Effect of probiotics as an immune modulator for the management of COVID-19.

COVID-19, an acute respiratory viral infection conveyed by pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected millions of individuals globally, and is a public health emergency of international concern. Till now, there are no highly effective therapies for this infection without vaccination. As they can evolve quickly and cross the strain level easily, these viruses are causing epidemics or pandemics that are allied with more severe clinical diseases. A new approach is needed to improve immunity to confirm the protection against emerging viral infections. Probiotics can modify gut microbial dysbiosis, improve the host immune system, and stimulate immune signaling, increasing systemic immunity. Several probiotic bacterial therapies have been proven to decrease the period of bacterial or viral infections. Superinduction of inflammation, termed cytokine storm, has been directly linked with pneumonia and severe complications of viral respiratory infections. In this case, probiotics as potential immunomodulatory agents can be an appropriate candidate to improve the host's response to respiratory viral infections. During this COVID-19 pandemic, any approach that can induce mucosal and systemic immunity could be helpful. Here, we summarize contexts regarding the effectiveness of various probiotics for preventing virus-induced respiratory infectious diseases, especially those that could be employed for COVID-19 patients. In addition, the effects of probiotics, their mechanisms on different aspects of immune responses against respiratory viral infection, and their antiviral properties in clinical findings have been described in detail.

Prevalence of polymyxin resistance through the food chain, the global crisis.

Antimicrobial resistance is one of the vital challenges facing global health today. Multi-drug resistant (MDR) infections are often treated with the narrow-spectrum drugs, colistin (polymyxin E) or polymyxin B, which are last-resort antibiotics for human therapeutics that are effective against Gram-negative bacteria. Unfortunately, resistance to these polymyxins has occurred because of selective pressure caused by the inappropriate use of those antibiotics, especially in farming. The mechanisms of resistance to polymyxins are mediated through intrinsic, mutational, or genetic alteration in chromosomal genes. The mechanism includes the regulatory network controlling chemical modifications of lipid A moiety of lipopolysaccharide, reducing the negative charge of lipid A and its affinity for polymyxins. Additionally, the unique mobile colistin/polymyxin B resistance (mcr) gene reported in Enterobacteriales is responsible for the horizontal dissemination of resistance to polymyxins via the food chain. There is now an urgent need to increase surveillance for detecting resistance to polymyxins. Therefore, this review presents an overview of presently available scientific literature on the mechanism of resistance to polymyxins, with their associated gene variants, evaluation methods, resistance transmission through the food chain via food bacteria, and related risk factors. We further focus on the significant implications of polymyxins usage in India and future views for food safety to preserve polymyxin activity.

Determining Cost-Optimal Next-Generation Sequencing Panels for Rare Disease and Pharmacogenomics Testing.

BACKGROUND: Multi-gene panel sequencing using next-generation sequencing (NGS) methods is a key tool for genomic medicine. However, with an estimated 140 000 genomic tests available, current system inefficiencies result in high genetic-testing costs. Reduced testing costs are needed to expand the availability of genomic medicine. One solution to improve efficiency and lower costs is to calculate the most cost-effective set of panels for a typical pattern of test requests. METHODS: We compiled rare diseases, associated genes, point prevalence, and test-order frequencies from a representative laboratory. We then modeled the costs of the relevant steps in the NGS process in detail. Using a simulated annealing-based optimization procedure, we determined panel sets that were more cost-optimal than whole exome sequencing (WES) or clinical exome sequencing (CES). Finally, we repeated this methodology to cost-optimize pharmacogenomics (PGx) testing. RESULTS: For rare disease testing, we show that an optimal choice of 4-6 panels, uniquely covering genes that comprise 95% of the total prevalence of monogenic diseases, saves $257-304 per sample compared with WES, and $66-135 per sample compared with CES. For PGx, we show that the optimal multipanel solution saves $6-7 (27%-40%) over a single panel covering all relevant gene-drug associations. CONCLUSIONS: Laboratories can reduce costs using the proposed method to obtain and run a cost-optimal set of panels for specific test requests. In addition, payers can use this method to inform reimbursement policy.

Ultrasensitive detection of tumor-specific mutations in saliva of patients with oral cavity squamous cell carcinoma.

BACKGROUND: Oral cavity squamous cell carcinoma (OCSCC) is the most common head and neck malignancy. Although the survival rate of patients with advanced-stage disease remains approximately 20% to 60%, when detected at an early stage, the survival rate approaches 80%, posing a pressing need for a well validated profiling method to assess patients who have a high risk of developing OCSCC. Tumor DNA detection in saliva may provide a robust biomarker platform that overcomes the limitations of current diagnostic tests. However, there is no routine saliva-based screening method for patients with OCSCC. METHODS: The authors designed a custom next-generation sequencing panel with unique molecular identifiers that covers coding regions of 7 frequently mutated genes in OCSCC and applied it on DNA extracted from 121 treatment-naive OCSCC tumors and matched preoperative saliva specimens. RESULTS: By using stringent variant-calling criteria, mutations were detected in 106 tumors, consistent with a predicted detection rate ≥88%. Moreover, mutations identified in primary malignancies were also detected in 93% of saliva samples. To ensure that variants are not errors resulting in false-positive calls, a multistep analytical validation of this approach was performed: 1) re-sequencing of 46 saliva samples confirmed 88% of somatic variants; 2) no functionally relevant mutations were detected in saliva samples from 11 healthy individuals without a history of tobacco or alcohol; and 3) using a panel of 7 synthetic loci across 8 sequencing runs, it was confirmed that the platform developed is reproducible and provides sensitivity on par with droplet digital polymerase chain reaction. CONCLUSIONS: The current data highlight the feasibility of somatic mutation identification in driver genes in saliva collected at the time of OCSCC diagnosis.

Landscape of clinically actionable mutations in breast cancer 'A cohort study'.

Breast cancer (BC) is a heterogeneous disease. Numerous chemotherapeutic agents are available for early stage or advanced/metastatic breast cancer to provide maximum benefit with minimum side effects. However, the clinical outcome of patients with the same clinical and pathological characteristics and treated with similar treatments may show major differences and a vast majority of patients still develop treatment resistance and eventually succumb to disease. It remains an unmet need to identify specific molecular defects, new biomarkers to enable clinicians to adopt individualized treatment for every patient in terms of endocrine, chemotherapy or targeted therapy which will improve clinical outcomes in BC. Our study aimed to identify frequent hotspot mutation profile in BC by targeted deep sequencing in cancer-related genes using Illumina Truseq amplicon/Swift Accel-Amplicon panel and MiSeq technology in an IRB-approved prospective study in a CLIA compliant laboratory. All the cases had pathology review for stage, histological type, hormonal status and Ki-67. Data was processed using Strand NGS™. Mutations identified in the tumor were assessed for 'actionability' i.e. response to therapy and impact on prognosis.