like cells derived after trans-differentiation of mesenchymal cells usually drive calcium deposition in various tissues. This study aims to explore the presence of osteoblast-like potential in lung cancer cells and its prevention. ALP assay, ALP staining, nodule formation, RT-PCR, RT-qPCR, and western blot analysis experiments were carried out in lung cancer A549 cells to achieve said objective. Expressions of various osteoblast markers (e.g., ALP, OPN, RUNX2, and Osterix) along with osteoinducer genes (BMP-2 and BMP-4) were observed in A549 cells. Moreover, ALP activity and ability leading to nodule formation revealed the presence of osteoblast-like potential in lung cancer cells. Here, BMP-2 treatment increased expressions of osteoblast transcription factors such as RUNX2 and Osterix, enhanced ALP activity, and augmented calcification in this cell line. It was also observed that antidiabetic metformin inhibited BMP-2 mediated increase in osteoblast-like potential and calcification in these cancer cells. The current study noted that metformin blocked BMP-2 mediated increase in epithelial to mesenchymal transition (EMT) in A549 cells. The above findings for the first time unravel that A549 cells possess osteoblast-like potential which drives lung cancer calcification. Metformin might prevent BMP-2 induced osteoblast-like phenotype of the lung cancer cells with concomitant inhibition of EMT to inhibit lung cancer tissue calcification.

Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems-a case study of Jaipur (India).

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 ribonucleic acids (SARS-CoV-2 RNA) in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during the second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the city's increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, wastewater-based epidemiology (WBE) evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) before the maximum cases and maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of ultraviolet (UV) and chlorine (Cl2) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl2), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl2), sequencing batch reactor (SBR), and SBR + Cl2, were compared with removal efficacy of SBR + Cl2 (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2 (36.4%). The study observed the trends and prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N > ORF1ab > RdRp > E gene suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp, & ORF1ab genes) increases the sensitivity in WBE.

Sewage surveillance for the presence of SARS-CoV-2 genome as a useful wastewater based epidemiology (WBE) tracking tool in India.

The infection with SARS-CoV-2 is reported to be accompanied by the shedding of the virus in fecal samples of infected patients. Earlier reports have suggested that COVID-19 agents can be present in the sewage samples and thus it can be a good indication of the pandemic extent in a community. However, no such studies have been reported in the Indian context. Hence, it becomes absolutely necessary to detect the presence of the SARS-CoV-2 in the wastewater samples from wastewater treatment plants (WWTPs) serving different localities of Jaipur city. Samples from different WWTPs and hospital wastewater samples were collected and wastewater based epidemiology (WBE) studies were carried out using the RT-PCR to confirm the presence of different COVID-19 target genes namely S gene, E gene, ORF1ab gene, RdRp gene and N gene. The results revealed that the untreated wastewater samples showed the presence of SARS-CoV-2 viral genome, which was correlated with the increased number of COVID-19 positive patients from the concerned areas, as reported in the publically available health data. This is the first study that investigated the presence of SARS-CoV-2 viral genome in wastewater, at higher ambient temperature (45 °C), further validating WBE as potential tool in predicting and mitigating outbreaks.

Uptake of parasite-derived vesicles by astrocytes and microglial phagocytosis of infected erythrocytes may drive neuroinflammation in cerebral malaria.

Astrocytes and microglia are activated during cerebral malaria (CM) and contribute to the production and release of several mediators during neuroinflammatory processes. Whether these changes are the consequence of a direct crosstalk between glial cells and the malarial parasite and how these cells participate in the pathogenesis of CM is not yet clear. We therefore examined the interaction of astrocytes and microglia with Plasmodium berghei ANKA-infected red blood cells using primary cell cultures derived from newborn C57BL/6 mice. We observed a dynamic transfer of vesicles from the parasite to astrocytes within minutes of contact, and the phagocytosis of infected red blood cells by microglia. Differential gene expression studies using the Affymetrix GeneChip® microarray, and quantitative PCR analyses showed the increase in expression of the set of genes belonging to the immune response network in parasite activated astrocytes and microglia. Interestingly, expression of these genes was also significantly upregulated in brains of mice dying from CM compared with uninfected mice or infected mice that did not develop the neuropathology. Accumulation of parasite-derived vesicles within astrocytes, and the phagocytosis of infected red blood cells by microglia induced a subsequent increase in interferon gamma inducible protein 10 (IP10) in both the brain and plasma of infected mice at the onset of CM, confirming a role for this molecule in CM pathogenesis. Altogether, these observations point to a possible role for glial cells in the neuropathological processes leading to CM. GLIA 2016 GLIA 2017;65:75-92.

Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave.

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.

Simvastatin prevents BMP-2 driven cell migration and invasion by suppressing oncogenic DNMT1 expression in breast cancer cells.

Both epigenetic and genetic changes in the cancer genome act simultaneously to promote tumor development and metastasis. Aberrant DNA methylation, a prime epigenetic event, is often observed in various cancer types. The elevated DNA methyltransferase 1 (DNMT1) enzyme creates DNA hypermethylation at CpG islands to drive oncogenic potential. This study emphasized to decipher the molecular mechanism of endogenous regulation of DNMT1 expression for finding upstream signaling molecules. Cancer database analyses found an upregulated DNMT1 expression in most cancer types including breast cancer. Overexpression of DNMT1 showed an increased cell migration, invasion, and stemness potential whereas 5-azacytidine (DNMT1 inhibitor) and siRNA mediated knockdown of DNMT1 exhibited inhibition of such cancer activities in breast cancer MDA-MB-231 and MCF-7 cells. Infact, cancer database analyses further found a positive correlation of DNMT1 transcript with both cholesterol pathway regulatory genes and BMP signaling molecules. Experimental observations documented that the cholesterol-lowering drug, simvastatin decreased DNMT1 transcript as well as protein, whereas BMP-2 treatment increased DNMT1 expression in breast cancer cells. In addition, expression of various key cholesterol regulatory genes was found to be upregulated in response to BMP-2 treatment. Moreover, simvastatin inhibited BMP-2 induced DNMT1 expression in breast cancer cells. Thus, this study for the first time reveals that both BMP-2 signaling and cholesterol pathways could regulate endogenous DNMT1 expression in cancer cells.

RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance.

Background: The COVID-19 pandemic showcased the power of genomic sequencing to tackle the emergence and spread of infectious diseases. However, metagenomic sequencing of total microbial RNAs in wastewater has the potential to assess multiple infectious diseases simultaneously and has yet to be explored. Methods: A retrospective RNA-Seq epidemiological survey of 140 untreated composite wastewater samples was performed across urban (n = 112) and rural (n = 28) areas of Nagpur, Central India. Composite wastewater samples were prepared by pooling 422 individual grab samples collected prospectively from sewer lines of urban municipality zones and open drains of rural areas from 3rd February to 3rd April 2021, during the second COVID-19 wave in India. Samples were pre-processed and total RNA was extracted prior to genomic sequencing. Findings: This is the first study that has utilised culture and/or probe-independent unbiased RNA-Seq to examine Indian wastewater samples. Our findings reveal the detection of zoonotic viruses including chikungunya, Jingmen tick and rabies viruses, which have not previously been reported in wastewater. SARS-CoV-2 was detectable in 83 locations (59%), with stark abundance variations observed between sampling sites. Hepatitis C virus was the most frequently detected infectious virus, identified in 113 locations and co-occurring 77 times with SARS-CoV-2; and both were more abundantly detected in rural areas than urban zones. Concurrent identification of segmented virus genomic fragments of influenza A virus, norovirus, and rotavirus was observed. Geographical differences were also observed for astrovirus, saffold virus, husavirus, and aichi virus that were more prevalent in urban samples, while the zoonotic viruses chikungunya and rabies, were more abundant in rural environments. Interpretation: RNA-Seq can effectively detect multiple infectious diseases simultaneously, facilitating geographical and epidemiological surveys of endemic viruses that could help direct healthcare interventions against emergent and pre-existent infectious diseases as well as cost-effectively and qualitatively characterising the health status of the population over time. Funding: UK Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) grant number H54810, as supported by Research England.

Mechanistic insights into synergy between nalidixic acid and tetracycline against clinical isolates of Acinetobacter baumannii and Escherichia coli.

The increasing prevalence of antimicrobial resistance has become a global health problem. Acinetobacter baumannii is an important nosocomial pathogen due to its capacity to persist in the hospital environment. It has a high mortality rate and few treatment options. Antibiotic combinations can help to fight multi-drug resistant (MDR) bacterial infections, but they are rarely used in the clinics and mostly unexplored. The interaction between bacteriostatic and bactericidal antibiotics are mostly reported as antagonism based on the results obtained in the susceptible model laboratory strain Escherichia coli. However, in the present study, we report a synergistic interaction between nalidixic acid and tetracycline against clinical multi-drug resistant A. baumannii and E. coli. Here we provide mechanistic insight into this dichotomy. The synergistic combination was studied by checkerboard assay and time-kill curve analysis. We also elucidate the mechanism behind this synergy using several techniques such as fluorescence spectroscopy, flow cytometry, fluorescence microscopy, morphometric analysis, and real-time polymerase chain reaction. Nalidixic acid and tetracycline combination displayed synergy against most of the MDR clinical isolates of A. baumannii and E. coli but not against susceptible isolates. Finally, we demonstrate that this combination is also effective in vivo in an A. baumannii/Caenorhabditis elegans infection model (p < 0.001).