@article {46742, title = {Biosensors: frontiers in rapid detection of COVID-19}, journal = {3 Biotech}, volume = {10}, year = {2020}, month = {AUG}, pages = {385}, type = {Review}, abstract = {

The rapid community-spread of novel human coronavirus 2019 (nCOVID19 or SARS-Cov2) and morbidity statistics has put forth an unprecedented urge for rapid diagnostics for quick and sensitive detection followed by contact tracing and containment strategies, especially when no vaccine or therapeutics are known. Currently, quantitative real-time polymerase chain reaction (qRT-PCR) is being used widely to detect COVID-19 from various types of biological specimens, which is time-consuming, labor-intensive and may not be rapidly deployable in remote or resource-limited settings. This might lead to hindrance in acquiring realistic data of infectivity and community spread of SARS-CoV-2 in the population. This review summarizes the existing status of current diagnostic methods, their possible limitations, and the advantages of biosensor-based diagnostics over the conventional ones for the detection of SARS-Cov-2. Novel biosensors used to detect RNA-viruses include CRISPR-Cas9 based paper strip, nucleic-acid based, aptamer-based, antigen-Au/Ag nanoparticles-based electrochemical biosensor, optical biosensor, and Surface Plasmon Resonance. These could be effective tools for rapid, authentic, portable, and more promising diagnosis in the current pandemic that has affected the world economies and humanity. Present challenges and future perspectives of developing robust biosensors devices for rapid, scalable, and sensitive detection and management of COVID-19 are presented in light of the test-test-test theme of the World Health Organization (WHO).

}, keywords = {Biosensors, COVID-19, Rapid detection, SARS-CoV-2}, issn = {2190-572X}, doi = {10.1007/s13205-020-02369-0}, author = {Samson, Rachel and Navale, Govinda R. and Dharne, Mahesh S.} } @article {46869, title = {Discovery of potential multi-target-directed ligands by targeting host-specific SARS-CoV-2 structurally conserved main protease}, journal = {Journal of Biomolecular Structure \& Dynamics}, year = {2020}, month = {MAY}, type = {Article; Early Access 2020}, abstract = {

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the current COVID-19 pandemic. Worldwide this disease has infected over 2.5 million individuals with a mortality rate ranging from 5 to 10\%. There are several efforts going on in the drug discovery to control the SARS-CoV-2 viral infection. The main protease (M-Pro) plays a critical role in viral replication and maturation, thus can serve as the primary drug target. To understand the structural evolution of M-Pro, we have performed phylogenetic and Sequence Similarity Network analysis, that depicted divergence of Coronaviridae M-Pro in five clusters specific to viral hosts. This clustering was corroborated with the comparison of M-Pro structures. Furthermore, it has been observed that backbone and binding site conformations are conserved despite variation in some of the residues. These attributes can be exploited to repurpose available viral protease inhibitors against SARS-CoV-2 M-Pro. In agreement with this, we performed screening of similar to 7100 molecules including active ingredients present in the Ayurvedic anti-tussive medicines, anti-viral phytochemicals and synthetic anti-virals against SARS-CoV-2 M-Pro as the primary target. We identified several natural molecules like delta-viniferin, myricitrin, taiwanhomoflavone A, lactucopicrin 15-oxalate, nympholide A, afzelin, biorobin, hesperidin and phyllaemblicin B that strongly binds to SARS-CoV-2 M-Pro. Intrestingly, these molecules also showed strong binding with other potential targets of SARS-CoV-2 infection like viral receptor human angiotensin-converting enzyme 2 (hACE-2) and RNA dependent RNA polymerase (RdRp). We anticipate that our approach for identification of multi-target-directed ligand will provide new avenues for drug discovery against SARS-CoV-2 infection. Communicated by Ramaswamy H. Sarma

}, keywords = {Coronavirus, COVID-19, hACE-2, MPro, multi-target-directed ligand, protease inhibitor, RdRp, SARS-CoV-2 virus}, issn = {0739-1102}, doi = {10.1080/07391102.2020.1760137, Early Access Date = MAY 2020}, author = {Joshi, Rakesh S. and Jagdale, Shounak S. and Bansode, Sneha B. and Shankar, S. Shiva and Tellis, Meenakshi B. and Pandya, Vaibhav Kumar and Chugh, Anita and Giri, Ashok P. and Kulkarni, Mahesh J.} } @article {47134, title = {Probiotics in the prophylaxis of COVID-19: something is better than nothing}, journal = {3 Biotech}, volume = {11}, year = {2021}, month = {JAN}, type = {Review}, abstract = {

The new viral pandemic of COVID-19 is caused by a novel coronavirus (SARS-CoV-2) that has brought the world at another unprecedented crisis in terms of health and economy. The lack of specific therapeutics necessitates other strategies to prevent the spread of infection caused by this previously unknown viral etiological agent. Recent pieces of evidence have shown an association between COVID-19 disease and intestinal dysbiosis. Probiotics comprise living microbes that upon oral administration benefit human health by reshaping the composition of gut microbiota. The close kinship of the gastrointestinal and respiratory tract suggests why the dysfunction of one may incite illness in others. The emerging studies suggest the capability of probiotics to regulate immune responses in the respiratory system. The efficacy of probiotics has been studied previously on several respiratory tract viral infections. Therefore, the purpose of this review is to comprehend existing information on the gut mediated-pulmonary immunity conferred by probiotic bacteria, in the course of respiratory virus infections and administration as a prophylactic measure in COVID-19 pandemic in managing intestinal dysbiosis as well.

}, keywords = {Anti-viral, COVID-19, Gut-lung axis, Probiotics, Respiratory tract infection}, issn = {2190-572X}, doi = {10.1007/s13205-020-02554-1}, author = {Gohil, Kushal and Samson, Rachel and Dastager, Syed and Dharne, Mahesh} } @article {47624, title = {COVID-19 associated mucormycosis: evolving technologies for early and rapid diagnosis}, journal = {3 Biotech}, volume = {12}, year = {2022}, month = {JAN}, pages = {6}, type = {Review}, abstract = {The post-coronavirus disease (COVID-19) mucormycosis is a deadly addition to the pandemic spectrum. Although it{\textquoteright}s a rare, aggressive, and opportunistic disease, the associated morbidity and mortality are significant. The complex interplay of factors aggravating CAM is uncontrolled diabetes, irrational and excessive use of antibiotics, steroids, and an impaired immune system. Recently, India has been witnessing a rapid surge in the cases of coronavirus disease-associated mucormycosis (CAM), since the second wave of COVID-19. The devastating and lethal implications of CAM had now become a matter of global attention. A delayed diagnosis is often associated with a poor prognosis. Therefore, the rapid and early diagnosis of infection would be life-saving. Prevention and effective management of mucormycosis depend upon its early and accurate diagnosis followed by a multimodal therapeutic approach. The current review summarizes an array of detection methods and highlights certain evolving technologies for early and rapid diagnosis of CAM. Furthermore, several potential management strategies have also been discussed, which would aid in tackling the neglected yet fatal crisis of mucormycosis associated with COVID-19.}, keywords = {Biosensors, COVID-19, Diagnostics, Mucormycosis, Probiotics}, issn = {2190-572X}, doi = {10.1007/s13205-021-03080-4}, author = {Samson, Rachel and Dharne, Mahesh} } @article {48236, title = {Machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys}, journal = {Computers in Biology and Medicine}, volume = {146}, year = {2022}, month = {JUL}, pages = {105419}, type = {Article}, abstract = {

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8\% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6\%-80.2\%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

}, keywords = {BBV152, Covaxin, COVID-19, Ensemble methods, Infection, machine learning, SARS-CoV-2}, issn = {0010-4825}, doi = {10.1016/j.compbiomed.2022.105419}, author = {Singh, Prateek and Ujjainiya, Rajat and Prakash, Satyartha and Naushin, Salwa and Sardana, Viren and Bhatheja, Nitin and Singh, Ajay Pratap and Barman, Joydeb and Kumar, Kartik and Gayali, Saurabh and Khan, Raju and Rawat, Birendra Singh and Tallapaka, Karthik Bharadwaj and Anumalla, Mahesh and Lahiri, Amit and Kar, Susanta and Bhosale, Vivek and Srivastava, Mrigank and Mugale, Madhav Nilakanth and Pandey, C. P. and Khan, Shaziya and Katiyar, Shivani and Raj, Desh and Ishteyaque, Sharmeen and Khanka, Sonu and Rani, Ankita and Promila and Sharma, Jyotsna and Seth, Anuradha and Dutta, Mukul and Saurabh, Nishant and Veerapandian, Murugan and Venkatachalam, Ganesh and Bansal, Deepak and Gupta, Dinesh and Halami, Prakash M. and Peddha, Muthukumar Serva and Veeranna, Ravindra P. and Pal, Anirban and Singh, Ranvijay Kumar and Anandasadagopan, Suresh Kumar and Karuppanan, Parimala and Rahman, Syed Nasar and Selvakumar, Gopika and Venkatesan, Subramanian and Karmakar, Malay Kumar and Sardana, Harish Kumar and Kothari, Anamika and Parihar, Devendra Singh and Thakur, Anupma and Saifi, Anas and Gupta, Naman and Singh, Yogita and Reddu, Ritu and Gautam, Rizul and Mishra, Anuj and Mishra, Avinash and Gogeri, Iranna and Rayasam, Geethavani and Padwad, Yogendra and Patial, Vikram and Hallan, Vipin and Singh, Damanpreet and Tirpude, Narendra and Chakrabarti, Partha and Maity, Sujay Krishna and Ganguly, Dipyaman and Sistla, Ramakrishna and Balthu, Narender Kumar and Kumar, Kiran A. and Ranjith, Siva and Kumar, B. Vijay and Jamwal, Piyush Singh and Wali, Anshu and Ahmed, Sajad and Chouhan, Rekha and Gandhi, Sumit G. and Sharma, Nancy and Rai, Garima and Irshad, Faisal and Jamwal, Vijay Lakshmi and Paddar, Masroor Ahmad and Khan, Sameer Ullah and Malik, Fayaz and Ghosh, Debashish and Thakkar, Ghanshyam and Barik, S. K. and Tripathi, Prabhanshu and Satija, Yatendra Kumar and Mohanty, Sneha and Khan, Md Tauseef and Subudhi, Umakanta and Sen, Pradip and Kumar, Rashmi and Bhardwaj, Anshu and Gupta, Pawan and Sharma, Deepak and Tuli, Amit and Chaudhuri, Saumya Ray and Krishnamurthi, Srinivasan and Prakash, L. and Rao, V. Ch and Singh, B. N. and Chaurasiya, Arvindkumar and Chaurasiya, Meera and Bhadange, Mayuri and Likhitkar, Bhagyashree and Mohite, Sharada and Patil, Yogita and Kulkarni, Mahesh and Joshi, Rakesh and Pandya, Vaibhav and Mahajan, Sachin and Patil, Amita and Samson, Rachel and Vare, Tejas and Dharne, Mahesh and Giri, Ashok and Mahajan, Sachin and Paranjape, Shilpa and Sastry, G. Narahari and Kalita, Jatin and Phukan, Tridip and Manna, Prasenjit and Romi, Wahengbam and Bharali, Pankaj and Ozah, Dibyajyoti and Sahu, RaviKumar and Dutta, Prachurjya and Singh, Moirangthem Goutam and Gogoi, Gayatri and Tapadar, Yasmin Begam and Babu, Elapavalooru V. S. S. K. and Sukumaran, Rajeev K. and Nair, Aishwarya R. and Puthiyamadam, Anoop and Valappil, Prajeesh Kooloth and Prasannakumari, Adrash Velayudhan Pillai and Chodankar, Kalpana and Damare, Samir and Agrawal, Ved Varun and Chaudhary, Kumardeep and Agrawal, Anurag and Sengupta, Shantanu and Dash, Debasis} } @article {48319, title = {Comprehensive molecular and clinical investigation of approved Anti-HCV drugs repurposing against SARS-CoV-2 infection: a glaring gap between benchside and bedside medicine}, journal = {Vaccines}, volume = {11}, year = {2023}, month = {MAR}, pages = {515}, type = {Article}, abstract = {

The limited availability of effective treatment against SARS-CoV-2 infection is a major challenge in managing COVID-19. This scenario has augmented the need for repurposing anti-virals for COVID-19 mitigation. In this report, the anti-SARS-CoV-2 potential of anti-HCV drugs such as daclatasvir (DCV) or ledipasvir (LDP) in combination with sofosbuvir (SOF) was evaluated. The binding mode and higher affinity of these molecules with RNA-dependent-RNA-polymerase of SARS-CoV-2 were apparent by computational analysis. In vitro anti-SARS-CoV-2 activity depicted that SOF/DCV and SOF/LDP combination has IC50 of 1.8 and 2.0 mu M, respectively, comparable to remdesivir, an approved drug for COVID-19. Furthermore, the clinical trial was conducted in 183 mild COVID-19 patients for 14 days to check the efficacy and safety of SOF/DCV and SOF/LDP compared to standard of care (SOC) in a parallel-group, hybrid, individually randomized, controlled clinical study. The primary outcomes of the study suggested no significant difference in negativity after 3, 7 and 14 days in both treatments. None of the patients displayed any worsening in the disease severity, and no mortality was observed in the study. Although, the post hoc exploratory analysis indicated significant normalization of the pulse rate showed in SOF/DCV and SOF/LDP treatment vs. SOC. The current study highlights the limitations of bench side models in predicting the clinical efficacy of drugs that are planned for repurposing.

}, keywords = {antiviral, COVID-19, daclatasvir, ledipasvir, SARS-CoV-2, sofosbuvir}, doi = {10.3390/vaccines11030515}, author = {Bansode, Sneha and Singh, Pawan Kumar and Tellis, Meenakshi and Chugh, Anita and Deshmukh, Narendra and Gupta, Mahesh and Verma, Savita and Giri, Ashok and Kulkarni, Mahesh and Joshi, Rakesh and Chaudhary, Dhruva} } @article {48995, title = {Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India}, journal = {Environmental Science and Pollution Research }, volume = {30}, year = {2023}, month = {DEC}, pages = {118976-118988}, type = {Article}, abstract = {

The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (similar to 28\%), BA.1.X (1.0-72\%), BA.2 (1.0-18\%), BA.2.X (1.0-97.4\%) BA.2.12 (0.8-0.25\%), BA.2.38 (0.8-1.0\%), BA.2.75 (0.01-0.02\%), BA.3 (0.09-6.3\%), BA.4 (0.24-0.29\%), and XBB (0.01-21.83\%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.

}, keywords = {Bioinformatics pipeline, COVID-19, Early warning, India, Next-generation sequencing, Omicron, Public health, SARS-CoV-2, wastewater, Wastewater-based epidemiology}, issn = {0944-1344}, doi = {10.1007/s11356-023-30709-z}, author = {Rajput, Vinay and Pramanik, Rinka and Malik, Vinita and Yadav, Rakeshkumar and Samson, Rachel and Kadam, Pradnya and Bhalerao, Unnati and Tupekar, Manisha and Deshpande, Dipti and Shah, Priyanki and Shashidhara, L. S. and Boargaonkar, Radhika and Patil, Dhawal and Kale, Saurabh and Bhalerao, Asim and Jain, Nidhi and Kamble, Sanjay and Dastager, Syed and Karmodiya, Krishanpal and Dharne, Mahesh} } @article {48819, title = {Tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India}, journal = {Journal of Infection and Public Health}, volume = {16}, year = {2023}, month = {AUG}, pages = {1290-1300}, type = {Article}, abstract = {

Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.Methods: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a {\textquoteleft}{\textquoteleft}band of five{\textquoteright}{\textquoteright} outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implica-tions for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.\& COPY; 2023 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

}, keywords = {COVID-19, Delta, Omicron, SARS-CoV-2 genomic surveillance, Variant of concern, Whole Genome Sequencing (WGS)}, issn = {1876-0341}, doi = {10.1016/j.jiph.2023.06.004}, author = {Niveditha, Divya and Khan, Soumen and Khilari, Ajinkya and Nadkarni, Sanica and Bhalerao, Unnati and Kadam, Pradnya and Yadav, Ritu and Kanekar, Jugal B. and Shah, Nikita and Likhitkar, Bhagyashree and Sawant, Rutuja and Thakur, Shikha and Tupekar, Manisha and Nagar, Dhriti and Rao, Anjani G. and Jagtap, Rutuja and Jogi, Shraddha and Belekar, Madhuri and Pathak, Maitreyee and Shah, Priyanki and Ranade, Shatakshi and Phadke, Nikhil and Das, Rashmita and Joshi, Suvarna and Karyakarte, Rajesh and Ghose, Aurnab and Kadoo, Narendra and Shashidhara, L. S. and Monteiro, Joy Merwin and Shanmugam, Dhanasekaran and Raghunathan, Anu and Karmodiya, Krishanpal} }