Covid-period-associated changes in organism profile of neonatal sepsis in a tertiary center from East India.

INTRODUCTION: Neonatal sepsis is a major cause of morbidity and mortality with a higher burden from the low- and middle-income countries. The coronavirus disease 2019 (Covid 19) pandemic has impacted healthcare in various ways including healthcare-associated infections (HAI). The objective of the present study was to determine changes in organism profile and incidence rates of HAI in neonates admitted to the index hospital during the pandemic and compared it with the data from the pre-pandemic period. MATERIALS AND METHODS: The study design was a retrospective, observational analysis of data from neonates with culture-positive sepsis, in a tertiary care children's hospital, between January 2018 and December 2021. Pre-Covid (January 2018 to December 2019) and Covid period data (January 2020 to December 2021) were analyzed for the significance of change. RESULTS: The prevalence of culture-positive sepsis, in pre-Covid and Covid periods, was 19.55% [95% confidence interval (95% CI) 17.13-21.52)] and 18.36% (CI 16.05-20.74), respectively. HAI rates/1000 patient days increased slightly during the Covid pandemic [7.2% (95% CI 6.98-10.08) to 9.8% (95% CI 9.78-13.67)] mainly due to an increase in fungal HAI (26% pre- vs. 41.5% Covid period). However, the proportion of Gram-negative (GN) infections fell significantly (70.5% vs. 48.6%) during the same period. In the pre-Covid period, Klebsiella followed by Burkholderia cepacia, Acinetobacter spp and Pseudomonas, were the major HAI isolates. During the Covid period, there was a decline in these isolates and Burkholderia spp was not detected. All fungal isolates were Candida species. The case fatality ratio (CFR) from HAI decreased significantly from 38% to 15.45%, mainly due to a decrease in GN HAI. CONCLUSION: During Covid pandemic, there was a significant decline in GN HAI and CFR from HAI, due to improved compliance with infection control measures in the neonatal intensive care unit (NICU). At the same time, there was a rise in the fungal HAI, possibly because of a higher proportion of premature, and sick neonates with longer hospital stay and more invasive procedures. Consolidations of gains in infection control and restriction of invasive procedures could help to minimize HAI in NICUs.

Blood stream infections in children less than 4 weeks old are known as neonatal sepsis. Several predisposing factors can make a neonate (less than 4 weeks) more prone to sepsis, such as prematurity, male gender, cultural practices, presence of underlying medical or surgical conditions, hospitalization, antibiotic use and invasive treatment. Neonatal sepsis in a hospitalized child can be either­pre-harbored infection (PHI), which means infection acquired prior to hospital admission or it could be healthcare-associated infection (HAI), where the infection is acquired during the hospital stay. Organisms causing neonatal sepsis in hospitalized neonates include bacteria and fungi. The coronavirus disease 2019 (Covid 19) pandemic impacted all aspects of life including healthcare. The investigators conducted the present study to look into the changes in the incidence rate as well as in the type of organisms causing healthcare-associated blood stream infections in neonates in the pre-Covid and during the Covid period.

Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19.

Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genes including Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.

Proteomics advances towards developing SARS-CoV-2 therapeutics using in silico drug repurposing approaches.

Standing amidst the COVID-19 pandemic, we have faced major medical and economic crisis in recent times which remains to be an unresolved issue till date. Although the scientific community has made significant progress towards diagnosis and understanding the disease; however, effective therapeutics are still lacking. Several omics-based studies, especially proteomics and interactomics, have contributed significantly in terms of identifying biomarker panels that can potentially be used for the disease prognosis. This has also paved the way to identify the targets for drug repurposing as a therapeutic alternative. US Food and Drug Administration (FDA) has set in motion more than 500 drug development programs on an emergency basis, most of them are focusing on repurposed drugs. Remdesivir is one such success of a robust and quick drug repurposing approach. The advancements in omics-based technologies has allowed to explore altered host proteins, which were earlier restricted to only SARS-CoV-2 protein signatures. In this article, we have reviewed major contributions of proteomics and interactomics techniques towards identifying therapeutic targets for COVID-19. Furthermore, in-silico molecular docking approaches to streamline potential drug candidates are also discussed.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

Proteomic investigation reveals dominant alterations of neutrophil degranulation and mRNA translation pathways in patients with COVID-19.

The altered molecular proteins and pathways in response to COVID-19 infection are still unclear. Here, we performed a comprehensive proteomics-based investigation of nasopharyngeal swab samples from patients with COVID-19 to study the host response by employing simple extraction strategies. Few of the host proteins such as interleukin-6, L-lactate dehydrogenase, C-reactive protein, Ferritin, and aspartate aminotransferase were found to be upregulated only in COVID-19-positive patients using targeted multiple reaction monitoring studies. The most important pathways identified by enrichment analysis were neutrophil degranulation, interleukin-12 signaling pathways, and mRNA translation of proteins thus providing the detailed investigation of host response in COVID-19 infection. Thus, we conclude that mass spectrometry-detected host proteins have a potential for disease severity progression; however, suitable validation strategies should be deployed for the clinical translation. Furthermore, the in silico docking of potential drugs with host proteins involved in the interleukin-12 signaling pathway might aid in COVID-19 therapeutic interventions.

Role of Multiomics Data to Understand Host-Pathogen Interactions in COVID-19 Pathogenesis.

Human infectious diseases are contributed equally by the host immune system's efficiency and any pathogens' infectivity. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the coronavirus strain causing the respiratory pandemic coronavirus disease 2019 (COVID-19). To understand the pathobiology of SARS-CoV-2, one needs to unravel the intricacies of host immune response to the virus, the viral pathogen's mode of transmission, and alterations in specific biological pathways in the host allowing viral survival. This review critically analyzes recent research using high-throughput "omics" technologies (including proteomics and metabolomics) on various biospecimens that allow an increased understanding of the pathobiology of SARS-CoV-2 in humans. The altered biomolecule profile facilitates an understanding of altered biological pathways. Further, we have performed a meta-analysis of significantly altered biomolecular profiles in COVID-19 patients using bioinformatics tools. Our analysis deciphered alterations in the immune response, fatty acid, and amino acid metabolism and other pathways that cumulatively result in COVID-19 disease, including symptoms such as hyperglycemic and hypoxic sequelae.