Transcriptionally active nasopharyngeal commensals and opportunistic microbial dynamics define mild symptoms in the COVID 19 vaccination breakthroughs.

The development of COVID 19 vaccines as an effort to mitigate the outbreak, has saved millions of lives globally. However, vaccination breakthroughs have continuously challenged the vaccines' effectiveness and provided incentives to explore facets holding potential to alter vaccination-induced immunity and protection from subsequent infection, especially VOCs (Variants Of Concern). We explored the functional dynamics of nasopharyngeal transcriptionally active microbes (TAMs) between vaccination breakthroughs and unvaccinated SARS-CoV-2 infected individuals. Microbial taxonomic communities were differentially altered with skewed enrichment of bacterial class/genera of Firmicutes and Gammaproteobacteria with grossly reduced phylum Bacteroidetes in vaccination breakthrough individuals. The Bacillus genus was abundant in Firmicutes in vaccination breakthrough whereas Prevotella among Bacteroides dominated the unvaccinated. Also, Pseudomonas and Salmonella of Gammaproteobacteria were overrepresented in vaccination breakthrough, whilst unvaccinated showed presence of several genera, Achromobacter, Bordetella, Burkholderia, Neisseria, Hemophilus, Salmonella and Pseudomonas, belonging to Proteobacteria. At species level, the microbiota of vaccination breakthrough exhibited relatively higher abundance of unique commensals, in comparison to potential opportunistic microbes enrichment in unvaccinated patients' microbiota. Functional metabolic pathways like amino acid biosynthesis, sulphate assimilation, fatty acid and beta oxidation, associated with generation of SCFAs (short chain fatty acids), were enriched in vaccination breakthroughs. Majorly, metabolic pathways of LCFAs biosynthesis (long chain fatty acids; oleate, dodecenoate, palmitoleate, gondoate) were found associated with the unvaccinated. Our research highlights that vaccination decreases the microbial diversity in terms of depleting opportunistic pathogens and increasing the preponderance of commensals with respect to unvaccinated patients. Metabolic pathway analysis substantiates the shift in diversity to functionally modulate immune response generation, which may be related to mild clinical manifestations and faster recovery times during vaccination breakthroughs.

Intertwined Dysregulation of Ribosomal Proteins and Immune Response Delineates SARS-CoV-2 Vaccination Breakthroughs.

Globally, COVID-19 vaccines have emerged as a boon, especially during the severe pandemic phases to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, saving millions of lives. However, mixed responses to vaccination with breakthrough challenges provided a rationale to explore the immune responses generated postvaccination, which plausibly alter the subsequent course of infection. In this regard, we comprehensively profiled the nasopharyngeal transcriptomic signature of double-dose-vaccinated individuals with breakthrough infections in comparison to unvaccinated infected persons. The vaccinated individuals demonstrated a gross downregulation of ribosomal proteins along with immune response genes and transcription/translational machinery that methodically modulated the entire innate immune landscape toward immune tolerance, a feature of innate immune memory. This coordinated response was orchestrated through 17 transcription factors captured as differentially expressed in the vaccination breakthroughs, including epigenetic modulators of CHD1 and LMNB1 and several immune response effectors, with ELF1 emerging as one of the important transcriptional regulators of the antiviral innate immune response. Deconvolution algorithm using bulk gene expression data revealed decreased T-cell populations with higher expression of memory B cells in the vaccination breakthroughs. Thus, vaccination might synergize the innate immune response with humoral and T-cell correlates of protection to more rapidly clear SARS-CoV-2 infections and reduce symptoms within a shorter span of time. An important feature invariably noted after secondary vaccination is downregulation of ribosomal proteins, which might plausibly be an important factor arising from epigenetic reprogramming leading to innate immune tolerance. IMPORTANCE The development of multiple vaccines against SARS-CoV-2 infection is an unprecedented milestone achieved globally. Immunization of the mass population is a rigorous process for getting the pandemic under control, yet continuous challenges are being faced, one of them being breakthrough infections. This is the first study wherein the vaccination breakthrough cases of COVD-19 relative to unvaccinated infected individuals have been explored. In the context of vaccination, how do innate and adaptive immune responses correspond to SARS-CoV-2 infection? How do these responses culminate in a milder observable phenotype with shorter hospital stay in vaccination breakthrough cases compared with the unvaccinated? We identified a subdued transcriptional landscape in vaccination breakthroughs with decreased expression of a large set of immune and ribosomal proteins genes. We propose a module of innate immune memory, i.e., immune tolerance, which plausibly helps to explain the observed mild phenotype and fast recovery in vaccination breakthroughs.

Transcriptomic study reveals lncRNA-mediated downregulation of innate immune and inflammatory response in the SARS-CoV-2 vaccination breakthrough infections.

Introduction: The emergence of multiple variants of concerns (VOCs) with higher number of Spike mutations have led to enhanced immune escape by the SARS-CoV-2. With the increasing number of vaccination breakthrough (VBT) infections, it is important to understand the possible reason/s of the breakthrough infections. Methods: We performed transcriptome sequencing of 57 VBT and unvaccinated COVID-19 patients, followed by differential expression and co-expression analysis of the lncRNAs and the mRNAs. The regulatory mechanism was highlighted by analysis towards repeat element distribution within the co-expressed lncRNAs, followed by repeats driven homologous interaction between the lncRNAs and the promoter regions of genes from the same topologically associated domains (TAD). Results: We identified 727 differentially expressed lncRNAs (153 upregulated and 574 downregulated) and 338 mRNAs (34 up- and 334 downregulated) in the VBT patients. This includes LUCAT1, MALAT1, ROR1-AS1, UGDH-AS1 and LINC00273 mediated modulation of immune response, whereas MALAT1, NEAT1 and GAS5 regulated inflammatory response in the VBT. LncRNA-mRNA co-expression analysis highlighted 34 lncRNAs interacting with 267 mRNAs. We also observed a higher abundance of Alu, LINE1 and LTRs within the interacting lncRNAs of the VBT patients. These interacting lncRNAs have higher interaction with the promoter region of the genes from the same TAD, compared to the non-interacting lncRNAs with the enrichment of Alu and LINE1 in the gene promoter. Discussion: Significant downregulation and GSEA of the TAD gene suggest Alu and LINE1 driven homologous interaction between the lncRNAs and the TAD genes as a possible mechanism of lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response. The lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response might explain the SARS-CoV-2 breakthrough infections with milder symptoms in the VBT. Besides, the study also highlights repeat element mediated regulation of genes in 3D as another possible way of lncRNA-mediated immune-regulation modulating vaccination breakthroughs milder disease phenotype and shorter hospital stay.

Transcriptomic study reveals lncRNA-mediated downregulation of innate immune and inflammatory response in the SARS-CoV-2 vaccination breakthrough infections

Introduction The emergence of multiple variants of concerns (VOCs) with higher number of Spike mutations have led to enhanced immune escape by the SARS-CoV-2. With the increasing number of vaccination breakthrough (VBT) infections, it is important to understand the possible reason/s of the breakthrough infections. Methods We performed transcriptome sequencing of 57 VBT and unvaccinated COVID-19 patients, followed by differential expression and co-expression analysis of the lncRNAs and the mRNAs. The regulatory mechanism was highlighted by analysis towards repeat element distribution within the co-expressed lncRNAs, followed by repeats driven homologous interaction between the lncRNAs and the promoter regions of genes from the same topologically associated domains (TAD). Results We identified 727 differentially expressed lncRNAs (153 upregulated and 574 downregulated) and 338 mRNAs (34 up- and 334 downregulated) in the VBT patients. This includes LUCAT1, MALAT1, ROR1-AS1, UGDH-AS1 and LINC00273 mediated modulation of immune response, whereas MALAT1, NEAT1 and GAS5 regulated inflammatory response in the VBT. LncRNA-mRNA co-expression analysis highlighted 34 lncRNAs interacting with 267 mRNAs. We also observed a higher abundance of Alu, LINE1 and LTRs within the interacting lncRNAs of the VBT patients. These interacting lncRNAs have higher interaction with the promoter region of the genes from the same TAD, compared to the non-interacting lncRNAs with the enrichment of Alu and LINE1 in the gene promoter. Discussion Significant downregulation and GSEA of the TAD gene suggest Alu and LINE1 driven homologous interaction between the lncRNAs and the TAD genes as a possible mechanism of lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response. The lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response might explain the SARS-CoV-2 breakthrough infections with milder symptoms in the VBT. Besides, the study also highlights repeat element mediated regulation of genes in 3D as another possible way of lncRNA-mediated immune-regulation modulating vaccination breakthroughs milder disease phenotype and shorter hospital stay.

Mutational dynamics across VOCs in International travellers and Community transmission underscores importance of Spike-ACE2 interaction.

BACKGROUND: Emergence of SARS-CoV-2 VOCs at different time points through COVID-19 pandemic raised concern for increased transmissibility, infectivity and vaccination breakthroughs. METHODS: 1567 international travellers plus community transmission COVID-19 cases were analysed for mutational profile of VOCS, that led to notable waves in India, namely Alpha, Delta, and Omicron. Spike mutations in Linkage Disequilibrium were investigated for potential impact on structural and functional changes of Spike-ACE2. RESULTS: ORF1ab and spike harboured diverse mutational signatures for each lineage. B.1.617.2 and AY. * demonstrated comparable profile, yet non-clade defining mutations were majorly unique between international vs community samples. Contrarily, Omicron lineages showed substantial overlap in non-clade defining mutations, signifying early phase of transmission and evolution within Indian community. Mutations in LD for Alpha [N501Y, A570D, D1118H, S982A], Delta [P681R, L452R, EFR:156-158 G, D950N, G142D] and Omicron [P681H, D796Y, N764K, N969K, N501Y, S375F] resulted in decreased binding affinity of Spike-ACE2 for Alpha and BA.1 whereas Delta, Omicron and BA.2 demonstrated strong binding. CONCLUSION: Genomic surveillance tracked spread of VOCs in international travellers' vs community transmission. Behavioural transmission patterns of variants, based on selective advantage incurred by spike mutations, led us to predict sudden takeover of Delta over Alpha and BA.2 over BA.1 in India.

Mutational dynamics across VOCs in International travellers and Community transmission underscores importance of Spike-ACE2 interaction☆

Background Emergence of SARS-CoV-2 VOCs at different time points through COVID-19 pandemic raised concern for increased transmissibility, infectivity and vaccination breakthroughs. Methods 1567 international travellers plus community transmission COVID-19 cases were analysed for mutational profile of VOCS, that led to notable waves in India, namely Alpha, Delta, and Omicron. Spike mutations in Linkage Disequilibrium were investigated for potential impact on structural and functional changes of Spike-ACE2. Results ORF1ab and spike harboured diverse mutational signatures for each lineage. B.1.617.2 and AY. * demonstrated comparable profile, yet non-clade defining mutations were majorly unique between international vs community samples. Contrarily, Omicron lineages showed substantial overlap in non-clade defining mutations, signifying early phase of transmission and evolution within Indian community. Mutations in LD for Alpha [N501Y, A570D, D1118H, S982A], Delta [P681R, L452R, EFR:156-158 G, D950N, G142D] and Omicron [P681H, D796Y, N764K, N969K, N501Y, S375F] resulted in decreased binding affinity of Spike-ACE2 for Alpha and BA.1 whereas Delta, Omicron and BA.2 demonstrated strong binding. Conclusion Genomic surveillance tracked spread of VOCs in international travellers’ vs community transmission. Behavioural transmission patterns of variants, based on selective advantage incurred by spike mutations, led us to predict sudden takeover of Delta over Alpha and BA.2 over BA.1 in India. Graphical

Increased Abundance of Achromobacter xylosoxidans and Bacillus cereus in Upper Airway Transcriptionally Active Microbiome of COVID-19 Mortality Patients Indicates Role of Co-Infections in Disease Severity and Outcome.

The modulators of severe COVID-19 have emerged as the most intriguing features of SARS-CoV-2 pathogenesis. This is especially true as we are encountering variants of concern (VOC) with increased transmissibility and vaccination breakthroughs. Microbial co-infections are being investigated as one of the crucial factors for exacerbation of disease severity and complications of COVID-19. A key question remains whether early transcriptionally active microbial signature/s in COVID-19 patients can provide a window for future disease severity susceptibility and outcome? Using complementary metagenomics sequencing approaches, respiratory virus oligo panel (RVOP) and Holo-seq, our study highlights the possible functional role of nasopharyngeal early resident transcriptionally active microbes in modulating disease severity, within recovered patients with sub-phenotypes (mild, moderate, severe) and mortality. The integrative analysis combines patients' clinical parameters, SARS-CoV-2 phylogenetic analysis, microbial differential composition, and their functional role. The clinical sub-phenotypes analysis led to the identification of transcriptionally active bacterial species associated with disease severity. We found significant transcript abundance of Achromobacter xylosoxidans and Bacillus cereus in the mortality, Leptotrichia buccalis in the severe, Veillonella parvula in the moderate, and Actinomyces meyeri and Halomonas sp. in the mild COVID-19 patients. Additionally, the metabolic pathways, distinguishing the microbial functional signatures between the clinical sub-phenotypes, were also identified. We report a plausible mechanism wherein the increased transcriptionally active bacterial isolates might contribute to enhanced inflammatory response and co-infections that could modulate the disease severity in these groups. Current study provides an opportunity for potentially using these bacterial species for screening and identifying COVID-19 patient sub-groups with severe disease outcome and priority medical care. IMPORTANCE COVID-19 is invariably a disease of diverse clinical manifestation, with multiple facets involved in modulating the progression and outcome. In this regard, we investigated the role of transcriptionally active microbial co-infections as possible modulators of disease pathology in hospital admitted SARS-CoV-2 infected patients. Specifically, can there be early nasopharyngeal microbial signatures indicative of prospective disease severity? Based on disease severity symptoms, the patients were segregated into clinical sub-phenotypes: mild, moderate, severe (recovered), and mortality. We identified significant presence of transcriptionally active isolates, Achromobacter xylosoxidans and Bacillus cereus in the mortality patients. Importantly, the bacterial species might contribute toward enhancing the inflammatory responses as well as reported to be resistant to common antibiotic therapy, which together hold potential to alter the disease severity and outcome.

SARS-CoV-2 Mutations and COVID-19 Clinical Outcome: Mutation Global Frequency Dynamics and Structural Modulation Hold the Key.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an enormous burden on the healthcare system worldwide as a consequence of its new emerging variants of concern (VOCs) since late 2019. Elucidating viral genome characteristics and its influence on disease severity and clinical outcome has been one of the crucial aspects toward pandemic management. Genomic surveillance holds the key to identify the spectrum of mutations vis-à-vis disease outcome. Here, in our study, we performed a comprehensive analysis of the mutation distribution among the coronavirus disease 2019 (COVID-19) recovered and mortality patients. In addition to the clinical data analysis, the significant mutations within the two groups were analyzed for their global presence in an effort to understand the temporal dynamics of the mutations globally in comparison with our cohort. Interestingly, we found that all the mutations within the recovered patients showed significantly low global presence, indicating the possibility of regional pool of mutations and the absence of preferential selection by the virus during the course of the pandemic. In addition, we found the mutation S194L to have the most significant occurrence in the mortality group, suggesting its role toward a severe disease progression. Also, we discovered three mutations within the mortality patients with a high cohort and global distribution, which later became a part of variants of interest (VOIs)/VOCs, suggesting its significant role in enhancing viral characteristics. To understand the possible mechanism, we performed molecular dynamics (MD) simulations of nucleocapsid mutations, S194L and S194*, from the mortality and recovered patients, respectively, to examine its impacts on protein structure and stability. Importantly, we observed the mutation S194* within the recovered to be comparatively unstable, hence showing a low global frequency, as we observed. Thus, our study provides integrative insights about the clinical features, mutations significantly associated with the two different clinical outcomes, its global presence, and its possible effects at the structural level to understand the role of mutations in driving the COVID-19 pandemic.

Clinico-Genomic Analysis Reiterates Mild Symptoms Post-vaccination Breakthrough: Should We Focus on Low-Frequency Mutations?

Vaccine development against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been of primary importance to contain the ongoing global pandemic. However, studies have demonstrated that vaccine effectiveness is reduced and the immune response is evaded by variants of concern (VOCs), which include Alpha, Beta, Delta, and, the most recent, Omicron. Subsequently, several vaccine breakthrough (VBT) infections have been reported among healthcare workers (HCWs) due to their prolonged exposure to viruses at healthcare facilities. We conducted a clinico-genomic study of ChAdOx1 (Covishield) VBT cases in HCWs after complete vaccination. Based on the clinical data analysis, most of the cases were categorized as mild, with minimal healthcare support requirements. These patients were divided into two sub-phenotypes based on symptoms: mild and mild plus. Statistical analysis showed a significant correlation of specific clinical parameters with VBT sub-phenotypes. Viral genomic sequence analysis of VBT cases revealed a spectrum of high- and low-frequency mutations. More in-depth analysis revealed the presence of low-frequency mutations within the functionally important regions of SARS-CoV-2 genomes. Emphasizing the potential benefits of surveillance, low-frequency mutations, D144H in the N gene and D138Y in the S gene, were observed to potentially alter the protein secondary structure with possible influence on viral characteristics. Substantiated by the literature, our study highlights the importance of integrative analysis of pathogen genomic and clinical data to offer insights into low-frequency mutations that could be a modulator of VBT infections.

SARS-CoV-2 Lineage Tracking, and Evolving Trends Seen during Three Consecutive Peaks of Infection in Delhi, India: a Clinico-Genomic Study.

Since its advent, the pandemic has caused havoc in multiple waves due partly to amplified transmissibility and immune escape to vaccines. Delhi, India also witnessed brutal multiple peaks causing exponential rise in cases. Here we had retrospectively investigated clade variation, emergence of new lineages and varied clinical characteristics during those three peaks in order to understand the trajectory of the ongoing pandemic. In this study, a total of 123,378 samples were collected for a time span of 14 months (1 June 2020 to 3 August 2021) encompassing three different peaks in Delhi. A subset of 747 samples was processed for sequencing. Complete clinical and demographic details of all the enrolled cases were also collected. We detected 26 lineages across three peaks nonuniformly from 612 quality passed samples. The first peak was driven by diverse early variants, while the second one by B.1.36 and B.1.617.2, unlike third peak caused entirely by B.1.617.2. A total of 18,316 mutations with median of 34 were reported. Majority of mutations were present in less than 1% of samples. Differences in clinical characteristics across three peaks was also reported. To be ahead of the frequently changing course of the ongoing pandemic, it is of utmost importance that novel lineages be tracked continuously. Prioritized sequencing of sudden local outburst and community hot spots must be done to swiftly detect a novel mutation/lineage of potential clinical importance. IMPORTANCE Genome surveillance of the Delhi data provides a more detailed picture of diverse circulating lineages. The added value that the current study provides by clinical details of the patients is of importance. We looked at the shifting patterns of lineages, clinical characteristics and mutation types and mutation load during each successive infection surge in Delhi. The importance of widespread genomic surveillance cannot be stressed enough to timely detect new variants so that appropriate policies can be immediately implemented upon to help control the infection spread. The entire idea of genomic surveillance is to arm us with the clues as to how the novel mutations and/or variants can prove to be more transmissible and/or fatal. In India, the densely populated cities have an added concern of the huge burden that even the milder variants of the virus combined with co-morbidity can have on the community/primary health care centers.

COVID-19 Risk Stratification and Mortality Prediction in Hospitalized Indian Patients: Harnessing clinical data for public health benefits.

The variability of clinical course and prognosis of COVID-19 highlights the necessity of patient sub-group risk stratification based on clinical data. In this study, clinical data from a cohort of Indian COVID-19 hospitalized patients is used to develop risk stratification and mortality prediction models. We analyzed a set of 70 clinical parameters including physiological and hematological for developing machine learning models to identify biomarkers. We also compared the Indian and Wuhan cohort, and analyzed the role of steroids. A bootstrap averaged ensemble of Bayesian networks was also learned to construct an explainable model for discovering actionable influences on mortality and days to outcome. We discovered blood parameters, diabetes, co-morbidity and SpO2 levels as important risk stratification features, whereas mortality prediction is dependent only on blood parameters. XGboost and logistic regression model yielded the best performance on risk stratification and mortality prediction, respectively (AUC score 0.83, AUC score 0.92). Blood coagulation parameters (ferritin, D-Dimer and INR), immune and inflammation parameters IL6, LDH and Neutrophil (%) are common features for both risk and mortality prediction. Compared with Wuhan patients, Indian patients with extreme blood parameters indicated higher survival rate. Analyses of medications suggest that a higher proportion of survivors and mild patients who were administered steroids had extreme neutrophil and lymphocyte percentages. The ensemble averaged Bayesian network structure revealed serum ferritin to be the most important predictor for mortality and Vitamin D to influence severity independent of days to outcome. The findings are important for effective triage during strains on healthcare infrastructure.

Secondary infections modify the overall course of hospitalized patients with COVID-19: a retrospective study from a network of hospitals across North India.

Objective: To gain better insight into the extent of secondary bacterial and fungal infections in hospitalized patients in India, and to assess how these alter the course of coronavirus disease 2019 (COVID-19) so that control measures can be suggested. Methods: In this retrospective, multicentre study, the data of all patients who tested positive for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) on reverse transcriptase polymerase chain reaction (RT-PCR), admitted to hospital between March 2020 and July 2021, were accessed from the electronic health records of a network of 10 hospitals across five states in North India. Results: Of 19,852 patients testing positive for SARS-CoV-2 on RT-PCR and admitted to the study hospitals during the study period, 1940 (9.8%) patients developed secondary infections (SIs). Patients with SIs were, on average, 8 years older than patients without SIs (median age 62.6 vs 54.3 years; P<0.001). The risk of SIs was significantly (P<0.001) associated with age, severity of disease at admission, diabetes, admission to the intensive care unit (ICU), and ventilator use. The most common site of infection was urine (41.7%), followed by blood (30.8%) and sputum/bronchoalveolar lavage/endotracheal fluid (24.8%); the least common was pus/wound discharge (2.6%). Gram-negative bacilli (GNB) were the most common organisms (63.2%), followed by Gram-positive cocci (GPC) (19.6%) and fungi (17.3%). Most patients with SIs were on multiple antimicrobials. The most commonly used antibiotics against GNB were beta-lactam/beta-lactamase inhibitors (76.9%), carbapenems (57.7%), cephalosporins (53.9%), and antibiotics against carbapenem-resistant Enterobacteriaceae (47.1%). Empirical use of antibiotics against GPC was seen in 58.9% of patients with SIs, and empirical use of antifungals was observed in 56.9% of patients with SIs. The average length of hospital stay for patients with SIs was almost twice as long as that of patients without SIs (median 13 vs 7 days). Overall mortality among patients with SIs (40.3%) was more than eight times higher than that among patients without SIs (4.6%). Only 1.2% of patients with SIs with mild COVID-19 at admission died, compared with 17.5% of those with moderate COVID-19 at admission and 58.5% of those with severe COVID-19 at admission (P<0.001). The mortality rate was highest in patients with bloodstream infections (49.8%), followed by those with hospital-acquired pneumonia (47.9%), urinary tract infections (29.4%), and skin and soft tissue infections (29.4%). The mortality rate in patients with diabetes with SIs was 45.2%, compared with 34.3% in those without diabetes (P<0.001). Conclusions: SIs complicate the course of patients hospitalized with COVID-19. These patients tend to have a much longer hospital stay, a higher requirement for oxygen and ICU care, and a significantly higher mortality rate compared with those without SIs. The groups most vulnerable to SIs are patients with more severe COVID-19, elderly patients and patients with diabetes. Judicious empirical use of combination antimicrobials in these groups of vulnerable patients can save lives. It is desirable to have region- or country-specific guidelines for appropriate use of antibiotics and antifungals to prevent their overuse.

A High Frequency of Candida auris Blood Stream Infections in Coronavirus Disease 2019 Patients Admitted to Intensive Care Units, Northwestern India: A Case Control Study.

BACKGROUND: The ongoing pandemic of coronavirus disease 2019 (COVID-19) has overwhelmed healthcare facilities and raises an important novel concern of nosocomial transmission of Candida species in the intensive care units (ICUs). METHODS: We evaluated the incidence and risk factors for development of candidemia in 2384 COVID-19 patients admitted during August 2020-January 2021 in ICUs of 2 hospitals (Delhi and Jaipur) in India. A 1:2 case-control matching was used to identify COVID-19 patients who did not develop candidemia as controls. RESULTS: A total of 33 patients developed candidemia and accounted for an overall incidence of 1.4% over a median ICU stay of 24 days. A 2-fold increase in the incidence of candidemia in COVID-19 versus non-COVID-19 patients was observed with an incidence rate of 14 and 15/1000 admissions in 2 ICUs. Candida auris was the predominant species (42%) followed by Candida tropicalis. Multivariable regression analysis revealed the use of tocilizumab, duration of ICU stay (24 vs 14 days), and raised ferritin level as an independent predictor for the development of candidemia. Azole resistance was observed in C auris and C tropicalis harboring mutations in the azole target ERG11 gene. Multilocus sequence typing (MLST) identified identical genotypes of C tropicalis in COVID-19 patients, raising concern for nosocomial transmission of resistant strains. CONCLUSIONS: Secondary bacterial infections have been a concern with the use of tocilizumab. In this cohort of critically ill COVID-19 patients, tocilizumab was associated with the development of candidemia. Surveillance of antifungal resistance is warranted to prevent transmission of multidrug-resistant strains of nosocomial yeasts in COVID-19 hospitalized patients.

Syndromic approach to SARS-CoV-2 detection using QIAstat-Dx SARS-CoV-2 panel from clinical samples.

The QIAstat-Dx SARS-CoV-2 panel is a multiplex cartridge based assay based on real time PCR which can detect 17 respiratory viruses, including the novel coronavirus SARS-CoV-2. A syndromic approach is the need of the hour for COVID-19 diagnostics among patients presenting with respiratory symptoms. The present study was done to evaluate 120 archived respiratory clinical specimens for SARS-CoV-2 on the SARS-CoV-2 panel. Further, 27 specimens were tested for other respiratory viruses, in comparison with the BioFire RP1.7 platform. The sensitivity and specificity for SARS-CoV-2 on SARS panel was found to be 90.00 % and 100 % respectively, indicating good diagnostic accuracy. The positive predictive value was found to be 100 %, negative predictive value was found to be 99.93 % and accuracy was 99.93 %. Detection of other respiratory viruses observed a concordance of 77.7 %. Despite advantages of speed, minimal expertise and accurate results; significant costs and discrepancies at Ct >35 remain important limitations of the SARS panel.

Respiratory Co-Infections: Modulators of SARS-CoV-2 Patients' Clinical Sub-Phenotype.

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

Multidrug-Resistant Candida auris Infections in Critically Ill Coronavirus Disease Patients, India, April-July 2020.

In New Delhi, India, candidemia affected 15 critically ill coronavirus disease patients admitted to an intensive care unit during April-July 2020. Candida auris accounted for two thirds of cases; case-fatality rate was high (60%). Hospital-acquired C. auris infections in coronavirus disease patients may lead to adverse outcomes and additional strain on healthcare resources.